diff --git a/.ai/skills/check-upstream/SKILL.md b/.ai/skills/check-upstream/SKILL.md
new file mode 100644
index 000000000..ac4835a4e
--- /dev/null
+++ b/.ai/skills/check-upstream/SKILL.md
@@ -0,0 +1,383 @@
+<!---
+  Licensed to the Apache Software Foundation (ASF) under one
+  or more contributor license agreements.  See the NOTICE file
+  distributed with this work for additional information
+  regarding copyright ownership.  The ASF licenses this file
+  to you under the Apache License, Version 2.0 (the
+  "License"); you may not use this file except in compliance
+  with the License.  You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+  Unless required by applicable law or agreed to in writing,
+  software distributed under the License is distributed on an
+  "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+  KIND, either express or implied.  See the License for the
+  specific language governing permissions and limitations
+  under the License.
+-->
+
+---
+name: check-upstream
+description: Check if upstream Apache DataFusion features (functions, DataFrame ops, SessionContext methods, FFI types) are exposed in this Python project. Use when adding missing functions, auditing API coverage, or ensuring parity with upstream.
+argument-hint: [area] (e.g., "scalar functions", "aggregate functions", "window functions", "dataframe", "session context", "ffi types", "all")
+---
+
+# Check Upstream DataFusion Feature Coverage
+
+You are auditing the datafusion-python project to find features from the upstream Apache DataFusion Rust library that are **not yet exposed** in this Python binding project. Your goal is to identify gaps and, if asked, implement the missing bindings.
+
+**IMPORTANT: The Python API is the source of truth for coverage.** A function or method is considered "exposed" if it exists in the Python API (e.g., `python/datafusion/functions.py`), even if there is no corresponding entry in the Rust bindings. Many upstream functions are aliases of other functions — the Python layer can expose these aliases by calling a different underlying Rust binding. Do NOT report a function as missing if it appears in the Python `__all__` list and has a working implementation, regardless of whether a matching `#[pyfunction]` exists in Rust.
+
+## Areas to Check
+
+The user may specify an area via `$ARGUMENTS`. If no area is specified or "all" is given, check all areas.
+
+### 1. Scalar Functions
+
+**Upstream source of truth:**
+- Rust docs: https://docs.rs/datafusion/latest/datafusion/functions/index.html
+- User docs: https://datafusion.apache.org/user-guide/sql/scalar_functions.html
+
+**Where they are exposed in this project:**
+- Python API: `python/datafusion/functions.py` — each function wraps a call to `datafusion._internal.functions`
+- Rust bindings: `crates/core/src/functions.rs` — `#[pyfunction]` definitions registered via `init_module()`
+
+**How to check:**
+1. Fetch the upstream scalar function documentation page
+2. Compare against functions listed in `python/datafusion/functions.py` (check the `__all__` list and function definitions)
+3. A function is covered if it exists in the Python API — it does NOT need a dedicated Rust `#[pyfunction]`. Many functions are aliases that reuse another function's Rust binding.
+4. Only report functions that are missing from the Python `__all__` list / function definitions
+
+### 2. Aggregate Functions
+
+**Upstream source of truth:**
+- Rust docs: https://docs.rs/datafusion/latest/datafusion/functions_aggregate/index.html
+- User docs: https://datafusion.apache.org/user-guide/sql/aggregate_functions.html
+
+**Where they are exposed in this project:**
+- Python API: `python/datafusion/functions.py` (aggregate functions are mixed in with scalar functions)
+- Rust bindings: `crates/core/src/functions.rs`
+
+**How to check:**
+1. Fetch the upstream aggregate function documentation page
+2. Compare against aggregate functions in `python/datafusion/functions.py` (check `__all__` list and function definitions)
+3. A function is covered if it exists in the Python API, even if it aliases another function's Rust binding
+4. Report only functions missing from the Python API
+
+### 3. Window Functions
+
+**Upstream source of truth:**
+- Rust docs: https://docs.rs/datafusion/latest/datafusion/functions_window/index.html
+- User docs: https://datafusion.apache.org/user-guide/sql/window_functions.html
+
+**Where they are exposed in this project:**
+- Python API: `python/datafusion/functions.py` (window functions like `rank`, `dense_rank`, `lag`, `lead`, etc.)
+- Rust bindings: `crates/core/src/functions.rs`
+
+**How to check:**
+1. Fetch the upstream window function documentation page
+2. Compare against window functions in `python/datafusion/functions.py` (check `__all__` list and function definitions)
+3. A function is covered if it exists in the Python API, even if it aliases another function's Rust binding
+4. Report only functions missing from the Python API
+
+### 4. Table Functions
+
+**Upstream source of truth:**
+- Rust docs: https://docs.rs/datafusion/latest/datafusion/functions_table/index.html
+- User docs: https://datafusion.apache.org/user-guide/sql/table_functions.html (if available)
+
+**Where they are exposed in this project:**
+- Python API: `python/datafusion/functions.py` and `python/datafusion/user_defined.py` (TableFunction/udtf)
+- Rust bindings: `crates/core/src/functions.rs` and `crates/core/src/udtf.rs`
+
+**How to check:**
+1. Fetch the upstream table function documentation
+2. Compare against what's available in the Python API
+3. A function is covered if it exists in the Python API, even if it aliases another function's Rust binding
+4. Report only functions missing from the Python API
+
+### 5. DataFrame Operations
+
+**Upstream source of truth:**
+- Rust docs: https://docs.rs/datafusion/latest/datafusion/dataframe/struct.DataFrame.html
+
+**Where they are exposed in this project:**
+- Python API: `python/datafusion/dataframe.py` — the `DataFrame` class
+- Rust bindings: `crates/core/src/dataframe.rs` — `PyDataFrame` with `#[pymethods]`
+
+**Evaluated and not requiring separate Python exposure:**
+- `show_limit` — already covered by `DataFrame.show()`, which provides the same functionality with a simpler API
+- `with_param_values` — already covered by the `param_values` argument on `SessionContext.sql()`, which accomplishes the same thing more robustly
+- `union_by_name_distinct` — already covered by `DataFrame.union_by_name(distinct=True)`, which provides a more Pythonic API
+
+**How to check:**
+1. Fetch the upstream DataFrame documentation page listing all methods
+2. Compare against methods in `python/datafusion/dataframe.py` — this is the source of truth for coverage
+3. The Rust bindings (`crates/core/src/dataframe.rs`) may be consulted for context, but a method is covered if it exists in the Python API
+4. Check against the "evaluated and not requiring exposure" list before flagging as a gap
+5. Report only methods missing from the Python API
+
+### 6. SessionContext Methods
+
+**Upstream source of truth:**
+- Rust docs: https://docs.rs/datafusion/latest/datafusion/execution/context/struct.SessionContext.html
+
+**Where they are exposed in this project:**
+- Python API: `python/datafusion/context.py` — the `SessionContext` class
+- Rust bindings: `crates/core/src/context.rs` — `PySessionContext` with `#[pymethods]`
+
+**How to check:**
+1. Fetch the upstream SessionContext documentation page listing all methods
+2. Compare against methods in `python/datafusion/context.py` — this is the source of truth for coverage
+3. The Rust bindings (`crates/core/src/context.rs`) may be consulted for context, but a method is covered if it exists in the Python API
+4. Report only methods missing from the Python API
+
+### 7. FFI Types (datafusion-ffi)
+
+**Upstream source of truth:**
+- Crate source: https://github.com/apache/datafusion/tree/main/datafusion/ffi/src
+- Rust docs: https://docs.rs/datafusion-ffi/latest/datafusion_ffi/
+
+**Where they are exposed in this project:**
+- Rust bindings: various files under `crates/core/src/` and `crates/util/src/`
+- FFI example: `examples/datafusion-ffi-example/src/`
+- Dependency declared in root `Cargo.toml` and `crates/core/Cargo.toml`
+
+**Discovering currently supported FFI types:**
+Grep for `use datafusion_ffi::` in `crates/core/src/` and `crates/util/src/` to find all FFI types currently imported and used.
+
+**Evaluated and not requiring direct Python exposure:**
+These upstream FFI types have been reviewed and do not need to be independently exposed to end users:
+- `FFI_ExecutionPlan` — already used indirectly through table providers; no need for direct exposure
+- `FFI_PhysicalExpr` / `FFI_PhysicalSortExpr` — internal physical planning types not expected to be needed by end users
+- `FFI_RecordBatchStream` — one level deeper than FFI_ExecutionPlan, used internally when execution plans stream results
+- `FFI_SessionRef` / `ForeignSession` — session sharing across FFI; Python manages sessions natively via SessionContext
+- `FFI_SessionConfig` — Python can configure sessions natively without FFI
+- `FFI_ConfigOptions` / `FFI_TableOptions` — internal configuration plumbing
+- `FFI_PlanProperties` / `FFI_Boundedness` / `FFI_EmissionType` — read from existing plans, not user-facing
+- `FFI_Partitioning` — supporting type for physical planning
+- Supporting/utility types (`FFI_Option`, `FFI_Result`, `WrappedSchema`, `WrappedArray`, `FFI_ColumnarValue`, `FFI_Volatility`, `FFI_InsertOp`, `FFI_AccumulatorArgs`, `FFI_Accumulator`, `FFI_GroupsAccumulator`, `FFI_EmitTo`, `FFI_AggregateOrderSensitivity`, `FFI_PartitionEvaluator`, `FFI_PartitionEvaluatorArgs`, `FFI_Range`, `FFI_SortOptions`, `FFI_Distribution`, `FFI_ExprProperties`, `FFI_SortProperties`, `FFI_Interval`, `FFI_TableProviderFilterPushDown`, `FFI_TableType`) — used as building blocks within the types above, not independently exposed
+
+**How to check:**
+1. Discover currently supported types by grepping for `use datafusion_ffi::` in `crates/core/src/` and `crates/util/src/`, then compare against the upstream `datafusion-ffi` crate's `lib.rs` exports
+2. If new FFI types appear upstream, evaluate whether they represent a user-facing capability
+3. Check against the "evaluated and not requiring exposure" list before flagging as a gap
+4. Report any genuinely new types that enable user-facing functionality
+5. For each currently supported FFI type, verify the full pipeline is present using the checklist from "Adding a New FFI Type":
+   - Rust PyO3 wrapper with `from_pycapsule()` method
+   - Python Protocol type (e.g., `ScalarUDFExportable`) for FFI objects
+   - Python wrapper class with full type hints on all public methods
+   - ABC base class (if the type can be user-implemented)
+   - Registered in Rust `init_module()` and Python `__init__.py`
+   - FFI example in `examples/datafusion-ffi-example/`
+   - Type appears in union type hints where accepted
+
+## Checking for Existing GitHub Issues
+
+After identifying missing APIs, search the open issues at https://github.com/apache/datafusion-python/issues for each gap to see if an issue already exists requesting that API be exposed. Search using the function or method name as the query.
+
+- If an existing issue is found, include a link to it in the report. Do NOT create a new issue.
+- If no existing issue is found, note that no issue exists yet. If the user asks to create issues for missing APIs, each issue should specify that Python test coverage is required as part of the implementation.
+
+## Output Format
+
+For each area checked, produce a report like:
+
+```
+## [Area Name] Coverage Report
+
+### Currently Exposed (X functions/methods)
+- list of what's already available
+
+### Missing from Upstream (Y functions/methods)
+- function_name — brief description of what it does (existing issue: #123)
+- function_name — brief description of what it does (no existing issue)
+
+### Notes
+- Any relevant observations about partial implementations, naming differences, etc.
+```
+
+## Implementation Pattern
+
+If the user asks you to implement missing features, follow these patterns:
+
+### Adding a New Function (Scalar/Aggregate/Window)
+
+**Step 1: Rust binding** in `crates/core/src/functions.rs`:
+```rust
+#[pyfunction]
+#[pyo3(signature = (arg1, arg2))]
+fn new_function_name(arg1: PyExpr, arg2: PyExpr) -> PyResult<PyExpr> {
+    Ok(datafusion::functions::module::expr_fn::new_function_name(arg1.expr, arg2.expr).into())
+}
+```
+Then register in `init_module()`:
+```rust
+m.add_wrapped(wrap_pyfunction!(new_function_name))?;
+```
+
+**Step 2: Python wrapper** in `python/datafusion/functions.py`:
+```python
+def new_function_name(arg1: Expr, arg2: Expr) -> Expr:
+    """Description of what the function does.
+
+    Args:
+        arg1: Description of first argument.
+        arg2: Description of second argument.
+
+    Returns:
+        Description of return value.
+    """
+    return Expr(f.new_function_name(arg1.expr, arg2.expr))
+```
+Add to `__all__` list.
+
+### Adding a New DataFrame Method
+
+**Step 1: Rust binding** in `crates/core/src/dataframe.rs`:
+```rust
+#[pymethods]
+impl PyDataFrame {
+    fn new_method(&self, py: Python, param: PyExpr) -> PyDataFusionResult<Self> {
+        let df = self.df.as_ref().clone().new_method(param.into())?;
+        Ok(Self::new(df))
+    }
+}
+```
+
+**Step 2: Python wrapper** in `python/datafusion/dataframe.py`:
+```python
+def new_method(self, param: Expr) -> DataFrame:
+    """Description of the method."""
+    return DataFrame(self.df.new_method(param.expr))
+```
+
+### Adding a New SessionContext Method
+
+**Step 1: Rust binding** in `crates/core/src/context.rs`:
+```rust
+#[pymethods]
+impl PySessionContext {
+    pub fn new_method(&self, py: Python, param: String) -> PyDataFusionResult<PyDataFrame> {
+        let df = wait_for_future(py, self.ctx.new_method(&param))?;
+        Ok(PyDataFrame::new(df))
+    }
+}
+```
+
+**Step 2: Python wrapper** in `python/datafusion/context.py`:
+```python
+def new_method(self, param: str) -> DataFrame:
+    """Description of the method."""
+    return DataFrame(self.ctx.new_method(param))
+```
+
+### Adding a New FFI Type
+
+FFI types require a full pipeline from C struct through to a typed Python wrapper. Each layer must be present.
+
+**Step 1: Rust PyO3 wrapper class** in a new or existing file under `crates/core/src/`:
+```rust
+use datafusion_ffi::new_type::FFI_NewType;
+
+#[pyclass(from_py_object, frozen, name = "RawNewType", module = "datafusion.module_name", subclass)]
+pub struct PyNewType {
+    pub inner: Arc<dyn NewTypeTrait>,
+}
+
+#[pymethods]
+impl PyNewType {
+    #[staticmethod]
+    fn from_pycapsule(obj: &Bound<'_, PyAny>) -> PyDataFusionResult<Self> {
+        let capsule = obj
+            .getattr("__datafusion_new_type__")?
+            .call0()?
+            .downcast::<PyCapsule>()?;
+        let ffi_ptr = unsafe { capsule.reference::<FFI_NewType>() };
+        let provider: Arc<dyn NewTypeTrait> = ffi_ptr.into();
+        Ok(Self { inner: provider })
+    }
+
+    fn some_method(&self) -> PyResult<...> {
+        // wrap inner trait method
+    }
+}
+```
+Register in the appropriate `init_module()`:
+```rust
+m.add_class::<PyNewType>()?;
+```
+
+**Step 2: Python Protocol type** in the appropriate Python module (e.g., `python/datafusion/catalog.py`):
+```python
+class NewTypeExportable(Protocol):
+    """Type hint for objects providing a __datafusion_new_type__ PyCapsule."""
+
+    def __datafusion_new_type__(self) -> object: ...
+```
+
+**Step 3: Python wrapper class** in the same module:
+```python
+class NewType:
+    """Description of the type.
+
+    This class wraps a DataFusion NewType, which can be created from a native
+    Python implementation or imported from an FFI-compatible library.
+    """
+
+    def __init__(
+        self,
+        new_type: df_internal.module_name.RawNewType | NewTypeExportable,
+    ) -> None:
+        if isinstance(new_type, df_internal.module_name.RawNewType):
+            self._raw = new_type
+        else:
+            self._raw = df_internal.module_name.RawNewType.from_pycapsule(new_type)
+
+    def some_method(self) -> ReturnType:
+        """Description of the method."""
+        return self._raw.some_method()
+```
+
+**Step 4: ABC base class** (if users should be able to subclass and provide custom implementations in Python):
+```python
+from abc import ABC, abstractmethod
+
+class NewTypeProvider(ABC):
+    """Abstract base class for implementing a custom NewType in Python."""
+
+    @abstractmethod
+    def some_method(self) -> ReturnType:
+        """Description of the method."""
+        ...
+```
+
+**Step 5: Module exports** — add to the appropriate `__init__.py`:
+- Add the wrapper class (`NewType`) to `python/datafusion/__init__.py`
+- Add the ABC (`NewTypeProvider`) if applicable
+- Add the Protocol type (`NewTypeExportable`) if it should be public
+
+**Step 6: FFI example** — add an example implementation under `examples/datafusion-ffi-example/src/`:
+```rust
+// examples/datafusion-ffi-example/src/new_type.rs
+use datafusion_ffi::new_type::FFI_NewType;
+// ... example showing how an external Rust library exposes this type via PyCapsule
+```
+
+**Checklist for each FFI type:**
+- [ ] Rust PyO3 wrapper with `from_pycapsule()` method
+- [ ] Python Protocol type (e.g., `NewTypeExportable`) for FFI objects
+- [ ] Python wrapper class with full type hints on all public methods
+- [ ] ABC base class (if the type can be user-implemented)
+- [ ] Registered in Rust `init_module()` and Python `__init__.py`
+- [ ] FFI example in `examples/datafusion-ffi-example/`
+- [ ] Type appears in union type hints where accepted (e.g., `Table | TableProviderExportable`)
+
+## Important Notes
+
+- The upstream DataFusion version used by this project is specified in `crates/core/Cargo.toml` — check the `datafusion` dependency version to ensure you're comparing against the right upstream version.
+- Some upstream features may intentionally not be exposed (e.g., internal-only APIs). Use judgment about what's user-facing.
+- When fetching upstream docs, prefer the published docs.rs documentation as it matches the crate version.
+- Function aliases (e.g., `array_append` / `list_append`) should both be exposed if upstream supports them.
+- Check the `__all__` list in `functions.py` to see what's publicly exported vs just defined.
diff --git a/.cargo/config.toml b/.cargo/config.toml
deleted file mode 100644
index af951327f..000000000
--- a/.cargo/config.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[target.x86_64-apple-darwin]
-rustflags = ["-C", "link-arg=-undefined", "-C", "link-arg=dynamic_lookup"]
-
-[target.aarch64-apple-darwin]
-rustflags = ["-C", "link-arg=-undefined", "-C", "link-arg=dynamic_lookup"]
diff --git a/.claude/skills b/.claude/skills
new file mode 120000
index 000000000..6838a1160
--- /dev/null
+++ b/.claude/skills
@@ -0,0 +1 @@
+../.ai/skills
\ No newline at end of file
diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml
index b86b37c6e..7682d6cb0 100644
--- a/.github/workflows/build.yml
+++ b/.github/workflows/build.yml
@@ -36,6 +36,7 @@ on:
 env:
   CARGO_TERM_COLOR: always
   RUST_BACKTRACE: 1
+  UV_LOCKED: true
 
 jobs:
   # ============================================
@@ -47,7 +48,7 @@ jobs:
       - uses: actions/checkout@v6
 
       - name: Setup Rust
-        uses: dtolnay/rust-toolchain@stable
+        uses: dtolnay/rust-toolchain@29eef336d9b2848a0b548edc03f92a220660cdb8
         with:
           toolchain: "nightly"
           components: rustfmt
@@ -68,7 +69,7 @@ jobs:
         with:
           python-version: "3.12"
 
-      - uses: astral-sh/setup-uv@v6
+      - uses: astral-sh/setup-uv@5a095e7a2014a4212f075830d4f7277575a9d098
         with:
           enable-cache: true
 
@@ -98,12 +99,21 @@ jobs:
       - name: Check Cargo.toml formatting
         run: taplo format --check
 
+  check-crates-patch:
+    if: inputs.build_mode == 'release' && startsWith(github.ref, 'refs/tags/')
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v6
+
+      - name: Ensure [patch.crates-io] is empty
+        run: python3 dev/check_crates_patch.py
+
   generate-license:
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v6
 
-      - uses: astral-sh/setup-uv@v6
+      - uses: astral-sh/setup-uv@5a095e7a2014a4212f075830d4f7277575a9d098
         with:
           enable-cache: true
 
@@ -115,7 +125,7 @@ jobs:
       - name: Generate license file
         run: uv run --no-project python ./dev/create_license.py
 
-      - uses: actions/upload-artifact@v6
+      - uses: actions/upload-artifact@v7
         with:
           name: python-wheel-license
           path: LICENSE.txt
@@ -132,23 +142,36 @@ jobs:
 
       - run: rm LICENSE.txt
       - name: Download LICENSE.txt
-        uses: actions/download-artifact@v7
+        uses: actions/download-artifact@v8
         with:
           name: python-wheel-license
           path: .
 
       - name: Setup Rust
-        uses: dtolnay/rust-toolchain@stable
+        uses: dtolnay/rust-toolchain@29eef336d9b2848a0b548edc03f92a220660cdb8
 
       - name: Cache Cargo
         uses: Swatinem/rust-cache@v2
         with:
           key: ${{ inputs.build_mode }}
 
-      - uses: astral-sh/setup-uv@v6
+      - uses: astral-sh/setup-uv@5a095e7a2014a4212f075830d4f7277575a9d098
         with:
           enable-cache: true
 
+      - name: Add extra swap for release build
+        if: inputs.build_mode == 'release'
+        run: |
+          set -euxo pipefail
+          sudo swapoff -a || true
+          sudo rm -f /swapfile
+          sudo fallocate -l 8G /swapfile || sudo dd if=/dev/zero of=/swapfile bs=1M count=8192
+          sudo chmod 600 /swapfile
+          sudo mkswap /swapfile
+          sudo swapon /swapfile
+          free -h
+          swapon --show
+
       - name: Build (release mode)
         uses: PyO3/maturin-action@v1
         if: inputs.build_mode == 'release'
@@ -177,13 +200,13 @@ jobs:
           rustup-components: rust-std
 
       - name: Archive wheels
-        uses: actions/upload-artifact@v6
+        uses: actions/upload-artifact@v7
         with:
           name: dist-manylinux-x86_64
           path: dist/*
 
       - name: Archive FFI test wheel
-        uses: actions/upload-artifact@v6
+        uses: actions/upload-artifact@v7
         with:
           name: test-ffi-manylinux-x86_64
           path: examples/datafusion-ffi-example/dist/*
@@ -200,23 +223,36 @@ jobs:
 
       - run: rm LICENSE.txt
       - name: Download LICENSE.txt
-        uses: actions/download-artifact@v7
+        uses: actions/download-artifact@v8
         with:
           name: python-wheel-license
           path: .
 
       - name: Setup Rust
-        uses: dtolnay/rust-toolchain@stable
+        uses: dtolnay/rust-toolchain@29eef336d9b2848a0b548edc03f92a220660cdb8
 
       - name: Cache Cargo
         uses: Swatinem/rust-cache@v2
         with:
           key: ${{ inputs.build_mode }}
 
-      - uses: astral-sh/setup-uv@v6
+      - uses: astral-sh/setup-uv@5a095e7a2014a4212f075830d4f7277575a9d098
         with:
           enable-cache: true
 
+      - name: Add extra swap for release build
+        if: inputs.build_mode == 'release'
+        run: |
+          set -euxo pipefail
+          sudo swapoff -a || true
+          sudo rm -f /swapfile
+          sudo fallocate -l 8G /swapfile || sudo dd if=/dev/zero of=/swapfile bs=1M count=8192
+          sudo chmod 600 /swapfile
+          sudo mkswap /swapfile
+          sudo swapon /swapfile
+          free -h
+          swapon --show
+
       - name: Build (release mode)
         uses: PyO3/maturin-action@v1
         if: inputs.build_mode == 'release'
@@ -236,7 +272,7 @@ jobs:
           rustup-components: rust-std
 
       - name: Archive wheels
-        uses: actions/upload-artifact@v6
+        uses: actions/upload-artifact@v7
         if: inputs.build_mode == 'release'
         with:
           name: dist-manylinux-aarch64
@@ -257,11 +293,11 @@ jobs:
     steps:
       - uses: actions/checkout@v6
 
-      - uses: dtolnay/rust-toolchain@stable
+      - uses: dtolnay/rust-toolchain@29eef336d9b2848a0b548edc03f92a220660cdb8
 
       - run: rm LICENSE.txt
       - name: Download LICENSE.txt
-        uses: actions/download-artifact@v7
+        uses: actions/download-artifact@v8
         with:
           name: python-wheel-license
           path: .
@@ -271,7 +307,7 @@ jobs:
         with:
           key: ${{ inputs.build_mode }}
 
-      - uses: astral-sh/setup-uv@v7
+      - uses: astral-sh/setup-uv@5a095e7a2014a4212f075830d4f7277575a9d098
         with:
           enable-cache: true
 
@@ -311,7 +347,7 @@ jobs:
         run: find target/wheels/
 
       - name: Archive wheels
-        uses: actions/upload-artifact@v6
+        uses: actions/upload-artifact@v7
         if: inputs.build_mode == 'release'
         with:
           name: dist-${{ matrix.os  }}
@@ -331,11 +367,11 @@ jobs:
     steps:
       - uses: actions/checkout@v6
 
-      - uses: dtolnay/rust-toolchain@stable
+      - uses: dtolnay/rust-toolchain@29eef336d9b2848a0b548edc03f92a220660cdb8
 
       - run: rm LICENSE.txt
       - name: Download LICENSE.txt
-        uses: actions/download-artifact@v7
+        uses: actions/download-artifact@v8
         with:
           name: python-wheel-license
           path: .
@@ -345,7 +381,7 @@ jobs:
         with:
           key: ${{ inputs.build_mode }}
 
-      - uses: astral-sh/setup-uv@v7
+      - uses: astral-sh/setup-uv@5a095e7a2014a4212f075830d4f7277575a9d098
         with:
           enable-cache: true
 
@@ -366,7 +402,7 @@ jobs:
         run: find target/wheels/
 
       - name: Archive wheels
-        uses: actions/upload-artifact@v6
+        uses: actions/upload-artifact@v7
         with:
           name: dist-macos-aarch64
           path: target/wheels/*
@@ -384,7 +420,7 @@ jobs:
       - uses: actions/checkout@v6
       - run: rm LICENSE.txt
       - name: Download LICENSE.txt
-        uses: actions/download-artifact@v7
+        uses: actions/download-artifact@v8
         with:
           name: python-wheel-license
           path: .
@@ -422,7 +458,7 @@ jobs:
       - build-sdist
     steps:
       - name: Merge Build Artifacts
-        uses: actions/upload-artifact/merge@v6
+        uses: actions/upload-artifact/merge@v7
         with:
           name: dist
           pattern: dist-*
@@ -469,13 +505,13 @@ jobs:
           python-version: "3.10"
 
       - name: Install dependencies
-        uses: astral-sh/setup-uv@v7
+        uses: astral-sh/setup-uv@5a095e7a2014a4212f075830d4f7277575a9d098
         with:
           enable-cache: true
 
       # Download the Linux wheel built in the previous job
       - name: Download pre-built Linux wheel
-        uses: actions/download-artifact@v7
+        uses: actions/download-artifact@v8
         with:
           name: dist-manylinux-x86_64
           path: wheels/
diff --git a/.github/workflows/codeql.yml b/.github/workflows/codeql.yml
new file mode 100644
index 000000000..a9855cf48
--- /dev/null
+++ b/.github/workflows/codeql.yml
@@ -0,0 +1,54 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+#
+
+name: "CodeQL"
+
+on:
+  push:
+    branches: [ "main" ]
+  pull_request:
+    branches: [ "main" ]
+  schedule:
+    - cron: '16 4 * * 1'
+
+permissions:
+  contents: read
+
+jobs:
+  analyze:
+    name: Analyze Actions
+    runs-on: ubuntu-latest
+    permissions:
+      contents: read
+      security-events: write
+
+    steps:
+    - name: Checkout repository
+      uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6
+      with:
+        persist-credentials: false
+
+    - name: Initialize CodeQL
+      uses: github/codeql-action/init@c793b717bc78562f491db7b0e93a3a178b099162 # v4
+      with:
+        languages: actions
+
+    - name: Perform CodeQL Analysis
+      uses: github/codeql-action/analyze@c793b717bc78562f491db7b0e93a3a178b099162 # v4
+      with:
+        category: "/language:actions"
diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml
index 55248b6bf..706ccbc55 100644
--- a/.github/workflows/test.yml
+++ b/.github/workflows/test.yml
@@ -23,6 +23,9 @@ name: Test
 on:
   workflow_call:
 
+env:
+  UV_LOCKED: true
+
 jobs:
   test-matrix:
     runs-on: ubuntu-latest
@@ -41,18 +44,6 @@ jobs:
     steps:
       - uses: actions/checkout@v6
 
-      - name: Verify example datafusion version
-        run: |
-          MAIN_VERSION=$(grep -A 1 "name = \"datafusion-common\"" Cargo.lock | grep "version = " | head -1 | sed 's/.*version = "\(.*\)"/\1/')
-          EXAMPLE_VERSION=$(grep -A 1 "name = \"datafusion-common\"" examples/datafusion-ffi-example/Cargo.lock | grep "version = " | head -1 | sed 's/.*version = "\(.*\)"/\1/')
-          echo "Main crate datafusion version: $MAIN_VERSION"
-          echo "FFI example datafusion version: $EXAMPLE_VERSION"
-
-          if [ "$MAIN_VERSION" != "$EXAMPLE_VERSION" ]; then
-            echo "❌ Error: FFI example datafusion versions don't match!"
-            exit 1
-          fi
-
       - name: Setup Python
         uses: actions/setup-python@v6
         with:
@@ -62,23 +53,23 @@ jobs:
         uses: actions/cache@v5
         with:
           path: ~/.cargo
-          key: cargo-cache-${{ steps.rust-toolchain.outputs.cachekey }}-${{ hashFiles('Cargo.lock') }}
+          key: cargo-cache-${{ matrix.toolchain }}-${{ hashFiles('Cargo.lock') }}
 
       - name: Install dependencies
-        uses: astral-sh/setup-uv@v7
+        uses: astral-sh/setup-uv@5a095e7a2014a4212f075830d4f7277575a9d098
         with:
-            enable-cache: true
+          enable-cache: true
 
       # Download the Linux wheel built in the build workflow
       - name: Download pre-built Linux wheel
-        uses: actions/download-artifact@v7
+        uses: actions/download-artifact@v8
         with:
           name: dist-manylinux-x86_64
           path: wheels/
 
       # Download the FFI test wheel
       - name: Download pre-built FFI test wheel
-        uses: actions/download-artifact@v7
+        uses: actions/download-artifact@v8
         with:
           name: test-ffi-manylinux-x86_64
           path: wheels/
@@ -106,28 +97,21 @@ jobs:
           RUST_BACKTRACE: 1
         run: |
           git submodule update --init
-          uv run --no-project pytest -v . --import-mode=importlib
+          uv run --no-project pytest -v --import-mode=importlib
 
       - name: FFI unit tests
         run: |
           cd examples/datafusion-ffi-example
           uv run --no-project pytest python/tests/_test*.py
 
-      - name: Cache the generated dataset
-        id: cache-tpch-dataset
-        uses: actions/cache@v5
-        with:
-          path: benchmarks/tpch/data
-          key: tpch-data-2.18.0
-
-      - name: Run dbgen to create 1 Gb dataset
-        if: ${{ steps.cache-tpch-dataset.outputs.cache-hit != 'true' }}
+      - name: Run tpchgen-cli to create 1 Gb dataset
         run: |
-          cd benchmarks/tpch
-          RUN_IN_CI=TRUE ./tpch-gen.sh 1
+          mkdir examples/tpch/data
+          cd examples/tpch/data
+          uv pip install tpchgen-cli
+          uv run --no-project tpchgen-cli -s 1 --format=parquet
 
       - name: Run TPC-H examples
         run: |
           cd examples/tpch
-          uv run --no-project python convert_data_to_parquet.py
           uv run --no-project pytest _tests.py
diff --git a/.github/workflows/verify-release-candidate.yml b/.github/workflows/verify-release-candidate.yml
index a7293b369..6ecb547b5 100644
--- a/.github/workflows/verify-release-candidate.yml
+++ b/.github/workflows/verify-release-candidate.yml
@@ -27,7 +27,7 @@ on:
         required: true
         type: string
       rc_number:
-        description: Release candidate number (e.g., 0)
+        description: Release candidate number (e.g., 1)
         required: true
         type: string
 
@@ -58,10 +58,10 @@ jobs:
             arch: x64
             runner: macos-15-intel
 
-          # Windows (disabled for now)
-          # - os: windows
-          #   arch: x64
-          #   runner: windows-latest
+          # Windows
+          - os: windows
+            arch: x64
+            runner: windows-latest
     runs-on: ${{ matrix.runner }}
     steps:
       - name: Checkout repository
@@ -73,6 +73,11 @@ jobs:
           version: "27.4"
           repo-token: ${{ secrets.GITHUB_TOKEN }}
 
+      - name: Set RUSTFLAGS for Windows GNU linker
+        if: matrix.os == 'windows'
+        shell: bash
+        run: echo "RUSTFLAGS=-C link-arg=-Wl,--exclude-libs=ALL" >> "$GITHUB_ENV"
+
       - name: Run release candidate verification
         shell: bash
         run: ./dev/release/verify-release-candidate.sh "${{ inputs.version }}" "${{ inputs.rc_number }}"
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index bcefa405d..2d3c2bc59 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -22,7 +22,7 @@ repos:
           - id: actionlint-docker
       - repo: https://github.com/astral-sh/ruff-pre-commit
         # Ruff version.
-        rev: v0.9.10
+        rev: v0.15.1
         hooks:
           # Run the linter.
           - id: ruff
@@ -53,5 +53,12 @@ repos:
             additional_dependencies:
               - tomli
 
+      - repo: https://github.com/astral-sh/uv-pre-commit
+        # uv version.
+        rev: 0.10.7
+        hooks:
+          # Update the uv lockfile
+          - id: uv-lock
+
 default_language_version:
       python: python3
diff --git a/AGENTS.md b/AGENTS.md
new file mode 100644
index 000000000..86c2e9c3b
--- /dev/null
+++ b/AGENTS.md
@@ -0,0 +1,56 @@
+<!---
+  Licensed to the Apache Software Foundation (ASF) under one
+  or more contributor license agreements.  See the NOTICE file
+  distributed with this work for additional information
+  regarding copyright ownership.  The ASF licenses this file
+  to you under the Apache License, Version 2.0 (the
+  "License"); you may not use this file except in compliance
+  with the License.  You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+  Unless required by applicable law or agreed to in writing,
+  software distributed under the License is distributed on an
+  "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+  KIND, either express or implied.  See the License for the
+  specific language governing permissions and limitations
+  under the License.
+-->
+
+# Agent Instructions
+
+This project uses AI agent skills stored in `.ai/skills/`. Each skill is a directory containing a `SKILL.md` file with instructions for performing a specific task.
+
+Skills follow the [Agent Skills](https://agentskills.io) open standard. Each skill directory contains:
+
+- `SKILL.md` — The skill definition with YAML frontmatter (name, description, argument-hint) and detailed instructions.
+- Additional supporting files as needed.
+
+## Python Function Docstrings
+
+Every Python function must include a docstring with usage examples.
+
+- **Examples are required**: Each function needs at least one doctest-style example
+  demonstrating basic usage.
+- **Optional parameters**: If a function has optional parameters, include separate
+  examples that show usage both without and with the optional arguments. Pass
+  optional arguments using their keyword name (e.g., `step=dfn.lit(3)`) so readers
+  can immediately see which parameter is being demonstrated.
+- **Reuse input data**: Use the same input data across examples wherever possible.
+  The examples should demonstrate how different optional arguments change the output
+  for the same input, making the effect of each option easy to understand.
+- **Alias functions**: Functions that are simple aliases (e.g., `list_sort` aliasing
+  `array_sort`) only need a one-line description and a `See Also` reference to the
+  primary function. They do not need their own examples.
+
+## Aggregate and Window Function Documentation
+
+When adding or updating an aggregate or window function, ensure the corresponding
+site documentation is kept in sync:
+
+- **Aggregations**: `docs/source/user-guide/common-operations/aggregations.rst` —
+  add new aggregate functions to the "Aggregate Functions" list and include usage
+  examples if appropriate.
+- **Window functions**: `docs/source/user-guide/common-operations/windows.rst` —
+  add new window functions to the "Available Functions" list and include usage
+  examples if appropriate.
diff --git a/CLAUDE.md b/CLAUDE.md
new file mode 120000
index 000000000..47dc3e3d8
--- /dev/null
+++ b/CLAUDE.md
@@ -0,0 +1 @@
+AGENTS.md
\ No newline at end of file
diff --git a/Cargo.lock b/Cargo.lock
index e830a46b3..4efca3eb6 100644
--- a/Cargo.lock
+++ b/Cargo.lock
@@ -111,9 +111,9 @@ dependencies = [
 
 [[package]]
 name = "anyhow"
-version = "1.0.101"
+version = "1.0.102"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "5f0e0fee31ef5ed1ba1316088939cea399010ed7731dba877ed44aeb407a75ea"
+checksum = "7f202df86484c868dbad7eaa557ef785d5c66295e41b460ef922eca0723b842c"
 
 [[package]]
 name = "apache-avro"
@@ -131,7 +131,7 @@ dependencies = [
  "miniz_oxide",
  "num-bigint",
  "quad-rand",
- "rand",
+ "rand 0.9.2",
  "regex-lite",
  "serde",
  "serde_bytes",
@@ -155,9 +155,9 @@ dependencies = [
 
 [[package]]
 name = "arc-swap"
-version = "1.8.2"
+version = "1.9.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "f9f3647c145568cec02c42054e07bdf9a5a698e15b466fb2341bfc393cd24aa5"
+checksum = "a07d1f37ff60921c83bdfc7407723bdefe89b44b98a9b772f225c8f9d67141a6"
 dependencies = [
  "rustversion",
 ]
@@ -176,9 +176,9 @@ checksum = "7c02d123df017efcdfbd739ef81735b36c5ba83ec3c59c80a9d7ecc718f92e50"
 
 [[package]]
 name = "arrow"
-version = "57.3.0"
+version = "58.1.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "e4754a624e5ae42081f464514be454b39711daae0458906dacde5f4c632f33a8"
+checksum = "d441fdda254b65f3e9025910eb2c2066b6295d9c8ed409522b8d2ace1ff8574c"
 dependencies = [
  "arrow-arith",
  "arrow-array",
@@ -198,9 +198,9 @@ dependencies = [
 
 [[package]]
 name = "arrow-arith"
-version = "57.3.0"
+version = "58.1.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "f7b3141e0ec5145a22d8694ea8b6d6f69305971c4fa1c1a13ef0195aef2d678b"
+checksum = "ced5406f8b720cc0bc3aa9cf5758f93e8593cda5490677aa194e4b4b383f9a59"
 dependencies = [
  "arrow-array",
  "arrow-buffer",
@@ -212,9 +212,9 @@ dependencies = [
 
 [[package]]
 name = "arrow-array"
-version = "57.3.0"
+version = "58.1.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "4c8955af33b25f3b175ee10af580577280b4bd01f7e823d94c7cdef7cf8c9aef"
+checksum = "772bd34cacdda8baec9418d80d23d0fb4d50ef0735685bd45158b83dfeb6e62d"
 dependencies = [
  "ahash",
  "arrow-buffer",
@@ -231,9 +231,9 @@ dependencies = [
 
 [[package]]
 name = "arrow-buffer"
-version = "57.3.0"
+version = "58.1.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "c697ddca96183182f35b3a18e50b9110b11e916d7b7799cbfd4d34662f2c56c2"
+checksum = "898f4cf1e9598fdb77f356fdf2134feedfd0ee8d5a4e0a5f573e7d0aec16baa4"
 dependencies = [
  "bytes",
  "half",
@@ -243,9 +243,9 @@ dependencies = [
 
 [[package]]
 name = "arrow-cast"
-version = "57.3.0"
+version = "58.1.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "646bbb821e86fd57189c10b4fcdaa941deaf4181924917b0daa92735baa6ada5"
+checksum = "b0127816c96533d20fc938729f48c52d3e48f99717e7a0b5ade77d742510736d"
 dependencies = [
  "arrow-array",
  "arrow-buffer",
@@ -265,9 +265,9 @@ dependencies = [
 
 [[package]]
 name = "arrow-csv"
-version = "57.3.0"
+version = "58.1.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "8da746f4180004e3ce7b83c977daf6394d768332349d3d913998b10a120b790a"
+checksum = "ca025bd0f38eeecb57c2153c0123b960494138e6a957bbda10da2b25415209fe"
 dependencies = [
  "arrow-array",
  "arrow-cast",
@@ -280,9 +280,9 @@ dependencies = [
 
 [[package]]
 name = "arrow-data"
-version = "57.3.0"
+version = "58.1.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "1fdd994a9d28e6365aa78e15da3f3950c0fdcea6b963a12fa1c391afb637b304"
+checksum = "42d10beeab2b1c3bb0b53a00f7c944a178b622173a5c7bcabc3cb45d90238df4"
 dependencies = [
  "arrow-buffer",
  "arrow-schema",
@@ -293,9 +293,9 @@ dependencies = [
 
 [[package]]
 name = "arrow-ipc"
-version = "57.3.0"
+version = "58.1.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "abf7df950701ab528bf7c0cf7eeadc0445d03ef5d6ffc151eaae6b38a58feff1"
+checksum = "609a441080e338147a84e8e6904b6da482cefb957c5cdc0f3398872f69a315d0"
 dependencies = [
  "arrow-array",
  "arrow-buffer",
@@ -309,9 +309,9 @@ dependencies = [
 
 [[package]]
 name = "arrow-json"
-version = "57.3.0"
+version = "58.1.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "0ff8357658bedc49792b13e2e862b80df908171275f8e6e075c460da5ee4bf86"
+checksum = "6ead0914e4861a531be48fe05858265cf854a4880b9ed12618b1d08cba9bebc8"
 dependencies = [
  "arrow-array",
  "arrow-buffer",
@@ -333,9 +333,9 @@ dependencies = [
 
 [[package]]
 name = "arrow-ord"
-version = "57.3.0"
+version = "58.1.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "f7d8f1870e03d4cbed632959498bcc84083b5a24bded52905ae1695bd29da45b"
+checksum = "763a7ba279b20b52dad300e68cfc37c17efa65e68623169076855b3a9e941ca5"
 dependencies = [
  "arrow-array",
  "arrow-buffer",
@@ -346,9 +346,9 @@ dependencies = [
 
 [[package]]
 name = "arrow-pyarrow"
-version = "57.3.0"
+version = "58.1.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "d18c442b4c266aaf3d7f7dd40fd7ae058cef7f113b00ff0cd8256e1e218ec544"
+checksum = "e63351dc11981a316c828a6032a5021345bba882f68bc4a36c36825a50725089"
 dependencies = [
  "arrow-array",
  "arrow-data",
@@ -358,9 +358,9 @@ dependencies = [
 
 [[package]]
 name = "arrow-row"
-version = "57.3.0"
+version = "58.1.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "18228633bad92bff92a95746bbeb16e5fc318e8382b75619dec26db79e4de4c0"
+checksum = "e14fe367802f16d7668163ff647830258e6e0aeea9a4d79aaedf273af3bdcd3e"
 dependencies = [
  "arrow-array",
  "arrow-buffer",
@@ -371,9 +371,9 @@ dependencies = [
 
 [[package]]
 name = "arrow-schema"
-version = "57.3.0"
+version = "58.1.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "8c872d36b7bf2a6a6a2b40de9156265f0242910791db366a2c17476ba8330d68"
+checksum = "c30a1365d7a7dc50cc847e54154e6af49e4c4b0fddc9f607b687f29212082743"
 dependencies = [
  "bitflags",
  "serde_core",
@@ -382,9 +382,9 @@ dependencies = [
 
 [[package]]
 name = "arrow-select"
-version = "57.3.0"
+version = "58.1.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "68bf3e3efbd1278f770d67e5dc410257300b161b93baedb3aae836144edcaf4b"
+checksum = "78694888660a9e8ac949853db393af2a8b8fc82c19ce333132dfa2e72cc1a7fe"
 dependencies = [
  "ahash",
  "arrow-array",
@@ -396,9 +396,9 @@ dependencies = [
 
 [[package]]
 name = "arrow-string"
-version = "57.3.0"
+version = "58.1.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "85e968097061b3c0e9fe3079cf2e703e487890700546b5b0647f60fca1b5a8d8"
+checksum = "61e04a01f8bb73ce54437514c5fd3ee2aa3e8abe4c777ee5cc55853b1652f79e"
 dependencies = [
  "arrow-array",
  "arrow-buffer",
@@ -425,9 +425,9 @@ dependencies = [
 
 [[package]]
 name = "async-compression"
-version = "0.4.40"
+version = "0.4.41"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "7d67d43201f4d20c78bcda740c142ca52482d81da80681533d33bf3f0596c8e2"
+checksum = "d0f9ee0f6e02ffd7ad5816e9464499fba7b3effd01123b515c41d1697c43dad1"
 dependencies = [
  "compression-codecs",
  "compression-core",
@@ -452,7 +452,7 @@ checksum = "3b43422f69d8ff38f95f1b2bb76517c91589a924d1559a0e935d7c8ce0274c11"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.116",
+ "syn 2.0.117",
 ]
 
 [[package]]
@@ -463,7 +463,7 @@ checksum = "9035ad2d096bed7955a320ee7e2230574d28fd3c3a0f186cbea1ff3c7eed5dbb"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.116",
+ "syn 2.0.117",
 ]
 
 [[package]]
@@ -533,7 +533,7 @@ dependencies = [
  "cc",
  "cfg-if",
  "constant_time_eq",
- "cpufeatures",
+ "cpufeatures 0.2.17",
 ]
 
 [[package]]
@@ -547,9 +547,9 @@ dependencies = [
 
 [[package]]
 name = "bon"
-version = "3.9.0"
+version = "3.9.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "2d13a61f2963b88eef9c1be03df65d42f6996dfeac1054870d950fcf66686f83"
+checksum = "f47dbe92550676ee653353c310dfb9cf6ba17ee70396e1f7cf0a2020ad49b2fe"
 dependencies = [
  "bon-macros",
  "rustversion",
@@ -557,9 +557,9 @@ dependencies = [
 
 [[package]]
 name = "bon-macros"
-version = "3.9.0"
+version = "3.9.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "d314cc62af2b6b0c65780555abb4d02a03dd3b799cd42419044f0c38d99738c0"
+checksum = "519bd3116aeeb42d5372c29d982d16d0170d3d4a5ed85fc7dd91642ffff3c67c"
 dependencies = [
  "darling",
  "ident_case",
@@ -567,7 +567,7 @@ dependencies = [
  "proc-macro2",
  "quote",
  "rustversion",
- "syn 2.0.116",
+ "syn 2.0.117",
 ]
 
 [[package]]
@@ -593,9 +593,9 @@ dependencies = [
 
 [[package]]
 name = "bumpalo"
-version = "3.20.0"
+version = "3.20.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "c81d250916401487680ed13b8b675660281dcfc3ab0121fe44c94bcab9eae2fb"
+checksum = "5d20789868f4b01b2f2caec9f5c4e0213b41e3e5702a50157d699ae31ced2fcb"
 
 [[package]]
 name = "byteorder"
@@ -620,9 +620,9 @@ dependencies = [
 
 [[package]]
 name = "cc"
-version = "1.2.56"
+version = "1.2.58"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "aebf35691d1bfb0ac386a69bac2fde4dd276fb618cf8bf4f5318fe285e821bb2"
+checksum = "e1e928d4b69e3077709075a938a05ffbedfa53a84c8f766efbf8220bb1ff60e1"
 dependencies = [
  "find-msvc-tools",
  "jobserver",
@@ -642,11 +642,22 @@ version = "0.2.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "613afe47fcd5fac7ccf1db93babcb082c5994d996f20b8b159f2ad1658eb5724"
 
+[[package]]
+name = "chacha20"
+version = "0.10.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "6f8d983286843e49675a4b7a2d174efe136dc93a18d69130dd18198a6c167601"
+dependencies = [
+ "cfg-if",
+ "cpufeatures 0.3.0",
+ "rand_core 0.10.0",
+]
+
 [[package]]
 name = "chrono"
-version = "0.4.43"
+version = "0.4.44"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "fac4744fb15ae8337dc853fee7fb3f4e48c0fbaa23d0afe49c447b4fab126118"
+checksum = "c673075a2e0e5f4a1dde27ce9dee1ea4558c7ffe648f576438a20ca1d2acc4b0"
 dependencies = [
  "iana-time-zone",
  "num-traits",
@@ -666,9 +677,9 @@ dependencies = [
 
 [[package]]
 name = "cmake"
-version = "0.1.57"
+version = "0.1.58"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "75443c44cd6b379beb8c5b45d85d0773baf31cce901fe7bb252f4eff3008ef7d"
+checksum = "c0f78a02292a74a88ac736019ab962ece0bc380e3f977bf72e376c5d78ff0678"
 dependencies = [
  "cc",
 ]
@@ -779,6 +790,15 @@ dependencies = [
  "libc",
 ]
 
+[[package]]
+name = "cpufeatures"
+version = "0.3.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "8b2a41393f66f16b0823bb79094d54ac5fbd34ab292ddafb9a0456ac9f87d201"
+dependencies = [
+ "libc",
+]
+
 [[package]]
 name = "crc32fast"
 version = "1.5.0"
@@ -870,7 +890,7 @@ dependencies = [
  "proc-macro2",
  "quote",
  "strsim",
- "syn 2.0.116",
+ "syn 2.0.117",
 ]
 
 [[package]]
@@ -881,7 +901,7 @@ checksum = "ac3984ec7bd6cfa798e62b4a642426a5be0e68f9401cfc2a01e3fa9ea2fcdb8d"
 dependencies = [
  "darling_core",
  "quote",
- "syn 2.0.116",
+ "syn 2.0.117",
 ]
 
 [[package]]
@@ -900,9 +920,9 @@ dependencies = [
 
 [[package]]
 name = "datafusion"
-version = "52.1.0"
+version = "53.0.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "d12ee9fdc6cdb5898c7691bb994f0ba606c4acc93a2258d78bb9f26ff8158bb3"
+checksum = "de9f8117889ba9503440f1dd79ebab32ba52ccf1720bb83cd718a29d4edc0d16"
 dependencies = [
  "arrow",
  "arrow-schema",
@@ -944,7 +964,7 @@ dependencies = [
  "object_store",
  "parking_lot",
  "parquet",
- "rand",
+ "rand 0.9.2",
  "regex",
  "sqlparser",
  "tempfile",
@@ -956,9 +976,9 @@ dependencies = [
 
 [[package]]
 name = "datafusion-catalog"
-version = "52.1.0"
+version = "53.0.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "462dc9ef45e5d688aeaae49a7e310587e81b6016b9d03bace5626ad0043e5a9e"
+checksum = "be893b73a13671f310ffcc8da2c546b81efcc54c22e0382c0a28aa3537017137"
 dependencies = [
  "arrow",
  "async-trait",
@@ -981,9 +1001,9 @@ dependencies = [
 
 [[package]]
 name = "datafusion-catalog-listing"
-version = "52.1.0"
+version = "53.0.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "1b96dbf1d728fc321817b744eb5080cdd75312faa6980b338817f68f3caa4208"
+checksum = "830487b51ed83807d6b32d6325f349c3144ae0c9bf772cf2a712db180c31d5e6"
 dependencies = [
  "arrow",
  "async-trait",
@@ -1004,9 +1024,9 @@ dependencies = [
 
 [[package]]
 name = "datafusion-common"
-version = "52.1.0"
+version = "53.0.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "3237a6ff0d2149af4631290074289cae548c9863c885d821315d54c6673a074a"
+checksum = "0d7663f3af955292f8004e74bcaf8f7ea3d66cc38438749615bb84815b61a293"
 dependencies = [
  "ahash",
  "apache-avro",
@@ -1016,6 +1036,7 @@ dependencies = [
  "half",
  "hashbrown 0.16.1",
  "indexmap",
+ "itertools",
  "libc",
  "log",
  "object_store",
@@ -1029,9 +1050,9 @@ dependencies = [
 
 [[package]]
 name = "datafusion-common-runtime"
-version = "52.1.0"
+version = "53.0.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "70b5e34026af55a1bfccb1ef0a763cf1f64e77c696ffcf5a128a278c31236528"
+checksum = "5f590205c7e32fe1fea48dd53ffb406e56ae0e7a062213a3ac848db8771641bd"
 dependencies = [
  "futures",
  "log",
@@ -1040,9 +1061,9 @@ dependencies = [
 
 [[package]]
 name = "datafusion-datasource"
-version = "52.1.0"
+version = "53.0.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "1b2a6be734cc3785e18bbf2a7f2b22537f6b9fb960d79617775a51568c281842"
+checksum = "fde1e030a9dc87b743c806fbd631f5ecfa2ccaa4ffb61fa19144a07fea406b79"
 dependencies = [
  "arrow",
  "async-compression",
@@ -1066,7 +1087,7 @@ dependencies = [
  "liblzma",
  "log",
  "object_store",
- "rand",
+ "rand 0.9.2",
  "tokio",
  "tokio-util",
  "url",
@@ -1075,9 +1096,9 @@ dependencies = [
 
 [[package]]
 name = "datafusion-datasource-arrow"
-version = "52.1.0"
+version = "53.0.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "1739b9b07c9236389e09c74f770e88aff7055250774e9def7d3f4f56b3dcc7be"
+checksum = "331ebae7055dc108f9b54994b93dff91f3a17445539efe5b74e89264f7b36e15"
 dependencies = [
  "arrow",
  "arrow-ipc",
@@ -1099,9 +1120,9 @@ dependencies = [
 
 [[package]]
 name = "datafusion-datasource-avro"
-version = "52.1.0"
+version = "53.0.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "828088c2fb681cc0e06fb42f541f76c82a0c10278f9fd6334e22c8d1e3574ee7"
+checksum = "49dda81c79b6ba57b1853a9158abc66eb85a3aa1cede0c517dabec6d8a4ed3aa"
 dependencies = [
  "apache-avro",
  "arrow",
@@ -1119,9 +1140,9 @@ dependencies = [
 
 [[package]]
 name = "datafusion-datasource-csv"
-version = "52.1.0"
+version = "53.0.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "61c73bc54b518bbba7c7650299d07d58730293cfba4356f6f428cc94c20b7600"
+checksum = "9e0d475088325e2986876aa27bb30d0574f72a22955a527d202f454681d55c5c"
 dependencies = [
  "arrow",
  "async-trait",
@@ -1142,9 +1163,9 @@ dependencies = [
 
 [[package]]
 name = "datafusion-datasource-json"
-version = "52.1.0"
+version = "53.0.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "37812c8494c698c4d889374ecfabbff780f1f26d9ec095dd1bddfc2a8ca12559"
+checksum = "ea1520d81f31770f3ad6ee98b391e75e87a68a5bb90de70064ace5e0a7182fe8"
 dependencies = [
  "arrow",
  "async-trait",
@@ -1159,14 +1180,16 @@ dependencies = [
  "datafusion-session",
  "futures",
  "object_store",
+ "serde_json",
  "tokio",
+ "tokio-stream",
 ]
 
 [[package]]
 name = "datafusion-datasource-parquet"
-version = "52.1.0"
+version = "53.0.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "2210937ecd9f0e824c397e73f4b5385c97cd1aff43ab2b5836fcfd2d321523fb"
+checksum = "95be805d0742ab129720f4c51ad9242cd872599cdb076098b03f061fcdc7f946"
 dependencies = [
  "arrow",
  "async-trait",
@@ -1194,36 +1217,38 @@ dependencies = [
 
 [[package]]
 name = "datafusion-doc"
-version = "52.1.0"
+version = "53.0.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "2c825f969126bc2ef6a6a02d94b3c07abff871acf4d6dd759ce1255edb7923ce"
+checksum = "5c93ad9e37730d2c7196e68616f3f2dd3b04c892e03acd3a8eeca6e177f3c06a"
 
 [[package]]
 name = "datafusion-execution"
-version = "52.1.0"
+version = "53.0.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "fa03ef05a2c2f90dd6c743e3e111078e322f4b395d20d4b4d431a245d79521ae"
+checksum = "9437d3cd5d363f9319f8122182d4d233427de79c7eb748f23054c9aaa0fdd8df"
 dependencies = [
  "arrow",
+ "arrow-buffer",
  "async-trait",
  "chrono",
  "dashmap",
  "datafusion-common",
  "datafusion-expr",
+ "datafusion-physical-expr-common",
  "futures",
  "log",
  "object_store",
  "parking_lot",
- "rand",
+ "rand 0.9.2",
  "tempfile",
  "url",
 ]
 
 [[package]]
 name = "datafusion-expr"
-version = "52.1.0"
+version = "53.0.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "ef33934c1f98ee695cc51192cc5f9ed3a8febee84fdbcd9131bf9d3a9a78276f"
+checksum = "67164333342b86521d6d93fa54081ee39839894fb10f7a700c099af96d7552cf"
 dependencies = [
  "arrow",
  "async-trait",
@@ -1244,9 +1269,9 @@ dependencies = [
 
 [[package]]
 name = "datafusion-expr-common"
-version = "52.1.0"
+version = "53.0.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "000c98206e3dd47d2939a94b6c67af4bfa6732dd668ac4fafdbde408fd9134ea"
+checksum = "ab05fdd00e05d5a6ee362882546d29d6d3df43a6c55355164a7fbee12d163bc9"
 dependencies = [
  "arrow",
  "datafusion-common",
@@ -1257,9 +1282,9 @@ dependencies = [
 
 [[package]]
 name = "datafusion-ffi"
-version = "52.1.0"
+version = "53.0.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "30f57f7f63a25a0b78b3f2a5e18c0ecbd54851b64064ac0d5a9eb05efd5586d2"
+checksum = "4b8250f7cdf463a0ad145f41d7508bcfa54c9b9f027317e599f0331097e3cc38"
 dependencies = [
  "abi_stable",
  "arrow",
@@ -1285,11 +1310,31 @@ dependencies = [
  "tokio",
 ]
 
+[[package]]
+name = "datafusion-ffi-example"
+version = "53.0.0"
+dependencies = [
+ "arrow",
+ "arrow-array",
+ "arrow-schema",
+ "async-trait",
+ "datafusion-catalog",
+ "datafusion-common",
+ "datafusion-expr",
+ "datafusion-ffi",
+ "datafusion-functions-aggregate",
+ "datafusion-functions-window",
+ "datafusion-python-util",
+ "pyo3",
+ "pyo3-build-config",
+ "pyo3-log",
+]
+
 [[package]]
 name = "datafusion-functions"
-version = "52.1.0"
+version = "53.0.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "379b01418ab95ca947014066248c22139fe9af9289354de10b445bd000d5d276"
+checksum = "04fb863482d987cf938db2079e07ab0d3bb64595f28907a6c2f8671ad71cca7e"
 dependencies = [
  "arrow",
  "arrow-buffer",
@@ -1308,8 +1353,9 @@ dependencies = [
  "itertools",
  "log",
  "md-5",
+ "memchr",
  "num-traits",
- "rand",
+ "rand 0.9.2",
  "regex",
  "sha2",
  "unicode-segmentation",
@@ -1318,9 +1364,9 @@ dependencies = [
 
 [[package]]
 name = "datafusion-functions-aggregate"
-version = "52.1.0"
+version = "53.0.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "fd00d5454ba4c3f8ebbd04bd6a6a9dc7ced7c56d883f70f2076c188be8459e4c"
+checksum = "829856f4e14275fb376c104f27cbf3c3b57a9cfe24885d98677525f5e43ce8d6"
 dependencies = [
  "ahash",
  "arrow",
@@ -1334,14 +1380,15 @@ dependencies = [
  "datafusion-physical-expr-common",
  "half",
  "log",
+ "num-traits",
  "paste",
 ]
 
 [[package]]
 name = "datafusion-functions-aggregate-common"
-version = "52.1.0"
+version = "53.0.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "aec06b380729a87210a4e11f555ec2d729a328142253f8d557b87593622ecc9f"
+checksum = "08af79cc3d2aa874a362fb97decfcbd73d687190cb096f16a6c85a7780cce311"
 dependencies = [
  "ahash",
  "arrow",
@@ -1352,9 +1399,9 @@ dependencies = [
 
 [[package]]
 name = "datafusion-functions-nested"
-version = "52.1.0"
+version = "53.0.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "904f48d45e0f1eb7d0eb5c0f80f2b5c6046a85454364a6b16a2e0b46f62e7dff"
+checksum = "465ae3368146d49c2eda3e2c0ef114424c87e8a6b509ab34c1026ace6497e790"
 dependencies = [
  "arrow",
  "arrow-ord",
@@ -1368,16 +1415,18 @@ dependencies = [
  "datafusion-functions-aggregate-common",
  "datafusion-macros",
  "datafusion-physical-expr-common",
+ "hashbrown 0.16.1",
  "itertools",
+ "itoa",
  "log",
  "paste",
 ]
 
 [[package]]
 name = "datafusion-functions-table"
-version = "52.1.0"
+version = "53.0.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "e9a0d20e2b887e11bee24f7734d780a2588b925796ac741c3118dd06d5aa77f0"
+checksum = "6156e6b22fcf1784112fc0173f3ae6e78c8fdb4d3ed0eace9543873b437e2af6"
 dependencies = [
  "arrow",
  "async-trait",
@@ -1391,9 +1440,9 @@ dependencies = [
 
 [[package]]
 name = "datafusion-functions-window"
-version = "52.1.0"
+version = "53.0.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "d3414b0a07e39b6979fe3a69c7aa79a9f1369f1d5c8e52146e66058be1b285ee"
+checksum = "ca7baec14f866729012efb89011a6973f3a346dc8090c567bfcd328deff551c1"
 dependencies = [
  "arrow",
  "datafusion-common",
@@ -1409,9 +1458,9 @@ dependencies = [
 
 [[package]]
 name = "datafusion-functions-window-common"
-version = "52.1.0"
+version = "53.0.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "5bf2feae63cd4754e31add64ce75cae07d015bce4bb41cd09872f93add32523a"
+checksum = "159228c3280d342658466bb556dc24de30047fe1d7e559dc5d16ccc5324166f9"
 dependencies = [
  "datafusion-common",
  "datafusion-physical-expr-common",
@@ -1419,20 +1468,20 @@ dependencies = [
 
 [[package]]
 name = "datafusion-macros"
-version = "52.1.0"
+version = "53.0.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "c4fe888aeb6a095c4bcbe8ac1874c4b9a4c7ffa2ba849db7922683ba20875aaf"
+checksum = "e5427e5da5edca4d21ea1c7f50e1c9421775fe33d7d5726e5641a833566e7578"
 dependencies = [
  "datafusion-doc",
  "quote",
- "syn 2.0.116",
+ "syn 2.0.117",
 ]
 
 [[package]]
 name = "datafusion-optimizer"
-version = "52.1.0"
+version = "53.0.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "8a6527c063ae305c11be397a86d8193936f4b84d137fe40bd706dfc178cf733c"
+checksum = "89099eefcd5b223ec685c36a41d35c69239236310d71d339f2af0fa4383f3f46"
 dependencies = [
  "arrow",
  "chrono",
@@ -1450,9 +1499,9 @@ dependencies = [
 
 [[package]]
 name = "datafusion-physical-expr"
-version = "52.1.0"
+version = "53.0.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "0bb028323dd4efd049dd8a78d78fe81b2b969447b39c51424167f973ac5811d9"
+checksum = "0f222df5195d605d79098ef37bdd5323bff0131c9d877a24da6ec98dfca9fe36"
 dependencies = [
  "ahash",
  "arrow",
@@ -1474,9 +1523,9 @@ dependencies = [
 
 [[package]]
 name = "datafusion-physical-expr-adapter"
-version = "52.1.0"
+version = "53.0.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "78fe0826aef7eab6b4b61533d811234a7a9e5e458331ebbf94152a51fc8ab433"
+checksum = "40838625d63d9c12549d81979db3dd675d159055eb9135009ba272ab0e8d0f64"
 dependencies = [
  "arrow",
  "datafusion-common",
@@ -1489,9 +1538,9 @@ dependencies = [
 
 [[package]]
 name = "datafusion-physical-expr-common"
-version = "52.1.0"
+version = "53.0.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "cfccd388620734c661bd8b7ca93c44cdd59fecc9b550eea416a78ffcbb29475f"
+checksum = "eacbcc4cfd502558184ed58fa3c72e775ec65bf077eef5fd2b3453db676f893c"
 dependencies = [
  "ahash",
  "arrow",
@@ -1506,9 +1555,9 @@ dependencies = [
 
 [[package]]
 name = "datafusion-physical-optimizer"
-version = "52.1.0"
+version = "53.0.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "bde5fa10e73259a03b705d5fddc136516814ab5f441b939525618a4070f5a059"
+checksum = "d501d0e1d0910f015677121601ac177ec59272ef5c9324d1147b394988f40941"
 dependencies = [
  "arrow",
  "datafusion-common",
@@ -1525,9 +1574,9 @@ dependencies = [
 
 [[package]]
 name = "datafusion-physical-plan"
-version = "52.1.0"
+version = "53.0.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "0e1098760fb29127c24cc9ade3277051dc73c9ed0ac0131bd7bcd742e0ad7470"
+checksum = "463c88ad6f1ecab1810f4c9f046898bee035b370137eb79b2b2db925e270631d"
 dependencies = [
  "ahash",
  "arrow",
@@ -1549,6 +1598,7 @@ dependencies = [
  "indexmap",
  "itertools",
  "log",
+ "num-traits",
  "parking_lot",
  "pin-project-lite",
  "tokio",
@@ -1556,9 +1606,9 @@ dependencies = [
 
 [[package]]
 name = "datafusion-proto"
-version = "52.1.0"
+version = "53.0.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "0cf75daf56aa6b1c6867cc33ff0fb035d517d6d06737fd355a3e1ef67cba6e7a"
+checksum = "677ee4448a010ed5faeff8d73ff78972c2ace59eff3cd7bd15833a1dafa00492"
 dependencies = [
  "arrow",
  "chrono",
@@ -1579,13 +1629,14 @@ dependencies = [
  "datafusion-proto-common",
  "object_store",
  "prost",
+ "rand 0.9.2",
 ]
 
 [[package]]
 name = "datafusion-proto-common"
-version = "52.1.0"
+version = "53.0.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "12a0cb3cce232a3de0d14ef44b58a6537aeb1362cfb6cf4d808691ddbb918956"
+checksum = "965eca01edc8259edbbd95883a00b6d81e329fd44a019cfac3a03b026a83eade"
 dependencies = [
  "arrow",
  "datafusion-common",
@@ -1594,9 +1645,9 @@ dependencies = [
 
 [[package]]
 name = "datafusion-pruning"
-version = "52.1.0"
+version = "53.0.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "64d0fef4201777b52951edec086c21a5b246f3c82621569ddb4a26f488bc38a9"
+checksum = "2857618a0ecbd8cd0cf29826889edd3a25774ec26b2995fc3862095c95d88fc6"
 dependencies = [
  "arrow",
  "datafusion-common",
@@ -1611,15 +1662,17 @@ dependencies = [
 
 [[package]]
 name = "datafusion-python"
-version = "52.0.0"
+version = "53.0.0"
 dependencies = [
  "arrow",
  "arrow-select",
  "async-trait",
+ "chrono",
  "cstr",
  "datafusion",
  "datafusion-ffi",
  "datafusion-proto",
+ "datafusion-python-util",
  "datafusion-substrait",
  "futures",
  "log",
@@ -1638,11 +1691,23 @@ dependencies = [
  "uuid",
 ]
 
+[[package]]
+name = "datafusion-python-util"
+version = "53.0.0"
+dependencies = [
+ "arrow",
+ "datafusion",
+ "datafusion-ffi",
+ "prost",
+ "pyo3",
+ "tokio",
+]
+
 [[package]]
 name = "datafusion-session"
-version = "52.1.0"
+version = "53.0.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "f71f1e39e8f2acbf1c63b0e93756c2e970a64729dab70ac789587d6237c4fde0"
+checksum = "ef8637e35022c5c775003b3ab1debc6b4a8f0eb41b069bdd5475dd3aa93f6eba"
 dependencies = [
  "async-trait",
  "datafusion-common",
@@ -1654,15 +1719,16 @@ dependencies = [
 
 [[package]]
 name = "datafusion-sql"
-version = "52.1.0"
+version = "53.0.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "f44693cfcaeb7a9f12d71d1c576c3a6dc025a12cef209375fa2d16fb3b5670ee"
+checksum = "12d9e9f16a1692a11c94bcc418191fa15fd2b4d72a0c1a0c607db93c0b84dd81"
 dependencies = [
  "arrow",
  "bigdecimal",
  "chrono",
  "datafusion-common",
  "datafusion-expr",
+ "datafusion-functions-nested",
  "indexmap",
  "log",
  "recursive",
@@ -1672,9 +1738,9 @@ dependencies = [
 
 [[package]]
 name = "datafusion-substrait"
-version = "52.1.0"
+version = "53.0.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "6042adacd0bd64e56c22f6a7f9ce0ce1793dd367c899d868179d029f110d9215"
+checksum = "d5e5656a7e63d51dd3e5af3dbd347ea83bbe993a77c66b854b74961570d16490"
 dependencies = [
  "async-recursion",
  "async-trait",
@@ -1688,7 +1754,6 @@ dependencies = [
  "substrait",
  "tokio",
  "url",
- "uuid",
 ]
 
 [[package]]
@@ -1710,7 +1775,7 @@ checksum = "97369cbbc041bc366949bc74d34658d6cda5621039731c6310521892a3a20ae0"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.116",
+ "syn 2.0.117",
 ]
 
 [[package]]
@@ -1863,7 +1928,7 @@ checksum = "e835b70203e41293343137df5c0664546da5745f82ec9b84d40be8336958447b"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.116",
+ "syn 2.0.117",
 ]
 
 [[package]]
@@ -1936,20 +2001,21 @@ dependencies = [
  "cfg-if",
  "js-sys",
  "libc",
- "r-efi",
+ "r-efi 5.3.0",
  "wasip2",
  "wasm-bindgen",
 ]
 
 [[package]]
 name = "getrandom"
-version = "0.4.1"
+version = "0.4.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "139ef39800118c7683f2fd3c98c1b23c09ae076556b435f8e9064ae108aaeeec"
+checksum = "0de51e6874e94e7bf76d726fc5d13ba782deca734ff60d5bb2fb2607c7406555"
 dependencies = [
  "cfg-if",
  "libc",
- "r-efi",
+ "r-efi 6.0.0",
+ "rand_core 0.10.0",
  "wasip2",
  "wasip3",
 ]
@@ -2286,15 +2352,6 @@ dependencies = [
  "serde_core",
 ]
 
-[[package]]
-name = "indoc"
-version = "2.0.7"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "79cf5c93f93228cf8efb3ba362535fb11199ac548a09ce117c9b1adc3030d706"
-dependencies = [
- "rustversion",
-]
-
 [[package]]
 name = "integer-encoding"
 version = "3.0.4"
@@ -2303,15 +2360,15 @@ checksum = "8bb03732005da905c88227371639bf1ad885cc712789c011c31c5fb3ab3ccf02"
 
 [[package]]
 name = "ipnet"
-version = "2.11.0"
+version = "2.12.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "469fb0b9cefa57e3ef31275ee7cacb78f2fdca44e4765491884a2b119d4eb130"
+checksum = "d98f6fed1fde3f8c21bc40a1abb88dd75e67924f9cffc3ef95607bad8017f8e2"
 
 [[package]]
 name = "iri-string"
-version = "0.7.10"
+version = "0.7.11"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "c91338f0783edbd6195decb37bae672fd3b165faffb89bf7b9e6942f8b1a731a"
+checksum = "d8e7418f59cc01c88316161279a7f665217ae316b388e58a0d10e29f54f1e5eb"
 dependencies = [
  "memchr",
  "serde",
@@ -2328,9 +2385,9 @@ dependencies = [
 
 [[package]]
 name = "itoa"
-version = "1.0.17"
+version = "1.0.18"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "92ecc6618181def0457392ccd0ee51198e065e016d1d527a7ac1b6dc7c1f09d2"
+checksum = "8f42a60cbdf9a97f5d2305f08a87dc4e09308d1276d28c869c684d7777685682"
 
 [[package]]
 name = "jobserver"
@@ -2344,9 +2401,9 @@ dependencies = [
 
 [[package]]
 name = "js-sys"
-version = "0.3.85"
+version = "0.3.91"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "8c942ebf8e95485ca0d52d97da7c5a2c387d0e7f0ba4c35e93bfcaee045955b3"
+checksum = "b49715b7073f385ba4bc528e5747d02e66cb39c6146efb66b781f131f0fb399c"
 dependencies = [
  "once_cell",
  "wasm-bindgen",
@@ -2423,9 +2480,9 @@ checksum = "2c4a545a15244c7d945065b5d392b2d2d7f21526fba56ce51467b06ed445e8f7"
 
 [[package]]
 name = "libc"
-version = "0.2.182"
+version = "0.2.183"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "6800badb6cb2082ffd7b6a67e6125bb39f18782f793520caee8cb8846be06112"
+checksum = "b5b646652bf6661599e1da8901b3b9522896f01e736bad5f723fe7a3a27f899d"
 
 [[package]]
 name = "libloading"
@@ -2475,9 +2532,9 @@ dependencies = [
 
 [[package]]
 name = "linux-raw-sys"
-version = "0.11.0"
+version = "0.12.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "df1d3c3b53da64cf5760482273a98e575c651a67eec7f77df96b5b642de8f039"
+checksum = "32a66949e030da00e8c7d4434b251670a91556f4144941d37452769c25d58a53"
 
 [[package]]
 name = "litemap"
@@ -2508,9 +2565,9 @@ checksum = "112b39cec0b298b6c1999fee3e31427f74f676e4cb9879ed1a121b43661a4154"
 
 [[package]]
 name = "lz4_flex"
-version = "0.12.0"
+version = "0.13.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "ab6473172471198271ff72e9379150e9dfd70d8e533e0752a27e515b48dd375e"
+checksum = "db9a0d582c2874f68138a16ce1867e0ffde6c0bb0a0df85e1f36d04146db488a"
 dependencies = [
  "twox-hash",
 ]
@@ -2531,15 +2588,6 @@ version = "2.8.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "f8ca58f447f06ed17d5fc4043ce1b10dd205e060fb3ce5b979b8ed8e59ff3f79"
 
-[[package]]
-name = "memoffset"
-version = "0.9.1"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "488016bfae457b036d996092f6cb448677611ce4449e970ceaf42695203f218a"
-dependencies = [
- "autocfg",
-]
-
 [[package]]
 name = "mimalloc"
 version = "0.1.48"
@@ -2561,9 +2609,9 @@ dependencies = [
 
 [[package]]
 name = "mio"
-version = "1.1.1"
+version = "1.2.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "a69bcab0ad47271a0234d9422b131806bf3968021e5dc9328caf2d4cd58557fc"
+checksum = "50b7e5b27aa02a74bac8c3f23f448f8d87ff11f92d3aac1a6ed369ee08cc56c1"
 dependencies = [
  "libc",
  "wasi",
@@ -2626,16 +2674,18 @@ dependencies = [
 
 [[package]]
 name = "object_store"
-version = "0.12.5"
+version = "0.13.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "fbfbfff40aeccab00ec8a910b57ca8ecf4319b335c542f2edcd19dd25a1e2a00"
+checksum = "622acbc9100d3c10e2ee15804b0caa40e55c933d5aa53814cd520805b7958a49"
 dependencies = [
  "async-trait",
  "base64",
  "bytes",
  "chrono",
  "form_urlencoded",
- "futures",
+ "futures-channel",
+ "futures-core",
+ "futures-util",
  "http",
  "http-body-util",
  "httparse",
@@ -2646,10 +2696,10 @@ dependencies = [
  "parking_lot",
  "percent-encoding",
  "quick-xml",
- "rand",
+ "rand 0.10.0",
  "reqwest",
  "ring",
- "rustls-pemfile",
+ "rustls-pki-types",
  "serde",
  "serde_json",
  "serde_urlencoded",
@@ -2664,9 +2714,9 @@ dependencies = [
 
 [[package]]
 name = "once_cell"
-version = "1.21.3"
+version = "1.21.4"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "42f5e15c9953c5e4ccceeb2e7382a716482c34515315f7b03532b8b4e8393d2d"
+checksum = "9f7c3e4beb33f85d45ae3e3a1792185706c8e16d043238c593331cc7cd313b50"
 
 [[package]]
 name = "openssl-probe"
@@ -2708,14 +2758,13 @@ dependencies = [
 
 [[package]]
 name = "parquet"
-version = "57.3.0"
+version = "58.1.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "6ee96b29972a257b855ff2341b37e61af5f12d6af1158b6dcdb5b31ea07bb3cb"
+checksum = "7d3f9f2205199603564127932b89695f52b62322f541d0fc7179d57c2e1c9877"
 dependencies = [
  "ahash",
  "arrow-array",
  "arrow-buffer",
- "arrow-cast",
  "arrow-data",
  "arrow-ipc",
  "arrow-schema",
@@ -2824,9 +2873,9 @@ dependencies = [
 
 [[package]]
 name = "pin-project-lite"
-version = "0.2.16"
+version = "0.2.17"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "3b3cff922bd51709b605d9ead9aa71031d81447142d828eb4a6eba76fe619f9b"
+checksum = "a89322df9ebe1c1578d689c92318e070967d1042b512afbe49518723f4e6d5cd"
 
 [[package]]
 name = "pin-utils"
@@ -2871,7 +2920,7 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "479ca8adacdd7ce8f1fb39ce9ecccbfe93a3f1344b3d0d97f20bc0196208f62b"
 dependencies = [
  "proc-macro2",
- "syn 2.0.116",
+ "syn 2.0.117",
 ]
 
 [[package]]
@@ -2908,7 +2957,7 @@ dependencies = [
  "prost",
  "prost-types",
  "regex",
- "syn 2.0.116",
+ "syn 2.0.117",
  "tempfile",
 ]
 
@@ -2922,7 +2971,7 @@ dependencies = [
  "itertools",
  "proc-macro2",
  "quote",
- "syn 2.0.116",
+ "syn 2.0.117",
 ]
 
 [[package]]
@@ -2955,28 +3004,26 @@ dependencies = [
 
 [[package]]
 name = "pyo3"
-version = "0.26.0"
+version = "0.28.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "7ba0117f4212101ee6544044dae45abe1083d30ce7b29c4b5cbdfa2354e07383"
+checksum = "cf85e27e86080aafd5a22eae58a162e133a589551542b3e5cee4beb27e54f8e1"
 dependencies = [
- "indoc",
  "libc",
- "memoffset",
  "once_cell",
  "portable-atomic",
  "pyo3-build-config",
  "pyo3-ffi",
  "pyo3-macros",
- "unindent",
 ]
 
 [[package]]
 name = "pyo3-async-runtimes"
-version = "0.26.0"
+version = "0.28.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "e6ee6d4cb3e8d5b925f5cdb38da183e0ff18122eb2048d4041c9e7034d026e23"
+checksum = "9e7364a95bf00e8377bbf9b0f09d7ff9715a29d8fcf93b47d1a967363b973178"
 dependencies = [
- "futures",
+ "futures-channel",
+ "futures-util",
  "once_cell",
  "pin-project-lite",
  "pyo3",
@@ -2985,18 +3032,18 @@ dependencies = [
 
 [[package]]
 name = "pyo3-build-config"
-version = "0.26.0"
+version = "0.28.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "4fc6ddaf24947d12a9aa31ac65431fb1b851b8f4365426e182901eabfb87df5f"
+checksum = "8bf94ee265674bf76c09fa430b0e99c26e319c945d96ca0d5a8215f31bf81cf7"
 dependencies = [
  "target-lexicon",
 ]
 
 [[package]]
 name = "pyo3-ffi"
-version = "0.26.0"
+version = "0.28.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "025474d3928738efb38ac36d4744a74a400c901c7596199e20e45d98eb194105"
+checksum = "491aa5fc66d8059dd44a75f4580a2962c1862a1c2945359db36f6c2818b748dc"
 dependencies = [
  "libc",
  "pyo3-build-config",
@@ -3015,27 +3062,27 @@ dependencies = [
 
 [[package]]
 name = "pyo3-macros"
-version = "0.26.0"
+version = "0.28.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "2e64eb489f22fe1c95911b77c44cc41e7c19f3082fc81cce90f657cdc42ffded"
+checksum = "f5d671734e9d7a43449f8480f8b38115df67bef8d21f76837fa75ee7aaa5e52e"
 dependencies = [
  "proc-macro2",
  "pyo3-macros-backend",
  "quote",
- "syn 2.0.116",
+ "syn 2.0.117",
 ]
 
 [[package]]
 name = "pyo3-macros-backend"
-version = "0.26.0"
+version = "0.28.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "100246c0ecf400b475341b8455a9213344569af29a3c841d29270e53102e0fcf"
+checksum = "22faaa1ce6c430a1f71658760497291065e6450d7b5dc2bcf254d49f66ee700a"
 dependencies = [
  "heck",
  "proc-macro2",
  "pyo3-build-config",
  "quote",
- "syn 2.0.116",
+ "syn 2.0.117",
 ]
 
 [[package]]
@@ -3046,9 +3093,9 @@ checksum = "5a651516ddc9168ebd67b24afd085a718be02f8858fe406591b013d101ce2f40"
 
 [[package]]
 name = "quick-xml"
-version = "0.38.4"
+version = "0.39.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "b66c2058c55a409d601666cffe35f04333cf1013010882cec174a7467cd4e21c"
+checksum = "958f21e8e7ceb5a1aa7fa87fab28e7c75976e0bfe7e23ff069e0a260f894067d"
 dependencies = [
  "memchr",
  "serde",
@@ -3076,14 +3123,14 @@ dependencies = [
 
 [[package]]
 name = "quinn-proto"
-version = "0.11.13"
+version = "0.11.14"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "f1906b49b0c3bc04b5fe5d86a77925ae6524a19b816ae38ce1e426255f1d8a31"
+checksum = "434b42fec591c96ef50e21e886936e66d3cc3f737104fdb9b737c40ffb94c098"
 dependencies = [
  "bytes",
  "getrandom 0.3.4",
  "lru-slab",
- "rand",
+ "rand 0.9.2",
  "ring",
  "rustc-hash",
  "rustls",
@@ -3111,9 +3158,9 @@ dependencies = [
 
 [[package]]
 name = "quote"
-version = "1.0.44"
+version = "1.0.45"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "21b2ebcf727b7760c461f091f9f0f539b77b8e87f2fd88131e7f1b433b3cece4"
+checksum = "41f2619966050689382d2b44f664f4bc593e129785a36d6ee376ddf37259b924"
 dependencies = [
  "proc-macro2",
 ]
@@ -3124,6 +3171,12 @@ version = "5.3.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "69cdb34c158ceb288df11e18b4bd39de994f6657d83847bdffdbd7f346754b0f"
 
+[[package]]
+name = "r-efi"
+version = "6.0.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "f8dcc9c7d52a811697d2151c701e0d08956f92b0e24136cf4cf27b57a6a0d9bf"
+
 [[package]]
 name = "rand"
 version = "0.9.2"
@@ -3131,7 +3184,18 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "6db2770f06117d490610c7488547d543617b21bfa07796d7a12f6f1bd53850d1"
 dependencies = [
  "rand_chacha",
- "rand_core",
+ "rand_core 0.9.5",
+]
+
+[[package]]
+name = "rand"
+version = "0.10.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "bc266eb313df6c5c09c1c7b1fbe2510961e5bcd3add930c1e31f7ed9da0feff8"
+dependencies = [
+ "chacha20",
+ "getrandom 0.4.2",
+ "rand_core 0.10.0",
 ]
 
 [[package]]
@@ -3141,7 +3205,7 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "d3022b5f1df60f26e1ffddd6c66e8aa15de382ae63b3a0c1bfc0e4d3e3f325cb"
 dependencies = [
  "ppv-lite86",
- "rand_core",
+ "rand_core 0.9.5",
 ]
 
 [[package]]
@@ -3153,6 +3217,12 @@ dependencies = [
  "getrandom 0.3.4",
 ]
 
+[[package]]
+name = "rand_core"
+version = "0.10.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "0c8d0fd677905edcbeedbf2edb6494d676f0e98d54d5cf9bda0b061cb8fb8aba"
+
 [[package]]
 name = "recursive"
 version = "0.1.1"
@@ -3170,7 +3240,7 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "76009fbe0614077fc1a2ce255e3a1881a2e3a3527097d5dc6d8212c585e7e38b"
 dependencies = [
  "quote",
- "syn 2.0.116",
+ "syn 2.0.117",
 ]
 
 [[package]]
@@ -3213,9 +3283,9 @@ checksum = "cab834c73d247e67f4fae452806d17d3c7501756d98c8808d7c9c7aa7d18f973"
 
 [[package]]
 name = "regex-syntax"
-version = "0.8.9"
+version = "0.8.10"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "a96887878f22d7bad8a3b6dc5b7440e0ada9a245242924394987b21cf2210a4c"
+checksum = "dc897dd8d9e8bd1ed8cdad82b5966c3e0ecae09fb1907d58efaa013543185d0a"
 
 [[package]]
 name = "regress"
@@ -3309,9 +3379,9 @@ dependencies = [
 
 [[package]]
 name = "rustix"
-version = "1.1.3"
+version = "1.1.4"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "146c9e247ccc180c1f61615433868c99f3de3ae256a30a43b49f67c2d9171f34"
+checksum = "b6fe4565b9518b83ef4f91bb47ce29620ca828bd32cb7e408f0062e9930ba190"
 dependencies = [
  "bitflags",
  "errno",
@@ -3322,9 +3392,9 @@ dependencies = [
 
 [[package]]
 name = "rustls"
-version = "0.23.36"
+version = "0.23.37"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "c665f33d38cea657d9614f766881e4d510e0eda4239891eea56b4cadcf01801b"
+checksum = "758025cb5fccfd3bc2fd74708fd4682be41d99e5dff73c377c0646c6012c73a4"
 dependencies = [
  "once_cell",
  "ring",
@@ -3346,15 +3416,6 @@ dependencies = [
  "security-framework",
 ]
 
-[[package]]
-name = "rustls-pemfile"
-version = "2.2.0"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "dce314e5fee3f39953d46bb63bb8a46d40c2f8fb7cc5a3b6cab2bde9721d6e50"
-dependencies = [
- "rustls-pki-types",
-]
-
 [[package]]
 name = "rustls-pki-types"
 version = "1.14.0"
@@ -3367,9 +3428,9 @@ dependencies = [
 
 [[package]]
 name = "rustls-webpki"
-version = "0.103.9"
+version = "0.103.10"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "d7df23109aa6c1567d1c575b9952556388da57401e4ace1d15f79eedad0d8f53"
+checksum = "df33b2b81ac578cabaf06b89b0631153a3f416b0a886e8a7a1707fb51abbd1ef"
 dependencies = [
  "ring",
  "rustls-pki-types",
@@ -3399,9 +3460,9 @@ dependencies = [
 
 [[package]]
 name = "schannel"
-version = "0.1.28"
+version = "0.1.29"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "891d81b926048e76efe18581bf793546b4c0eaf8448d72be8de2bbee5fd166e1"
+checksum = "91c1b7e4904c873ef0710c1f407dde2e6287de2bebc1bbbf7d430bb7cbffd939"
 dependencies = [
  "windows-sys 0.61.2",
 ]
@@ -3427,7 +3488,7 @@ dependencies = [
  "proc-macro2",
  "quote",
  "serde_derive_internals",
- "syn 2.0.116",
+ "syn 2.0.117",
 ]
 
 [[package]]
@@ -3438,9 +3499,9 @@ checksum = "94143f37725109f92c262ed2cf5e59bce7498c01bcc1502d7b9afe439a4e9f49"
 
 [[package]]
 name = "security-framework"
-version = "3.6.0"
+version = "3.7.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "d17b898a6d6948c3a8ee4372c17cb384f90d2e6e912ef00895b14fd7ab54ec38"
+checksum = "b7f4bc775c73d9a02cde8bf7b2ec4c9d12743edf609006c7facc23998404cd1d"
 dependencies = [
  "bitflags",
  "core-foundation",
@@ -3451,9 +3512,9 @@ dependencies = [
 
 [[package]]
 name = "security-framework-sys"
-version = "2.16.0"
+version = "2.17.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "321c8673b092a9a42605034a9879d73cb79101ed5fd117bc9a597b89b4e9e61a"
+checksum = "6ce2691df843ecc5d231c0b14ece2acc3efb62c0a398c7e1d875f3983ce020e3"
 dependencies = [
  "core-foundation-sys",
  "libc",
@@ -3512,7 +3573,7 @@ checksum = "d540f220d3187173da220f885ab66608367b6574e925011a9353e4badda91d79"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.116",
+ "syn 2.0.117",
 ]
 
 [[package]]
@@ -3523,7 +3584,7 @@ checksum = "18d26a20a969b9e3fdf2fc2d9f21eda6c40e2de84c9408bb5d3b05d499aae711"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.116",
+ "syn 2.0.117",
 ]
 
 [[package]]
@@ -3541,14 +3602,14 @@ dependencies = [
 
 [[package]]
 name = "serde_tokenstream"
-version = "0.2.2"
+version = "0.2.3"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "64060d864397305347a78851c51588fd283767e7e7589829e8121d65512340f1"
+checksum = "d7c49585c52c01f13c5c2ebb333f14f6885d76daa768d8a037d28017ec538c69"
 dependencies = [
  "proc-macro2",
  "quote",
  "serde",
- "syn 2.0.116",
+ "syn 2.0.117",
 ]
 
 [[package]]
@@ -3583,7 +3644,7 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "a7507d819769d01a365ab707794a4084392c824f54a7a6a7862f8c3d0892b283"
 dependencies = [
  "cfg-if",
- "cpufeatures",
+ "cpufeatures 0.2.17",
  "digest",
 ]
 
@@ -3595,9 +3656,9 @@ checksum = "0fda2ff0d084019ba4d7c6f371c95d8fd75ce3524c3cb8fb653a3023f6323e64"
 
 [[package]]
 name = "simd-adler32"
-version = "0.3.8"
+version = "0.3.9"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "e320a6c5ad31d271ad523dcf3ad13e2767ad8b1cb8f047f75a8aeaf8da139da2"
+checksum = "703d5c7ef118737c72f1af64ad2f6f8c5e1921f818cdcb97b8fe6fc69bf66214"
 
 [[package]]
 name = "simdutf8"
@@ -3631,19 +3692,19 @@ checksum = "1b6b67fb9a61334225b5b790716f609cd58395f895b3fe8b328786812a40bc3b"
 
 [[package]]
 name = "socket2"
-version = "0.6.2"
+version = "0.6.3"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "86f4aa3ad99f2088c990dfa82d367e19cb29268ed67c574d10d0a4bfe71f07e0"
+checksum = "3a766e1110788c36f4fa1c2b71b387a7815aa65f88ce0229841826633d93723e"
 dependencies = [
  "libc",
- "windows-sys 0.60.2",
+ "windows-sys 0.61.2",
 ]
 
 [[package]]
 name = "sqlparser"
-version = "0.59.0"
+version = "0.61.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "4591acadbcf52f0af60eafbb2c003232b2b4cd8de5f0e9437cb8b1b59046cc0f"
+checksum = "dbf5ea8d4d7c808e1af1cbabebca9a2abe603bcefc22294c5b95018d53200cb7"
 dependencies = [
  "log",
  "recursive",
@@ -3652,13 +3713,13 @@ dependencies = [
 
 [[package]]
 name = "sqlparser_derive"
-version = "0.3.0"
+version = "0.5.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "da5fc6819faabb412da764b99d3b713bb55083c11e7e0c00144d386cd6a1939c"
+checksum = "a6dd45d8fc1c79299bfbb7190e42ccbbdf6a5f52e4a6ad98d92357ea965bd289"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.116",
+ "syn 2.0.117",
 ]
 
 [[package]]
@@ -3701,7 +3762,7 @@ dependencies = [
  "heck",
  "proc-macro2",
  "quote",
- "syn 2.0.116",
+ "syn 2.0.117",
 ]
 
 [[package]]
@@ -3725,7 +3786,7 @@ dependencies = [
  "serde",
  "serde_json",
  "serde_yaml",
- "syn 2.0.116",
+ "syn 2.0.117",
  "typify",
  "walkdir",
 ]
@@ -3749,9 +3810,9 @@ dependencies = [
 
 [[package]]
 name = "syn"
-version = "2.0.116"
+version = "2.0.117"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "3df424c70518695237746f84cede799c9c58fcb37450d7b23716568cc8bc69cb"
+checksum = "e665b8803e7b1d2a727f4023456bbbbe74da67099c585258af0ad9c5013b9b99"
 dependencies = [
  "proc-macro2",
  "quote",
@@ -3775,7 +3836,7 @@ checksum = "728a70f3dbaf5bab7f0c4b1ac8d7ae5ea60a4b5549c8a5914361c99147a709d2"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.116",
+ "syn 2.0.117",
 ]
 
 [[package]]
@@ -3786,12 +3847,12 @@ checksum = "adb6935a6f5c20170eeceb1a3835a49e12e19d792f6dd344ccc76a985ca5a6ca"
 
 [[package]]
 name = "tempfile"
-version = "3.25.0"
+version = "3.27.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "0136791f7c95b1f6dd99f9cc786b91bb81c3800b639b3478e561ddb7be95e5f1"
+checksum = "32497e9a4c7b38532efcdebeef879707aa9f794296a4f0244f6f69e9bc8574bd"
 dependencies = [
  "fastrand",
- "getrandom 0.4.1",
+ "getrandom 0.4.2",
  "once_cell",
  "rustix",
  "windows-sys 0.61.2",
@@ -3814,7 +3875,7 @@ checksum = "ebc4ee7f67670e9b64d05fa4253e753e016c6c95ff35b89b7941d6b856dec1d5"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.116",
+ "syn 2.0.117",
 ]
 
 [[package]]
@@ -3849,9 +3910,9 @@ dependencies = [
 
 [[package]]
 name = "tinyvec"
-version = "1.10.0"
+version = "1.11.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "bfa5fdc3bce6191a1dbc8c02d5c8bffcf557bafa17c124c5264a458f1b0613fa"
+checksum = "3e61e67053d25a4e82c844e8424039d9745781b3fc4f32b8d55ed50f5f667ef3"
 dependencies = [
  "tinyvec_macros",
 ]
@@ -3864,9 +3925,9 @@ checksum = "1f3ccbac311fea05f86f61904b462b55fb3df8837a366dfc601a0161d0532f20"
 
 [[package]]
 name = "tokio"
-version = "1.49.0"
+version = "1.50.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "72a2903cd7736441aac9df9d7688bd0ce48edccaadf181c3b90be801e81d3d86"
+checksum = "27ad5e34374e03cfffefc301becb44e9dc3c17584f414349ebe29ed26661822d"
 dependencies = [
  "bytes",
  "libc",
@@ -3879,13 +3940,13 @@ dependencies = [
 
 [[package]]
 name = "tokio-macros"
-version = "2.6.0"
+version = "2.6.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "af407857209536a95c8e56f8231ef2c2e2aff839b22e07a1ffcbc617e9db9fa5"
+checksum = "5c55a2eff8b69ce66c84f85e1da1c233edc36ceb85a2058d11b0d6a3c7e7569c"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.116",
+ "syn 2.0.117",
 ]
 
 [[package]]
@@ -3898,6 +3959,18 @@ dependencies = [
  "tokio",
 ]
 
+[[package]]
+name = "tokio-stream"
+version = "0.1.18"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "32da49809aab5c3bc678af03902d4ccddea2a87d028d86392a4b1560c6906c70"
+dependencies = [
+ "futures-core",
+ "pin-project-lite",
+ "tokio",
+ "tokio-util",
+]
+
 [[package]]
 name = "tokio-util"
 version = "0.7.18"
@@ -3975,7 +4048,7 @@ checksum = "7490cfa5ec963746568740651ac6781f701c9c5ea257c58e057f3ba8cf69e8da"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.116",
+ "syn 2.0.117",
 ]
 
 [[package]]
@@ -4057,7 +4130,7 @@ dependencies = [
  "semver",
  "serde",
  "serde_json",
- "syn 2.0.116",
+ "syn 2.0.117",
  "thiserror",
  "unicode-ident",
 ]
@@ -4075,7 +4148,7 @@ dependencies = [
  "serde",
  "serde_json",
  "serde_tokenstream",
- "syn 2.0.116",
+ "syn 2.0.117",
  "typify-impl",
 ]
 
@@ -4087,9 +4160,9 @@ checksum = "e6e4313cd5fcd3dad5cafa179702e2b244f760991f45397d14d4ebf38247da75"
 
 [[package]]
 name = "unicode-segmentation"
-version = "1.12.0"
+version = "1.13.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "f6ccf251212114b54433ec949fd6a7841275f9ada20dddd2f29e9ceea4501493"
+checksum = "9629274872b2bfaf8d66f5f15725007f635594914870f65218920345aa11aa8c"
 
 [[package]]
 name = "unicode-width"
@@ -4103,12 +4176,6 @@ version = "0.2.6"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "ebc1c04c71510c7f702b52b7c350734c9ff1295c464a03335b00bb84fc54f853"
 
-[[package]]
-name = "unindent"
-version = "0.2.4"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "7264e107f553ccae879d21fbea1d6724ac785e8c3bfc762137959b5802826ef3"
-
 [[package]]
 name = "unsafe-libyaml"
 version = "0.2.11"
@@ -4141,11 +4208,11 @@ checksum = "b6c140620e7ffbb22c2dee59cafe6084a59b5ffc27a8859a5f0d494b5d52b6be"
 
 [[package]]
 name = "uuid"
-version = "1.21.0"
+version = "1.23.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "b672338555252d43fd2240c714dc444b8c6fb0a5c5335e65a07bba7742735ddb"
+checksum = "5ac8b6f42ead25368cf5b098aeb3dc8a1a2c05a3eee8a9a1a68c640edbfc79d9"
 dependencies = [
- "getrandom 0.4.1",
+ "getrandom 0.4.2",
  "js-sys",
  "serde_core",
  "wasm-bindgen",
@@ -4202,9 +4269,9 @@ dependencies = [
 
 [[package]]
 name = "wasm-bindgen"
-version = "0.2.108"
+version = "0.2.114"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "64024a30ec1e37399cf85a7ffefebdb72205ca1c972291c51512360d90bd8566"
+checksum = "6532f9a5c1ece3798cb1c2cfdba640b9b3ba884f5db45973a6f442510a87d38e"
 dependencies = [
  "cfg-if",
  "once_cell",
@@ -4215,9 +4282,9 @@ dependencies = [
 
 [[package]]
 name = "wasm-bindgen-futures"
-version = "0.4.58"
+version = "0.4.64"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "70a6e77fd0ae8029c9ea0063f87c46fde723e7d887703d74ad2616d792e51e6f"
+checksum = "e9c5522b3a28661442748e09d40924dfb9ca614b21c00d3fd135720e48b67db8"
 dependencies = [
  "cfg-if",
  "futures-util",
@@ -4229,9 +4296,9 @@ dependencies = [
 
 [[package]]
 name = "wasm-bindgen-macro"
-version = "0.2.108"
+version = "0.2.114"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "008b239d9c740232e71bd39e8ef6429d27097518b6b30bdf9086833bd5b6d608"
+checksum = "18a2d50fcf105fb33bb15f00e7a77b772945a2ee45dcf454961fd843e74c18e6"
 dependencies = [
  "quote",
  "wasm-bindgen-macro-support",
@@ -4239,22 +4306,22 @@ dependencies = [
 
 [[package]]
 name = "wasm-bindgen-macro-support"
-version = "0.2.108"
+version = "0.2.114"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "5256bae2d58f54820e6490f9839c49780dff84c65aeab9e772f15d5f0e913a55"
+checksum = "03ce4caeaac547cdf713d280eda22a730824dd11e6b8c3ca9e42247b25c631e3"
 dependencies = [
  "bumpalo",
  "proc-macro2",
  "quote",
- "syn 2.0.116",
+ "syn 2.0.117",
  "wasm-bindgen-shared",
 ]
 
 [[package]]
 name = "wasm-bindgen-shared"
-version = "0.2.108"
+version = "0.2.114"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "1f01b580c9ac74c8d8f0c0e4afb04eeef2acf145458e52c03845ee9cd23e3d12"
+checksum = "75a326b8c223ee17883a4251907455a2431acc2791c98c26279376490c378c16"
 dependencies = [
  "unicode-ident",
 ]
@@ -4308,9 +4375,9 @@ dependencies = [
 
 [[package]]
 name = "web-sys"
-version = "0.3.85"
+version = "0.3.91"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "312e32e551d92129218ea9a2452120f4aabc03529ef03e4d0d82fb2780608598"
+checksum = "854ba17bb104abfb26ba36da9729addc7ce7f06f5c0f90f3c391f8461cca21f9"
 dependencies = [
  "js-sys",
  "wasm-bindgen",
@@ -4378,7 +4445,7 @@ checksum = "053e2e040ab57b9dc951b72c264860db7eb3b0200ba345b4e4c3b14f67855ddf"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.116",
+ "syn 2.0.117",
 ]
 
 [[package]]
@@ -4389,7 +4456,7 @@ checksum = "3f316c4a2570ba26bbec722032c4099d8c8bc095efccdc15688708623367e358"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.116",
+ "syn 2.0.117",
 ]
 
 [[package]]
@@ -4611,7 +4678,7 @@ dependencies = [
  "heck",
  "indexmap",
  "prettyplease",
- "syn 2.0.116",
+ "syn 2.0.117",
  "wasm-metadata",
  "wit-bindgen-core",
  "wit-component",
@@ -4627,7 +4694,7 @@ dependencies = [
  "prettyplease",
  "proc-macro2",
  "quote",
- "syn 2.0.116",
+ "syn 2.0.117",
  "wit-bindgen-core",
  "wit-bindgen-rust",
 ]
@@ -4694,28 +4761,28 @@ checksum = "b659052874eb698efe5b9e8cf382204678a0086ebf46982b79d6ca3182927e5d"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.116",
+ "syn 2.0.117",
  "synstructure",
 ]
 
 [[package]]
 name = "zerocopy"
-version = "0.8.39"
+version = "0.8.47"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "db6d35d663eadb6c932438e763b262fe1a70987f9ae936e60158176d710cae4a"
+checksum = "efbb2a062be311f2ba113ce66f697a4dc589f85e78a4aea276200804cea0ed87"
 dependencies = [
  "zerocopy-derive",
 ]
 
 [[package]]
 name = "zerocopy-derive"
-version = "0.8.39"
+version = "0.8.47"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "4122cd3169e94605190e77839c9a40d40ed048d305bfdc146e7df40ab0f3e517"
+checksum = "0e8bc7269b54418e7aeeef514aa68f8690b8c0489a06b0136e5f57c4c5ccab89"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.116",
+ "syn 2.0.117",
 ]
 
 [[package]]
@@ -4735,7 +4802,7 @@ checksum = "d71e5d6e06ab090c67b5e44993ec16b72dcbaabc526db883a360057678b48502"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.116",
+ "syn 2.0.117",
  "synstructure",
 ]
 
@@ -4775,14 +4842,14 @@ checksum = "eadce39539ca5cb3985590102671f2567e659fca9666581ad3411d59207951f3"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.116",
+ "syn 2.0.117",
 ]
 
 [[package]]
 name = "zlib-rs"
-version = "0.6.2"
+version = "0.6.3"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "c745c48e1007337ed136dc99df34128b9faa6ed542d80a1c673cf55a6d7236c8"
+checksum = "3be3d40e40a133f9c916ee3f9f4fa2d9d63435b5fbe1bfc6d9dae0aa0ada1513"
 
 [[package]]
 name = "zmij"
diff --git a/Cargo.toml b/Cargo.toml
index afa167bb1..d0e87a9a4 100644
--- a/Cargo.toml
+++ b/Cargo.toml
@@ -15,9 +15,8 @@
 # specific language governing permissions and limitations
 # under the License.
 
-[package]
-name = "datafusion-python"
-version = "52.0.0"
+[workspace.package]
+version = "53.0.0"
 homepage = "https://datafusion.apache.org/python"
 repository = "https://github.com/apache/datafusion-python"
 authors = ["Apache DataFusion <dev@datafusion.apache.org>"]
@@ -26,68 +25,49 @@ readme = "README.md"
 license = "Apache-2.0"
 edition = "2024"
 rust-version = "1.88"
-include = [
-  "/src",
-  "/datafusion",
-  "/LICENSE.txt",
-  "build.rs",
-  "pyproject.toml",
-  "Cargo.toml",
-  "Cargo.lock",
-]
 
-[features]
-default = ["mimalloc"]
-protoc = ["datafusion-substrait/protoc"]
-substrait = ["dep:datafusion-substrait"]
+[workspace]
+members = ["crates/core", "crates/util", "examples/datafusion-ffi-example"]
+resolver = "3"
 
-[dependencies]
-tokio = { version = "1.47", features = [
-  "macros",
-  "rt",
-  "rt-multi-thread",
-  "sync",
-] }
-pyo3 = { version = "0.26", features = [
-  "extension-module",
-  "abi3",
-  "abi3-py310",
-] }
-pyo3-async-runtimes = { version = "0.26", features = ["tokio-runtime"] }
-pyo3-log = "0.13.2"
-arrow = { version = "57", features = ["pyarrow"] }
-arrow-select = { version = "57" }
-datafusion = { version = "52", features = ["avro", "unicode_expressions"] }
-datafusion-substrait = { version = "52", optional = true }
-datafusion-proto = { version = "52" }
-datafusion-ffi = { version = "52" }
-prost = "0.14.1" # keep in line with `datafusion-substrait`
+[workspace.dependencies]
+tokio = { version = "1.50" }
+pyo3 = { version = "0.28" }
+pyo3-async-runtimes = { version = "0.28" }
+pyo3-log = "0.13.3"
+chrono = { version = "0.4", default-features = false }
+arrow = { version = "58" }
+arrow-array = { version = "58" }
+arrow-schema = { version = "58" }
+arrow-select = { version = "58" }
+datafusion = { version = "53" }
+datafusion-substrait = { version = "53" }
+datafusion-proto = { version = "53" }
+datafusion-ffi = { version = "53" }
+datafusion-catalog = { version = "53", default-features = false }
+datafusion-common = { version = "53", default-features = false }
+datafusion-functions-aggregate = { version = "53" }
+datafusion-functions-window = { version = "53" }
+datafusion-expr = { version = "53" }
+prost = "0.14.3"
 serde_json = "1"
-uuid = { version = "1.18", features = ["v4"] }
-mimalloc = { version = "0.1", optional = true, default-features = false, features = [
-  "local_dynamic_tls",
-] }
+uuid = { version = "1.23" }
+mimalloc = { version = "0.1", default-features = false }
 async-trait = "0.1.89"
 futures = "0.3"
 cstr = "0.2"
-object_store = { version = "0.12.4", features = [
-  "aws",
-  "gcp",
-  "azure",
-  "http",
-] }
+object_store = { version = "0.13.1" }
 url = "2"
-log = "0.4.27"
+log = "0.4.29"
 parking_lot = "0.12"
-
-[build-dependencies]
-prost-types = "0.14.1"     # keep in line with `datafusion-substrait`
-pyo3-build-config = "0.26"
-
-[lib]
-name = "datafusion_python"
-crate-type = ["cdylib", "rlib"]
+prost-types = "0.14.3"                                                # keep in line with `datafusion-substrait`
+pyo3-build-config = "0.28"
+datafusion-python-util = { path = "crates/util", version = "53.0.0" }
 
 [profile.release]
-lto = true
-codegen-units = 1
+lto = "thin"
+codegen-units = 2
+
+# We cannot publish to crates.io with any patches in the below section. Developers
+# must remove any entries in this section before creating a release candidate.
+[patch.crates-io]
diff --git a/README.md b/README.md
index 810ac8710..7849e7a02 100644
--- a/README.md
+++ b/README.md
@@ -275,7 +275,16 @@ needing to activate the virtual environment:
 
 ```bash
 uv run --no-project maturin develop --uv
-uv run --no-project pytest .
+uv run --no-project pytest
+```
+
+To run the FFI tests within the examples folder, after you have built
+`datafusion-python` with the previous commands:
+
+```bash
+cd examples/datafusion-ffi-example
+uv run --no-project maturin develop --uv
+uv run --no-project pytest python/tests/_test_*py
 ```
 
 ### Running & Installing pre-commit hooks
@@ -303,6 +312,33 @@ There are scripts in `ci/scripts` for running Rust and Python linters.
 ./ci/scripts/rust_toml_fmt.sh
 ```
 
+## Checking Upstream DataFusion Coverage
+
+This project includes an [AI agent skill](.ai/skills/check-upstream/SKILL.md) for auditing which
+features from the upstream Apache DataFusion Rust library are not yet exposed in these Python
+bindings. This is useful when adding missing functions, auditing API coverage, or ensuring parity
+with upstream.
+
+The skill accepts an optional area argument:
+
+```
+scalar functions
+aggregate functions
+window functions
+dataframe
+session context
+ffi types
+all
+```
+
+If no argument is provided, it defaults to checking all areas. The skill will fetch the upstream
+DataFusion documentation, compare it against the functions and methods exposed in this project, and
+produce a coverage report listing what is currently exposed and what is missing.
+
+The skill definition lives in `.ai/skills/check-upstream/SKILL.md` and follows the
+[Agent Skills](https://agentskills.io) open standard. It can be used by any AI coding agent that
+supports skill discovery, or followed manually.
+
 ## How to update dependencies
 
 To change test dependencies, change the `pyproject.toml` and run
diff --git a/python/datafusion/udf.py b/conftest.py
similarity index 58%
rename from python/datafusion/udf.py
rename to conftest.py
index c7265fa09..0c9410636 100644
--- a/python/datafusion/udf.py
+++ b/conftest.py
@@ -15,15 +15,22 @@
 # specific language governing permissions and limitations
 # under the License.
 
-"""Deprecated module for user defined functions."""
+"""Pytest configuration for doctest namespace injection."""
 
-import warnings
+import datafusion as dfn
+import numpy as np
+import pyarrow as pa
+import pytest
+from datafusion import col, lit
+from datafusion import functions as F
 
-from datafusion.user_defined import *  # noqa: F403
 
-warnings.warn(
-    "The module 'udf' is deprecated and will be removed in the next release. "
-    "Please use 'user_defined' instead.",
-    DeprecationWarning,
-    stacklevel=2,
-)
+@pytest.fixture(autouse=True)
+def _doctest_namespace(doctest_namespace: dict) -> None:
+    """Add common imports to the doctest namespace."""
+    doctest_namespace["dfn"] = dfn
+    doctest_namespace["np"] = np
+    doctest_namespace["pa"] = pa
+    doctest_namespace["col"] = col
+    doctest_namespace["lit"] = lit
+    doctest_namespace["F"] = F
diff --git a/crates/core/Cargo.toml b/crates/core/Cargo.toml
new file mode 100644
index 000000000..d714dc978
--- /dev/null
+++ b/crates/core/Cargo.toml
@@ -0,0 +1,83 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+[package]
+name = "datafusion-python"
+version.workspace = true
+edition.workspace = true
+rust-version.workspace = true
+license.workspace = true
+description.workspace = true
+homepage.workspace = true
+repository.workspace = true
+include = [
+  "src",
+  "../LICENSE.txt",
+  "build.rs",
+  "../pyproject.toml",
+  "Cargo.toml",
+  "../Cargo.lock",
+]
+
+[dependencies]
+tokio = { workspace = true, features = [
+  "macros",
+  "rt",
+  "rt-multi-thread",
+  "sync",
+] }
+pyo3 = { workspace = true, features = [
+  "extension-module",
+  "abi3",
+  "abi3-py310",
+] }
+pyo3-async-runtimes = { workspace = true, features = ["tokio-runtime"] }
+pyo3-log = { workspace = true }
+chrono = { workspace = true }
+arrow = { workspace = true, features = ["pyarrow"] }
+arrow-select = { workspace = true }
+datafusion = { workspace = true, features = ["avro", "unicode_expressions"] }
+datafusion-substrait = { workspace = true, optional = true }
+datafusion-proto = { workspace = true }
+datafusion-ffi = { workspace = true }
+prost = { workspace = true } # keep in line with `datafusion-substrait`
+serde_json = { workspace = true }
+uuid = { workspace = true, features = ["v4"] }
+mimalloc = { workspace = true, optional = true, features = [
+  "local_dynamic_tls",
+] }
+async-trait = { workspace = true }
+futures = { workspace = true }
+cstr = { workspace = true }
+object_store = { workspace = true, features = ["aws", "gcp", "azure", "http"] }
+url = { workspace = true }
+log = { workspace = true }
+parking_lot = { workspace = true }
+datafusion-python-util = { workspace = true }
+
+[build-dependencies]
+prost-types = { workspace = true }
+pyo3-build-config = { workspace = true }
+
+[features]
+default = ["mimalloc"]
+protoc = ["datafusion-substrait/protoc"]
+substrait = ["dep:datafusion-substrait"]
+
+[lib]
+name = "datafusion_python"
+crate-type = ["cdylib", "rlib"]
diff --git a/build.rs b/crates/core/build.rs
similarity index 100%
rename from build.rs
rename to crates/core/build.rs
diff --git a/src/array.rs b/crates/core/src/array.rs
similarity index 89%
rename from src/array.rs
rename to crates/core/src/array.rs
index 8be9a01e3..f284fa9de 100644
--- a/src/array.rs
+++ b/crates/core/src/array.rs
@@ -15,6 +15,7 @@
 // specific language governing permissions and limitations
 // under the License.
 
+use std::ptr::NonNull;
 use std::sync::Arc;
 
 use arrow::array::{Array, ArrayRef};
@@ -26,11 +27,15 @@ use pyo3::types::PyCapsule;
 use pyo3::{Bound, PyAny, PyResult, Python, pyclass, pymethods};
 
 use crate::errors::PyDataFusionResult;
-use crate::utils::validate_pycapsule;
 
 /// A Python object which implements the Arrow PyCapsule for importing
 /// into other libraries.
-#[pyclass(name = "ArrowArrayExportable", module = "datafusion", frozen)]
+#[pyclass(
+    from_py_object,
+    name = "ArrowArrayExportable",
+    module = "datafusion",
+    frozen
+)]
 #[derive(Clone)]
 pub struct PyArrowArrayExportable {
     array: ArrayRef,
@@ -46,9 +51,10 @@ impl PyArrowArrayExportable {
         requested_schema: Option<Bound<'py, PyCapsule>>,
     ) -> PyDataFusionResult<(Bound<'py, PyCapsule>, Bound<'py, PyCapsule>)> {
         let field = if let Some(schema_capsule) = requested_schema {
-            validate_pycapsule(&schema_capsule, "arrow_schema")?;
-
-            let schema_ptr = unsafe { schema_capsule.reference::<FFI_ArrowSchema>() };
+            let data: NonNull<FFI_ArrowSchema> = schema_capsule
+                .pointer_checked(Some(c"arrow_schema"))?
+                .cast();
+            let schema_ptr = unsafe { data.as_ref() };
             let desired_field = Field::try_from(schema_ptr)?;
 
             Arc::new(desired_field)
diff --git a/src/catalog.rs b/crates/core/src/catalog.rs
similarity index 94%
rename from src/catalog.rs
rename to crates/core/src/catalog.rs
index 29d95ea5d..30ec4744c 100644
--- a/src/catalog.rs
+++ b/crates/core/src/catalog.rs
@@ -17,6 +17,7 @@
 
 use std::any::Any;
 use std::collections::HashSet;
+use std::ptr::NonNull;
 use std::sync::Arc;
 
 use async_trait::async_trait;
@@ -29,20 +30,21 @@ use datafusion::datasource::TableProvider;
 use datafusion_ffi::catalog_provider::FFI_CatalogProvider;
 use datafusion_ffi::proto::logical_extension_codec::FFI_LogicalExtensionCodec;
 use datafusion_ffi::schema_provider::FFI_SchemaProvider;
+use datafusion_python_util::{
+    create_logical_extension_capsule, ffi_logical_codec_from_pycapsule, wait_for_future,
+};
 use pyo3::IntoPyObjectExt;
 use pyo3::exceptions::PyKeyError;
 use pyo3::prelude::*;
 use pyo3::types::PyCapsule;
 
+use crate::context::PySessionContext;
 use crate::dataset::Dataset;
 use crate::errors::{PyDataFusionError, PyDataFusionResult, py_datafusion_err, to_datafusion_err};
 use crate::table::PyTable;
-use crate::utils::{
-    create_logical_extension_capsule, extract_logical_extension_codec, validate_pycapsule,
-    wait_for_future,
-};
 
 #[pyclass(
+    from_py_object,
     frozen,
     name = "RawCatalogList",
     module = "datafusion.catalog",
@@ -54,14 +56,26 @@ pub struct PyCatalogList {
     codec: Arc<FFI_LogicalExtensionCodec>,
 }
 
-#[pyclass(frozen, name = "RawCatalog", module = "datafusion.catalog", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "RawCatalog",
+    module = "datafusion.catalog",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyCatalog {
     pub catalog: Arc<dyn CatalogProvider>,
     codec: Arc<FFI_LogicalExtensionCodec>,
 }
 
-#[pyclass(frozen, name = "RawSchema", module = "datafusion.catalog", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "RawSchema",
+    module = "datafusion.catalog",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PySchema {
     pub schema: Arc<dyn SchemaProvider>,
@@ -642,10 +656,11 @@ fn extract_catalog_provider_from_pyobj(
             .call1((codec_capsule,))?;
     }
 
-    let provider = if let Ok(capsule) = catalog_provider.downcast::<PyCapsule>() {
-        validate_pycapsule(capsule, "datafusion_catalog_provider")?;
-
-        let provider = unsafe { capsule.reference::<FFI_CatalogProvider>() };
+    let provider = if let Ok(capsule) = catalog_provider.cast::<PyCapsule>() {
+        let data: NonNull<FFI_CatalogProvider> = capsule
+            .pointer_checked(Some(c"datafusion_catalog_provider"))?
+            .cast();
+        let provider = unsafe { data.as_ref() };
         let provider: Arc<dyn CatalogProvider + Send> = provider.into();
         provider as Arc<dyn CatalogProvider>
     } else {
@@ -673,10 +688,11 @@ fn extract_schema_provider_from_pyobj(
             .call1((codec_capsule,))?;
     }
 
-    let provider = if let Ok(capsule) = schema_provider.downcast::<PyCapsule>() {
-        validate_pycapsule(capsule, "datafusion_schema_provider")?;
-
-        let provider = unsafe { capsule.reference::<FFI_SchemaProvider>() };
+    let provider = if let Ok(capsule) = schema_provider.cast::<PyCapsule>() {
+        let data: NonNull<FFI_SchemaProvider> = capsule
+            .pointer_checked(Some(c"datafusion_schema_provider"))?
+            .cast();
+        let provider = unsafe { data.as_ref() };
         let provider: Arc<dyn SchemaProvider + Send> = provider.into();
         provider as Arc<dyn SchemaProvider>
     } else {
@@ -690,6 +706,17 @@ fn extract_schema_provider_from_pyobj(
     Ok(provider)
 }
 
+fn extract_logical_extension_codec(
+    py: Python,
+    obj: Option<Bound<PyAny>>,
+) -> PyResult<Arc<FFI_LogicalExtensionCodec>> {
+    let obj = match obj {
+        Some(obj) => obj,
+        None => PySessionContext::global_ctx()?.into_bound_py_any(py)?,
+    };
+    ffi_logical_codec_from_pycapsule(obj).map(Arc::new)
+}
+
 pub(crate) fn init_module(m: &Bound<'_, PyModule>) -> PyResult<()> {
     m.add_class::<PyCatalog>()?;
     m.add_class::<PySchema>()?;
diff --git a/src/common.rs b/crates/core/src/common.rs
similarity index 100%
rename from src/common.rs
rename to crates/core/src/common.rs
diff --git a/src/common/data_type.rs b/crates/core/src/common/data_type.rs
similarity index 97%
rename from src/common/data_type.rs
rename to crates/core/src/common/data_type.rs
index 1ff332ebb..af4179806 100644
--- a/src/common/data_type.rs
+++ b/crates/core/src/common/data_type.rs
@@ -15,6 +15,8 @@
 // specific language governing permissions and limitations
 // under the License.
 
+use std::sync::Arc;
+
 use datafusion::arrow::array::Array;
 use datafusion::arrow::datatypes::{DataType, IntervalUnit, TimeUnit};
 use datafusion::common::ScalarValue;
@@ -40,7 +42,14 @@ impl From<PyScalarValue> for ScalarValue {
 }
 
 #[derive(Debug, Clone, PartialEq, Eq, Hash, PartialOrd, Ord)]
-#[pyclass(frozen, eq, eq_int, name = "RexType", module = "datafusion.common")]
+#[pyclass(
+    from_py_object,
+    frozen,
+    eq,
+    eq_int,
+    name = "RexType",
+    module = "datafusion.common"
+)]
 pub enum RexType {
     Alias,
     Literal,
@@ -61,7 +70,12 @@ pub enum RexType {
 /// to map types from one system to another.
 // TODO: This looks like this needs pyo3 tracking so leaving unfrozen for now
 #[derive(Debug, Clone)]
-#[pyclass(name = "DataTypeMap", module = "datafusion.common", subclass)]
+#[pyclass(
+    from_py_object,
+    name = "DataTypeMap",
+    module = "datafusion.common",
+    subclass
+)]
 pub struct DataTypeMap {
     #[pyo3(get, set)]
     pub arrow_type: PyDataType,
@@ -347,6 +361,10 @@ impl DataTypeMap {
             ScalarValue::Map(_) => Err(PyNotImplementedError::new_err(
                 "ScalarValue::Map".to_string(),
             )),
+            ScalarValue::RunEndEncoded(field1, field2, _) => Ok(DataType::RunEndEncoded(
+                Arc::clone(field1),
+                Arc::clone(field2),
+            )),
         }
     }
 }
@@ -587,7 +605,12 @@ impl DataTypeMap {
 /// Since `DataType` exists in another package we cannot make that happen here so we wrap
 /// `DataType` as `PyDataType` This exists solely to satisfy those constraints.
 #[derive(Debug, Clone, PartialEq, Eq, Hash, PartialOrd, Ord)]
-#[pyclass(frozen, name = "DataType", module = "datafusion.common")]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "DataType",
+    module = "datafusion.common"
+)]
 pub struct PyDataType {
     pub data_type: DataType,
 }
@@ -645,7 +668,14 @@ impl From<DataType> for PyDataType {
 
 /// Represents the possible Python types that can be mapped to the SQL types
 #[derive(Debug, Clone, PartialEq, Eq, Hash, PartialOrd, Ord)]
-#[pyclass(frozen, eq, eq_int, name = "PythonType", module = "datafusion.common")]
+#[pyclass(
+    from_py_object,
+    frozen,
+    eq,
+    eq_int,
+    name = "PythonType",
+    module = "datafusion.common"
+)]
 pub enum PythonType {
     Array,
     Bool,
@@ -665,7 +695,14 @@ pub enum PythonType {
 #[allow(non_camel_case_types)]
 #[allow(clippy::upper_case_acronyms)]
 #[derive(Debug, Clone, PartialEq, Eq, Hash, PartialOrd, Ord)]
-#[pyclass(frozen, eq, eq_int, name = "SqlType", module = "datafusion.common")]
+#[pyclass(
+    from_py_object,
+    frozen,
+    eq,
+    eq_int,
+    name = "SqlType",
+    module = "datafusion.common"
+)]
 pub enum SqlType {
     ANY,
     ARRAY,
@@ -724,6 +761,7 @@ pub enum SqlType {
 #[allow(clippy::upper_case_acronyms)]
 #[derive(Debug, Clone, PartialEq, Eq, Hash, PartialOrd, Ord)]
 #[pyclass(
+    from_py_object,
     frozen,
     eq,
     eq_int,
diff --git a/src/common/df_schema.rs b/crates/core/src/common/df_schema.rs
similarity index 93%
rename from src/common/df_schema.rs
rename to crates/core/src/common/df_schema.rs
index eb62469cf..9167e772e 100644
--- a/src/common/df_schema.rs
+++ b/crates/core/src/common/df_schema.rs
@@ -21,7 +21,13 @@ use datafusion::common::DFSchema;
 use pyo3::prelude::*;
 
 #[derive(Debug, Clone)]
-#[pyclass(frozen, name = "DFSchema", module = "datafusion.common", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "DFSchema",
+    module = "datafusion.common",
+    subclass
+)]
 pub struct PyDFSchema {
     schema: Arc<DFSchema>,
 }
diff --git a/src/common/function.rs b/crates/core/src/common/function.rs
similarity index 93%
rename from src/common/function.rs
rename to crates/core/src/common/function.rs
index bc6f23160..41cab515f 100644
--- a/src/common/function.rs
+++ b/crates/core/src/common/function.rs
@@ -22,7 +22,13 @@ use pyo3::prelude::*;
 
 use super::data_type::PyDataType;
 
-#[pyclass(frozen, name = "SqlFunction", module = "datafusion.common", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "SqlFunction",
+    module = "datafusion.common",
+    subclass
+)]
 #[derive(Debug, Clone)]
 pub struct SqlFunction {
     pub name: String,
diff --git a/src/common/schema.rs b/crates/core/src/common/schema.rs
similarity index 92%
rename from src/common/schema.rs
rename to crates/core/src/common/schema.rs
index 4e46592aa..29a27b204 100644
--- a/src/common/schema.rs
+++ b/crates/core/src/common/schema.rs
@@ -34,7 +34,13 @@ use super::data_type::DataTypeMap;
 use super::function::SqlFunction;
 use crate::sql::logical::PyLogicalPlan;
 
-#[pyclass(name = "SqlSchema", module = "datafusion.common", subclass, frozen)]
+#[pyclass(
+    from_py_object,
+    name = "SqlSchema",
+    module = "datafusion.common",
+    subclass,
+    frozen
+)]
 #[derive(Debug, Clone)]
 pub struct SqlSchema {
     name: Arc<RwLock<String>>,
@@ -43,7 +49,12 @@ pub struct SqlSchema {
     functions: Arc<RwLock<Vec<SqlFunction>>>,
 }
 
-#[pyclass(name = "SqlTable", module = "datafusion.common", subclass)]
+#[pyclass(
+    from_py_object,
+    name = "SqlTable",
+    module = "datafusion.common",
+    subclass
+)]
 #[derive(Debug, Clone)]
 pub struct SqlTable {
     #[pyo3(get, set)]
@@ -87,7 +98,12 @@ impl SqlTable {
     }
 }
 
-#[pyclass(name = "SqlView", module = "datafusion.common", subclass)]
+#[pyclass(
+    from_py_object,
+    name = "SqlView",
+    module = "datafusion.common",
+    subclass
+)]
 #[derive(Debug, Clone)]
 pub struct SqlView {
     #[pyo3(get, set)]
@@ -247,7 +263,13 @@ fn is_supported_push_down_expr(_expr: &Expr) -> bool {
     true
 }
 
-#[pyclass(frozen, name = "SqlStatistics", module = "datafusion.common", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "SqlStatistics",
+    module = "datafusion.common",
+    subclass
+)]
 #[derive(Debug, Clone)]
 pub struct SqlStatistics {
     row_count: f64,
@@ -266,7 +288,13 @@ impl SqlStatistics {
     }
 }
 
-#[pyclass(frozen, name = "Constraints", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "Constraints",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyConstraints {
     pub constraints: Constraints,
@@ -291,7 +319,14 @@ impl Display for PyConstraints {
 }
 
 #[derive(Debug, Clone, PartialEq, Eq, Hash, PartialOrd, Ord)]
-#[pyclass(frozen, eq, eq_int, name = "TableType", module = "datafusion.common")]
+#[pyclass(
+    from_py_object,
+    frozen,
+    eq,
+    eq_int,
+    name = "TableType",
+    module = "datafusion.common"
+)]
 pub enum PyTableType {
     Base,
     View,
@@ -318,7 +353,13 @@ impl From<TableType> for PyTableType {
     }
 }
 
-#[pyclass(frozen, name = "TableSource", module = "datafusion.common", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "TableSource",
+    module = "datafusion.common",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyTableSource {
     pub table_source: Arc<dyn TableSource>,
diff --git a/src/config.rs b/crates/core/src/config.rs
similarity index 96%
rename from src/config.rs
rename to crates/core/src/config.rs
index 38936e6c5..fdb693a12 100644
--- a/src/config.rs
+++ b/crates/core/src/config.rs
@@ -24,7 +24,13 @@ use pyo3::types::*;
 
 use crate::common::data_type::PyScalarValue;
 use crate::errors::PyDataFusionResult;
-#[pyclass(name = "Config", module = "datafusion", subclass, frozen)]
+#[pyclass(
+    from_py_object,
+    name = "Config",
+    module = "datafusion",
+    subclass,
+    frozen
+)]
 #[derive(Clone)]
 pub(crate) struct PyConfig {
     config: Arc<RwLock<ConfigOptions>>,
diff --git a/src/context.rs b/crates/core/src/context.rs
similarity index 80%
rename from src/context.rs
rename to crates/core/src/context.rs
index 336ce0258..e46d359d6 100644
--- a/src/context.rs
+++ b/crates/core/src/context.rs
@@ -17,6 +17,7 @@
 
 use std::collections::{HashMap, HashSet};
 use std::path::PathBuf;
+use std::ptr::NonNull;
 use std::str::FromStr;
 use std::sync::Arc;
 
@@ -26,8 +27,8 @@ use arrow::pyarrow::FromPyArrow;
 use datafusion::arrow::datatypes::{DataType, Schema, SchemaRef};
 use datafusion::arrow::pyarrow::PyArrowType;
 use datafusion::arrow::record_batch::RecordBatch;
-use datafusion::catalog::{CatalogProvider, CatalogProviderList};
-use datafusion::common::{ScalarValue, TableReference, exec_err};
+use datafusion::catalog::{CatalogProvider, CatalogProviderList, TableProviderFactory};
+use datafusion::common::{DFSchema, ScalarValue, TableReference, exec_err};
 use datafusion::datasource::file_format::file_compression_type::FileCompressionType;
 use datafusion::datasource::file_format::parquet::ParquetFormat;
 use datafusion::datasource::listing::{
@@ -40,20 +41,26 @@ use datafusion::execution::context::{
 };
 use datafusion::execution::disk_manager::DiskManagerMode;
 use datafusion::execution::memory_pool::{FairSpillPool, GreedyMemoryPool, UnboundedMemoryPool};
-use datafusion::execution::options::ReadOptions;
+use datafusion::execution::options::{ArrowReadOptions, ReadOptions};
 use datafusion::execution::runtime_env::RuntimeEnvBuilder;
 use datafusion::execution::session_state::SessionStateBuilder;
 use datafusion::prelude::{
-    AvroReadOptions, CsvReadOptions, DataFrame, NdJsonReadOptions, ParquetReadOptions,
+    AvroReadOptions, CsvReadOptions, DataFrame, JsonReadOptions, ParquetReadOptions,
 };
 use datafusion_ffi::catalog_provider::FFI_CatalogProvider;
 use datafusion_ffi::catalog_provider_list::FFI_CatalogProviderList;
+use datafusion_ffi::config::extension_options::FFI_ExtensionOptions;
 use datafusion_ffi::execution::FFI_TaskContextProvider;
 use datafusion_ffi::proto::logical_extension_codec::FFI_LogicalExtensionCodec;
+use datafusion_ffi::table_provider_factory::FFI_TableProviderFactory;
 use datafusion_proto::logical_plan::DefaultLogicalExtensionCodec;
+use datafusion_python_util::{
+    create_logical_extension_capsule, ffi_logical_codec_from_pycapsule, get_global_ctx,
+    get_tokio_runtime, spawn_future, wait_for_future,
+};
 use object_store::ObjectStore;
 use pyo3::IntoPyObjectExt;
-use pyo3::exceptions::{PyKeyError, PyValueError};
+use pyo3::exceptions::{PyKeyError, PyRuntimeError, PyValueError};
 use pyo3::prelude::*;
 use pyo3::types::{PyCapsule, PyDict, PyList, PyTuple};
 use url::Url;
@@ -63,11 +70,13 @@ use crate::catalog::{
     PyCatalog, PyCatalogList, RustWrappedPyCatalogProvider, RustWrappedPyCatalogProviderList,
 };
 use crate::common::data_type::PyScalarValue;
+use crate::common::df_schema::PyDFSchema;
 use crate::dataframe::PyDataFrame;
 use crate::dataset::Dataset;
 use crate::errors::{
     PyDataFusionError, PyDataFusionResult, from_datafusion_error, py_datafusion_err,
 };
+use crate::expr::PyExpr;
 use crate::expr::sort_expr::PySortExpr;
 use crate::options::PyCsvReadOptions;
 use crate::physical_plan::PyExecutionPlan;
@@ -75,18 +84,20 @@ use crate::record_batch::PyRecordBatchStream;
 use crate::sql::logical::PyLogicalPlan;
 use crate::sql::util::replace_placeholders_with_strings;
 use crate::store::StorageContexts;
-use crate::table::PyTable;
+use crate::table::{PyTable, RustWrappedPyTableProviderFactory};
 use crate::udaf::PyAggregateUDF;
 use crate::udf::PyScalarUDF;
 use crate::udtf::PyTableFunction;
 use crate::udwf::PyWindowUDF;
-use crate::utils::{
-    create_logical_extension_capsule, extract_logical_extension_codec, get_global_ctx,
-    get_tokio_runtime, spawn_future, validate_pycapsule, wait_for_future,
-};
 
 /// Configuration options for a SessionContext
-#[pyclass(frozen, name = "SessionConfig", module = "datafusion", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "SessionConfig",
+    module = "datafusion",
+    subclass
+)]
 #[derive(Clone, Default)]
 pub struct PySessionConfig {
     pub config: SessionConfig,
@@ -176,10 +187,43 @@ impl PySessionConfig {
     fn set(&self, key: &str, value: &str) -> Self {
         Self::from(self.config.clone().set_str(key, value))
     }
+
+    pub fn with_extension(&self, extension: Bound<PyAny>) -> PyResult<Self> {
+        if !extension.hasattr("__datafusion_extension_options__")? {
+            return Err(pyo3::exceptions::PyAttributeError::new_err(
+                "Expected extension object to define __datafusion_extension_options__()",
+            ));
+        }
+        let capsule = extension.call_method0("__datafusion_extension_options__")?;
+        let capsule = capsule.cast::<PyCapsule>()?;
+
+        let extension: NonNull<FFI_ExtensionOptions> = capsule
+            .pointer_checked(Some(c"datafusion_extension_options"))?
+            .cast();
+        let mut extension = unsafe { extension.as_ref() }.clone();
+
+        let mut config = self.config.clone();
+        let options = config.options_mut();
+        if let Some(prior_extension) = options.extensions.get::<FFI_ExtensionOptions>() {
+            extension
+                .merge(prior_extension)
+                .map_err(py_datafusion_err)?;
+        }
+
+        options.extensions.insert(extension);
+
+        Ok(Self::from(config))
+    }
 }
 
 /// Runtime options for a SessionContext
-#[pyclass(frozen, name = "RuntimeEnvBuilder", module = "datafusion", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "RuntimeEnvBuilder",
+    module = "datafusion",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyRuntimeEnvBuilder {
     pub builder: RuntimeEnvBuilder,
@@ -266,7 +310,13 @@ impl PyRuntimeEnvBuilder {
 }
 
 /// `PySQLOptions` allows you to specify options to the sql execution.
-#[pyclass(frozen, name = "SQLOptions", module = "datafusion", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "SQLOptions",
+    module = "datafusion",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PySQLOptions {
     pub options: SQLOptions,
@@ -305,7 +355,13 @@ impl PySQLOptions {
 /// `PySessionContext` is able to plan and execute DataFusion plans.
 /// It has a powerful optimizer, a physical planner for local execution, and a
 /// multi-threaded execution engine to perform the execution.
-#[pyclass(frozen, name = "SessionContext", module = "datafusion", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "SessionContext",
+    module = "datafusion",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PySessionContext {
     pub ctx: Arc<SessionContext>,
@@ -380,11 +436,25 @@ impl PySessionContext {
             &upstream_host
         };
         let url_string = format!("{scheme}{derived_host}");
-        let url = Url::parse(&url_string).unwrap();
+        let url = Url::parse(&url_string).map_err(|e| PyValueError::new_err(e.to_string()))?;
         self.ctx.runtime_env().register_object_store(&url, store);
         Ok(())
     }
 
+    /// Deregister an object store with the given url
+    #[pyo3(signature = (scheme, host=None))]
+    pub fn deregister_object_store(
+        &self,
+        scheme: &str,
+        host: Option<&str>,
+    ) -> PyDataFusionResult<()> {
+        let host = host.unwrap_or("");
+        let url_string = format!("{scheme}{host}");
+        let url = Url::parse(&url_string).map_err(|e| PyDataFusionError::Common(e.to_string()))?;
+        self.ctx.runtime_env().deregister_object_store(&url)?;
+        Ok(())
+    }
+
     #[allow(clippy::too_many_arguments)]
     #[pyo3(signature = (name, path, table_partition_cols=vec![],
     file_extension=".parquet",
@@ -438,6 +508,10 @@ impl PySessionContext {
         self.ctx.register_udtf(&name, func);
     }
 
+    pub fn deregister_udtf(&self, name: &str) {
+        self.ctx.deregister_udtf(name);
+    }
+
     #[pyo3(signature = (query, options=None, param_values=HashMap::default(), param_strings=HashMap::default()))]
     pub fn sql_with_options(
         &self,
@@ -633,6 +707,41 @@ impl PySessionContext {
         Ok(())
     }
 
+    pub fn register_table_factory(
+        &self,
+        format: &str,
+        mut factory: Bound<'_, PyAny>,
+    ) -> PyDataFusionResult<()> {
+        if factory.hasattr("__datafusion_table_provider_factory__")? {
+            let py = factory.py();
+            let codec_capsule = create_logical_extension_capsule(py, self.logical_codec.as_ref())?;
+            factory = factory
+                .getattr("__datafusion_table_provider_factory__")?
+                .call1((codec_capsule,))?;
+        }
+
+        let factory: Arc<dyn TableProviderFactory> =
+            if let Ok(capsule) = factory.cast::<PyCapsule>().map_err(py_datafusion_err) {
+                let data: NonNull<FFI_TableProviderFactory> = capsule
+                    .pointer_checked(Some(c"datafusion_table_provider_factory"))?
+                    .cast();
+                let factory = unsafe { data.as_ref() };
+                factory.into()
+            } else {
+                Arc::new(RustWrappedPyTableProviderFactory::new(
+                    factory.into(),
+                    self.logical_codec.clone(),
+                ))
+            };
+
+        let st = self.ctx.state_ref();
+        let mut lock = st.write();
+        lock.table_factories_mut()
+            .insert(format.to_owned(), factory);
+
+        Ok(())
+    }
+
     pub fn register_catalog_provider_list(
         &self,
         mut provider: Bound<PyAny>,
@@ -645,22 +754,22 @@ impl PySessionContext {
                 .call1((codec_capsule,))?;
         }
 
-        let provider =
-            if let Ok(capsule) = provider.downcast::<PyCapsule>().map_err(py_datafusion_err) {
-                validate_pycapsule(capsule, "datafusion_catalog_provider_list")?;
-
-                let provider = unsafe { capsule.reference::<FFI_CatalogProviderList>() };
-                let provider: Arc<dyn CatalogProviderList + Send> = provider.into();
-                provider as Arc<dyn CatalogProviderList>
-            } else {
-                match provider.extract::<PyCatalogList>() {
-                    Ok(py_catalog_list) => py_catalog_list.catalog_list,
-                    Err(_) => Arc::new(RustWrappedPyCatalogProviderList::new(
-                        provider.into(),
-                        Arc::clone(&self.logical_codec),
-                    )) as Arc<dyn CatalogProviderList>,
-                }
-            };
+        let provider = if let Ok(capsule) = provider.cast::<PyCapsule>() {
+            let data: NonNull<FFI_CatalogProviderList> = capsule
+                .pointer_checked(Some(c"datafusion_catalog_provider_list"))?
+                .cast();
+            let provider = unsafe { data.as_ref() };
+            let provider: Arc<dyn CatalogProviderList + Send> = provider.into();
+            provider as Arc<dyn CatalogProviderList>
+        } else {
+            match provider.extract::<PyCatalogList>() {
+                Ok(py_catalog_list) => py_catalog_list.catalog_list,
+                Err(_) => Arc::new(RustWrappedPyCatalogProviderList::new(
+                    provider.into(),
+                    Arc::clone(&self.logical_codec),
+                )) as Arc<dyn CatalogProviderList>,
+            }
+        };
 
         self.ctx.register_catalog_list(provider);
 
@@ -680,22 +789,22 @@ impl PySessionContext {
                 .call1((codec_capsule,))?;
         }
 
-        let provider =
-            if let Ok(capsule) = provider.downcast::<PyCapsule>().map_err(py_datafusion_err) {
-                validate_pycapsule(capsule, "datafusion_catalog_provider")?;
-
-                let provider = unsafe { capsule.reference::<FFI_CatalogProvider>() };
-                let provider: Arc<dyn CatalogProvider + Send> = provider.into();
-                provider as Arc<dyn CatalogProvider>
-            } else {
-                match provider.extract::<PyCatalog>() {
-                    Ok(py_catalog) => py_catalog.catalog,
-                    Err(_) => Arc::new(RustWrappedPyCatalogProvider::new(
-                        provider.into(),
-                        Arc::clone(&self.logical_codec),
-                    )) as Arc<dyn CatalogProvider>,
-                }
-            };
+        let provider = if let Ok(capsule) = provider.cast::<PyCapsule>() {
+            let data: NonNull<FFI_CatalogProvider> = capsule
+                .pointer_checked(Some(c"datafusion_catalog_provider"))?
+                .cast();
+            let provider = unsafe { data.as_ref() };
+            let provider: Arc<dyn CatalogProvider + Send> = provider.into();
+            provider as Arc<dyn CatalogProvider>
+        } else {
+            match provider.extract::<PyCatalog>() {
+                Ok(py_catalog) => py_catalog.catalog,
+                Err(_) => Arc::new(RustWrappedPyCatalogProvider::new(
+                    provider.into(),
+                    Arc::clone(&self.logical_codec),
+                )) as Arc<dyn CatalogProvider>,
+            }
+        };
 
         let _ = self.ctx.register_catalog(name, provider);
 
@@ -815,7 +924,7 @@ impl PySessionContext {
             .to_str()
             .ok_or_else(|| PyValueError::new_err("Unable to convert path to a string"))?;
 
-        let mut options = NdJsonReadOptions::default()
+        let mut options = JsonReadOptions::default()
             .file_compression_type(parse_file_compression_type(file_compression_type)?)
             .table_partition_cols(
                 table_partition_cols
@@ -867,6 +976,39 @@ impl PySessionContext {
         Ok(())
     }
 
+    #[pyo3(signature = (name, path, schema=None, file_extension=".arrow", table_partition_cols=vec![]))]
+    pub fn register_arrow(
+        &self,
+        name: &str,
+        path: &str,
+        schema: Option<PyArrowType<Schema>>,
+        file_extension: &str,
+        table_partition_cols: Vec<(String, PyArrowType<DataType>)>,
+        py: Python,
+    ) -> PyDataFusionResult<()> {
+        let mut options = ArrowReadOptions::default().table_partition_cols(
+            table_partition_cols
+                .into_iter()
+                .map(|(name, ty)| (name, ty.0))
+                .collect::<Vec<(String, DataType)>>(),
+        );
+        options.file_extension = file_extension;
+        options.schema = schema.as_ref().map(|x| &x.0);
+
+        let result = self.ctx.register_arrow(name, path, options);
+        wait_for_future(py, result)??;
+        Ok(())
+    }
+
+    pub fn register_batch(
+        &self,
+        name: &str,
+        batch: PyArrowType<RecordBatch>,
+    ) -> PyDataFusionResult<()> {
+        self.ctx.register_batch(name, batch.0)?;
+        Ok(())
+    }
+
     // Registers a PyArrow.Dataset
     pub fn register_dataset(
         &self,
@@ -886,16 +1028,28 @@ impl PySessionContext {
         Ok(())
     }
 
+    pub fn deregister_udf(&self, name: &str) {
+        self.ctx.deregister_udf(name);
+    }
+
     pub fn register_udaf(&self, udaf: PyAggregateUDF) -> PyResult<()> {
         self.ctx.register_udaf(udaf.function);
         Ok(())
     }
 
+    pub fn deregister_udaf(&self, name: &str) {
+        self.ctx.deregister_udaf(name);
+    }
+
     pub fn register_udwf(&self, udwf: PyWindowUDF) -> PyResult<()> {
         self.ctx.register_udwf(udwf.function);
         Ok(())
     }
 
+    pub fn deregister_udwf(&self, name: &str) {
+        self.ctx.deregister_udwf(name);
+    }
+
     #[pyo3(signature = (name="datafusion"))]
     pub fn catalog(&self, py: Python, name: &str) -> PyResult<Py<PyAny>> {
         let catalog = self.ctx.catalog(name).ok_or(PyKeyError::new_err(format!(
@@ -918,21 +1072,6 @@ impl PySessionContext {
         self.ctx.catalog_names().into_iter().collect()
     }
 
-    pub fn tables(&self) -> HashSet<String> {
-        self.ctx
-            .catalog_names()
-            .into_iter()
-            .filter_map(|name| self.ctx.catalog(&name))
-            .flat_map(move |catalog| {
-                catalog
-                    .schema_names()
-                    .into_iter()
-                    .filter_map(move |name| catalog.schema(&name))
-            })
-            .flat_map(|schema| schema.table_names())
-            .collect()
-    }
-
     pub fn table(&self, name: &str, py: Python) -> PyResult<PyDataFrame> {
         let res = wait_for_future(py, self.ctx.table(name))
             .map_err(|e| PyKeyError::new_err(e.to_string()))?;
@@ -961,6 +1100,49 @@ impl PySessionContext {
         self.ctx.session_id()
     }
 
+    pub fn session_start_time(&self) -> String {
+        self.ctx.session_start_time().to_rfc3339()
+    }
+
+    pub fn enable_ident_normalization(&self) -> bool {
+        self.ctx.enable_ident_normalization()
+    }
+
+    pub fn parse_sql_expr(&self, sql: &str, schema: PyDFSchema) -> PyDataFusionResult<PyExpr> {
+        let df_schema: DFSchema = schema.into();
+        Ok(self.ctx.parse_sql_expr(sql, &df_schema)?.into())
+    }
+
+    pub fn execute_logical_plan(
+        &self,
+        plan: PyLogicalPlan,
+        py: Python,
+    ) -> PyDataFusionResult<PyDataFrame> {
+        let df = wait_for_future(
+            py,
+            self.ctx.execute_logical_plan(plan.plan.as_ref().clone()),
+        )??;
+        Ok(PyDataFrame::new(df))
+    }
+
+    pub fn refresh_catalogs(&self, py: Python) -> PyDataFusionResult<()> {
+        wait_for_future(py, self.ctx.refresh_catalogs())??;
+        Ok(())
+    }
+
+    pub fn remove_optimizer_rule(&self, name: &str) -> bool {
+        self.ctx.remove_optimizer_rule(name)
+    }
+
+    pub fn table_provider(&self, name: &str, py: Python) -> PyResult<PyTable> {
+        let provider = wait_for_future(py, self.ctx.table_provider(name))
+            // Outer error: runtime/async failure
+            .map_err(|e| PyRuntimeError::new_err(e.to_string()))?
+            // Inner error: table not found
+            .map_err(|e| PyKeyError::new_err(e.to_string()))?;
+        Ok(PyTable { table: provider })
+    }
+
     #[allow(clippy::too_many_arguments)]
     #[pyo3(signature = (path, schema=None, schema_infer_max_records=1000, file_extension=".json", table_partition_cols=vec![], file_compression_type=None))]
     pub fn read_json(
@@ -976,7 +1158,7 @@ impl PySessionContext {
         let path = path
             .to_str()
             .ok_or_else(|| PyValueError::new_err("Unable to convert path to a string"))?;
-        let mut options = NdJsonReadOptions::default()
+        let mut options = JsonReadOptions::default()
             .table_partition_cols(
                 table_partition_cols
                     .into_iter()
@@ -1095,6 +1277,29 @@ impl PySessionContext {
         Ok(PyDataFrame::new(df))
     }
 
+    #[pyo3(signature = (path, schema=None, file_extension=".arrow", table_partition_cols=vec![]))]
+    pub fn read_arrow(
+        &self,
+        path: &str,
+        schema: Option<PyArrowType<Schema>>,
+        file_extension: &str,
+        table_partition_cols: Vec<(String, PyArrowType<DataType>)>,
+        py: Python,
+    ) -> PyDataFusionResult<PyDataFrame> {
+        let mut options = ArrowReadOptions::default().table_partition_cols(
+            table_partition_cols
+                .into_iter()
+                .map(|(name, ty)| (name, ty.0))
+                .collect::<Vec<(String, DataType)>>(),
+        );
+        options.file_extension = file_extension;
+        options.schema = schema.as_ref().map(|x| &x.0);
+
+        let result = self.ctx.read_arrow(path, options);
+        let df = wait_for_future(py, result)??;
+        Ok(PyDataFrame::new(df))
+    }
+
     pub fn read_table(&self, table: Bound<'_, PyAny>) -> PyDataFusionResult<PyDataFrame> {
         let session = self.clone().into_bound_py_any(table.py())?;
         let table = PyTable::new(table, Some(session))?;
@@ -1155,8 +1360,7 @@ impl PySessionContext {
         &self,
         codec: Bound<'py, PyAny>,
     ) -> PyDataFusionResult<Self> {
-        let py = codec.py();
-        let logical_codec = extract_logical_extension_codec(py, Some(codec))?;
+        let logical_codec = Arc::new(ffi_logical_codec_from_pycapsule(codec)?);
 
         Ok({
             Self {
@@ -1214,7 +1418,7 @@ impl PySessionContext {
 
     fn default_logical_codec(ctx: &Arc<SessionContext>) -> Arc<FFI_LogicalExtensionCodec> {
         let codec = Arc::new(DefaultLogicalExtensionCodec {});
-        let runtime = get_tokio_runtime().0.handle().clone();
+        let runtime = get_tokio_runtime().handle().clone();
         let ctx_provider = Arc::clone(ctx) as Arc<dyn TaskContextProvider>;
         Arc::new(FFI_LogicalExtensionCodec::new(
             codec,
diff --git a/src/dataframe.rs b/crates/core/src/dataframe.rs
similarity index 85%
rename from src/dataframe.rs
rename to crates/core/src/dataframe.rs
index 53fab58c6..2e74991b8 100644
--- a/src/dataframe.rs
+++ b/crates/core/src/dataframe.rs
@@ -17,6 +17,7 @@
 
 use std::collections::HashMap;
 use std::ffi::{CStr, CString};
+use std::ptr::NonNull;
 use std::str::FromStr;
 use std::sync::Arc;
 
@@ -36,10 +37,17 @@ use datafusion::config::{CsvOptions, ParquetColumnOptions, ParquetOptions, Table
 use datafusion::dataframe::{DataFrame, DataFrameWriteOptions};
 use datafusion::error::DataFusionError;
 use datafusion::execution::SendableRecordBatchStream;
-use datafusion::logical_expr::SortExpr;
+use datafusion::execution::context::TaskContext;
 use datafusion::logical_expr::dml::InsertOp;
+use datafusion::logical_expr::{LogicalPlan, SortExpr};
 use datafusion::parquet::basic::{BrotliLevel, Compression, GzipLevel, ZstdLevel};
+use datafusion::physical_plan::{
+    ExecutionPlan as DFExecutionPlan, collect as df_collect,
+    collect_partitioned as df_collect_partitioned, execute_stream as df_execute_stream,
+    execute_stream_partitioned as df_execute_stream_partitioned,
+};
 use datafusion::prelude::*;
+use datafusion_python_util::{is_ipython_env, spawn_future, wait_for_future};
 use futures::{StreamExt, TryStreamExt};
 use parking_lot::Mutex;
 use pyo3::PyErr;
@@ -56,7 +64,6 @@ use crate::physical_plan::PyExecutionPlan;
 use crate::record_batch::{PyRecordBatchStream, poll_next_batch};
 use crate::sql::logical::PyLogicalPlan;
 use crate::table::{PyTable, TempViewTable};
-use crate::utils::{is_ipython_env, spawn_future, validate_pycapsule, wait_for_future};
 
 /// File-level static CStr for the Arrow array stream capsule name.
 static ARROW_ARRAY_STREAM_NAME: &CStr = cstr!("arrow_array_stream");
@@ -139,11 +146,11 @@ fn import_python_formatter(py: Python<'_>) -> PyResult<Bound<'_, PyAny>> {
 // Helper function to extract attributes with fallback to default
 fn get_attr<'a, T>(py_object: &'a Bound<'a, PyAny>, attr_name: &str, default_value: T) -> T
 where
-    T: for<'py> pyo3::FromPyObject<'py> + Clone,
+    T: for<'py> pyo3::FromPyObject<'py, 'py> + Clone,
 {
     py_object
         .getattr(attr_name)
-        .and_then(|v| v.extract::<T>())
+        .and_then(|v| v.extract::<T>().map_err(Into::<PyErr>::into))
         .unwrap_or_else(|_| default_value.clone())
 }
 
@@ -183,7 +190,13 @@ fn build_formatter_config_from_python(formatter: &Bound<'_, PyAny>) -> PyResult<
 }
 
 /// Python mapping of `ParquetOptions` (includes just the writer-related options).
-#[pyclass(frozen, name = "ParquetWriterOptions", module = "datafusion", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "ParquetWriterOptions",
+    module = "datafusion",
+    subclass
+)]
 #[derive(Clone, Default)]
 pub struct PyParquetWriterOptions {
     options: ParquetOptions,
@@ -247,7 +260,13 @@ impl PyParquetWriterOptions {
 }
 
 /// Python mapping of `ParquetColumnOptions`.
-#[pyclass(frozen, name = "ParquetColumnOptions", module = "datafusion", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "ParquetColumnOptions",
+    module = "datafusion",
+    subclass
+)]
 #[derive(Clone, Default)]
 pub struct PyParquetColumnOptions {
     options: ParquetColumnOptions,
@@ -282,13 +301,22 @@ impl PyParquetColumnOptions {
 /// A PyDataFrame is a representation of a logical plan and an API to compose statements.
 /// Use it to build a plan and `.collect()` to execute the plan and collect the result.
 /// The actual execution of a plan runs natively on Rust and Arrow on a multi-threaded environment.
-#[pyclass(name = "DataFrame", module = "datafusion", subclass, frozen)]
+#[pyclass(
+    from_py_object,
+    name = "DataFrame",
+    module = "datafusion",
+    subclass,
+    frozen
+)]
 #[derive(Clone)]
 pub struct PyDataFrame {
     df: Arc<DataFrame>,
 
     // In IPython environment cache batches between __repr__ and _repr_html_ calls.
     batches: SharedCachedBatches,
+
+    // Cache the last physical plan so that metrics are available after execution.
+    last_plan: Arc<Mutex<Option<Arc<dyn DFExecutionPlan>>>>,
 }
 
 impl PyDataFrame {
@@ -297,6 +325,7 @@ impl PyDataFrame {
         Self {
             df: Arc::new(df),
             batches: Arc::new(Mutex::new(None)),
+            last_plan: Arc::new(Mutex::new(None)),
         }
     }
 
@@ -368,6 +397,20 @@ impl PyDataFrame {
         Ok(html_str)
     }
 
+    /// Create the physical plan, cache it in `last_plan`, and return the plan together
+    /// with a task context. Centralises the repeated three-line pattern that appears in
+    /// `collect`, `collect_partitioned`, `execute_stream`, and `execute_stream_partitioned`.
+    fn create_and_cache_plan(
+        &self,
+        py: Python,
+    ) -> PyDataFusionResult<(Arc<dyn DFExecutionPlan>, Arc<TaskContext>)> {
+        let df = self.df.as_ref().clone();
+        let new_plan = wait_for_future(py, df.create_physical_plan())??;
+        *self.last_plan.lock() = Some(Arc::clone(&new_plan));
+        let task_ctx = Arc::new(self.df.as_ref().task_ctx());
+        Ok((new_plan, task_ctx))
+    }
+
     async fn collect_column_inner(&self, column: &str) -> Result<ArrayRef, DataFusionError> {
         let batches = self
             .df
@@ -449,17 +492,17 @@ impl PyDataFrame {
     fn __getitem__(&self, key: Bound<'_, PyAny>) -> PyDataFusionResult<Self> {
         if let Ok(key) = key.extract::<PyBackedStr>() {
             // df[col]
-            self.select_columns(vec![key])
-        } else if let Ok(tuple) = key.downcast::<PyTuple>() {
+            self.select_exprs(vec![key])
+        } else if let Ok(tuple) = key.cast::<PyTuple>() {
             // df[col1, col2, col3]
             let keys = tuple
                 .iter()
                 .map(|item| item.extract::<PyBackedStr>())
                 .collect::<PyResult<Vec<PyBackedStr>>>()?;
-            self.select_columns(keys)
+            self.select_exprs(keys)
         } else if let Ok(keys) = key.extract::<Vec<PyBackedStr>>() {
             // df[[col1, col2, col3]]
-            self.select_columns(keys)
+            self.select_exprs(keys)
         } else {
             let message = "DataFrame can only be indexed by string index or indices".to_string();
             Err(PyDataFusionError::Common(message))
@@ -535,13 +578,6 @@ impl PyDataFrame {
         Ok(PyTable::from(table_provider))
     }
 
-    #[pyo3(signature = (*args))]
-    fn select_columns(&self, args: Vec<PyBackedStr>) -> PyDataFusionResult<Self> {
-        let args = args.iter().map(|s| s.as_ref()).collect::<Vec<&str>>();
-        let df = self.df.as_ref().clone().select_columns(&args)?;
-        Ok(Self::new(df))
-    }
-
     #[pyo3(signature = (*args))]
     fn select_exprs(&self, args: Vec<PyBackedStr>) -> PyDataFusionResult<Self> {
         let args = args.iter().map(|s| s.as_ref()).collect::<Vec<&str>>();
@@ -563,6 +599,14 @@ impl PyDataFrame {
         Ok(Self::new(df))
     }
 
+    /// Apply window function expressions to the DataFrame
+    #[pyo3(signature = (*exprs))]
+    fn window(&self, exprs: Vec<PyExpr>) -> PyDataFusionResult<Self> {
+        let window_exprs = exprs.into_iter().map(|e| e.into()).collect();
+        let df = self.df.as_ref().clone().window(window_exprs)?;
+        Ok(Self::new(df))
+    }
+
     fn filter(&self, predicate: PyExpr) -> PyDataFusionResult<Self> {
         let df = self.df.as_ref().clone().filter(predicate.into())?;
         Ok(Self::new(df))
@@ -626,8 +670,9 @@ impl PyDataFrame {
     /// Unless some order is specified in the plan, there is no
     /// guarantee of the order of the result.
     fn collect<'py>(&self, py: Python<'py>) -> PyResult<Vec<Bound<'py, PyAny>>> {
-        let batches = wait_for_future(py, self.df.as_ref().clone().collect())?
-            .map_err(PyDataFusionError::from)?;
+        let (plan, task_ctx) = self.create_and_cache_plan(py)?;
+        let batches =
+            wait_for_future(py, df_collect(plan, task_ctx))?.map_err(PyDataFusionError::from)?;
         // cannot use PyResult<Vec<RecordBatch>> return type due to
         // https://github.com/PyO3/pyo3/issues/1813
         batches.into_iter().map(|rb| rb.to_pyarrow(py)).collect()
@@ -642,7 +687,8 @@ impl PyDataFrame {
     /// Executes this DataFrame and collects all results into a vector of vector of RecordBatch
     /// maintaining the input partitioning.
     fn collect_partitioned<'py>(&self, py: Python<'py>) -> PyResult<Vec<Vec<Bound<'py, PyAny>>>> {
-        let batches = wait_for_future(py, self.df.as_ref().clone().collect_partitioned())?
+        let (plan, task_ctx) = self.create_and_cache_plan(py)?;
+        let batches = wait_for_future(py, df_collect_partitioned(plan, task_ctx))?
             .map_err(PyDataFusionError::from)?;
 
         batches
@@ -661,7 +707,15 @@ impl PyDataFrame {
     /// Print the result, 20 lines by default
     #[pyo3(signature = (num=20))]
     fn show(&self, py: Python, num: usize) -> PyDataFusionResult<()> {
-        let df = self.df.as_ref().clone().limit(0, Some(num))?;
+        let mut df = self.df.as_ref().clone();
+        df = match self.df.logical_plan() {
+            LogicalPlan::Explain(_) | LogicalPlan::Analyze(_) => {
+                // Explain and Analyzer require they are at the top
+                // of the plan, so do not add a limit.
+                df
+            }
+            _ => df.limit(0, Some(num))?,
+        };
         print_dataframe(py, df)
     }
 
@@ -785,9 +839,27 @@ impl PyDataFrame {
     }
 
     /// Print the query plan
-    #[pyo3(signature = (verbose=false, analyze=false))]
-    fn explain(&self, py: Python, verbose: bool, analyze: bool) -> PyDataFusionResult<()> {
-        let df = self.df.as_ref().clone().explain(verbose, analyze)?;
+    #[pyo3(signature = (verbose=false, analyze=false, format=None))]
+    fn explain(
+        &self,
+        py: Python,
+        verbose: bool,
+        analyze: bool,
+        format: Option<&str>,
+    ) -> PyDataFusionResult<()> {
+        let explain_format = match format {
+            Some(f) => f
+                .parse::<datafusion::common::format::ExplainFormat>()
+                .map_err(|e| {
+                    PyDataFusionError::Common(format!("Invalid explain format '{}': {}", f, e))
+                })?,
+            None => datafusion::common::format::ExplainFormat::Indent,
+        };
+        let opts = datafusion::logical_expr::ExplainOption::default()
+            .with_verbose(verbose)
+            .with_analyze(analyze)
+            .with_format(explain_format);
+        let df = self.df.as_ref().clone().explain_with_options(opts)?;
         print_dataframe(py, df)
     }
 
@@ -802,7 +874,13 @@ impl PyDataFrame {
     }
 
     /// Get the execution plan for this `DataFrame`
+    ///
+    /// If the DataFrame has already been executed (e.g. via `collect()`),
+    /// returns the cached plan which includes populated metrics.
     fn execution_plan(&self, py: Python) -> PyDataFusionResult<PyExecutionPlan> {
+        if let Some(plan) = self.last_plan.lock().as_ref() {
+            return Ok(PyExecutionPlan::new(Arc::clone(plan)));
+        }
         let plan = wait_for_future(py, self.df.as_ref().clone().create_physical_plan())??;
         Ok(plan.into())
     }
@@ -845,39 +923,14 @@ impl PyDataFrame {
         Ok(Self::new(new_df))
     }
 
-    /// Calculate the distinct union of two `DataFrame`s.  The
-    /// two `DataFrame`s must have exactly the same schema
-    fn union_distinct(&self, py_df: PyDataFrame) -> PyDataFusionResult<Self> {
-        let new_df = self
-            .df
-            .as_ref()
-            .clone()
-            .union_distinct(py_df.df.as_ref().clone())?;
-        Ok(Self::new(new_df))
-    }
-
-    #[pyo3(signature = (column, preserve_nulls=true))]
-    fn unnest_column(&self, column: &str, preserve_nulls: bool) -> PyDataFusionResult<Self> {
-        // TODO: expose RecursionUnnestOptions
-        // REF: https://github.com/apache/datafusion/pull/11577
-        let unnest_options = UnnestOptions::default().with_preserve_nulls(preserve_nulls);
-        let df = self
-            .df
-            .as_ref()
-            .clone()
-            .unnest_columns_with_options(&[column], unnest_options)?;
-        Ok(Self::new(df))
-    }
-
-    #[pyo3(signature = (columns, preserve_nulls=true))]
+    #[pyo3(signature = (columns, preserve_nulls=true, recursions=None))]
     fn unnest_columns(
         &self,
         columns: Vec<String>,
         preserve_nulls: bool,
+        recursions: Option<Vec<(String, String, usize)>>,
     ) -> PyDataFusionResult<Self> {
-        // TODO: expose RecursionUnnestOptions
-        // REF: https://github.com/apache/datafusion/pull/11577
-        let unnest_options = UnnestOptions::default().with_preserve_nulls(preserve_nulls);
+        let unnest_options = build_unnest_options(preserve_nulls, recursions);
         let cols = columns.iter().map(|s| s.as_ref()).collect::<Vec<&str>>();
         let df = self
             .df
@@ -888,21 +941,79 @@ impl PyDataFrame {
     }
 
     /// Calculate the intersection of two `DataFrame`s.  The two `DataFrame`s must have exactly the same schema
-    fn intersect(&self, py_df: PyDataFrame) -> PyDataFusionResult<Self> {
-        let new_df = self
-            .df
-            .as_ref()
-            .clone()
-            .intersect(py_df.df.as_ref().clone())?;
+    #[pyo3(signature = (py_df, distinct=false))]
+    fn intersect(&self, py_df: PyDataFrame, distinct: bool) -> PyDataFusionResult<Self> {
+        let base = self.df.as_ref().clone();
+        let other = py_df.df.as_ref().clone();
+        let new_df = if distinct {
+            base.intersect_distinct(other)?
+        } else {
+            base.intersect(other)?
+        };
         Ok(Self::new(new_df))
     }
 
     /// Calculate the exception of two `DataFrame`s.  The two `DataFrame`s must have exactly the same schema
-    fn except_all(&self, py_df: PyDataFrame) -> PyDataFusionResult<Self> {
-        let new_df = self.df.as_ref().clone().except(py_df.df.as_ref().clone())?;
+    #[pyo3(signature = (py_df, distinct=false))]
+    fn except_all(&self, py_df: PyDataFrame, distinct: bool) -> PyDataFusionResult<Self> {
+        let base = self.df.as_ref().clone();
+        let other = py_df.df.as_ref().clone();
+        let new_df = if distinct {
+            base.except_distinct(other)?
+        } else {
+            base.except(other)?
+        };
         Ok(Self::new(new_df))
     }
 
+    /// Union two DataFrames matching columns by name
+    #[pyo3(signature = (py_df, distinct=false))]
+    fn union_by_name(&self, py_df: PyDataFrame, distinct: bool) -> PyDataFusionResult<Self> {
+        let base = self.df.as_ref().clone();
+        let other = py_df.df.as_ref().clone();
+        let new_df = if distinct {
+            base.union_by_name_distinct(other)?
+        } else {
+            base.union_by_name(other)?
+        };
+        Ok(Self::new(new_df))
+    }
+
+    /// Deduplicate rows based on specific columns, keeping the first row per group
+    fn distinct_on(
+        &self,
+        on_expr: Vec<PyExpr>,
+        select_expr: Vec<PyExpr>,
+        sort_expr: Option<Vec<PySortExpr>>,
+    ) -> PyDataFusionResult<Self> {
+        let on_expr = on_expr.into_iter().map(|e| e.into()).collect();
+        let select_expr = select_expr.into_iter().map(|e| e.into()).collect();
+        let sort_expr = sort_expr.map(to_sort_expressions);
+        let df = self
+            .df
+            .as_ref()
+            .clone()
+            .distinct_on(on_expr, select_expr, sort_expr)?;
+        Ok(Self::new(df))
+    }
+
+    /// Sort by column expressions with ascending order and nulls last
+    fn sort_by(&self, exprs: Vec<PyExpr>) -> PyDataFusionResult<Self> {
+        let exprs = exprs.into_iter().map(|e| e.into()).collect();
+        let df = self.df.as_ref().clone().sort_by(exprs)?;
+        Ok(Self::new(df))
+    }
+
+    /// Return fully qualified column expressions for the given column names
+    fn find_qualified_columns(&self, names: Vec<String>) -> PyDataFusionResult<Vec<PyExpr>> {
+        let name_refs: Vec<&str> = names.iter().map(|s| s.as_str()).collect();
+        let qualified = self.df.find_qualified_columns(&name_refs)?;
+        Ok(qualified
+            .into_iter()
+            .map(|q| Expr::Column(Column::from(q)).into())
+            .collect())
+    }
+
     /// Write a `DataFrame` to a CSV file.
     fn write_csv(
         &self,
@@ -1097,9 +1208,10 @@ impl PyDataFrame {
         let mut projection: Option<SchemaRef> = None;
 
         if let Some(schema_capsule) = requested_schema {
-            validate_pycapsule(&schema_capsule, "arrow_schema")?;
-
-            let schema_ptr = unsafe { schema_capsule.reference::<FFI_ArrowSchema>() };
+            let data: NonNull<FFI_ArrowSchema> = schema_capsule
+                .pointer_checked(Some(c"arrow_schema"))?
+                .cast();
+            let schema_ptr = unsafe { data.as_ref() };
             let desired_schema = Schema::try_from(schema_ptr)?;
 
             schema = project_schema(schema, desired_schema)?;
@@ -1126,14 +1238,17 @@ impl PyDataFrame {
     }
 
     fn execute_stream(&self, py: Python) -> PyDataFusionResult<PyRecordBatchStream> {
-        let df = self.df.as_ref().clone();
-        let stream = spawn_future(py, async move { df.execute_stream().await })?;
+        let (plan, task_ctx) = self.create_and_cache_plan(py)?;
+        let stream = spawn_future(py, async move { df_execute_stream(plan, task_ctx) })?;
         Ok(PyRecordBatchStream::new(stream))
     }
 
     fn execute_stream_partitioned(&self, py: Python) -> PyResult<Vec<PyRecordBatchStream>> {
-        let df = self.df.as_ref().clone();
-        let streams = spawn_future(py, async move { df.execute_stream_partitioned().await })?;
+        let (plan, task_ctx) = self.create_and_cache_plan(py)?;
+        let streams = spawn_future(
+            py,
+            async move { df_execute_stream_partitioned(plan, task_ctx) },
+        )?;
         Ok(streams.into_iter().map(PyRecordBatchStream::new).collect())
     }
 
@@ -1203,7 +1318,14 @@ impl PyDataFrame {
 }
 
 #[derive(Debug, Clone, PartialEq, Eq, Hash, PartialOrd, Ord)]
-#[pyclass(frozen, eq, eq_int, name = "InsertOp", module = "datafusion")]
+#[pyclass(
+    from_py_object,
+    frozen,
+    eq,
+    eq_int,
+    name = "InsertOp",
+    module = "datafusion"
+)]
 pub enum PyInsertOp {
     APPEND,
     REPLACE,
@@ -1221,7 +1343,12 @@ impl From<PyInsertOp> for InsertOp {
 }
 
 #[derive(Debug, Clone)]
-#[pyclass(frozen, name = "DataFrameWriteOptions", module = "datafusion")]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "DataFrameWriteOptions",
+    module = "datafusion"
+)]
 pub struct PyDataFrameWriteOptions {
     insert_operation: InsertOp,
     single_file_output: bool,
@@ -1263,6 +1390,26 @@ impl PyDataFrameWriteOptions {
     }
 }
 
+fn build_unnest_options(
+    preserve_nulls: bool,
+    recursions: Option<Vec<(String, String, usize)>>,
+) -> UnnestOptions {
+    let mut opts = UnnestOptions::default().with_preserve_nulls(preserve_nulls);
+    if let Some(recs) = recursions {
+        opts.recursions = recs
+            .into_iter()
+            .map(
+                |(input, output, depth)| datafusion::common::RecursionUnnestOption {
+                    input_column: datafusion::common::Column::from(input.as_str()),
+                    output_column: datafusion::common::Column::from(output.as_str()),
+                    depth,
+                },
+            )
+            .collect();
+    }
+    opts
+}
+
 /// Print DataFrame
 fn print_dataframe(py: Python, df: DataFrame) -> PyDataFusionResult<()> {
     // Get string representation of record batches
diff --git a/src/dataset.rs b/crates/core/src/dataset.rs
similarity index 98%
rename from src/dataset.rs
rename to crates/core/src/dataset.rs
index 6a4fdb1fa..dbeafcd9f 100644
--- a/src/dataset.rs
+++ b/crates/core/src/dataset.rs
@@ -47,7 +47,7 @@ impl Dataset {
         // Ensure that we were passed an instance of pyarrow.dataset.Dataset
         let ds = PyModule::import(py, "pyarrow.dataset")?;
         let ds_attr = ds.getattr("Dataset")?;
-        let ds_type = ds_attr.downcast::<PyType>()?;
+        let ds_type = ds_attr.cast::<PyType>()?;
         if dataset.is_instance(ds_type)? {
             Ok(Dataset {
                 dataset: dataset.clone().unbind(),
diff --git a/src/dataset_exec.rs b/crates/core/src/dataset_exec.rs
similarity index 96%
rename from src/dataset_exec.rs
rename to crates/core/src/dataset_exec.rs
index 61e1544cd..a7dd1500d 100644
--- a/src/dataset_exec.rs
+++ b/crates/core/src/dataset_exec.rs
@@ -31,7 +31,7 @@ use datafusion::physical_plan::execution_plan::{Boundedness, EmissionType};
 use datafusion::physical_plan::stream::RecordBatchStreamAdapter;
 use datafusion::physical_plan::{
     DisplayAs, DisplayFormatType, ExecutionPlan, ExecutionPlanProperties, Partitioning,
-    SendableRecordBatchStream, Statistics,
+    PlanProperties, SendableRecordBatchStream, Statistics,
 };
 use futures::{TryStreamExt, stream};
 /// Implements a Datafusion physical ExecutionPlan that delegates to a PyArrow Dataset
@@ -71,7 +71,7 @@ pub(crate) struct DatasetExec {
     columns: Option<Vec<String>>,
     filter_expr: Option<Py<PyAny>>,
     projected_statistics: Statistics,
-    plan_properties: datafusion::physical_plan::PlanProperties,
+    plan_properties: Arc<PlanProperties>,
 }
 
 impl DatasetExec {
@@ -111,7 +111,7 @@ impl DatasetExec {
 
         let scanner = dataset.call_method("scanner", (), Some(&kwargs))?;
 
-        let schema = Arc::new(
+        let schema: SchemaRef = Arc::new(
             scanner
                 .getattr("projected_schema")?
                 .extract::<PyArrowType<_>>()?
@@ -128,15 +128,15 @@ impl DatasetExec {
         )?;
 
         let fragments_iter = pylist.call1((fragments_iterator,))?;
-        let fragments = fragments_iter.downcast::<PyList>().map_err(PyErr::from)?;
+        let fragments = fragments_iter.cast::<PyList>().map_err(PyErr::from)?;
 
         let projected_statistics = Statistics::new_unknown(&schema);
-        let plan_properties = datafusion::physical_plan::PlanProperties::new(
+        let plan_properties = Arc::new(PlanProperties::new(
             EquivalenceProperties::new(schema.clone()),
             Partitioning::UnknownPartitioning(fragments.len()),
             EmissionType::Final,
             Boundedness::Bounded,
-        );
+        ));
 
         Ok(DatasetExec {
             dataset: dataset.clone().unbind(),
@@ -235,11 +235,11 @@ impl ExecutionPlan for DatasetExec {
         })
     }
 
-    fn statistics(&self) -> DFResult<Statistics> {
+    fn partition_statistics(&self, _partition: Option<usize>) -> DFResult<Statistics> {
         Ok(self.projected_statistics.clone())
     }
 
-    fn properties(&self) -> &datafusion::physical_plan::PlanProperties {
+    fn properties(&self) -> &Arc<PlanProperties> {
         &self.plan_properties
     }
 }
diff --git a/src/expr/grouping_set.rs b/crates/core/src/errors.rs
similarity index 61%
rename from src/expr/grouping_set.rs
rename to crates/core/src/errors.rs
index 107dd9370..8babc5a56 100644
--- a/src/expr/grouping_set.rs
+++ b/crates/core/src/errors.rs
@@ -15,23 +15,4 @@
 // specific language governing permissions and limitations
 // under the License.
 
-use datafusion::logical_expr::GroupingSet;
-use pyo3::prelude::*;
-
-#[pyclass(frozen, name = "GroupingSet", module = "datafusion.expr", subclass)]
-#[derive(Clone)]
-pub struct PyGroupingSet {
-    grouping_set: GroupingSet,
-}
-
-impl From<PyGroupingSet> for GroupingSet {
-    fn from(grouping_set: PyGroupingSet) -> Self {
-        grouping_set.grouping_set
-    }
-}
-
-impl From<GroupingSet> for PyGroupingSet {
-    fn from(grouping_set: GroupingSet) -> PyGroupingSet {
-        PyGroupingSet { grouping_set }
-    }
-}
+pub use datafusion_python_util::errors::*;
diff --git a/src/expr.rs b/crates/core/src/expr.rs
similarity index 97%
rename from src/expr.rs
rename to crates/core/src/expr.rs
index 919174029..c4f2a12da 100644
--- a/src/expr.rs
+++ b/crates/core/src/expr.rs
@@ -24,7 +24,7 @@ use datafusion::arrow::pyarrow::PyArrowType;
 use datafusion::functions::core::expr_ext::FieldAccessor;
 use datafusion::logical_expr::expr::{
     AggregateFunction, AggregateFunctionParams, FieldMetadata, InList, InSubquery, ScalarFunction,
-    WindowFunction,
+    SetComparison, WindowFunction,
 };
 use datafusion::logical_expr::utils::exprlist_to_fields;
 use datafusion::logical_expr::{
@@ -98,6 +98,7 @@ pub mod recursive_query;
 pub mod repartition;
 pub mod scalar_subquery;
 pub mod scalar_variable;
+pub mod set_comparison;
 pub mod signature;
 pub mod sort;
 pub mod sort_expr;
@@ -114,7 +115,13 @@ pub mod window;
 use sort_expr::{PySortExpr, to_sort_expressions};
 
 /// A PyExpr that can be used on a DataFrame
-#[pyclass(frozen, name = "RawExpr", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "RawExpr",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Debug, Clone)]
 pub struct PyExpr {
     pub expr: Expr,
@@ -210,6 +217,9 @@ impl PyExpr {
             Expr::Unnest(value) => {
                 Ok(unnest_expr::PyUnnestExpr::from(value.clone()).into_bound_py_any(py)?)
             }
+            Expr::SetComparison(value) => {
+                Ok(set_comparison::PySetComparison::from(value.clone()).into_bound_py_any(py)?)
+            }
         })
     }
 
@@ -376,7 +386,8 @@ impl PyExpr {
             | Expr::Placeholder { .. }
             | Expr::OuterReferenceColumn(_, _)
             | Expr::Unnest(_)
-            | Expr::IsNotUnknown(_) => RexType::Call,
+            | Expr::IsNotUnknown(_)
+            | Expr::SetComparison(_) => RexType::Call,
             Expr::ScalarSubquery(..) => RexType::ScalarSubquery,
             #[allow(deprecated)]
             Expr::Wildcard { .. } => {
@@ -427,7 +438,10 @@ impl PyExpr {
             | Expr::Negative(expr)
             | Expr::Cast(Cast { expr, .. })
             | Expr::TryCast(TryCast { expr, .. })
-            | Expr::InSubquery(InSubquery { expr, .. }) => Ok(vec![PyExpr::from(*expr.clone())]),
+            | Expr::InSubquery(InSubquery { expr, .. })
+            | Expr::SetComparison(SetComparison { expr, .. }) => {
+                Ok(vec![PyExpr::from(*expr.clone())])
+            }
 
             // Expr variants containing a collection of Expr(s) for operands
             Expr::AggregateFunction(AggregateFunction {
@@ -648,7 +662,13 @@ impl PyExpr {
     }
 }
 
-#[pyclass(frozen, name = "ExprFuncBuilder", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "ExprFuncBuilder",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Debug, Clone)]
 pub struct PyExprFuncBuilder {
     pub builder: ExprFuncBuilder,
@@ -759,7 +779,8 @@ impl PyExpr {
                 | Operator::AtQuestion
                 | Operator::Question
                 | Operator::QuestionAnd
-                | Operator::QuestionPipe => Err(py_type_err(format!("Unsupported expr: ${op}"))),
+                | Operator::QuestionPipe
+                | Operator::Colon => Err(py_type_err(format!("Unsupported expr: ${op}"))),
             },
             Expr::Cast(Cast { expr: _, data_type }) => DataTypeMap::map_from_arrow_type(data_type),
             Expr::Literal(scalar_value, _) => DataTypeMap::map_from_scalar_value(scalar_value),
diff --git a/src/expr/aggregate.rs b/crates/core/src/expr/aggregate.rs
similarity index 97%
rename from src/expr/aggregate.rs
rename to crates/core/src/expr/aggregate.rs
index 9ff280fa9..5a6a771a7 100644
--- a/src/expr/aggregate.rs
+++ b/crates/core/src/expr/aggregate.rs
@@ -30,7 +30,13 @@ use crate::errors::py_type_err;
 use crate::expr::PyExpr;
 use crate::sql::logical::PyLogicalPlan;
 
-#[pyclass(frozen, name = "Aggregate", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "Aggregate",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyAggregate {
     aggregate: Aggregate,
diff --git a/src/expr/aggregate_expr.rs b/crates/core/src/expr/aggregate_expr.rs
similarity index 99%
rename from src/expr/aggregate_expr.rs
rename to crates/core/src/expr/aggregate_expr.rs
index d3b695a27..88e47999f 100644
--- a/src/expr/aggregate_expr.rs
+++ b/crates/core/src/expr/aggregate_expr.rs
@@ -23,6 +23,7 @@ use pyo3::prelude::*;
 use crate::expr::PyExpr;
 
 #[pyclass(
+    from_py_object,
     frozen,
     name = "AggregateFunction",
     module = "datafusion.expr",
diff --git a/src/expr/alias.rs b/crates/core/src/expr/alias.rs
similarity index 94%
rename from src/expr/alias.rs
rename to crates/core/src/expr/alias.rs
index c6d486284..b76e82e22 100644
--- a/src/expr/alias.rs
+++ b/crates/core/src/expr/alias.rs
@@ -22,7 +22,13 @@ use pyo3::prelude::*;
 
 use crate::expr::PyExpr;
 
-#[pyclass(frozen, name = "Alias", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "Alias",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyAlias {
     alias: Alias,
diff --git a/src/expr/analyze.rs b/crates/core/src/expr/analyze.rs
similarity index 95%
rename from src/expr/analyze.rs
rename to crates/core/src/expr/analyze.rs
index 3aae6f315..137765fe1 100644
--- a/src/expr/analyze.rs
+++ b/crates/core/src/expr/analyze.rs
@@ -25,7 +25,13 @@ use super::logical_node::LogicalNode;
 use crate::common::df_schema::PyDFSchema;
 use crate::sql::logical::PyLogicalPlan;
 
-#[pyclass(frozen, name = "Analyze", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "Analyze",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyAnalyze {
     analyze: Analyze,
diff --git a/src/expr/between.rs b/crates/core/src/expr/between.rs
similarity index 94%
rename from src/expr/between.rs
rename to crates/core/src/expr/between.rs
index 4f0b34add..6943b6c3b 100644
--- a/src/expr/between.rs
+++ b/crates/core/src/expr/between.rs
@@ -22,7 +22,13 @@ use pyo3::prelude::*;
 
 use crate::expr::PyExpr;
 
-#[pyclass(frozen, name = "Between", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "Between",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyBetween {
     between: Between,
diff --git a/src/expr/binary_expr.rs b/crates/core/src/expr/binary_expr.rs
similarity index 93%
rename from src/expr/binary_expr.rs
rename to crates/core/src/expr/binary_expr.rs
index f67a08c7c..2326ba705 100644
--- a/src/expr/binary_expr.rs
+++ b/crates/core/src/expr/binary_expr.rs
@@ -20,7 +20,13 @@ use pyo3::prelude::*;
 
 use crate::expr::PyExpr;
 
-#[pyclass(frozen, name = "BinaryExpr", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "BinaryExpr",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyBinaryExpr {
     expr: BinaryExpr,
diff --git a/src/expr/bool_expr.rs b/crates/core/src/expr/bool_expr.rs
similarity index 83%
rename from src/expr/bool_expr.rs
rename to crates/core/src/expr/bool_expr.rs
index abd259409..9e374c7e2 100644
--- a/src/expr/bool_expr.rs
+++ b/crates/core/src/expr/bool_expr.rs
@@ -22,7 +22,13 @@ use pyo3::prelude::*;
 
 use super::PyExpr;
 
-#[pyclass(frozen, name = "Not", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "Not",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone, Debug)]
 pub struct PyNot {
     expr: Expr,
@@ -52,7 +58,13 @@ impl PyNot {
     }
 }
 
-#[pyclass(frozen, name = "IsNotNull", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "IsNotNull",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone, Debug)]
 pub struct PyIsNotNull {
     expr: Expr,
@@ -82,7 +94,13 @@ impl PyIsNotNull {
     }
 }
 
-#[pyclass(frozen, name = "IsNull", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "IsNull",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone, Debug)]
 pub struct PyIsNull {
     expr: Expr,
@@ -112,7 +130,13 @@ impl PyIsNull {
     }
 }
 
-#[pyclass(frozen, name = "IsTrue", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "IsTrue",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone, Debug)]
 pub struct PyIsTrue {
     expr: Expr,
@@ -142,7 +166,13 @@ impl PyIsTrue {
     }
 }
 
-#[pyclass(frozen, name = "IsFalse", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "IsFalse",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone, Debug)]
 pub struct PyIsFalse {
     expr: Expr,
@@ -172,7 +202,13 @@ impl PyIsFalse {
     }
 }
 
-#[pyclass(frozen, name = "IsUnknown", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "IsUnknown",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone, Debug)]
 pub struct PyIsUnknown {
     expr: Expr,
@@ -202,7 +238,13 @@ impl PyIsUnknown {
     }
 }
 
-#[pyclass(frozen, name = "IsNotTrue", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "IsNotTrue",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone, Debug)]
 pub struct PyIsNotTrue {
     expr: Expr,
@@ -232,7 +274,13 @@ impl PyIsNotTrue {
     }
 }
 
-#[pyclass(frozen, name = "IsNotFalse", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "IsNotFalse",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone, Debug)]
 pub struct PyIsNotFalse {
     expr: Expr,
@@ -262,7 +310,13 @@ impl PyIsNotFalse {
     }
 }
 
-#[pyclass(frozen, name = "IsNotUnknown", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "IsNotUnknown",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone, Debug)]
 pub struct PyIsNotUnknown {
     expr: Expr,
@@ -292,7 +346,13 @@ impl PyIsNotUnknown {
     }
 }
 
-#[pyclass(frozen, name = "Negative", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "Negative",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone, Debug)]
 pub struct PyNegative {
     expr: Expr,
diff --git a/src/expr/case.rs b/crates/core/src/expr/case.rs
similarity index 93%
rename from src/expr/case.rs
rename to crates/core/src/expr/case.rs
index b49c19081..4f00449d8 100644
--- a/src/expr/case.rs
+++ b/crates/core/src/expr/case.rs
@@ -20,7 +20,13 @@ use pyo3::prelude::*;
 
 use crate::expr::PyExpr;
 
-#[pyclass(frozen, name = "Case", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "Case",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyCase {
     case: Case,
diff --git a/src/expr/cast.rs b/crates/core/src/expr/cast.rs
similarity index 91%
rename from src/expr/cast.rs
rename to crates/core/src/expr/cast.rs
index 1aca9ea95..37d603538 100644
--- a/src/expr/cast.rs
+++ b/crates/core/src/expr/cast.rs
@@ -21,7 +21,13 @@ use pyo3::prelude::*;
 use crate::common::data_type::PyDataType;
 use crate::expr::PyExpr;
 
-#[pyclass(frozen, name = "Cast", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "Cast",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyCast {
     cast: Cast,
@@ -50,7 +56,7 @@ impl PyCast {
     }
 }
 
-#[pyclass(name = "TryCast", module = "datafusion.expr", subclass)]
+#[pyclass(from_py_object, name = "TryCast", module = "datafusion.expr", subclass)]
 #[derive(Clone)]
 pub struct PyTryCast {
     try_cast: TryCast,
diff --git a/src/expr/column.rs b/crates/core/src/expr/column.rs
similarity index 93%
rename from src/expr/column.rs
rename to crates/core/src/expr/column.rs
index 300079481..c1238f98a 100644
--- a/src/expr/column.rs
+++ b/crates/core/src/expr/column.rs
@@ -18,7 +18,13 @@
 use datafusion::common::Column;
 use pyo3::prelude::*;
 
-#[pyclass(frozen, name = "Column", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "Column",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyColumn {
     pub col: Column,
diff --git a/src/expr/conditional_expr.rs b/crates/core/src/expr/conditional_expr.rs
similarity index 95%
rename from src/expr/conditional_expr.rs
rename to crates/core/src/expr/conditional_expr.rs
index da6102dbf..ea21fdb20 100644
--- a/src/expr/conditional_expr.rs
+++ b/crates/core/src/expr/conditional_expr.rs
@@ -24,7 +24,13 @@ use crate::expr::PyExpr;
 
 // TODO(tsaucer) replace this all with CaseBuilder after it implements Clone
 #[derive(Clone, Debug)]
-#[pyclass(name = "CaseBuilder", module = "datafusion.expr", subclass, frozen)]
+#[pyclass(
+    from_py_object,
+    name = "CaseBuilder",
+    module = "datafusion.expr",
+    subclass,
+    frozen
+)]
 pub struct PyCaseBuilder {
     expr: Option<Expr>,
     when: Vec<Expr>,
diff --git a/src/expr/copy_to.rs b/crates/core/src/expr/copy_to.rs
similarity index 93%
rename from src/expr/copy_to.rs
rename to crates/core/src/expr/copy_to.rs
index 807104fc1..78e53cdff 100644
--- a/src/expr/copy_to.rs
+++ b/crates/core/src/expr/copy_to.rs
@@ -27,7 +27,13 @@ use pyo3::prelude::*;
 use super::logical_node::LogicalNode;
 use crate::sql::logical::PyLogicalPlan;
 
-#[pyclass(frozen, name = "CopyTo", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "CopyTo",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyCopyTo {
     copy: CopyTo,
@@ -113,7 +119,13 @@ impl PyCopyTo {
     }
 }
 
-#[pyclass(frozen, name = "FileType", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "FileType",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyFileType {
     file_type: Arc<dyn FileType>,
diff --git a/src/expr/create_catalog.rs b/crates/core/src/expr/create_catalog.rs
similarity index 95%
rename from src/expr/create_catalog.rs
rename to crates/core/src/expr/create_catalog.rs
index 0131014eb..fa95980c0 100644
--- a/src/expr/create_catalog.rs
+++ b/crates/core/src/expr/create_catalog.rs
@@ -26,7 +26,13 @@ use super::logical_node::LogicalNode;
 use crate::common::df_schema::PyDFSchema;
 use crate::sql::logical::PyLogicalPlan;
 
-#[pyclass(frozen, name = "CreateCatalog", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "CreateCatalog",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyCreateCatalog {
     create: CreateCatalog,
diff --git a/src/expr/create_catalog_schema.rs b/crates/core/src/expr/create_catalog_schema.rs
similarity index 99%
rename from src/expr/create_catalog_schema.rs
rename to crates/core/src/expr/create_catalog_schema.rs
index 63ed3a2d2..d836284a0 100644
--- a/src/expr/create_catalog_schema.rs
+++ b/crates/core/src/expr/create_catalog_schema.rs
@@ -27,6 +27,7 @@ use crate::common::df_schema::PyDFSchema;
 use crate::sql::logical::PyLogicalPlan;
 
 #[pyclass(
+    from_py_object,
     frozen,
     name = "CreateCatalogSchema",
     module = "datafusion.expr",
diff --git a/src/expr/create_external_table.rs b/crates/core/src/expr/create_external_table.rs
similarity index 99%
rename from src/expr/create_external_table.rs
rename to crates/core/src/expr/create_external_table.rs
index cb4bb781a..980eea131 100644
--- a/src/expr/create_external_table.rs
+++ b/crates/core/src/expr/create_external_table.rs
@@ -31,6 +31,7 @@ use crate::expr::PyExpr;
 use crate::sql::logical::PyLogicalPlan;
 
 #[pyclass(
+    from_py_object,
     frozen,
     name = "CreateExternalTable",
     module = "datafusion.expr",
diff --git a/src/expr/create_function.rs b/crates/core/src/expr/create_function.rs
similarity index 94%
rename from src/expr/create_function.rs
rename to crates/core/src/expr/create_function.rs
index 3433363a0..622858913 100644
--- a/src/expr/create_function.rs
+++ b/crates/core/src/expr/create_function.rs
@@ -30,7 +30,13 @@ use crate::common::data_type::PyDataType;
 use crate::common::df_schema::PyDFSchema;
 use crate::sql::logical::PyLogicalPlan;
 
-#[pyclass(frozen, name = "CreateFunction", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "CreateFunction",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyCreateFunction {
     create: CreateFunction,
@@ -55,6 +61,7 @@ impl Display for PyCreateFunction {
 }
 
 #[pyclass(
+    from_py_object,
     frozen,
     name = "OperateFunctionArg",
     module = "datafusion.expr",
@@ -66,7 +73,14 @@ pub struct PyOperateFunctionArg {
 }
 
 #[derive(Debug, Clone, PartialEq, Eq, Hash, PartialOrd, Ord)]
-#[pyclass(frozen, eq, eq_int, name = "Volatility", module = "datafusion.expr")]
+#[pyclass(
+    from_py_object,
+    frozen,
+    eq,
+    eq_int,
+    name = "Volatility",
+    module = "datafusion.expr"
+)]
 pub enum PyVolatility {
     Immutable,
     Stable,
@@ -74,6 +88,7 @@ pub enum PyVolatility {
 }
 
 #[pyclass(
+    from_py_object,
     frozen,
     name = "CreateFunctionBody",
     module = "datafusion.expr",
diff --git a/src/expr/create_index.rs b/crates/core/src/expr/create_index.rs
similarity index 96%
rename from src/expr/create_index.rs
rename to crates/core/src/expr/create_index.rs
index ebe0620ca..5f9bd11e8 100644
--- a/src/expr/create_index.rs
+++ b/crates/core/src/expr/create_index.rs
@@ -27,7 +27,13 @@ use super::sort_expr::PySortExpr;
 use crate::common::df_schema::PyDFSchema;
 use crate::sql::logical::PyLogicalPlan;
 
-#[pyclass(frozen, name = "CreateIndex", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "CreateIndex",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyCreateIndex {
     create: CreateIndex,
diff --git a/src/expr/create_memory_table.rs b/crates/core/src/expr/create_memory_table.rs
similarity index 99%
rename from src/expr/create_memory_table.rs
rename to crates/core/src/expr/create_memory_table.rs
index c11a816aa..3214dab0e 100644
--- a/src/expr/create_memory_table.rs
+++ b/crates/core/src/expr/create_memory_table.rs
@@ -25,6 +25,7 @@ use super::logical_node::LogicalNode;
 use crate::sql::logical::PyLogicalPlan;
 
 #[pyclass(
+    from_py_object,
     frozen,
     name = "CreateMemoryTable",
     module = "datafusion.expr",
diff --git a/src/expr/create_view.rs b/crates/core/src/expr/create_view.rs
similarity index 96%
rename from src/expr/create_view.rs
rename to crates/core/src/expr/create_view.rs
index 52882ddbc..6941ef769 100644
--- a/src/expr/create_view.rs
+++ b/crates/core/src/expr/create_view.rs
@@ -25,7 +25,13 @@ use super::logical_node::LogicalNode;
 use crate::errors::py_type_err;
 use crate::sql::logical::PyLogicalPlan;
 
-#[pyclass(frozen, name = "CreateView", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "CreateView",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyCreateView {
     create: CreateView,
diff --git a/src/expr/describe_table.rs b/crates/core/src/expr/describe_table.rs
similarity index 95%
rename from src/expr/describe_table.rs
rename to crates/core/src/expr/describe_table.rs
index 721c13ab9..73955bb34 100644
--- a/src/expr/describe_table.rs
+++ b/crates/core/src/expr/describe_table.rs
@@ -28,7 +28,13 @@ use super::logical_node::LogicalNode;
 use crate::common::df_schema::PyDFSchema;
 use crate::sql::logical::PyLogicalPlan;
 
-#[pyclass(frozen, name = "DescribeTable", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "DescribeTable",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyDescribeTable {
     describe: DescribeTable,
diff --git a/src/expr/distinct.rs b/crates/core/src/expr/distinct.rs
similarity index 95%
rename from src/expr/distinct.rs
rename to crates/core/src/expr/distinct.rs
index c7da9c7f6..68c2a17fe 100644
--- a/src/expr/distinct.rs
+++ b/crates/core/src/expr/distinct.rs
@@ -24,7 +24,13 @@ use pyo3::prelude::*;
 use super::logical_node::LogicalNode;
 use crate::sql::logical::PyLogicalPlan;
 
-#[pyclass(frozen, name = "Distinct", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "Distinct",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyDistinct {
     distinct: Distinct,
diff --git a/src/expr/dml.rs b/crates/core/src/expr/dml.rs
similarity index 91%
rename from src/expr/dml.rs
rename to crates/core/src/expr/dml.rs
index 84a34e65f..26f975820 100644
--- a/src/expr/dml.rs
+++ b/crates/core/src/expr/dml.rs
@@ -25,7 +25,13 @@ use crate::common::df_schema::PyDFSchema;
 use crate::common::schema::PyTableSource;
 use crate::sql::logical::PyLogicalPlan;
 
-#[pyclass(frozen, name = "DmlStatement", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "DmlStatement",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyDmlStatement {
     dml: DmlStatement,
@@ -89,15 +95,21 @@ impl PyDmlStatement {
 }
 
 #[derive(Debug, Clone, PartialEq, Eq, Hash, PartialOrd, Ord)]
-#[pyclass(eq, eq_int, name = "WriteOp", module = "datafusion.expr")]
+#[pyclass(
+    from_py_object,
+    eq,
+    eq_int,
+    name = "WriteOp",
+    module = "datafusion.expr"
+)]
 pub enum PyWriteOp {
     Append,
     Overwrite,
     Replace,
-
     Update,
     Delete,
     Ctas,
+    Truncate,
 }
 
 impl From<WriteOp> for PyWriteOp {
@@ -106,10 +118,10 @@ impl From<WriteOp> for PyWriteOp {
             WriteOp::Insert(InsertOp::Append) => PyWriteOp::Append,
             WriteOp::Insert(InsertOp::Overwrite) => PyWriteOp::Overwrite,
             WriteOp::Insert(InsertOp::Replace) => PyWriteOp::Replace,
-
             WriteOp::Update => PyWriteOp::Update,
             WriteOp::Delete => PyWriteOp::Delete,
             WriteOp::Ctas => PyWriteOp::Ctas,
+            WriteOp::Truncate => PyWriteOp::Truncate,
         }
     }
 }
@@ -120,10 +132,10 @@ impl From<PyWriteOp> for WriteOp {
             PyWriteOp::Append => WriteOp::Insert(InsertOp::Append),
             PyWriteOp::Overwrite => WriteOp::Insert(InsertOp::Overwrite),
             PyWriteOp::Replace => WriteOp::Insert(InsertOp::Replace),
-
             PyWriteOp::Update => WriteOp::Update,
             PyWriteOp::Delete => WriteOp::Delete,
             PyWriteOp::Ctas => WriteOp::Ctas,
+            PyWriteOp::Truncate => WriteOp::Truncate,
         }
     }
 }
diff --git a/src/expr/drop_catalog_schema.rs b/crates/core/src/expr/drop_catalog_schema.rs
similarity index 99%
rename from src/expr/drop_catalog_schema.rs
rename to crates/core/src/expr/drop_catalog_schema.rs
index 339e11968..fd5105332 100644
--- a/src/expr/drop_catalog_schema.rs
+++ b/crates/core/src/expr/drop_catalog_schema.rs
@@ -30,6 +30,7 @@ use crate::common::df_schema::PyDFSchema;
 use crate::sql::logical::PyLogicalPlan;
 
 #[pyclass(
+    from_py_object,
     frozen,
     name = "DropCatalogSchema",
     module = "datafusion.expr",
diff --git a/src/expr/drop_function.rs b/crates/core/src/expr/drop_function.rs
similarity index 95%
rename from src/expr/drop_function.rs
rename to crates/core/src/expr/drop_function.rs
index db0942a0c..0599dd49e 100644
--- a/src/expr/drop_function.rs
+++ b/crates/core/src/expr/drop_function.rs
@@ -26,7 +26,13 @@ use super::logical_node::LogicalNode;
 use crate::common::df_schema::PyDFSchema;
 use crate::sql::logical::PyLogicalPlan;
 
-#[pyclass(frozen, name = "DropFunction", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "DropFunction",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyDropFunction {
     drop: DropFunction,
diff --git a/src/expr/drop_table.rs b/crates/core/src/expr/drop_table.rs
similarity index 95%
rename from src/expr/drop_table.rs
rename to crates/core/src/expr/drop_table.rs
index 9bf2c6530..46fe67465 100644
--- a/src/expr/drop_table.rs
+++ b/crates/core/src/expr/drop_table.rs
@@ -24,7 +24,13 @@ use pyo3::prelude::*;
 use super::logical_node::LogicalNode;
 use crate::sql::logical::PyLogicalPlan;
 
-#[pyclass(frozen, name = "DropTable", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "DropTable",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyDropTable {
     drop: DropTable,
diff --git a/src/expr/drop_view.rs b/crates/core/src/expr/drop_view.rs
similarity index 95%
rename from src/expr/drop_view.rs
rename to crates/core/src/expr/drop_view.rs
index 187865f4f..0d0c51f13 100644
--- a/src/expr/drop_view.rs
+++ b/crates/core/src/expr/drop_view.rs
@@ -26,7 +26,13 @@ use super::logical_node::LogicalNode;
 use crate::common::df_schema::PyDFSchema;
 use crate::sql::logical::PyLogicalPlan;
 
-#[pyclass(frozen, name = "DropView", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "DropView",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyDropView {
     drop: DropView,
diff --git a/src/expr/empty_relation.rs b/crates/core/src/expr/empty_relation.rs
similarity index 95%
rename from src/expr/empty_relation.rs
rename to crates/core/src/expr/empty_relation.rs
index 4a9e82358..f3c237731 100644
--- a/src/expr/empty_relation.rs
+++ b/crates/core/src/expr/empty_relation.rs
@@ -25,7 +25,13 @@ use super::logical_node::LogicalNode;
 use crate::common::df_schema::PyDFSchema;
 use crate::sql::logical::PyLogicalPlan;
 
-#[pyclass(frozen, name = "EmptyRelation", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "EmptyRelation",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyEmptyRelation {
     empty: EmptyRelation,
diff --git a/src/expr/exists.rs b/crates/core/src/expr/exists.rs
similarity index 91%
rename from src/expr/exists.rs
rename to crates/core/src/expr/exists.rs
index 392bfcb9e..d2e816127 100644
--- a/src/expr/exists.rs
+++ b/crates/core/src/expr/exists.rs
@@ -20,7 +20,13 @@ use pyo3::prelude::*;
 
 use super::subquery::PySubquery;
 
-#[pyclass(frozen, name = "Exists", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "Exists",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyExists {
     exists: Exists,
diff --git a/src/expr/explain.rs b/crates/core/src/expr/explain.rs
similarity index 96%
rename from src/expr/explain.rs
rename to crates/core/src/expr/explain.rs
index 2100df5c7..6259951de 100644
--- a/src/expr/explain.rs
+++ b/crates/core/src/expr/explain.rs
@@ -27,7 +27,13 @@ use crate::common::df_schema::PyDFSchema;
 use crate::errors::py_type_err;
 use crate::sql::logical::PyLogicalPlan;
 
-#[pyclass(frozen, name = "Explain", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "Explain",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyExplain {
     explain: Explain,
diff --git a/src/expr/extension.rs b/crates/core/src/expr/extension.rs
similarity index 92%
rename from src/expr/extension.rs
rename to crates/core/src/expr/extension.rs
index 2d9ac45f9..a0b617565 100644
--- a/src/expr/extension.rs
+++ b/crates/core/src/expr/extension.rs
@@ -22,7 +22,13 @@ use pyo3::prelude::*;
 use super::logical_node::LogicalNode;
 use crate::sql::logical::PyLogicalPlan;
 
-#[pyclass(frozen, name = "Extension", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "Extension",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyExtension {
     pub node: Extension,
diff --git a/src/expr/filter.rs b/crates/core/src/expr/filter.rs
similarity index 95%
rename from src/expr/filter.rs
rename to crates/core/src/expr/filter.rs
index bee180565..67426806d 100644
--- a/src/expr/filter.rs
+++ b/crates/core/src/expr/filter.rs
@@ -26,7 +26,13 @@ use crate::expr::PyExpr;
 use crate::expr::logical_node::LogicalNode;
 use crate::sql::logical::PyLogicalPlan;
 
-#[pyclass(frozen, name = "Filter", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "Filter",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyFilter {
     filter: Filter,
diff --git a/crates/core/src/expr/grouping_set.rs b/crates/core/src/expr/grouping_set.rs
new file mode 100644
index 000000000..11d8f4fcd
--- /dev/null
+++ b/crates/core/src/expr/grouping_set.rs
@@ -0,0 +1,78 @@
+// Licensed to the Apache Software Foundation (ASF) under one
+// or more contributor license agreements.  See the NOTICE file
+// distributed with this work for additional information
+// regarding copyright ownership.  The ASF licenses this file
+// to you under the Apache License, Version 2.0 (the
+// "License"); you may not use this file except in compliance
+// with the License.  You may obtain a copy of the License at
+//
+//   http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing,
+// software distributed under the License is distributed on an
+// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+// KIND, either express or implied.  See the License for the
+// specific language governing permissions and limitations
+// under the License.
+
+use datafusion::logical_expr::{Expr, GroupingSet};
+use pyo3::prelude::*;
+
+use crate::expr::PyExpr;
+
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "GroupingSet",
+    module = "datafusion.expr",
+    subclass
+)]
+#[derive(Clone)]
+pub struct PyGroupingSet {
+    grouping_set: GroupingSet,
+}
+
+#[pymethods]
+impl PyGroupingSet {
+    #[staticmethod]
+    #[pyo3(signature = (*exprs))]
+    fn rollup(exprs: Vec<PyExpr>) -> PyExpr {
+        Expr::GroupingSet(GroupingSet::Rollup(
+            exprs.into_iter().map(|e| e.expr).collect(),
+        ))
+        .into()
+    }
+
+    #[staticmethod]
+    #[pyo3(signature = (*exprs))]
+    fn cube(exprs: Vec<PyExpr>) -> PyExpr {
+        Expr::GroupingSet(GroupingSet::Cube(
+            exprs.into_iter().map(|e| e.expr).collect(),
+        ))
+        .into()
+    }
+
+    #[staticmethod]
+    #[pyo3(signature = (*expr_lists))]
+    fn grouping_sets(expr_lists: Vec<Vec<PyExpr>>) -> PyExpr {
+        Expr::GroupingSet(GroupingSet::GroupingSets(
+            expr_lists
+                .into_iter()
+                .map(|list| list.into_iter().map(|e| e.expr).collect())
+                .collect(),
+        ))
+        .into()
+    }
+}
+
+impl From<PyGroupingSet> for GroupingSet {
+    fn from(grouping_set: PyGroupingSet) -> Self {
+        grouping_set.grouping_set
+    }
+}
+
+impl From<GroupingSet> for PyGroupingSet {
+    fn from(grouping_set: GroupingSet) -> PyGroupingSet {
+        PyGroupingSet { grouping_set }
+    }
+}
diff --git a/src/expr/in_list.rs b/crates/core/src/expr/in_list.rs
similarity index 92%
rename from src/expr/in_list.rs
rename to crates/core/src/expr/in_list.rs
index 128c3f4c2..0612cc21e 100644
--- a/src/expr/in_list.rs
+++ b/crates/core/src/expr/in_list.rs
@@ -20,7 +20,13 @@ use pyo3::prelude::*;
 
 use crate::expr::PyExpr;
 
-#[pyclass(frozen, name = "InList", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "InList",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyInList {
     in_list: InList,
diff --git a/src/expr/in_subquery.rs b/crates/core/src/expr/in_subquery.rs
similarity index 92%
rename from src/expr/in_subquery.rs
rename to crates/core/src/expr/in_subquery.rs
index 139e8376e..81a2c5794 100644
--- a/src/expr/in_subquery.rs
+++ b/crates/core/src/expr/in_subquery.rs
@@ -21,7 +21,13 @@ use pyo3::prelude::*;
 use super::PyExpr;
 use super::subquery::PySubquery;
 
-#[pyclass(frozen, name = "InSubquery", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "InSubquery",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyInSubquery {
     in_subquery: InSubquery,
diff --git a/src/expr/indexed_field.rs b/crates/core/src/expr/indexed_field.rs
similarity index 94%
rename from src/expr/indexed_field.rs
rename to crates/core/src/expr/indexed_field.rs
index 1dfa0ed2f..98a90d8d4 100644
--- a/src/expr/indexed_field.rs
+++ b/crates/core/src/expr/indexed_field.rs
@@ -15,14 +15,21 @@
 // specific language governing permissions and limitations
 // under the License.
 
-use crate::expr::PyExpr;
+use std::fmt::{Display, Formatter};
+
 use datafusion::logical_expr::expr::{GetFieldAccess, GetIndexedField};
 use pyo3::prelude::*;
-use std::fmt::{Display, Formatter};
 
 use super::literal::PyLiteral;
+use crate::expr::PyExpr;
 
-#[pyclass(frozen, name = "GetIndexedField", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "GetIndexedField",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyGetIndexedField {
     indexed_field: GetIndexedField,
diff --git a/src/expr/join.rs b/crates/core/src/expr/join.rs
similarity index 94%
rename from src/expr/join.rs
rename to crates/core/src/expr/join.rs
index 2cfd8cc28..b90f2f57d 100644
--- a/src/expr/join.rs
+++ b/crates/core/src/expr/join.rs
@@ -28,7 +28,7 @@ use crate::expr::logical_node::LogicalNode;
 use crate::sql::logical::PyLogicalPlan;
 
 #[derive(Debug, Clone, PartialEq, Eq, Hash)]
-#[pyclass(frozen, name = "JoinType", module = "datafusion.expr")]
+#[pyclass(from_py_object, frozen, name = "JoinType", module = "datafusion.expr")]
 pub struct PyJoinType {
     join_type: JoinType,
 }
@@ -63,7 +63,12 @@ impl Display for PyJoinType {
 }
 
 #[derive(Debug, Clone, Copy)]
-#[pyclass(frozen, name = "JoinConstraint", module = "datafusion.expr")]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "JoinConstraint",
+    module = "datafusion.expr"
+)]
 pub struct PyJoinConstraint {
     join_constraint: JoinConstraint,
 }
@@ -90,7 +95,13 @@ impl PyJoinConstraint {
     }
 }
 
-#[pyclass(frozen, name = "Join", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "Join",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyJoin {
     join: Join,
diff --git a/src/expr/like.rs b/crates/core/src/expr/like.rs
similarity index 92%
rename from src/expr/like.rs
rename to crates/core/src/expr/like.rs
index 94860bd6c..417dc9182 100644
--- a/src/expr/like.rs
+++ b/crates/core/src/expr/like.rs
@@ -22,7 +22,13 @@ use pyo3::prelude::*;
 
 use crate::expr::PyExpr;
 
-#[pyclass(frozen, name = "Like", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "Like",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyLike {
     like: Like,
@@ -80,7 +86,13 @@ impl PyLike {
     }
 }
 
-#[pyclass(frozen, name = "ILike", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "ILike",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyILike {
     like: Like,
@@ -138,7 +150,13 @@ impl PyILike {
     }
 }
 
-#[pyclass(frozen, name = "SimilarTo", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "SimilarTo",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PySimilarTo {
     like: Like,
diff --git a/src/expr/limit.rs b/crates/core/src/expr/limit.rs
similarity index 96%
rename from src/expr/limit.rs
rename to crates/core/src/expr/limit.rs
index aad921605..c04b8bfa8 100644
--- a/src/expr/limit.rs
+++ b/crates/core/src/expr/limit.rs
@@ -25,7 +25,13 @@ use crate::common::df_schema::PyDFSchema;
 use crate::expr::logical_node::LogicalNode;
 use crate::sql::logical::PyLogicalPlan;
 
-#[pyclass(frozen, name = "Limit", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "Limit",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyLimit {
     limit: Limit,
diff --git a/src/expr/literal.rs b/crates/core/src/expr/literal.rs
similarity index 97%
rename from src/expr/literal.rs
rename to crates/core/src/expr/literal.rs
index f97c2b491..9db0f594b 100644
--- a/src/expr/literal.rs
+++ b/crates/core/src/expr/literal.rs
@@ -22,7 +22,13 @@ use pyo3::prelude::*;
 
 use crate::errors::PyDataFusionError;
 
-#[pyclass(name = "Literal", module = "datafusion.expr", subclass, frozen)]
+#[pyclass(
+    from_py_object,
+    name = "Literal",
+    module = "datafusion.expr",
+    subclass,
+    frozen
+)]
 #[derive(Clone)]
 pub struct PyLiteral {
     pub value: ScalarValue,
diff --git a/src/expr/logical_node.rs b/crates/core/src/expr/logical_node.rs
similarity index 100%
rename from src/expr/logical_node.rs
rename to crates/core/src/expr/logical_node.rs
diff --git a/src/expr/placeholder.rs b/crates/core/src/expr/placeholder.rs
similarity index 93%
rename from src/expr/placeholder.rs
rename to crates/core/src/expr/placeholder.rs
index f1e8694a9..6bd88321c 100644
--- a/src/expr/placeholder.rs
+++ b/crates/core/src/expr/placeholder.rs
@@ -22,7 +22,13 @@ use pyo3::prelude::*;
 
 use crate::common::data_type::PyDataType;
 
-#[pyclass(frozen, name = "Placeholder", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "Placeholder",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyPlaceholder {
     placeholder: Placeholder,
diff --git a/src/expr/projection.rs b/crates/core/src/expr/projection.rs
similarity index 96%
rename from src/expr/projection.rs
rename to crates/core/src/expr/projection.rs
index 1bce3389f..456e06412 100644
--- a/src/expr/projection.rs
+++ b/crates/core/src/expr/projection.rs
@@ -27,7 +27,13 @@ use crate::expr::PyExpr;
 use crate::expr::logical_node::LogicalNode;
 use crate::sql::logical::PyLogicalPlan;
 
-#[pyclass(frozen, name = "Projection", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "Projection",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyProjection {
     pub projection: Projection,
diff --git a/src/expr/recursive_query.rs b/crates/core/src/expr/recursive_query.rs
similarity index 96%
rename from src/expr/recursive_query.rs
rename to crates/core/src/expr/recursive_query.rs
index 3f6d06558..e03137b80 100644
--- a/src/expr/recursive_query.rs
+++ b/crates/core/src/expr/recursive_query.rs
@@ -24,7 +24,13 @@ use pyo3::prelude::*;
 use super::logical_node::LogicalNode;
 use crate::sql::logical::PyLogicalPlan;
 
-#[pyclass(frozen, name = "RecursiveQuery", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "RecursiveQuery",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyRecursiveQuery {
     query: RecursiveQuery,
diff --git a/src/expr/repartition.rs b/crates/core/src/expr/repartition.rs
similarity index 94%
rename from src/expr/repartition.rs
rename to crates/core/src/expr/repartition.rs
index b4fd78bc3..be39b9978 100644
--- a/src/expr/repartition.rs
+++ b/crates/core/src/expr/repartition.rs
@@ -27,13 +27,25 @@ use super::logical_node::LogicalNode;
 use crate::errors::py_type_err;
 use crate::sql::logical::PyLogicalPlan;
 
-#[pyclass(frozen, name = "Repartition", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "Repartition",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyRepartition {
     repartition: Repartition,
 }
 
-#[pyclass(frozen, name = "Partitioning", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "Partitioning",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyPartitioning {
     partitioning: Partitioning,
diff --git a/src/expr/scalar_subquery.rs b/crates/core/src/expr/scalar_subquery.rs
similarity index 91%
rename from src/expr/scalar_subquery.rs
rename to crates/core/src/expr/scalar_subquery.rs
index e58d66e19..c7852a4c4 100644
--- a/src/expr/scalar_subquery.rs
+++ b/crates/core/src/expr/scalar_subquery.rs
@@ -20,7 +20,13 @@ use pyo3::prelude::*;
 
 use super::subquery::PySubquery;
 
-#[pyclass(frozen, name = "ScalarSubquery", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "ScalarSubquery",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyScalarSubquery {
     subquery: Subquery,
diff --git a/src/expr/scalar_variable.rs b/crates/core/src/expr/scalar_variable.rs
similarity index 92%
rename from src/expr/scalar_variable.rs
rename to crates/core/src/expr/scalar_variable.rs
index 5bc056e76..2d3bc4b76 100644
--- a/src/expr/scalar_variable.rs
+++ b/crates/core/src/expr/scalar_variable.rs
@@ -20,7 +20,13 @@ use pyo3::prelude::*;
 
 use crate::common::data_type::PyDataType;
 
-#[pyclass(frozen, name = "ScalarVariable", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "ScalarVariable",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyScalarVariable {
     field: FieldRef,
diff --git a/crates/core/src/expr/set_comparison.rs b/crates/core/src/expr/set_comparison.rs
new file mode 100644
index 000000000..9f0c077e1
--- /dev/null
+++ b/crates/core/src/expr/set_comparison.rs
@@ -0,0 +1,59 @@
+// Licensed to the Apache Software Foundation (ASF) under one
+// or more contributor license agreements.  See the NOTICE file
+// distributed with this work for additional information
+// regarding copyright ownership.  The ASF licenses this file
+// to you under the Apache License, Version 2.0 (the
+// "License"); you may not use this file except in compliance
+// with the License.  You may obtain a copy of the License at
+//
+//   http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing,
+// software distributed under the License is distributed on an
+// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+// KIND, either express or implied.  See the License for the
+// specific language governing permissions and limitations
+// under the License.
+
+use datafusion::logical_expr::expr::SetComparison;
+use pyo3::prelude::*;
+
+use super::subquery::PySubquery;
+use crate::expr::PyExpr;
+
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "SetComparison",
+    module = "datafusion.set_comparison",
+    subclass
+)]
+#[derive(Clone)]
+pub struct PySetComparison {
+    set_comparison: SetComparison,
+}
+
+impl From<SetComparison> for PySetComparison {
+    fn from(set_comparison: SetComparison) -> Self {
+        PySetComparison { set_comparison }
+    }
+}
+
+#[pymethods]
+impl PySetComparison {
+    fn expr(&self) -> PyExpr {
+        (*self.set_comparison.expr).clone().into()
+    }
+
+    fn subquery(&self) -> PySubquery {
+        self.set_comparison.subquery.clone().into()
+    }
+
+    fn op(&self) -> String {
+        format!("{}", self.set_comparison.op)
+    }
+
+    fn quantifier(&self) -> String {
+        format!("{}", self.set_comparison.quantifier)
+    }
+}
diff --git a/src/expr/signature.rs b/crates/core/src/expr/signature.rs
similarity index 91%
rename from src/expr/signature.rs
rename to crates/core/src/expr/signature.rs
index e2c23dce9..35268e3a9 100644
--- a/src/expr/signature.rs
+++ b/crates/core/src/expr/signature.rs
@@ -19,7 +19,13 @@ use datafusion::logical_expr::{TypeSignature, Volatility};
 use pyo3::prelude::*;
 
 #[allow(dead_code)]
-#[pyclass(frozen, name = "Signature", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "Signature",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PySignature {
     type_signature: TypeSignature,
diff --git a/src/expr/sort.rs b/crates/core/src/expr/sort.rs
similarity index 96%
rename from src/expr/sort.rs
rename to crates/core/src/expr/sort.rs
index db2f870b4..7c1e654c5 100644
--- a/src/expr/sort.rs
+++ b/crates/core/src/expr/sort.rs
@@ -27,7 +27,13 @@ use crate::expr::logical_node::LogicalNode;
 use crate::expr::sort_expr::PySortExpr;
 use crate::sql::logical::PyLogicalPlan;
 
-#[pyclass(frozen, name = "Sort", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "Sort",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PySort {
     sort: Sort,
diff --git a/src/expr/sort_expr.rs b/crates/core/src/expr/sort_expr.rs
similarity index 95%
rename from src/expr/sort_expr.rs
rename to crates/core/src/expr/sort_expr.rs
index 23c066156..3c3c86bc1 100644
--- a/src/expr/sort_expr.rs
+++ b/crates/core/src/expr/sort_expr.rs
@@ -22,7 +22,13 @@ use pyo3::prelude::*;
 
 use crate::expr::PyExpr;
 
-#[pyclass(frozen, name = "SortExpr", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "SortExpr",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PySortExpr {
     pub(crate) sort: SortExpr,
diff --git a/src/expr/statement.rs b/crates/core/src/expr/statement.rs
similarity index 94%
rename from src/expr/statement.rs
rename to crates/core/src/expr/statement.rs
index 8f362e608..5aa1e4e9c 100644
--- a/src/expr/statement.rs
+++ b/crates/core/src/expr/statement.rs
@@ -31,6 +31,7 @@ use super::logical_node::LogicalNode;
 use crate::sql::logical::PyLogicalPlan;
 
 #[pyclass(
+    from_py_object,
     frozen,
     name = "TransactionStart",
     module = "datafusion.expr",
@@ -67,6 +68,7 @@ impl LogicalNode for PyTransactionStart {
 
 #[derive(Debug, Clone, PartialEq, Eq, Hash, PartialOrd, Ord)]
 #[pyclass(
+    from_py_object,
     frozen,
     eq,
     eq_int,
@@ -100,6 +102,7 @@ impl TryFrom<PyTransactionAccessMode> for TransactionAccessMode {
 
 #[derive(Debug, Clone, PartialEq, Eq, Hash, PartialOrd, Ord)]
 #[pyclass(
+    from_py_object,
     frozen,
     eq,
     eq_int,
@@ -178,7 +181,13 @@ impl PyTransactionStart {
     }
 }
 
-#[pyclass(frozen, name = "TransactionEnd", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "TransactionEnd",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyTransactionEnd {
     transaction_end: TransactionEnd,
@@ -210,6 +219,7 @@ impl LogicalNode for PyTransactionEnd {
 
 #[derive(Debug, Clone, PartialEq, Eq, Hash, PartialOrd, Ord)]
 #[pyclass(
+    from_py_object,
     frozen,
     eq,
     eq_int,
@@ -259,7 +269,13 @@ impl PyTransactionEnd {
     }
 }
 
-#[pyclass(frozen, name = "ResetVariable", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "ResetVariable",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyResetVariable {
     reset_variable: ResetVariable,
@@ -303,7 +319,13 @@ impl PyResetVariable {
     }
 }
 
-#[pyclass(frozen, name = "SetVariable", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "SetVariable",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PySetVariable {
     set_variable: SetVariable,
@@ -351,7 +373,13 @@ impl PySetVariable {
     }
 }
 
-#[pyclass(frozen, name = "Prepare", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "Prepare",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyPrepare {
     prepare: Prepare,
@@ -416,7 +444,13 @@ impl PyPrepare {
     }
 }
 
-#[pyclass(frozen, name = "Execute", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "Execute",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyExecute {
     execute: Execute,
@@ -473,7 +507,13 @@ impl PyExecute {
     }
 }
 
-#[pyclass(frozen, name = "Deallocate", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "Deallocate",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyDeallocate {
     deallocate: Deallocate,
diff --git a/src/expr/subquery.rs b/crates/core/src/expr/subquery.rs
similarity index 95%
rename from src/expr/subquery.rs
rename to crates/core/src/expr/subquery.rs
index 5d50e8ed2..c6fa83db8 100644
--- a/src/expr/subquery.rs
+++ b/crates/core/src/expr/subquery.rs
@@ -24,7 +24,13 @@ use pyo3::prelude::*;
 use super::logical_node::LogicalNode;
 use crate::sql::logical::PyLogicalPlan;
 
-#[pyclass(frozen, name = "Subquery", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "Subquery",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PySubquery {
     subquery: Subquery,
diff --git a/src/expr/subquery_alias.rs b/crates/core/src/expr/subquery_alias.rs
similarity index 95%
rename from src/expr/subquery_alias.rs
rename to crates/core/src/expr/subquery_alias.rs
index 0170d1281..a6b09e842 100644
--- a/src/expr/subquery_alias.rs
+++ b/crates/core/src/expr/subquery_alias.rs
@@ -25,7 +25,13 @@ use super::logical_node::LogicalNode;
 use crate::common::df_schema::PyDFSchema;
 use crate::sql::logical::PyLogicalPlan;
 
-#[pyclass(frozen, name = "SubqueryAlias", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "SubqueryAlias",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PySubqueryAlias {
     subquery_alias: SubqueryAlias,
diff --git a/src/expr/table_scan.rs b/crates/core/src/expr/table_scan.rs
similarity index 97%
rename from src/expr/table_scan.rs
rename to crates/core/src/expr/table_scan.rs
index 94bc37085..8ba7e4a69 100644
--- a/src/expr/table_scan.rs
+++ b/crates/core/src/expr/table_scan.rs
@@ -27,7 +27,13 @@ use crate::expr::PyExpr;
 use crate::expr::logical_node::LogicalNode;
 use crate::sql::logical::PyLogicalPlan;
 
-#[pyclass(frozen, name = "TableScan", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "TableScan",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyTableScan {
     table_scan: TableScan,
diff --git a/src/expr/union.rs b/crates/core/src/expr/union.rs
similarity index 95%
rename from src/expr/union.rs
rename to crates/core/src/expr/union.rs
index 41370ab51..a3b9efe91 100644
--- a/src/expr/union.rs
+++ b/crates/core/src/expr/union.rs
@@ -25,7 +25,13 @@ use crate::common::df_schema::PyDFSchema;
 use crate::expr::logical_node::LogicalNode;
 use crate::sql::logical::PyLogicalPlan;
 
-#[pyclass(frozen, name = "Union", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "Union",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyUnion {
     union_: Union,
diff --git a/src/expr/unnest.rs b/crates/core/src/expr/unnest.rs
similarity index 95%
rename from src/expr/unnest.rs
rename to crates/core/src/expr/unnest.rs
index 9b7afb778..880d0a279 100644
--- a/src/expr/unnest.rs
+++ b/crates/core/src/expr/unnest.rs
@@ -25,7 +25,13 @@ use crate::common::df_schema::PyDFSchema;
 use crate::expr::logical_node::LogicalNode;
 use crate::sql::logical::PyLogicalPlan;
 
-#[pyclass(frozen, name = "Unnest", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "Unnest",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyUnnest {
     unnest_: Unnest,
diff --git a/src/expr/unnest_expr.rs b/crates/core/src/expr/unnest_expr.rs
similarity index 93%
rename from src/expr/unnest_expr.rs
rename to crates/core/src/expr/unnest_expr.rs
index dc6c4cb50..97feef1d1 100644
--- a/src/expr/unnest_expr.rs
+++ b/crates/core/src/expr/unnest_expr.rs
@@ -22,7 +22,13 @@ use pyo3::prelude::*;
 
 use super::PyExpr;
 
-#[pyclass(frozen, name = "UnnestExpr", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "UnnestExpr",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyUnnestExpr {
     unnest: Unnest,
diff --git a/src/expr/values.rs b/crates/core/src/expr/values.rs
similarity index 95%
rename from src/expr/values.rs
rename to crates/core/src/expr/values.rs
index d89d4f242..d40b0e7cf 100644
--- a/src/expr/values.rs
+++ b/crates/core/src/expr/values.rs
@@ -26,7 +26,13 @@ use super::logical_node::LogicalNode;
 use crate::common::df_schema::PyDFSchema;
 use crate::sql::logical::PyLogicalPlan;
 
-#[pyclass(frozen, name = "Values", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "Values",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyValues {
     values: Values,
diff --git a/src/expr/window.rs b/crates/core/src/expr/window.rs
similarity index 97%
rename from src/expr/window.rs
rename to crates/core/src/expr/window.rs
index c6972b20e..92d909bfc 100644
--- a/src/expr/window.rs
+++ b/crates/core/src/expr/window.rs
@@ -32,13 +32,25 @@ use crate::expr::logical_node::LogicalNode;
 use crate::expr::sort_expr::{PySortExpr, py_sort_expr_list};
 use crate::sql::logical::PyLogicalPlan;
 
-#[pyclass(frozen, name = "WindowExpr", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "WindowExpr",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyWindowExpr {
     window: Window,
 }
 
-#[pyclass(frozen, name = "WindowFrame", module = "datafusion.expr", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "WindowFrame",
+    module = "datafusion.expr",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyWindowFrame {
     window_frame: WindowFrame,
@@ -57,6 +69,7 @@ impl From<WindowFrame> for PyWindowFrame {
 }
 
 #[pyclass(
+    from_py_object,
     frozen,
     name = "WindowFrameBound",
     module = "datafusion.expr",
diff --git a/src/functions.rs b/crates/core/src/functions.rs
similarity index 87%
rename from src/functions.rs
rename to crates/core/src/functions.rs
index 90b3a0a4b..7feb62d79 100644
--- a/src/functions.rs
+++ b/crates/core/src/functions.rs
@@ -18,20 +18,14 @@
 use std::collections::HashMap;
 
 use datafusion::common::{Column, ScalarValue, TableReference};
-use datafusion::execution::FunctionRegistry;
-use datafusion::functions_aggregate::all_default_aggregate_functions;
-use datafusion::functions_window::all_default_window_functions;
-use datafusion::logical_expr::expr::{
-    Alias, FieldMetadata, NullTreatment as DFNullTreatment, WindowFunction, WindowFunctionParams,
-};
-use datafusion::logical_expr::{Expr, ExprFunctionExt, WindowFrame, WindowFunctionDefinition, lit};
+use datafusion::logical_expr::expr::{Alias, FieldMetadata, NullTreatment as DFNullTreatment};
+use datafusion::logical_expr::{Expr, ExprFunctionExt, lit};
 use datafusion::{functions, functions_aggregate, functions_window};
 use pyo3::prelude::*;
 use pyo3::wrap_pyfunction;
 
 use crate::common::data_type::{NullTreatment, PyScalarValue};
-use crate::context::PySessionContext;
-use crate::errors::{PyDataFusionError, PyDataFusionResult};
+use crate::errors::PyDataFusionResult;
 use crate::expr::PyExpr;
 use crate::expr::conditional_expr::PyCaseBuilder;
 use crate::expr::sort_expr::{PySortExpr, to_sort_expressions};
@@ -93,6 +87,57 @@ fn array_cat(exprs: Vec<PyExpr>) -> PyExpr {
     array_concat(exprs)
 }
 
+#[pyfunction]
+fn array_distance(array1: PyExpr, array2: PyExpr) -> PyExpr {
+    let args = vec![array1.into(), array2.into()];
+    Expr::ScalarFunction(datafusion::logical_expr::expr::ScalarFunction::new_udf(
+        datafusion::functions_nested::distance::array_distance_udf(),
+        args,
+    ))
+    .into()
+}
+
+#[pyfunction]
+fn arrays_zip(exprs: Vec<PyExpr>) -> PyExpr {
+    let exprs = exprs.into_iter().map(|x| x.into()).collect();
+    datafusion::functions_nested::expr_fn::arrays_zip(exprs).into()
+}
+
+#[pyfunction]
+#[pyo3(signature = (string, delimiter, null_string=None))]
+fn string_to_array(string: PyExpr, delimiter: PyExpr, null_string: Option<PyExpr>) -> PyExpr {
+    let mut args = vec![string.into(), delimiter.into()];
+    if let Some(null_string) = null_string {
+        args.push(null_string.into());
+    }
+    Expr::ScalarFunction(datafusion::logical_expr::expr::ScalarFunction::new_udf(
+        datafusion::functions_nested::string::string_to_array_udf(),
+        args,
+    ))
+    .into()
+}
+
+#[pyfunction]
+#[pyo3(signature = (start, stop, step=None))]
+fn gen_series(start: PyExpr, stop: PyExpr, step: Option<PyExpr>) -> PyExpr {
+    let mut args = vec![start.into(), stop.into()];
+    if let Some(step) = step {
+        args.push(step.into());
+    }
+    Expr::ScalarFunction(datafusion::logical_expr::expr::ScalarFunction::new_udf(
+        datafusion::functions_nested::range::gen_series_udf(),
+        args,
+    ))
+    .into()
+}
+
+#[pyfunction]
+fn make_map(keys: Vec<PyExpr>, values: Vec<PyExpr>) -> PyExpr {
+    let keys = keys.into_iter().map(|x| x.into()).collect();
+    let values = values.into_iter().map(|x| x.into()).collect();
+    datafusion::functions_nested::map::map(keys, values).into()
+}
+
 #[pyfunction]
 #[pyo3(signature = (array, element, index=None))]
 fn array_position(array: PyExpr, element: PyExpr, index: Option<i64>) -> PyExpr {
@@ -255,126 +300,6 @@ fn when(when: PyExpr, then: PyExpr) -> PyResult<PyCaseBuilder> {
     Ok(PyCaseBuilder::new(None).when(when, then))
 }
 
-/// Helper function to find the appropriate window function.
-///
-/// Search procedure:
-/// 1) Search built in window functions, which are being deprecated.
-/// 1) If a session context is provided:
-///      1) search User Defined Aggregate Functions (UDAFs)
-///      1) search registered window functions
-///      1) search registered aggregate functions
-/// 1) If no function has been found, search default aggregate functions.
-///
-/// NOTE: we search the built-ins first because the `UDAF` versions currently do not have the same behavior.
-fn find_window_fn(
-    name: &str,
-    ctx: Option<PySessionContext>,
-) -> PyDataFusionResult<WindowFunctionDefinition> {
-    if let Some(ctx) = ctx {
-        // search UDAFs
-        let udaf = ctx
-            .ctx
-            .udaf(name)
-            .map(WindowFunctionDefinition::AggregateUDF)
-            .ok();
-
-        if let Some(udaf) = udaf {
-            return Ok(udaf);
-        }
-
-        let session_state = ctx.ctx.state();
-
-        // search registered window functions
-        let window_fn = session_state
-            .window_functions()
-            .get(name)
-            .map(|f| WindowFunctionDefinition::WindowUDF(f.clone()));
-
-        if let Some(window_fn) = window_fn {
-            return Ok(window_fn);
-        }
-
-        // search registered aggregate functions
-        let agg_fn = session_state
-            .aggregate_functions()
-            .get(name)
-            .map(|f| WindowFunctionDefinition::AggregateUDF(f.clone()));
-
-        if let Some(agg_fn) = agg_fn {
-            return Ok(agg_fn);
-        }
-    }
-
-    // search default aggregate functions
-    let agg_fn = all_default_aggregate_functions()
-        .iter()
-        .find(|v| v.name() == name || v.aliases().contains(&name.to_string()))
-        .map(|f| WindowFunctionDefinition::AggregateUDF(f.clone()));
-
-    if let Some(agg_fn) = agg_fn {
-        return Ok(agg_fn);
-    }
-
-    // search default window functions
-    let window_fn = all_default_window_functions()
-        .iter()
-        .find(|v| v.name() == name || v.aliases().contains(&name.to_string()))
-        .map(|f| WindowFunctionDefinition::WindowUDF(f.clone()));
-
-    if let Some(window_fn) = window_fn {
-        return Ok(window_fn);
-    }
-
-    Err(PyDataFusionError::Common(format!(
-        "window function `{name}` not found"
-    )))
-}
-
-/// Creates a new Window function expression
-#[allow(clippy::too_many_arguments)]
-#[pyfunction]
-#[pyo3(signature = (name, args, partition_by=None, order_by=None, window_frame=None, filter=None, distinct=false, ctx=None))]
-fn window(
-    name: &str,
-    args: Vec<PyExpr>,
-    partition_by: Option<Vec<PyExpr>>,
-    order_by: Option<Vec<PySortExpr>>,
-    window_frame: Option<PyWindowFrame>,
-    filter: Option<PyExpr>,
-    distinct: bool,
-    ctx: Option<PySessionContext>,
-) -> PyResult<PyExpr> {
-    let fun = find_window_fn(name, ctx)?;
-
-    let window_frame = window_frame
-        .map(|w| w.into())
-        .unwrap_or(WindowFrame::new(order_by.as_ref().map(|v| !v.is_empty())));
-    let filter = filter.map(|f| f.expr.into());
-
-    Ok(PyExpr {
-        expr: datafusion::logical_expr::Expr::WindowFunction(Box::new(WindowFunction {
-            fun,
-            params: WindowFunctionParams {
-                args: args.into_iter().map(|x| x.expr).collect::<Vec<_>>(),
-                partition_by: partition_by
-                    .unwrap_or_default()
-                    .into_iter()
-                    .map(|x| x.expr)
-                    .collect::<Vec<_>>(),
-                order_by: order_by
-                    .unwrap_or_default()
-                    .into_iter()
-                    .map(|x| x.into())
-                    .collect::<Vec<_>>(),
-                window_frame,
-                filter,
-                distinct,
-                null_treatment: None,
-            },
-        })),
-    })
-}
-
 // Generates a [pyo3] wrapper for associated aggregate functions.
 // All of the builder options are exposed to the python internal
 // function and we rely on the wrappers to only use those that
@@ -494,6 +419,13 @@ expr_fn!(length, string);
 expr_fn!(char_length, string);
 expr_fn!(chr, arg, "Returns the character with the given code.");
 expr_fn_vec!(coalesce);
+expr_fn_vec!(greatest);
+expr_fn_vec!(least);
+expr_fn!(
+    contains,
+    string search_str,
+    "Return true if search_str is found within string (case-sensitive)."
+);
 expr_fn!(cos, num);
 expr_fn!(cosh, num);
 expr_fn!(cot, num);
@@ -543,6 +475,11 @@ expr_fn!(
     x y,
     "Returns x if x is not NULL otherwise returns y."
 );
+expr_fn!(
+    nvl2,
+    x y z,
+    "Returns y if x is not NULL; otherwise returns z."
+);
 expr_fn!(nullif, arg_1 arg_2);
 expr_fn!(
     octet_length,
@@ -601,6 +538,9 @@ expr_fn!(
     "Converts the number to its equivalent hexadecimal representation."
 );
 expr_fn!(now);
+expr_fn_vec!(to_date);
+expr_fn_vec!(to_local_time);
+expr_fn_vec!(to_time);
 expr_fn_vec!(to_timestamp);
 expr_fn_vec!(to_timestamp_millis);
 expr_fn_vec!(to_timestamp_nanos);
@@ -613,6 +553,8 @@ expr_fn!(date_part, part date);
 expr_fn!(date_trunc, part date);
 expr_fn!(date_bin, stride source origin);
 expr_fn!(make_date, year month day);
+expr_fn!(make_time, hour minute second);
+expr_fn!(to_char, datetime format);
 
 expr_fn!(translate, string from to, "Replaces each character in string that matches a character in the from set with the corresponding character in the to set. If from is longer than to, occurrences of the extra characters in from are deleted.");
 expr_fn_vec!(
@@ -627,8 +569,29 @@ expr_fn_vec!(named_struct);
 expr_fn!(from_unixtime, unixtime);
 expr_fn!(arrow_typeof, arg_1);
 expr_fn!(arrow_cast, arg_1 datatype);
+expr_fn_vec!(arrow_metadata);
+expr_fn!(union_tag, arg1);
 expr_fn!(random);
 
+#[pyfunction]
+fn get_field(expr: PyExpr, name: PyExpr) -> PyExpr {
+    functions::core::get_field()
+        .call(vec![expr.into(), name.into()])
+        .into()
+}
+
+#[pyfunction]
+fn union_extract(union_expr: PyExpr, field_name: PyExpr) -> PyExpr {
+    functions::core::union_extract()
+        .call(vec![union_expr.into(), field_name.into()])
+        .into()
+}
+
+#[pyfunction]
+fn version() -> PyExpr {
+    functions::core::version().call(vec![]).into()
+}
+
 // Array Functions
 array_fn!(array_append, array element);
 array_fn!(array_to_string, array delimiter);
@@ -657,10 +620,20 @@ array_fn!(array_intersect, first_array second_array);
 array_fn!(array_union, array1 array2);
 array_fn!(array_except, first_array second_array);
 array_fn!(array_resize, array size value);
+array_fn!(array_any_value, array);
+array_fn!(array_max, array);
+array_fn!(array_min, array);
+array_fn!(array_reverse, array);
 array_fn!(cardinality, array);
 array_fn!(flatten, array);
 array_fn!(range, start stop step);
 
+// Map Functions
+array_fn!(map_keys, map);
+array_fn!(map_values, map);
+array_fn!(map_extract, map key);
+array_fn!(map_entries, map);
+
 aggregate_function!(array_agg);
 aggregate_function!(max);
 aggregate_function!(min);
@@ -692,9 +665,10 @@ aggregate_function!(var_pop);
 aggregate_function!(approx_distinct);
 aggregate_function!(approx_median);
 
-// Code is commented out since grouping is not yet implemented
-// https://github.com/apache/datafusion-python/issues/861
-// aggregate_function!(grouping);
+// The grouping function's physical plan is not implemented, but the
+// ResolveGroupingFunction analyzer rule rewrites it before the physical
+// planner sees it, so it works correctly at runtime.
+aggregate_function!(grouping);
 
 #[pyfunction]
 #[pyo3(signature = (sort_expression, percentile, num_centroids=None, filter=None))]
@@ -732,6 +706,19 @@ pub fn approx_percentile_cont_with_weight(
     add_builder_fns_to_aggregate(agg_fn, None, filter, None, None)
 }
 
+#[pyfunction]
+#[pyo3(signature = (sort_expression, percentile, filter=None))]
+pub fn percentile_cont(
+    sort_expression: PySortExpr,
+    percentile: f64,
+    filter: Option<PyExpr>,
+) -> PyDataFusionResult<PyExpr> {
+    let agg_fn =
+        functions_aggregate::expr_fn::percentile_cont(sort_expression.sort, lit(percentile));
+
+    add_builder_fns_to_aggregate(agg_fn, None, filter, None, None)
+}
+
 // We handle last_value explicitly because the signature expects an order_by
 // https://github.com/apache/datafusion/issues/12376
 #[pyfunction]
@@ -932,10 +919,12 @@ pub(crate) fn init_module(m: &Bound<'_, PyModule>) -> PyResult<()> {
     m.add_wrapped(wrap_pyfunction!(approx_median))?;
     m.add_wrapped(wrap_pyfunction!(approx_percentile_cont))?;
     m.add_wrapped(wrap_pyfunction!(approx_percentile_cont_with_weight))?;
+    m.add_wrapped(wrap_pyfunction!(percentile_cont))?;
     m.add_wrapped(wrap_pyfunction!(range))?;
     m.add_wrapped(wrap_pyfunction!(array_agg))?;
     m.add_wrapped(wrap_pyfunction!(arrow_typeof))?;
     m.add_wrapped(wrap_pyfunction!(arrow_cast))?;
+    m.add_wrapped(wrap_pyfunction!(arrow_metadata))?;
     m.add_wrapped(wrap_pyfunction!(ascii))?;
     m.add_wrapped(wrap_pyfunction!(asin))?;
     m.add_wrapped(wrap_pyfunction!(asinh))?;
@@ -956,6 +945,7 @@ pub(crate) fn init_module(m: &Bound<'_, PyModule>) -> PyResult<()> {
     m.add_wrapped(wrap_pyfunction!(col))?;
     m.add_wrapped(wrap_pyfunction!(concat_ws))?;
     m.add_wrapped(wrap_pyfunction!(concat))?;
+    m.add_wrapped(wrap_pyfunction!(contains))?;
     m.add_wrapped(wrap_pyfunction!(corr))?;
     m.add_wrapped(wrap_pyfunction!(cos))?;
     m.add_wrapped(wrap_pyfunction!(cosh))?;
@@ -970,6 +960,7 @@ pub(crate) fn init_module(m: &Bound<'_, PyModule>) -> PyResult<()> {
     m.add_wrapped(wrap_pyfunction!(date_part))?;
     m.add_wrapped(wrap_pyfunction!(date_trunc))?;
     m.add_wrapped(wrap_pyfunction!(make_date))?;
+    m.add_wrapped(wrap_pyfunction!(make_time))?;
     m.add_wrapped(wrap_pyfunction!(digest))?;
     m.add_wrapped(wrap_pyfunction!(ends_with))?;
     m.add_wrapped(wrap_pyfunction!(exp))?;
@@ -977,13 +968,15 @@ pub(crate) fn init_module(m: &Bound<'_, PyModule>) -> PyResult<()> {
     m.add_wrapped(wrap_pyfunction!(floor))?;
     m.add_wrapped(wrap_pyfunction!(from_unixtime))?;
     m.add_wrapped(wrap_pyfunction!(gcd))?;
-    // m.add_wrapped(wrap_pyfunction!(grouping))?;
+    m.add_wrapped(wrap_pyfunction!(greatest))?;
+    m.add_wrapped(wrap_pyfunction!(grouping))?;
     m.add_wrapped(wrap_pyfunction!(in_list))?;
     m.add_wrapped(wrap_pyfunction!(initcap))?;
     m.add_wrapped(wrap_pyfunction!(isnan))?;
     m.add_wrapped(wrap_pyfunction!(iszero))?;
     m.add_wrapped(wrap_pyfunction!(levenshtein))?;
     m.add_wrapped(wrap_pyfunction!(lcm))?;
+    m.add_wrapped(wrap_pyfunction!(least))?;
     m.add_wrapped(wrap_pyfunction!(left))?;
     m.add_wrapped(wrap_pyfunction!(length))?;
     m.add_wrapped(wrap_pyfunction!(ln))?;
@@ -1001,6 +994,7 @@ pub(crate) fn init_module(m: &Bound<'_, PyModule>) -> PyResult<()> {
     m.add_wrapped(wrap_pyfunction!(named_struct))?;
     m.add_wrapped(wrap_pyfunction!(nanvl))?;
     m.add_wrapped(wrap_pyfunction!(nvl))?;
+    m.add_wrapped(wrap_pyfunction!(nvl2))?;
     m.add_wrapped(wrap_pyfunction!(now))?;
     m.add_wrapped(wrap_pyfunction!(nullif))?;
     m.add_wrapped(wrap_pyfunction!(octet_length))?;
@@ -1045,6 +1039,10 @@ pub(crate) fn init_module(m: &Bound<'_, PyModule>) -> PyResult<()> {
     m.add_wrapped(wrap_pyfunction!(tan))?;
     m.add_wrapped(wrap_pyfunction!(tanh))?;
     m.add_wrapped(wrap_pyfunction!(to_hex))?;
+    m.add_wrapped(wrap_pyfunction!(to_char))?;
+    m.add_wrapped(wrap_pyfunction!(to_date))?;
+    m.add_wrapped(wrap_pyfunction!(to_local_time))?;
+    m.add_wrapped(wrap_pyfunction!(to_time))?;
     m.add_wrapped(wrap_pyfunction!(to_timestamp))?;
     m.add_wrapped(wrap_pyfunction!(to_timestamp_millis))?;
     m.add_wrapped(wrap_pyfunction!(to_timestamp_nanos))?;
@@ -1055,10 +1053,13 @@ pub(crate) fn init_module(m: &Bound<'_, PyModule>) -> PyResult<()> {
     m.add_wrapped(wrap_pyfunction!(trim))?;
     m.add_wrapped(wrap_pyfunction!(trunc))?;
     m.add_wrapped(wrap_pyfunction!(upper))?;
+    m.add_wrapped(wrap_pyfunction!(get_field))?;
+    m.add_wrapped(wrap_pyfunction!(union_extract))?;
+    m.add_wrapped(wrap_pyfunction!(union_tag))?;
+    m.add_wrapped(wrap_pyfunction!(version))?;
     m.add_wrapped(wrap_pyfunction!(self::uuid))?; // Use self to avoid name collision
     m.add_wrapped(wrap_pyfunction!(var_pop))?;
     m.add_wrapped(wrap_pyfunction!(var_sample))?;
-    m.add_wrapped(wrap_pyfunction!(window))?;
     m.add_wrapped(wrap_pyfunction!(regr_avgx))?;
     m.add_wrapped(wrap_pyfunction!(regr_avgy))?;
     m.add_wrapped(wrap_pyfunction!(regr_count))?;
@@ -1113,9 +1114,24 @@ pub(crate) fn init_module(m: &Bound<'_, PyModule>) -> PyResult<()> {
     m.add_wrapped(wrap_pyfunction!(array_replace_all))?;
     m.add_wrapped(wrap_pyfunction!(array_sort))?;
     m.add_wrapped(wrap_pyfunction!(array_slice))?;
+    m.add_wrapped(wrap_pyfunction!(array_any_value))?;
+    m.add_wrapped(wrap_pyfunction!(array_distance))?;
+    m.add_wrapped(wrap_pyfunction!(array_max))?;
+    m.add_wrapped(wrap_pyfunction!(array_min))?;
+    m.add_wrapped(wrap_pyfunction!(array_reverse))?;
+    m.add_wrapped(wrap_pyfunction!(arrays_zip))?;
+    m.add_wrapped(wrap_pyfunction!(string_to_array))?;
+    m.add_wrapped(wrap_pyfunction!(gen_series))?;
     m.add_wrapped(wrap_pyfunction!(flatten))?;
     m.add_wrapped(wrap_pyfunction!(cardinality))?;
 
+    // Map Functions
+    m.add_wrapped(wrap_pyfunction!(make_map))?;
+    m.add_wrapped(wrap_pyfunction!(map_keys))?;
+    m.add_wrapped(wrap_pyfunction!(map_values))?;
+    m.add_wrapped(wrap_pyfunction!(map_extract))?;
+    m.add_wrapped(wrap_pyfunction!(map_entries))?;
+
     // Window Functions
     m.add_wrapped(wrap_pyfunction!(lead))?;
     m.add_wrapped(wrap_pyfunction!(lag))?;
diff --git a/src/lib.rs b/crates/core/src/lib.rs
similarity index 94%
rename from src/lib.rs
rename to crates/core/src/lib.rs
index 081366b20..77d69911a 100644
--- a/src/lib.rs
+++ b/crates/core/src/lib.rs
@@ -16,9 +16,9 @@
 // under the License.
 
 // Re-export Apache Arrow DataFusion dependencies
-pub use datafusion;
 pub use datafusion::{
-    common as datafusion_common, logical_expr as datafusion_expr, optimizer, sql as datafusion_sql,
+    self, common as datafusion_common, logical_expr as datafusion_expr, optimizer,
+    sql as datafusion_sql,
 };
 #[cfg(feature = "substrait")]
 pub use datafusion_substrait;
@@ -43,6 +43,7 @@ pub mod errors;
 pub mod expr;
 #[allow(clippy::borrow_deref_ref)]
 mod functions;
+pub mod metrics;
 mod options;
 pub mod physical_plan;
 mod pyarrow_filter_expression;
@@ -62,15 +63,11 @@ mod udaf;
 mod udf;
 pub mod udtf;
 mod udwf;
-pub mod utils;
 
 #[cfg(feature = "mimalloc")]
 #[global_allocator]
 static GLOBAL: MiMalloc = MiMalloc;
 
-// Used to define Tokio Runtime as a Python module attribute
-pub(crate) struct TokioRuntime(tokio::runtime::Runtime);
-
 /// Low-level DataFusion internal package.
 ///
 /// The higher-level public API is defined in pure python files under the
@@ -96,6 +93,8 @@ fn _internal(py: Python, m: Bound<'_, PyModule>) -> PyResult<()> {
     m.add_class::<udtf::PyTableFunction>()?;
     m.add_class::<config::PyConfig>()?;
     m.add_class::<sql::logical::PyLogicalPlan>()?;
+    m.add_class::<metrics::PyMetricsSet>()?;
+    m.add_class::<metrics::PyMetric>()?;
     m.add_class::<physical_plan::PyExecutionPlan>()?;
     m.add_class::<record_batch::PyRecordBatch>()?;
     m.add_class::<record_batch::PyRecordBatchStream>()?;
diff --git a/crates/core/src/metrics.rs b/crates/core/src/metrics.rs
new file mode 100644
index 000000000..ee0937e25
--- /dev/null
+++ b/crates/core/src/metrics.rs
@@ -0,0 +1,169 @@
+// Licensed to the Apache Software Foundation (ASF) under one
+// or more contributor license agreements.  See the NOTICE file
+// distributed with this work for additional information
+// regarding copyright ownership.  The ASF licenses this file
+// to you under the Apache License, Version 2.0 (the
+// "License"); you may not use this file except in compliance
+// with the License.  You may obtain a copy of the License at
+//
+//   http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing,
+// software distributed under the License is distributed on an
+// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+// KIND, either express or implied.  See the License for the
+// specific language governing permissions and limitations
+// under the License.
+
+use std::collections::HashMap;
+use std::sync::Arc;
+
+use chrono::{Datelike, Timelike};
+use datafusion::physical_plan::metrics::{Metric, MetricValue, MetricsSet, Timestamp};
+use pyo3::prelude::*;
+
+#[pyclass(from_py_object, frozen, name = "MetricsSet", module = "datafusion")]
+#[derive(Debug, Clone)]
+pub struct PyMetricsSet {
+    metrics: MetricsSet,
+}
+
+impl PyMetricsSet {
+    pub fn new(metrics: MetricsSet) -> Self {
+        Self { metrics }
+    }
+}
+
+#[pymethods]
+impl PyMetricsSet {
+    fn metrics(&self) -> Vec<PyMetric> {
+        self.metrics
+            .iter()
+            .map(|m| PyMetric::new(Arc::clone(m)))
+            .collect()
+    }
+
+    fn output_rows(&self) -> Option<usize> {
+        self.metrics.output_rows()
+    }
+
+    fn elapsed_compute(&self) -> Option<usize> {
+        self.metrics.elapsed_compute()
+    }
+
+    fn spill_count(&self) -> Option<usize> {
+        self.metrics.spill_count()
+    }
+
+    fn spilled_bytes(&self) -> Option<usize> {
+        self.metrics.spilled_bytes()
+    }
+
+    fn spilled_rows(&self) -> Option<usize> {
+        self.metrics.spilled_rows()
+    }
+
+    fn sum_by_name(&self, name: &str) -> Option<usize> {
+        self.metrics.sum_by_name(name).map(|v| v.as_usize())
+    }
+
+    fn __repr__(&self) -> String {
+        format!("{}", self.metrics)
+    }
+}
+
+#[pyclass(from_py_object, frozen, name = "Metric", module = "datafusion")]
+#[derive(Debug, Clone)]
+pub struct PyMetric {
+    metric: Arc<Metric>,
+}
+
+impl PyMetric {
+    pub fn new(metric: Arc<Metric>) -> Self {
+        Self { metric }
+    }
+
+    fn timestamp_to_pyobject<'py>(
+        py: Python<'py>,
+        ts: &Timestamp,
+    ) -> PyResult<Option<Bound<'py, PyAny>>> {
+        match ts.value() {
+            Some(dt) => {
+                let datetime_mod = py.import("datetime")?;
+                let datetime_cls = datetime_mod.getattr("datetime")?;
+                let tz_utc = datetime_mod.getattr("timezone")?.getattr("utc")?;
+                let result = datetime_cls.call1((
+                    dt.year(),
+                    dt.month(),
+                    dt.day(),
+                    dt.hour(),
+                    dt.minute(),
+                    dt.second(),
+                    dt.timestamp_subsec_micros(),
+                    tz_utc,
+                ))?;
+                Ok(Some(result))
+            }
+            None => Ok(None),
+        }
+    }
+}
+
+#[pymethods]
+impl PyMetric {
+    #[getter]
+    fn name(&self) -> String {
+        self.metric.value().name().to_string()
+    }
+
+    #[getter]
+    fn value<'py>(&self, py: Python<'py>) -> PyResult<Option<Bound<'py, PyAny>>> {
+        match self.metric.value() {
+            MetricValue::OutputRows(c) => Ok(Some(c.value().into_pyobject(py)?.into_any())),
+            MetricValue::OutputBytes(c) => Ok(Some(c.value().into_pyobject(py)?.into_any())),
+            MetricValue::ElapsedCompute(t) => Ok(Some(t.value().into_pyobject(py)?.into_any())),
+            MetricValue::SpillCount(c) => Ok(Some(c.value().into_pyobject(py)?.into_any())),
+            MetricValue::SpilledBytes(c) => Ok(Some(c.value().into_pyobject(py)?.into_any())),
+            MetricValue::SpilledRows(c) => Ok(Some(c.value().into_pyobject(py)?.into_any())),
+            MetricValue::CurrentMemoryUsage(g) => Ok(Some(g.value().into_pyobject(py)?.into_any())),
+            MetricValue::Count { count, .. } => {
+                Ok(Some(count.value().into_pyobject(py)?.into_any()))
+            }
+            MetricValue::Gauge { gauge, .. } => {
+                Ok(Some(gauge.value().into_pyobject(py)?.into_any()))
+            }
+            MetricValue::Time { time, .. } => Ok(Some(time.value().into_pyobject(py)?.into_any())),
+            MetricValue::StartTimestamp(ts) | MetricValue::EndTimestamp(ts) => {
+                Self::timestamp_to_pyobject(py, ts)
+            }
+            _ => Ok(None),
+        }
+    }
+
+    #[getter]
+    fn value_as_datetime<'py>(&self, py: Python<'py>) -> PyResult<Option<Bound<'py, PyAny>>> {
+        match self.metric.value() {
+            MetricValue::StartTimestamp(ts) | MetricValue::EndTimestamp(ts) => {
+                Self::timestamp_to_pyobject(py, ts)
+            }
+            _ => Ok(None),
+        }
+    }
+
+    #[getter]
+    fn partition(&self) -> Option<usize> {
+        self.metric.partition()
+    }
+
+    fn labels(&self) -> HashMap<String, String> {
+        self.metric
+            .labels()
+            .iter()
+            .map(|l| (l.name().to_string(), l.value().to_string()))
+            .collect()
+    }
+
+    fn __repr__(&self) -> String {
+        format!("{}", self.metric.value())
+    }
+}
diff --git a/src/options.rs b/crates/core/src/options.rs
similarity index 100%
rename from src/options.rs
rename to crates/core/src/options.rs
diff --git a/src/physical_plan.rs b/crates/core/src/physical_plan.rs
similarity index 91%
rename from src/physical_plan.rs
rename to crates/core/src/physical_plan.rs
index 0069e5e6e..fac973884 100644
--- a/src/physical_plan.rs
+++ b/crates/core/src/physical_plan.rs
@@ -26,8 +26,15 @@ use pyo3::types::PyBytes;
 
 use crate::context::PySessionContext;
 use crate::errors::PyDataFusionResult;
-
-#[pyclass(frozen, name = "ExecutionPlan", module = "datafusion", subclass)]
+use crate::metrics::PyMetricsSet;
+
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "ExecutionPlan",
+    module = "datafusion",
+    subclass
+)]
 #[derive(Debug, Clone)]
 pub struct PyExecutionPlan {
     pub plan: Arc<dyn ExecutionPlan>,
@@ -77,7 +84,7 @@ impl PyExecutionPlan {
         ctx: PySessionContext,
         proto_msg: Bound<'_, PyBytes>,
     ) -> PyDataFusionResult<Self> {
-        let bytes: &[u8] = proto_msg.extract()?;
+        let bytes: &[u8] = proto_msg.extract().map_err(Into::<PyErr>::into)?;
         let proto_plan =
             datafusion_proto::protobuf::PhysicalPlanNode::decode(bytes).map_err(|e| {
                 PyRuntimeError::new_err(format!(
@@ -90,6 +97,10 @@ impl PyExecutionPlan {
         Ok(Self::new(plan))
     }
 
+    pub fn metrics(&self) -> Option<PyMetricsSet> {
+        self.plan.metrics().map(PyMetricsSet::new)
+    }
+
     fn __repr__(&self) -> String {
         self.display_indent()
     }
diff --git a/src/pyarrow_filter_expression.rs b/crates/core/src/pyarrow_filter_expression.rs
similarity index 100%
rename from src/pyarrow_filter_expression.rs
rename to crates/core/src/pyarrow_filter_expression.rs
diff --git a/src/pyarrow_util.rs b/crates/core/src/pyarrow_util.rs
similarity index 95%
rename from src/pyarrow_util.rs
rename to crates/core/src/pyarrow_util.rs
index 2a119274f..1401a4938 100644
--- a/src/pyarrow_util.rs
+++ b/crates/core/src/pyarrow_util.rs
@@ -26,7 +26,7 @@ use arrow::pyarrow::{FromPyArrow, ToPyArrow};
 use datafusion::common::exec_err;
 use datafusion::scalar::ScalarValue;
 use pyo3::types::{PyAnyMethods, PyList};
-use pyo3::{Bound, FromPyObject, PyAny, PyResult, Python};
+use pyo3::{Borrowed, Bound, FromPyObject, PyAny, PyErr, PyResult, Python};
 
 use crate::common::data_type::PyScalarValue;
 use crate::errors::PyDataFusionError;
@@ -142,9 +142,11 @@ impl FromPyArrow for PyScalarValue {
     }
 }
 
-impl<'source> FromPyObject<'source> for PyScalarValue {
-    fn extract_bound(value: &Bound<'source, PyAny>) -> PyResult<Self> {
-        Self::from_pyarrow_bound(value)
+impl<'source> FromPyObject<'_, 'source> for PyScalarValue {
+    type Error = PyErr;
+
+    fn extract(value: Borrowed<'_, 'source, PyAny>) -> Result<Self, Self::Error> {
+        Self::from_pyarrow_bound(&value)
     }
 }
 
diff --git a/src/record_batch.rs b/crates/core/src/record_batch.rs
similarity index 98%
rename from src/record_batch.rs
rename to crates/core/src/record_batch.rs
index e8abc641b..0492c6c76 100644
--- a/src/record_batch.rs
+++ b/crates/core/src/record_batch.rs
@@ -20,6 +20,7 @@ use std::sync::Arc;
 use datafusion::arrow::pyarrow::ToPyArrow;
 use datafusion::arrow::record_batch::RecordBatch;
 use datafusion::physical_plan::SendableRecordBatchStream;
+use datafusion_python_util::wait_for_future;
 use futures::StreamExt;
 use pyo3::exceptions::{PyStopAsyncIteration, PyStopIteration};
 use pyo3::prelude::*;
@@ -27,7 +28,6 @@ use pyo3::{PyAny, PyResult, Python, pyclass, pymethods};
 use tokio::sync::Mutex;
 
 use crate::errors::PyDataFusionError;
-use crate::utils::wait_for_future;
 
 #[pyclass(name = "RecordBatch", module = "datafusion", subclass, frozen)]
 pub struct PyRecordBatch {
diff --git a/src/sql.rs b/crates/core/src/sql.rs
similarity index 100%
rename from src/sql.rs
rename to crates/core/src/sql.rs
diff --git a/src/sql/exceptions.rs b/crates/core/src/sql/exceptions.rs
similarity index 100%
rename from src/sql/exceptions.rs
rename to crates/core/src/sql/exceptions.rs
diff --git a/src/sql/logical.rs b/crates/core/src/sql/logical.rs
similarity index 98%
rename from src/sql/logical.rs
rename to crates/core/src/sql/logical.rs
index cd2ed73d3..631aa9b09 100644
--- a/src/sql/logical.rs
+++ b/crates/core/src/sql/logical.rs
@@ -66,7 +66,14 @@ use crate::expr::unnest::PyUnnest;
 use crate::expr::values::PyValues;
 use crate::expr::window::PyWindowExpr;
 
-#[pyclass(frozen, name = "LogicalPlan", module = "datafusion", subclass, eq)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "LogicalPlan",
+    module = "datafusion",
+    subclass,
+    eq
+)]
 #[derive(Debug, Clone, PartialEq, Eq)]
 pub struct PyLogicalPlan {
     pub(crate) plan: Arc<LogicalPlan>,
@@ -203,7 +210,7 @@ impl PyLogicalPlan {
         ctx: PySessionContext,
         proto_msg: Bound<'_, PyBytes>,
     ) -> PyDataFusionResult<Self> {
-        let bytes: &[u8] = proto_msg.extract()?;
+        let bytes: &[u8] = proto_msg.extract().map_err(Into::<PyErr>::into)?;
         let proto_plan =
             datafusion_proto::protobuf::LogicalPlanNode::decode(bytes).map_err(|e| {
                 PyRuntimeError::new_err(format!(
diff --git a/src/sql/util.rs b/crates/core/src/sql/util.rs
similarity index 100%
rename from src/sql/util.rs
rename to crates/core/src/sql/util.rs
diff --git a/src/store.rs b/crates/core/src/store.rs
similarity index 94%
rename from src/store.rs
rename to crates/core/src/store.rs
index 3eae866bc..8535e83b7 100644
--- a/src/store.rs
+++ b/crates/core/src/store.rs
@@ -36,6 +36,7 @@ pub enum StorageContexts {
 }
 
 #[pyclass(
+    from_py_object,
     frozen,
     name = "LocalFileSystem",
     module = "datafusion.store",
@@ -66,7 +67,13 @@ impl PyLocalFileSystemContext {
     }
 }
 
-#[pyclass(frozen, name = "MicrosoftAzure", module = "datafusion.store", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "MicrosoftAzure",
+    module = "datafusion.store",
+    subclass
+)]
 #[derive(Debug, Clone)]
 pub struct PyMicrosoftAzureContext {
     pub inner: Arc<MicrosoftAzure>,
@@ -143,7 +150,13 @@ impl PyMicrosoftAzureContext {
     }
 }
 
-#[pyclass(frozen, name = "GoogleCloud", module = "datafusion.store", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "GoogleCloud",
+    module = "datafusion.store",
+    subclass
+)]
 #[derive(Debug, Clone)]
 pub struct PyGoogleCloudContext {
     pub inner: Arc<GoogleCloudStorage>,
@@ -173,7 +186,13 @@ impl PyGoogleCloudContext {
     }
 }
 
-#[pyclass(frozen, name = "AmazonS3", module = "datafusion.store", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "AmazonS3",
+    module = "datafusion.store",
+    subclass
+)]
 #[derive(Debug, Clone)]
 pub struct PyAmazonS3Context {
     pub inner: Arc<AmazonS3>,
@@ -237,7 +256,13 @@ impl PyAmazonS3Context {
     }
 }
 
-#[pyclass(frozen, name = "Http", module = "datafusion.store", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "Http",
+    module = "datafusion.store",
+    subclass
+)]
 #[derive(Debug, Clone)]
 pub struct PyHttpContext {
     pub url: String,
diff --git a/src/substrait.rs b/crates/core/src/substrait.rs
similarity index 89%
rename from src/substrait.rs
rename to crates/core/src/substrait.rs
index 1cbf3256c..27e446f48 100644
--- a/src/substrait.rs
+++ b/crates/core/src/substrait.rs
@@ -15,6 +15,7 @@
 // specific language governing permissions and limitations
 // under the License.
 
+use datafusion_python_util::wait_for_future;
 use datafusion_substrait::logical_plan::{consumer, producer};
 use datafusion_substrait::serializer;
 use datafusion_substrait::substrait::proto::Plan;
@@ -25,9 +26,14 @@ use pyo3::types::PyBytes;
 use crate::context::PySessionContext;
 use crate::errors::{PyDataFusionError, PyDataFusionResult, py_datafusion_err, to_datafusion_err};
 use crate::sql::logical::PyLogicalPlan;
-use crate::utils::wait_for_future;
 
-#[pyclass(frozen, name = "Plan", module = "datafusion.substrait", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "Plan",
+    module = "datafusion.substrait",
+    subclass
+)]
 #[derive(Debug, Clone)]
 pub struct PyPlan {
     pub plan: Plan,
@@ -72,7 +78,13 @@ impl From<Plan> for PyPlan {
 /// A PySubstraitSerializer is a representation of a Serializer that is capable of both serializing
 /// a `LogicalPlan` instance to Substrait Protobuf bytes and also deserialize Substrait Protobuf bytes
 /// to a valid `LogicalPlan` instance.
-#[pyclass(frozen, name = "Serde", module = "datafusion.substrait", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "Serde",
+    module = "datafusion.substrait",
+    subclass
+)]
 #[derive(Debug, Clone)]
 pub struct PySubstraitSerializer;
 
@@ -96,7 +108,7 @@ impl PySubstraitSerializer {
         py: Python,
     ) -> PyDataFusionResult<PyPlan> {
         PySubstraitSerializer::serialize_bytes(sql, ctx, py).and_then(|proto_bytes| {
-            let proto_bytes = proto_bytes.bind(py).downcast::<PyBytes>().unwrap();
+            let proto_bytes = proto_bytes.bind(py).cast::<PyBytes>().unwrap();
             PySubstraitSerializer::deserialize_bytes(proto_bytes.as_bytes().to_vec(), py)
         })
     }
@@ -125,7 +137,13 @@ impl PySubstraitSerializer {
     }
 }
 
-#[pyclass(frozen, name = "Producer", module = "datafusion.substrait", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "Producer",
+    module = "datafusion.substrait",
+    subclass
+)]
 #[derive(Debug, Clone)]
 pub struct PySubstraitProducer;
 
@@ -142,7 +160,13 @@ impl PySubstraitProducer {
     }
 }
 
-#[pyclass(frozen, name = "Consumer", module = "datafusion.substrait", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "Consumer",
+    module = "datafusion.substrait",
+    subclass
+)]
 #[derive(Debug, Clone)]
 pub struct PySubstraitConsumer;
 
diff --git a/src/table.rs b/crates/core/src/table.rs
similarity index 74%
rename from src/table.rs
rename to crates/core/src/table.rs
index 0683b544d..623349771 100644
--- a/src/table.rs
+++ b/crates/core/src/table.rs
@@ -21,24 +21,35 @@ use std::sync::Arc;
 use arrow::datatypes::SchemaRef;
 use arrow::pyarrow::ToPyArrow;
 use async_trait::async_trait;
-use datafusion::catalog::Session;
+use datafusion::catalog::{Session, TableProviderFactory};
 use datafusion::common::Column;
 use datafusion::datasource::{TableProvider, TableType};
-use datafusion::logical_expr::{Expr, LogicalPlanBuilder, TableProviderFilterPushDown};
+use datafusion::logical_expr::{
+    CreateExternalTable, Expr, LogicalPlanBuilder, TableProviderFilterPushDown,
+};
 use datafusion::physical_plan::ExecutionPlan;
 use datafusion::prelude::DataFrame;
+use datafusion_ffi::proto::logical_extension_codec::FFI_LogicalExtensionCodec;
+use datafusion_python_util::{create_logical_extension_capsule, table_provider_from_pycapsule};
 use pyo3::IntoPyObjectExt;
 use pyo3::prelude::*;
 
 use crate::context::PySessionContext;
 use crate::dataframe::PyDataFrame;
 use crate::dataset::Dataset;
-use crate::utils::table_provider_from_pycapsule;
+use crate::errors;
+use crate::expr::create_external_table::PyCreateExternalTable;
 
 /// This struct is used as a common method for all TableProviders,
 /// whether they refer to an FFI provider, an internally known
 /// implementation, a dataset, or a dataframe view.
-#[pyclass(frozen, name = "RawTable", module = "datafusion.catalog", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "RawTable",
+    module = "datafusion.catalog",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyTable {
     pub table: Arc<dyn TableProvider>,
@@ -68,7 +79,7 @@ impl PyTable {
             Ok(py_table)
         } else if let Ok(py_table) = obj
             .getattr("_inner")
-            .and_then(|inner| inner.extract::<PyTable>())
+            .and_then(|inner| inner.extract::<PyTable>().map_err(Into::<PyErr>::into))
         {
             Ok(py_table)
         } else if let Ok(py_df) = obj.extract::<PyDataFrame>() {
@@ -76,7 +87,7 @@ impl PyTable {
             Ok(PyTable::from(provider))
         } else if let Ok(py_df) = obj
             .getattr("df")
-            .and_then(|inner| inner.extract::<PyDataFrame>())
+            .and_then(|inner| inner.extract::<PyDataFrame>().map_err(Into::<PyErr>::into))
         {
             let provider = py_df.inner_df().as_ref().clone().into_view();
             Ok(PyTable::from(provider))
@@ -200,3 +211,51 @@ impl TableProvider for TempViewTable {
         Ok(vec![TableProviderFilterPushDown::Exact; filters.len()])
     }
 }
+
+#[derive(Debug)]
+pub(crate) struct RustWrappedPyTableProviderFactory {
+    pub(crate) table_provider_factory: Py<PyAny>,
+    pub(crate) codec: Arc<FFI_LogicalExtensionCodec>,
+}
+
+impl RustWrappedPyTableProviderFactory {
+    pub fn new(table_provider_factory: Py<PyAny>, codec: Arc<FFI_LogicalExtensionCodec>) -> Self {
+        Self {
+            table_provider_factory,
+            codec,
+        }
+    }
+
+    fn create_inner(
+        &self,
+        cmd: CreateExternalTable,
+        codec: Bound<PyAny>,
+    ) -> PyResult<Arc<dyn TableProvider>> {
+        Python::attach(|py| {
+            let provider = self.table_provider_factory.bind(py);
+            let cmd = PyCreateExternalTable::from(cmd);
+
+            provider
+                .call_method1("create", (cmd,))
+                .and_then(|t| PyTable::new(t, Some(codec)))
+                .map(|t| t.table())
+        })
+    }
+}
+
+#[async_trait]
+impl TableProviderFactory for RustWrappedPyTableProviderFactory {
+    async fn create(
+        &self,
+        _: &dyn Session,
+        cmd: &CreateExternalTable,
+    ) -> datafusion::common::Result<Arc<dyn TableProvider>> {
+        Python::attach(|py| {
+            let codec = create_logical_extension_capsule(py, self.codec.as_ref())
+                .map_err(errors::to_datafusion_err)?;
+
+            self.create_inner(cmd.clone(), codec.into_any())
+                .map_err(errors::to_datafusion_err)
+        })
+    }
+}
diff --git a/src/udaf.rs b/crates/core/src/udaf.rs
similarity index 93%
rename from src/udaf.rs
rename to crates/core/src/udaf.rs
index cc166035d..80ef51716 100644
--- a/src/udaf.rs
+++ b/crates/core/src/udaf.rs
@@ -15,6 +15,7 @@
 // specific language governing permissions and limitations
 // under the License.
 
+use std::ptr::NonNull;
 use std::sync::Arc;
 
 use datafusion::arrow::array::ArrayRef;
@@ -26,13 +27,13 @@ use datafusion::logical_expr::{
     Accumulator, AccumulatorFactoryFunction, AggregateUDF, AggregateUDFImpl, create_udaf,
 };
 use datafusion_ffi::udaf::FFI_AggregateUDF;
+use datafusion_python_util::parse_volatility;
 use pyo3::prelude::*;
 use pyo3::types::{PyCapsule, PyTuple};
 
 use crate::common::data_type::PyScalarValue;
 use crate::errors::{PyDataFusionResult, py_datafusion_err, to_datafusion_err};
 use crate::expr::PyExpr;
-use crate::utils::{parse_volatility, validate_pycapsule};
 
 #[derive(Debug)]
 struct RustAccumulator {
@@ -155,16 +156,23 @@ pub fn to_rust_accumulator(accum: Py<PyAny>) -> AccumulatorFactoryFunction {
 }
 
 fn aggregate_udf_from_capsule(capsule: &Bound<'_, PyCapsule>) -> PyDataFusionResult<AggregateUDF> {
-    validate_pycapsule(capsule, "datafusion_aggregate_udf")?;
-
-    let udaf = unsafe { capsule.reference::<FFI_AggregateUDF>() };
+    let data: NonNull<FFI_AggregateUDF> = capsule
+        .pointer_checked(Some(c"datafusion_aggregate_udf"))?
+        .cast();
+    let udaf = unsafe { data.as_ref() };
     let udaf: Arc<dyn AggregateUDFImpl> = udaf.into();
 
     Ok(AggregateUDF::new_from_shared_impl(udaf))
 }
 
 /// Represents an AggregateUDF
-#[pyclass(frozen, name = "AggregateUDF", module = "datafusion", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "AggregateUDF",
+    module = "datafusion",
+    subclass
+)]
 #[derive(Debug, Clone)]
 pub struct PyAggregateUDF {
     pub(crate) function: AggregateUDF,
@@ -196,14 +204,14 @@ impl PyAggregateUDF {
     #[staticmethod]
     pub fn from_pycapsule(func: Bound<'_, PyAny>) -> PyDataFusionResult<Self> {
         if func.is_instance_of::<PyCapsule>() {
-            let capsule = func.downcast::<PyCapsule>().map_err(py_datafusion_err)?;
+            let capsule = func.cast::<PyCapsule>().map_err(py_datafusion_err)?;
             let function = aggregate_udf_from_capsule(capsule)?;
             return Ok(Self { function });
         }
 
         if func.hasattr("__datafusion_aggregate_udf__")? {
             let capsule = func.getattr("__datafusion_aggregate_udf__")?.call0()?;
-            let capsule = capsule.downcast::<PyCapsule>().map_err(py_datafusion_err)?;
+            let capsule = capsule.cast::<PyCapsule>().map_err(py_datafusion_err)?;
             let function = aggregate_udf_from_capsule(capsule)?;
             return Ok(Self { function });
         }
diff --git a/src/udf.rs b/crates/core/src/udf.rs
similarity index 92%
rename from src/udf.rs
rename to crates/core/src/udf.rs
index e1f8291d6..c0a39cb47 100644
--- a/src/udf.rs
+++ b/crates/core/src/udf.rs
@@ -17,6 +17,7 @@
 
 use std::any::Any;
 use std::hash::{Hash, Hasher};
+use std::ptr::NonNull;
 use std::sync::Arc;
 
 use arrow::datatypes::{Field, FieldRef};
@@ -31,13 +32,13 @@ use datafusion::logical_expr::{
     Volatility,
 };
 use datafusion_ffi::udf::FFI_ScalarUDF;
+use datafusion_python_util::parse_volatility;
 use pyo3::prelude::*;
 use pyo3::types::{PyCapsule, PyTuple};
 
 use crate::array::PyArrowArrayExportable;
-use crate::errors::{PyDataFusionResult, py_datafusion_err, to_datafusion_err};
+use crate::errors::{PyDataFusionResult, to_datafusion_err};
 use crate::expr::PyExpr;
-use crate::utils::{parse_volatility, validate_pycapsule};
 
 /// This struct holds the Python written function that is a
 /// ScalarUDF.
@@ -153,7 +154,13 @@ impl ScalarUDFImpl for PythonFunctionScalarUDF {
 }
 
 /// Represents a PyScalarUDF
-#[pyclass(frozen, name = "ScalarUDF", module = "datafusion", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "ScalarUDF",
+    module = "datafusion",
+    subclass
+)]
 #[derive(Debug, Clone)]
 pub struct PyScalarUDF {
     pub(crate) function: ScalarUDF,
@@ -186,10 +193,11 @@ impl PyScalarUDF {
     pub fn from_pycapsule(func: Bound<'_, PyAny>) -> PyDataFusionResult<Self> {
         if func.hasattr("__datafusion_scalar_udf__")? {
             let capsule = func.getattr("__datafusion_scalar_udf__")?.call0()?;
-            let capsule = capsule.downcast::<PyCapsule>().map_err(py_datafusion_err)?;
-            validate_pycapsule(capsule, "datafusion_scalar_udf")?;
-
-            let udf = unsafe { capsule.reference::<FFI_ScalarUDF>() };
+            let capsule = capsule.cast::<PyCapsule>().map_err(to_datafusion_err)?;
+            let data: NonNull<FFI_ScalarUDF> = capsule
+                .pointer_checked(Some(c"datafusion_scalar_udf"))?
+                .cast();
+            let udf = unsafe { data.as_ref() };
             let udf: Arc<dyn ScalarUDFImpl> = udf.into();
 
             Ok(Self {
diff --git a/src/udtf.rs b/crates/core/src/udtf.rs
similarity index 92%
rename from src/udtf.rs
rename to crates/core/src/udtf.rs
index 24cf25824..9371732dc 100644
--- a/src/udtf.rs
+++ b/crates/core/src/udtf.rs
@@ -15,6 +15,7 @@
 // specific language governing permissions and limitations
 // under the License.
 
+use std::ptr::NonNull;
 use std::sync::Arc;
 
 use datafusion::catalog::{TableFunctionImpl, TableProvider};
@@ -30,10 +31,9 @@ use crate::context::PySessionContext;
 use crate::errors::{py_datafusion_err, to_datafusion_err};
 use crate::expr::PyExpr;
 use crate::table::PyTable;
-use crate::utils::validate_pycapsule;
 
 /// Represents a user defined table function
-#[pyclass(frozen, name = "TableFunction", module = "datafusion")]
+#[pyclass(from_py_object, frozen, name = "TableFunction", module = "datafusion")]
 #[derive(Debug, Clone)]
 pub struct PyTableFunction {
     pub(crate) name: String,
@@ -71,10 +71,11 @@ impl PyTableFunction {
                     err
                 }
             })?;
-            let capsule = capsule.downcast::<PyCapsule>().map_err(py_datafusion_err)?;
-            validate_pycapsule(capsule, "datafusion_table_function")?;
-
-            let ffi_func = unsafe { capsule.reference::<FFI_TableFunction>() };
+            let capsule = capsule.cast::<PyCapsule>()?;
+            let data: NonNull<FFI_TableFunction> = capsule
+                .pointer_checked(Some(c"datafusion_table_function"))?
+                .cast();
+            let ffi_func = unsafe { data.as_ref() };
             let foreign_func: Arc<dyn TableFunctionImpl> = ffi_func.to_owned().into();
 
             PyTableFunctionInner::FFIFunction(foreign_func)
diff --git a/src/udwf.rs b/crates/core/src/udwf.rs
similarity index 95%
rename from src/udwf.rs
rename to crates/core/src/udwf.rs
index 4bf55a850..1d3608ada 100644
--- a/src/udwf.rs
+++ b/crates/core/src/udwf.rs
@@ -17,6 +17,7 @@
 
 use std::any::Any;
 use std::ops::Range;
+use std::ptr::NonNull;
 use std::sync::Arc;
 
 use arrow::array::{Array, ArrayData, ArrayRef, make_array};
@@ -31,14 +32,14 @@ use datafusion::logical_expr::{
 };
 use datafusion::scalar::ScalarValue;
 use datafusion_ffi::udwf::FFI_WindowUDF;
+use datafusion_python_util::parse_volatility;
 use pyo3::exceptions::PyValueError;
 use pyo3::prelude::*;
 use pyo3::types::{PyCapsule, PyList, PyTuple};
 
 use crate::common::data_type::PyScalarValue;
-use crate::errors::{PyDataFusionResult, py_datafusion_err, to_datafusion_err};
+use crate::errors::{PyDataFusionResult, to_datafusion_err};
 use crate::expr::PyExpr;
-use crate::utils::{parse_volatility, validate_pycapsule};
 
 #[derive(Debug)]
 struct RustPartitionEvaluator {
@@ -209,7 +210,13 @@ pub fn to_rust_partition_evaluator(evaluator: Py<PyAny>) -> PartitionEvaluatorFa
 }
 
 /// Represents an WindowUDF
-#[pyclass(frozen, name = "WindowUDF", module = "datafusion", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "WindowUDF",
+    module = "datafusion",
+    subclass
+)]
 #[derive(Debug, Clone)]
 pub struct PyWindowUDF {
     pub(crate) function: WindowUDF,
@@ -254,10 +261,11 @@ impl PyWindowUDF {
             func
         };
 
-        let capsule = capsule.downcast::<PyCapsule>().map_err(py_datafusion_err)?;
-        validate_pycapsule(capsule, "datafusion_window_udf")?;
-
-        let udwf = unsafe { capsule.reference::<FFI_WindowUDF>() };
+        let capsule = capsule.cast::<PyCapsule>().map_err(to_datafusion_err)?;
+        let data: NonNull<FFI_WindowUDF> = capsule
+            .pointer_checked(Some(c"datafusion_window_udf"))?
+            .cast();
+        let udwf = unsafe { data.as_ref() };
         let udwf: Arc<dyn WindowUDFImpl> = udwf.into();
 
         Ok(Self {
diff --git a/src/unparser/dialect.rs b/crates/core/src/unparser/dialect.rs
similarity index 93%
rename from src/unparser/dialect.rs
rename to crates/core/src/unparser/dialect.rs
index 5df0a0c2e..52a2da00b 100644
--- a/src/unparser/dialect.rs
+++ b/crates/core/src/unparser/dialect.rs
@@ -22,7 +22,13 @@ use datafusion::sql::unparser::dialect::{
 };
 use pyo3::prelude::*;
 
-#[pyclass(frozen, name = "Dialect", module = "datafusion.unparser", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "Dialect",
+    module = "datafusion.unparser",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyDialect {
     pub dialect: Arc<dyn Dialect>,
diff --git a/src/unparser/mod.rs b/crates/core/src/unparser/mod.rs
similarity index 94%
rename from src/unparser/mod.rs
rename to crates/core/src/unparser/mod.rs
index 203e334c3..5142b918e 100644
--- a/src/unparser/mod.rs
+++ b/crates/core/src/unparser/mod.rs
@@ -27,7 +27,13 @@ use pyo3::prelude::*;
 
 use crate::sql::logical::PyLogicalPlan;
 
-#[pyclass(frozen, name = "Unparser", module = "datafusion.unparser", subclass)]
+#[pyclass(
+    from_py_object,
+    frozen,
+    name = "Unparser",
+    module = "datafusion.unparser",
+    subclass
+)]
 #[derive(Clone)]
 pub struct PyUnparser {
     dialect: Arc<dyn Dialect>,
diff --git a/python/datafusion/html_formatter.py b/crates/util/Cargo.toml
similarity index 62%
rename from python/datafusion/html_formatter.py
rename to crates/util/Cargo.toml
index 65eb1f042..00d5946a5 100644
--- a/python/datafusion/html_formatter.py
+++ b/crates/util/Cargo.toml
@@ -15,15 +15,20 @@
 # specific language governing permissions and limitations
 # under the License.
 
-"""Deprecated module for dataframe formatting."""
+[package]
+name = "datafusion-python-util"
+version.workspace = true
+edition.workspace = true
+rust-version.workspace = true
+license.workspace = true
+description.workspace = true
+homepage.workspace = true
+repository.workspace = true
 
-import warnings
-
-from datafusion.dataframe_formatter import *  # noqa: F403
-
-warnings.warn(
-    "The module 'html_formatter' is deprecated and will be removed in the next release."
-    "Please use 'dataframe_formatter' instead.",
-    DeprecationWarning,
-    stacklevel=3,
-)
+[dependencies]
+tokio = { workspace = true, features = ["macros", "rt", "rt-multi-thread"] }
+pyo3 = { workspace = true }
+datafusion = { workspace = true }
+datafusion-ffi = { workspace = true }
+arrow = { workspace = true }
+prost = { workspace = true }
diff --git a/src/errors.rs b/crates/util/src/errors.rs
similarity index 100%
rename from src/errors.rs
rename to crates/util/src/errors.rs
diff --git a/src/utils.rs b/crates/util/src/lib.rs
similarity index 78%
rename from src/utils.rs
rename to crates/util/src/lib.rs
index 28b58ba0f..5b1c89936 100644
--- a/src/utils.rs
+++ b/crates/util/src/lib.rs
@@ -16,6 +16,7 @@
 // under the License.
 
 use std::future::Future;
+use std::ptr::NonNull;
 use std::sync::{Arc, OnceLock};
 use std::time::Duration;
 
@@ -24,7 +25,6 @@ use datafusion::execution::context::SessionContext;
 use datafusion::logical_expr::Volatility;
 use datafusion_ffi::proto::logical_extension_codec::FFI_LogicalExtensionCodec;
 use datafusion_ffi::table_provider::FFI_TableProvider;
-use pyo3::IntoPyObjectExt;
 use pyo3::exceptions::{PyImportError, PyTypeError, PyValueError};
 use pyo3::prelude::*;
 use pyo3::types::{PyCapsule, PyType};
@@ -32,24 +32,24 @@ use tokio::runtime::Runtime;
 use tokio::task::JoinHandle;
 use tokio::time::sleep;
 
-use crate::TokioRuntime;
-use crate::context::PySessionContext;
-use crate::errors::{PyDataFusionError, PyDataFusionResult, py_datafusion_err, to_datafusion_err};
+use crate::errors::{PyDataFusionError, PyDataFusionResult, to_datafusion_err};
+
+pub mod errors;
 
 /// Utility to get the Tokio Runtime from Python
 #[inline]
-pub(crate) fn get_tokio_runtime() -> &'static TokioRuntime {
+pub fn get_tokio_runtime() -> &'static Runtime {
     // NOTE: Other pyo3 python libraries have had issues with using tokio
     // behind a forking app-server like `gunicorn`
     // If we run into that problem, in the future we can look to `delta-rs`
     // which adds a check in that disallows calls from a forked process
     // https://github.com/delta-io/delta-rs/blob/87010461cfe01563d91a4b9cd6fa468e2ad5f283/python/src/utils.rs#L10-L31
-    static RUNTIME: OnceLock<TokioRuntime> = OnceLock::new();
-    RUNTIME.get_or_init(|| TokioRuntime(tokio::runtime::Runtime::new().unwrap()))
+    static RUNTIME: OnceLock<Runtime> = OnceLock::new();
+    RUNTIME.get_or_init(|| Runtime::new().unwrap())
 }
 
 #[inline]
-pub(crate) fn is_ipython_env(py: Python) -> &'static bool {
+pub fn is_ipython_env(py: Python) -> &'static bool {
     static IS_IPYTHON_ENV: OnceLock<bool> = OnceLock::new();
     IS_IPYTHON_ENV.get_or_init(|| {
         py.import("IPython")
@@ -61,7 +61,7 @@ pub(crate) fn is_ipython_env(py: Python) -> &'static bool {
 
 /// Utility to get the Global Datafussion CTX
 #[inline]
-pub(crate) fn get_global_ctx() -> &'static Arc<SessionContext> {
+pub fn get_global_ctx() -> &'static Arc<SessionContext> {
     static CTX: OnceLock<Arc<SessionContext>> = OnceLock::new();
     CTX.get_or_init(|| Arc::new(SessionContext::new()))
 }
@@ -75,7 +75,7 @@ where
     F: Future + Send,
     F::Output: Send,
 {
-    let runtime: &Runtime = &get_tokio_runtime().0;
+    let runtime: &Runtime = get_tokio_runtime();
     const INTERVAL_CHECK_SIGNALS: Duration = Duration::from_millis(1_000);
 
     // Some fast running processes that generate many `wait_for_future` calls like
@@ -109,12 +109,12 @@ where
 
 /// Spawn a [`Future`] on the Tokio runtime and wait for completion
 /// while respecting Python signal handling.
-pub(crate) fn spawn_future<F, T>(py: Python, fut: F) -> PyDataFusionResult<T>
+pub fn spawn_future<F, T>(py: Python, fut: F) -> PyDataFusionResult<T>
 where
     F: Future<Output = datafusion::common::Result<T>> + Send + 'static,
     T: Send + 'static,
 {
-    let rt = &get_tokio_runtime().0;
+    let rt = get_tokio_runtime();
     let handle: JoinHandle<datafusion::common::Result<T>> = rt.spawn(fut);
     // Wait for the join handle while respecting Python signal handling.
     // We handle errors in two steps so `?` maps the error types correctly:
@@ -136,7 +136,7 @@ where
     Ok(inner_result?)
 }
 
-pub(crate) fn parse_volatility(value: &str) -> PyDataFusionResult<Volatility> {
+pub fn parse_volatility(value: &str) -> PyDataFusionResult<Volatility> {
     Ok(match value {
         "immutable" => Volatility::Immutable,
         "stable" => Volatility::Stable,
@@ -150,7 +150,7 @@ pub(crate) fn parse_volatility(value: &str) -> PyDataFusionResult<Volatility> {
     })
 }
 
-pub(crate) fn validate_pycapsule(capsule: &Bound<PyCapsule>, name: &str) -> PyResult<()> {
+pub fn validate_pycapsule(capsule: &Bound<PyCapsule>, name: &str) -> PyResult<()> {
     let capsule_name = capsule.name()?;
     if capsule_name.is_none() {
         return Err(PyValueError::new_err(format!(
@@ -158,7 +158,7 @@ pub(crate) fn validate_pycapsule(capsule: &Bound<PyCapsule>, name: &str) -> PyRe
         )));
     }
 
-    let capsule_name = capsule_name.unwrap().to_str()?;
+    let capsule_name = unsafe { capsule_name.unwrap().as_cstr().to_str()? };
     if capsule_name != name {
         return Err(PyValueError::new_err(format!(
             "Expected name '{name}' in PyCapsule, instead got '{capsule_name}'"
@@ -168,7 +168,7 @@ pub(crate) fn validate_pycapsule(capsule: &Bound<PyCapsule>, name: &str) -> PyRe
     Ok(())
 }
 
-pub(crate) fn table_provider_from_pycapsule<'py>(
+pub fn table_provider_from_pycapsule<'py>(
     mut obj: Bound<'py, PyAny>,
     session: Bound<'py, PyAny>,
 ) -> PyResult<Option<Arc<dyn TableProvider>>> {
@@ -185,10 +185,11 @@ pub(crate) fn table_provider_from_pycapsule<'py>(
         })?;
     }
 
-    if let Ok(capsule) = obj.downcast::<PyCapsule>().map_err(py_datafusion_err) {
-        validate_pycapsule(capsule, "datafusion_table_provider")?;
-
-        let provider = unsafe { capsule.reference::<FFI_TableProvider>() };
+    if let Ok(capsule) = obj.cast::<PyCapsule>() {
+        let data: NonNull<FFI_TableProvider> = capsule
+            .pointer_checked(Some(c"datafusion_table_provider"))?
+            .cast();
+        let provider = unsafe { data.as_ref() };
         let provider: Arc<dyn TableProvider> = provider.into();
 
         Ok(Some(provider))
@@ -197,29 +198,7 @@ pub(crate) fn table_provider_from_pycapsule<'py>(
     }
 }
 
-pub(crate) fn extract_logical_extension_codec(
-    py: Python,
-    obj: Option<Bound<PyAny>>,
-) -> PyResult<Arc<FFI_LogicalExtensionCodec>> {
-    let obj = match obj {
-        Some(obj) => obj,
-        None => PySessionContext::global_ctx()?.into_bound_py_any(py)?,
-    };
-    let capsule = if obj.hasattr("__datafusion_logical_extension_codec__")? {
-        obj.getattr("__datafusion_logical_extension_codec__")?
-            .call0()?
-    } else {
-        obj
-    };
-    let capsule = capsule.downcast::<PyCapsule>().map_err(py_datafusion_err)?;
-
-    validate_pycapsule(capsule, "datafusion_logical_extension_codec")?;
-
-    let codec = unsafe { capsule.reference::<FFI_LogicalExtensionCodec>() };
-    Ok(Arc::new(codec.clone()))
-}
-
-pub(crate) fn create_logical_extension_capsule<'py>(
+pub fn create_logical_extension_capsule<'py>(
     py: Python<'py>,
     codec: &FFI_LogicalExtensionCodec,
 ) -> PyResult<Bound<'py, PyCapsule>> {
@@ -228,3 +207,20 @@ pub(crate) fn create_logical_extension_capsule<'py>(
 
     PyCapsule::new(py, codec, Some(name))
 }
+
+pub fn ffi_logical_codec_from_pycapsule(obj: Bound<PyAny>) -> PyResult<FFI_LogicalExtensionCodec> {
+    let attr_name = "__datafusion_logical_extension_codec__";
+    let capsule = if obj.hasattr(attr_name)? {
+        obj.getattr(attr_name)?.call0()?
+    } else {
+        obj
+    };
+
+    let capsule = capsule.cast::<PyCapsule>()?;
+    let data: NonNull<FFI_LogicalExtensionCodec> = capsule
+        .pointer_checked(Some(c"datafusion_logical_extension_codec"))?
+        .cast();
+    let codec = unsafe { data.as_ref() };
+
+    Ok(codec.clone())
+}
diff --git a/dev/changelog/53.0.0.md b/dev/changelog/53.0.0.md
new file mode 100644
index 000000000..3e27a852d
--- /dev/null
+++ b/dev/changelog/53.0.0.md
@@ -0,0 +1,107 @@
+<!--
+Licensed to the Apache Software Foundation (ASF) under one
+or more contributor license agreements.  See the NOTICE file
+distributed with this work for additional information
+regarding copyright ownership.  The ASF licenses this file
+to you under the Apache License, Version 2.0 (the
+"License"); you may not use this file except in compliance
+with the License.  You may obtain a copy of the License at
+
+  http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing,
+software distributed under the License is distributed on an
+"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+KIND, either express or implied.  See the License for the
+specific language governing permissions and limitations
+under the License.
+-->
+
+# Apache DataFusion Python 53.0.0 Changelog
+
+This release consists of 52 commits from 9 contributors. See credits at the end of this changelog for more information.
+
+**Breaking changes:**
+
+- minor: remove deprecated interfaces [#1481](https://github.com/apache/datafusion-python/pull/1481) (timsaucer)
+
+**Implemented enhancements:**
+
+- feat: feat: add to_time, to_local_time, to_date functions [#1387](https://github.com/apache/datafusion-python/pull/1387) (mesejo)
+- feat: Add FFI_TableProviderFactory support [#1396](https://github.com/apache/datafusion-python/pull/1396) (davisp)
+
+**Fixed bugs:**
+
+- fix: satisfy rustfmt check in lib.rs re-exports [#1406](https://github.com/apache/datafusion-python/pull/1406) (kevinjqliu)
+
+**Documentation updates:**
+
+- docs: clarify DataFusion 52 FFI session-parameter requirement for provider hooks [#1439](https://github.com/apache/datafusion-python/pull/1439) (kevinjqliu)
+
+**Other:**
+
+- Merge release 52.0.0 into main [#1389](https://github.com/apache/datafusion-python/pull/1389) (timsaucer)
+- Add workflow to verify release candidate on multiple systems [#1388](https://github.com/apache/datafusion-python/pull/1388) (timsaucer)
+- Allow running "verify release candidate" github workflow on Windows [#1392](https://github.com/apache/datafusion-python/pull/1392) (kevinjqliu)
+- ci: update pre-commit hooks, fix linting, and refresh dependencies [#1385](https://github.com/apache/datafusion-python/pull/1385) (dariocurr)
+- Add CI check for crates.io patches [#1407](https://github.com/apache/datafusion-python/pull/1407) (timsaucer)
+- Enable doc tests in local and CI testing [#1409](https://github.com/apache/datafusion-python/pull/1409) (ntjohnson1)
+- Upgrade to DataFusion 53 [#1402](https://github.com/apache/datafusion-python/pull/1402) (nuno-faria)
+- Catch warnings in FFI unit tests [#1410](https://github.com/apache/datafusion-python/pull/1410) (timsaucer)
+- Add docstring examples for Scalar trigonometric functions [#1411](https://github.com/apache/datafusion-python/pull/1411) (ntjohnson1)
+- Create workspace with core and util crates [#1414](https://github.com/apache/datafusion-python/pull/1414) (timsaucer)
+- Add docstring examples for Scalar regex, crypto, struct and other [#1422](https://github.com/apache/datafusion-python/pull/1422) (ntjohnson1)
+- Add docstring examples for Scalar math functions [#1421](https://github.com/apache/datafusion-python/pull/1421) (ntjohnson1)
+- Add docstring examples for Common utility functions [#1419](https://github.com/apache/datafusion-python/pull/1419) (ntjohnson1)
+- Add docstring examples for Aggregate basic and bitwise/boolean functions [#1416](https://github.com/apache/datafusion-python/pull/1416) (ntjohnson1)
+- Fix CI errors on main [#1432](https://github.com/apache/datafusion-python/pull/1432) (timsaucer)
+- Add docstring examples for Scalar temporal functions [#1424](https://github.com/apache/datafusion-python/pull/1424) (ntjohnson1)
+- Add docstring examples for Aggregate statistical and regression functions [#1417](https://github.com/apache/datafusion-python/pull/1417) (ntjohnson1)
+- Add docstring examples for Scalar array/list functions [#1420](https://github.com/apache/datafusion-python/pull/1420) (ntjohnson1)
+- Add docstring examples for Scalar string functions [#1423](https://github.com/apache/datafusion-python/pull/1423) (ntjohnson1)
+- Add docstring examples for Aggregate window functions [#1418](https://github.com/apache/datafusion-python/pull/1418) (ntjohnson1)
+- ci: pin third-party actions to Apache-approved SHAs [#1438](https://github.com/apache/datafusion-python/pull/1438) (kevinjqliu)
+- minor: bump datafusion to release version [#1441](https://github.com/apache/datafusion-python/pull/1441) (timsaucer)
+- ci: add swap during build, use tpchgen-cli [#1443](https://github.com/apache/datafusion-python/pull/1443) (timsaucer)
+- Update remaining existing examples to make testable/standalone executable [#1437](https://github.com/apache/datafusion-python/pull/1437) (ntjohnson1)
+- Do not run validate_pycapsule if pointer_checked is used [#1426](https://github.com/apache/datafusion-python/pull/1426) (Tpt)
+- Implement configuration extension support [#1391](https://github.com/apache/datafusion-python/pull/1391) (timsaucer)
+- Add a working, more complete example of using a catalog (docs) [#1427](https://github.com/apache/datafusion-python/pull/1427) (toppyy)
+- chore: update dependencies [#1447](https://github.com/apache/datafusion-python/pull/1447) (timsaucer)
+- Complete doc string examples for functions.py [#1435](https://github.com/apache/datafusion-python/pull/1435) (ntjohnson1)
+- chore: enforce uv lockfile consistency in CI and pre-commit [#1398](https://github.com/apache/datafusion-python/pull/1398) (mesejo)
+- CI: Add CodeQL workflow for GitHub Actions security scanning [#1408](https://github.com/apache/datafusion-python/pull/1408) (kevinjqliu)
+- ci: update codespell paths [#1469](https://github.com/apache/datafusion-python/pull/1469) (timsaucer)
+- Add missing datetime functions [#1467](https://github.com/apache/datafusion-python/pull/1467) (timsaucer)
+- Add AI skill to check current repository against upstream APIs [#1460](https://github.com/apache/datafusion-python/pull/1460) (timsaucer)
+- Add missing string function `contains` [#1465](https://github.com/apache/datafusion-python/pull/1465) (timsaucer)
+- Add missing conditional functions [#1464](https://github.com/apache/datafusion-python/pull/1464) (timsaucer)
+- Reduce peak memory usage during release builds to fix OOM on manylinux runners [#1445](https://github.com/apache/datafusion-python/pull/1445) (kevinjqliu)
+- Add missing map functions [#1461](https://github.com/apache/datafusion-python/pull/1461) (timsaucer)
+- minor: Fix pytest instructions in the README [#1477](https://github.com/apache/datafusion-python/pull/1477) (nuno-faria)
+- Add missing array functions [#1468](https://github.com/apache/datafusion-python/pull/1468) (timsaucer)
+- Add missing scalar functions  [#1470](https://github.com/apache/datafusion-python/pull/1470) (timsaucer)
+- Add missing aggregate functions [#1471](https://github.com/apache/datafusion-python/pull/1471) (timsaucer)
+- Add missing Dataframe functions [#1472](https://github.com/apache/datafusion-python/pull/1472) (timsaucer)
+- Add missing deregister methods to SessionContext [#1473](https://github.com/apache/datafusion-python/pull/1473) (timsaucer)
+- Add missing registration methods [#1474](https://github.com/apache/datafusion-python/pull/1474) (timsaucer)
+- Add missing SessionContext utility methods [#1475](https://github.com/apache/datafusion-python/pull/1475) (timsaucer)
+
+## Credits
+
+Thank you to everyone who contributed to this release. Here is a breakdown of commits (PRs merged) per contributor.
+
+```
+    25	Tim Saucer
+    13	Nick
+     6	Kevin Liu
+     2	Daniel Mesejo
+     2	Nuno Faria
+     1	Paul J. Davis
+     1	Thomas Tanon
+     1	Topias Pyykkönen
+     1	dario curreri
+```
+
+Thank you also to everyone who contributed in other ways such as filing issues, reviewing PRs, and providing feedback on this release.
+
diff --git a/dev/check_crates_patch.py b/dev/check_crates_patch.py
new file mode 100644
index 000000000..74e489e1f
--- /dev/null
+++ b/dev/check_crates_patch.py
@@ -0,0 +1,61 @@
+#!/usr/bin/env python3
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+"""Check that no Cargo.toml files contain [patch.crates-io] entries.
+
+Release builds must not depend on patched crates. During development it is
+common to temporarily patch crates-io dependencies, but those patches must
+be removed before creating a release.
+
+An empty [patch.crates-io] section is allowed.
+"""
+
+import sys
+from pathlib import Path
+
+import tomllib
+
+
+def main() -> int:
+    errors: list[str] = []
+    for cargo_toml in sorted(Path().rglob("Cargo.toml")):
+        if "target" in cargo_toml.parts:
+            continue
+        with Path.open(cargo_toml, "rb") as f:
+            data = tomllib.load(f)
+        patch = data.get("patch", {}).get("crates-io", {})
+        if patch:
+            errors.append(str(cargo_toml))
+            for name, spec in patch.items():
+                errors.append(f"  {name} = {spec}")
+
+    if errors:
+        print("ERROR: Release builds must not contain [patch.crates-io] entries.")
+        print()
+        for line in errors:
+            print(line)
+        print()
+        print("Remove all [patch.crates-io] entries before creating a release.")
+        return 1
+
+    print("OK: No [patch.crates-io] entries found.")
+    return 0
+
+
+if __name__ == "__main__":
+    sys.exit(main())
diff --git a/dev/release/README.md b/dev/release/README.md
index 5b70b80f4..4833be55a 100644
--- a/dev/release/README.md
+++ b/dev/release/README.md
@@ -26,11 +26,11 @@ required due to changes in DataFusion rather than having a large amount of work
 is available.
 
 When there is a new official release of DataFusion, we update the `main` branch to point to that, update the version
-number, and create a new release branch, such as `branch-0.8`. Once this branch is created, we switch the `main` branch
+number, and create a new release branch, such as `branch-53`. Once this branch is created, we switch the `main` branch
 back to using GitHub dependencies. The release activity (such as generating the changelog) can then happen on the
 release branch without blocking ongoing development in the `main` branch.
 
-We can cherry-pick commits from the `main` branch into `branch-0.8` as needed and then create new patch releases
+We can cherry-pick commits from the `main` branch into `branch-53` as needed and then create new patch releases
 from that branch.
 
 ## Detailed Guide
@@ -54,7 +54,8 @@ Before creating a new release:
 
 - We need to ensure that the main branch does not have any GitHub dependencies
 - a PR should be created and merged to update the major version number of the project
-- A new release branch should be created, such as `branch-0.8`
+- A new release branch should be created, such as `branch-53`
+- It is best to push this branch to the apache repository rather than a personal fork in case patch releases are required.
 
 ## Preparing a Release Candidate
 
@@ -65,14 +66,14 @@ We maintain a `CHANGELOG.md` so our users know what has been changed between rel
 The changelog is generated using a Python script:
 
 ```bash
-$ GITHUB_TOKEN=<TOKEN> ./dev/release/generate-changelog.py 24.0.0 HEAD 25.0.0 > dev/changelog/25.0.0.md
+$ GITHUB_TOKEN=<TOKEN> ./dev/release/generate-changelog.py 52.0.0 HEAD 53.0.0 > dev/changelog/53.0.0.md
 ```
 
 This script creates a changelog from GitHub PRs based on the labels associated with them as well as looking for
 titles starting with `feat:`, `fix:`, or `docs:` . The script will produce output similar to:
 
 ```
-Fetching list of commits between 24.0.0 and HEAD
+Fetching list of commits between 52.0.0 and HEAD
 Fetching pull requests
 Categorizing pull requests
 Generating changelog content
@@ -81,6 +82,7 @@ Generating changelog content
 ### Update the version number
 
 The only place you should need to update the version is in the root `Cargo.toml`.
+You will need to update this both in the workspace section and also in the dependencies.
 After updating the toml file, run `cargo update` to update the cargo lock file.
 If you do not want to update all the dependencies, you can instead run `cargo build`
 which should only update the version number for `datafusion-python`.
@@ -94,14 +96,14 @@ you need to push a tag to start the CI process for release candidates. The follo
 the upstream repository is called `apache`.
 
 ```bash
-git tag 0.8.0-rc1
-git push apache 0.8.0-rc1
+git tag 53.0.0-rc1
+git push apache 53.0.0-rc1
 ```
 
 ### Create a source release
 
 ```bash
-./dev/release/create-tarball.sh 0.8.0 1
+./dev/release/create-tarball.sh 53.0.0 1
 ```
 
 This will also create the email template to send to the mailing list.
@@ -124,10 +126,10 @@ Click on the action and scroll down to the bottom of the page titled "Artifacts"
 contain files such as:
 
 ```text
-datafusion-22.0.0-cp37-abi3-macosx_10_7_x86_64.whl
-datafusion-22.0.0-cp37-abi3-macosx_11_0_arm64.whl
-datafusion-22.0.0-cp37-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
-datafusion-22.0.0-cp37-abi3-win_amd64.whl
+datafusion-53.0.0-cp37-abi3-macosx_10_7_x86_64.whl
+datafusion-53.0.0-cp37-abi3-macosx_11_0_arm64.whl
+datafusion-53.0.0-cp37-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
+datafusion-53.0.0-cp37-abi3-win_amd64.whl
 ```
 
 Upload the wheels to testpypi.
@@ -135,35 +137,35 @@ Upload the wheels to testpypi.
 ```bash
 unzip dist.zip
 python3 -m pip install --upgrade setuptools twine build
-python3 -m twine upload --repository testpypi datafusion-22.0.0-cp37-abi3-*.whl
+python3 -m twine upload --repository testpypi datafusion-53.0.0-cp37-abi3-*.whl
 ```
 
 When prompted for username, enter `__token__`. When prompted for a password, enter a valid GitHub Personal Access Token
 
 #### Publish Python Source Distribution to testpypi
 
-Download the source tarball created in the previous step, untar it, and run:
+Download the source tarball from the Apache server created in the previous step, untar it, and run:
 
 ```bash
 maturin sdist
 ```
 
-This will create a file named `dist/datafusion-0.7.0.tar.gz`. Upload this to testpypi:
+This will create a file named `dist/datafusion-53.0.0.tar.gz`. Upload this to testpypi:
 
 ```bash
-python3 -m twine upload --repository testpypi dist/datafusion-0.7.0.tar.gz
+python3 -m twine upload --repository testpypi dist/datafusion-53.0.0.tar.gz
 ```
 
 ### Run Verify Release Candidate Workflow
 
 Before sending the vote email, run the manually triggered GitHub Actions workflow
 "Verify Release Candidate" and confirm all matrix jobs pass across the OS/architecture matrix
-(for example, Linux and macOS runners):
+(for example, Linux, macOS, and Windows runners):
 
 1. Go to https://github.com/apache/datafusion-python/actions/workflows/verify-release-candidate.yml
 2. Click "Run workflow"
-3. Set `version` to the release version (for example, `52.0.0`)
-4. Set `rc_number` to the RC number (for example, `0`)
+3. Set `version` to the release version (for example, `53.0.0`)
+4. Set `rc_number` to the RC number (for example, `1`)
 5. Wait for all jobs to complete successfully
 
 Include a short note in the vote email template that this workflow was run across all OS/architecture
@@ -183,7 +185,7 @@ Releases may be verified using `verify-release-candidate.sh`:
 
 ```bash
 git clone https://github.com/apache/datafusion-python.git
-dev/release/verify-release-candidate.sh 48.0.0 1
+dev/release/verify-release-candidate.sh 53.0.0 1
 ```
 
 Alternatively, one can run unit tests against a testpypi release candidate:
@@ -195,7 +197,7 @@ cd datafusion-python
 
 # checkout the release commit
 git fetch --tags
-git checkout 40.0.0-rc1
+git checkout 53.0.0-rc1
 git submodule update --init --recursive
 
 # create the env
@@ -203,7 +205,7 @@ python3 -m venv .venv
 source .venv/bin/activate
 
 # install release candidate
-pip install --extra-index-url https://test.pypi.org/simple/ datafusion==40.0.0
+pip install --extra-index-url https://test.pypi.org/simple/ datafusion==53.0.0
 
 # install test dependencies
 pip install pytest numpy pytest-asyncio
@@ -224,7 +226,7 @@ Once the vote passes, we can publish the release.
 Create the source release tarball:
 
 ```bash
-./dev/release/release-tarball.sh 0.8.0 1
+./dev/release/release-tarball.sh 53.0.0 1
 ```
 
 ### Publishing Rust Crate to crates.io
@@ -232,7 +234,7 @@ Create the source release tarball:
 Some projects depend on the Rust crate directly, so we publish this to crates.io
 
 ```shell
-cargo publish
+cargo publish --workspace
 ```
 
 ### Publishing Python Artifacts to PyPi
@@ -252,15 +254,15 @@ Pypi packages auto upload to conda-forge via [datafusion feedstock](https://gith
 ### Push the Release Tag
 
 ```bash
-git checkout 0.8.0-rc1
-git tag 0.8.0
-git push apache 0.8.0
+git checkout 53.0.0-rc1
+git tag 53.0.0
+git push apache 53.0.0
 ```
 
 ### Add the release to Apache Reporter
 
 Add the release to https://reporter.apache.org/addrelease.html?datafusion with a version name prefixed with `DATAFUSION-PYTHON`,
-for example `DATAFUSION-PYTHON-31.0.0`.
+for example `DATAFUSION-PYTHON-53.0.0`.
 
 The release information is used to generate a template for a board report (see example from Apache Arrow
 [here](https://github.com/apache/arrow/pull/14357)).
@@ -283,7 +285,7 @@ svn ls https://dist.apache.org/repos/dist/dev/datafusion | grep datafusion-pytho
 Delete a release candidate:
 
 ```bash
-svn delete -m "delete old DataFusion RC" https://dist.apache.org/repos/dist/dev/datafusion/apache-datafusion-python-7.1.0-rc1/
+svn delete -m "delete old DataFusion RC" https://dist.apache.org/repos/dist/dev/datafusion/apache-datafusion-python-53.0.0-rc1/
 ```
 
 #### Deleting old releases from `release` svn
@@ -299,5 +301,5 @@ svn ls https://dist.apache.org/repos/dist/release/datafusion | grep datafusion-p
 Delete a release:
 
 ```bash
-svn delete -m "delete old DataFusion release" https://dist.apache.org/repos/dist/release/datafusion/datafusion-python-7.0.0
+svn delete -m "delete old DataFusion release" https://dist.apache.org/repos/dist/release/datafusion/datafusion-python-52.0.0
 ```
diff --git a/dev/release/rat_exclude_files.txt b/dev/release/rat_exclude_files.txt
index dcd5d9aac..b2db144e8 100644
--- a/dev/release/rat_exclude_files.txt
+++ b/dev/release/rat_exclude_files.txt
@@ -47,4 +47,5 @@ benchmarks/tpch/queries/q*.sql
 benchmarks/tpch/create_tables.sql
 .cargo/config.toml
 **/.cargo/config.toml
-uv.lock
\ No newline at end of file
+uv.lock
+examples/tpch/answers_sf1/*.tbl
\ No newline at end of file
diff --git a/dev/release/verify-release-candidate.sh b/dev/release/verify-release-candidate.sh
index 2bfce0e2d..9591e0335 100755
--- a/dev/release/verify-release-candidate.sh
+++ b/dev/release/verify-release-candidate.sh
@@ -112,8 +112,17 @@ test_source_distribution() {
 
   curl https://sh.rustup.rs -sSf | sh -s -- -y --no-modify-path
 
-  export PATH=$RUSTUP_HOME/bin:$PATH
-  source $RUSTUP_HOME/env
+  # On Unix, rustup creates an env file. On Windows GitHub runners (MSYS bash),
+  # that file may not exist, so fall back to adding Cargo bin directly.
+  if [ -f "$CARGO_HOME/env" ]; then
+    # shellcheck disable=SC1090
+    source "$CARGO_HOME/env"
+  elif [ -f "$RUSTUP_HOME/env" ]; then
+    # shellcheck disable=SC1090
+    source "$RUSTUP_HOME/env"
+  else
+    export PATH="$CARGO_HOME/bin:$PATH"
+  fi
 
   # build and test rust
 
@@ -126,10 +135,20 @@ test_source_distribution() {
   git clone https://github.com/apache/parquet-testing.git parquet-testing
 
   python3 -m venv .venv
-  source .venv/bin/activate
-  python3 -m pip install -U pip
-  python3 -m pip install -U maturin
-  maturin develop
+  if [ -x ".venv/bin/python" ]; then
+    VENV_PYTHON=".venv/bin/python"
+  elif [ -x ".venv/Scripts/python.exe" ]; then
+    VENV_PYTHON=".venv/Scripts/python.exe"
+  elif [ -x ".venv/Scripts/python" ]; then
+    VENV_PYTHON=".venv/Scripts/python"
+  else
+    echo "Unable to find python executable in virtual environment"
+    exit 1
+  fi
+
+  "$VENV_PYTHON" -m pip install -U pip
+  "$VENV_PYTHON" -m pip install -U maturin
+  "$VENV_PYTHON" -m maturin develop
 
   #TODO: we should really run tests here as well
   #python3 -m pytest
diff --git a/docs/source/contributor-guide/ffi.rst b/docs/source/contributor-guide/ffi.rst
index 5006b0ca4..e0158e0a2 100644
--- a/docs/source/contributor-guide/ffi.rst
+++ b/docs/source/contributor-guide/ffi.rst
@@ -156,7 +156,7 @@ instead of mutating the container directly:
 
 .. code-block:: rust
 
-    #[pyclass(name = "Config", module = "datafusion", subclass, frozen)]
+    #[pyclass(from_py_object, name = "Config", module = "datafusion", subclass, frozen)]
     #[derive(Clone)]
     pub(crate) struct PyConfig {
         config: Arc<RwLock<ConfigOptions>>,
@@ -170,7 +170,7 @@ existing instance in place:
 
 .. code-block:: rust
 
-    #[pyclass(frozen, name = "SessionContext", module = "datafusion", subclass)]
+    #[pyclass(from_py_object, frozen, name = "SessionContext", module = "datafusion", subclass)]
     #[derive(Clone)]
     pub struct PySessionContext {
         pub ctx: SessionContext,
@@ -186,7 +186,7 @@ field updates:
 
     // TODO: This looks like this needs pyo3 tracking so leaving unfrozen for now
     #[derive(Debug, Clone)]
-    #[pyclass(name = "DataTypeMap", module = "datafusion.common", subclass)]
+    #[pyclass(from_py_object, name = "DataTypeMap", module = "datafusion.common", subclass)]
     pub struct DataTypeMap {
         #[pyo3(get, set)]
         pub arrow_type: PyDataType,
@@ -232,8 +232,11 @@ can then be turned into a ``ForeignTableProvider`` the associated code is:
 
 .. code-block:: rust
 
-    let capsule = capsule.downcast::<PyCapsule>()?;
-    let provider = unsafe { capsule.reference::<FFI_TableProvider>() };
+    let capsule = capsule.cast::<PyCapsule>()?;
+    let data: NonNull<FFI_TableProvider> = capsule
+        .pointer_checked(Some(name))?
+        .cast();
+    let codec = unsafe { data.as_ref() };
 
 By convention the ``datafusion-python`` library expects a Python object that has a
 ``TableProvider`` PyCapsule to have this capsule accessible by calling a function named
diff --git a/docs/source/user-guide/common-operations/aggregations.rst b/docs/source/user-guide/common-operations/aggregations.rst
index e458e5fcb..de24a2ba5 100644
--- a/docs/source/user-guide/common-operations/aggregations.rst
+++ b/docs/source/user-guide/common-operations/aggregations.rst
@@ -163,6 +163,168 @@ Suppose we want to find the speed values for only Pokemon that have low Attack v
         f.avg(col_speed, filter=col_attack < lit(50)).alias("Avg Speed Low Attack")])
 
 
+Grouping Sets
+-------------
+
+The default style of aggregation produces one row per group. Sometimes you want a single query to
+produce rows at multiple levels of detail — for example, totals per type *and* an overall grand
+total, or subtotals for every combination of two columns plus the individual column totals. Writing
+separate queries and concatenating them is tedious and runs the data multiple times. Grouping sets
+solve this by letting you specify several grouping levels in one pass.
+
+DataFusion supports three grouping set styles through the
+:py:class:`~datafusion.expr.GroupingSet` class:
+
+- :py:meth:`~datafusion.expr.GroupingSet.rollup` — hierarchical subtotals, like a drill-down report
+- :py:meth:`~datafusion.expr.GroupingSet.cube` — every possible subtotal combination, like a pivot table
+- :py:meth:`~datafusion.expr.GroupingSet.grouping_sets` — explicitly list exactly which grouping levels you want
+
+Because result rows come from different grouping levels, a column that is *not* part of a
+particular level will be ``null`` in that row. Use :py:func:`~datafusion.functions.grouping` to
+distinguish a real ``null`` in the data from one that means "this column was aggregated across."
+It returns ``0`` when the column is a grouping key for that row, and ``1`` when it is not.
+
+Rollup
+^^^^^^
+
+:py:meth:`~datafusion.expr.GroupingSet.rollup` creates a hierarchy. ``rollup(a, b)`` produces
+grouping sets ``(a, b)``, ``(a)``, and ``()`` — like nested subtotals in a report. This is useful
+when your columns have a natural hierarchy, such as region → city or type → subtype.
+
+Suppose we want to summarize Pokemon stats by ``Type 1`` with subtotals and a grand total. With
+the default aggregation style we would need two separate queries. With ``rollup`` we get it all at
+once:
+
+.. ipython:: python
+
+    from datafusion.expr import GroupingSet
+
+    df.aggregate(
+        [GroupingSet.rollup(col_type_1)],
+        [f.count(col_speed).alias("Count"),
+         f.avg(col_speed).alias("Avg Speed"),
+         f.max(col_speed).alias("Max Speed")]
+    ).sort(col_type_1.sort(ascending=True, nulls_first=True))
+
+The first row — where ``Type 1`` is ``null`` — is the grand total across all types. But how do you
+tell a grand-total ``null`` apart from a Pokemon that genuinely has no type? The
+:py:func:`~datafusion.functions.grouping` function returns ``0`` when the column is a grouping key
+for that row and ``1`` when it is aggregated across.
+
+.. note::
+
+    Due to an upstream DataFusion limitation
+    (`apache/datafusion#21411 <https://github.com/apache/datafusion/issues/21411>`_),
+    ``.alias()`` cannot be applied directly to a ``grouping()`` expression — it will raise an
+    error at execution time. Instead, use
+    :py:meth:`~datafusion.dataframe.DataFrame.with_column_renamed` on the result DataFrame to
+    give the column a readable name. Once the upstream issue is resolved, you will be able to
+    use ``.alias()`` directly and the workaround below will no longer be necessary.
+
+The raw column name generated by ``grouping()`` contains internal identifiers, so we use
+:py:meth:`~datafusion.dataframe.DataFrame.with_column_renamed` to clean it up:
+
+.. ipython:: python
+
+    result = df.aggregate(
+        [GroupingSet.rollup(col_type_1)],
+        [f.count(col_speed).alias("Count"),
+         f.avg(col_speed).alias("Avg Speed"),
+         f.grouping(col_type_1)]
+    )
+    for field in result.schema():
+        if field.name.startswith("grouping("):
+            result = result.with_column_renamed(field.name, "Is Total")
+    result.sort(col_type_1.sort(ascending=True, nulls_first=True))
+
+With two columns the hierarchy becomes more apparent. ``rollup(Type 1, Type 2)`` produces:
+
+- one row per ``(Type 1, Type 2)`` pair — the most detailed level
+- one row per ``Type 1`` — subtotals
+- one grand total row
+
+.. ipython:: python
+
+    df.aggregate(
+        [GroupingSet.rollup(col_type_1, col_type_2)],
+        [f.count(col_speed).alias("Count"),
+         f.avg(col_speed).alias("Avg Speed")]
+    ).sort(
+        col_type_1.sort(ascending=True, nulls_first=True),
+        col_type_2.sort(ascending=True, nulls_first=True)
+    )
+
+Cube
+^^^^
+
+:py:meth:`~datafusion.expr.GroupingSet.cube` produces every possible subset. ``cube(a, b)``
+produces grouping sets ``(a, b)``, ``(a)``, ``(b)``, and ``()`` — one more than ``rollup`` because
+it also includes ``(b)`` alone. This is useful when neither column is "above" the other in a
+hierarchy and you want all cross-tabulations.
+
+For our Pokemon data, ``cube(Type 1, Type 2)`` gives us stats broken down by the type pair,
+by ``Type 1`` alone, by ``Type 2`` alone, and a grand total — all in one query:
+
+.. ipython:: python
+
+    df.aggregate(
+        [GroupingSet.cube(col_type_1, col_type_2)],
+        [f.count(col_speed).alias("Count"),
+         f.avg(col_speed).alias("Avg Speed")]
+    ).sort(
+        col_type_1.sort(ascending=True, nulls_first=True),
+        col_type_2.sort(ascending=True, nulls_first=True)
+    )
+
+Compared to the ``rollup`` example above, notice the extra rows where ``Type 1`` is ``null`` but
+``Type 2`` has a value — those are the per-``Type 2`` subtotals that ``rollup`` does not include.
+
+Explicit Grouping Sets
+^^^^^^^^^^^^^^^^^^^^^^
+
+:py:meth:`~datafusion.expr.GroupingSet.grouping_sets` lets you list exactly which grouping levels
+you need when ``rollup`` or ``cube`` would produce too many or too few. Each argument is a list of
+columns forming one grouping set.
+
+For example, if we want only the per-``Type 1`` totals and per-``Type 2`` totals — but *not* the
+full ``(Type 1, Type 2)`` detail rows or the grand total — we can ask for exactly that:
+
+.. ipython:: python
+
+    df.aggregate(
+        [GroupingSet.grouping_sets([col_type_1], [col_type_2])],
+        [f.count(col_speed).alias("Count"),
+         f.avg(col_speed).alias("Avg Speed")]
+    ).sort(
+        col_type_1.sort(ascending=True, nulls_first=True),
+        col_type_2.sort(ascending=True, nulls_first=True)
+    )
+
+Each row belongs to exactly one grouping level. The :py:func:`~datafusion.functions.grouping`
+function tells you which level each row comes from:
+
+.. ipython:: python
+
+    result = df.aggregate(
+        [GroupingSet.grouping_sets([col_type_1], [col_type_2])],
+        [f.count(col_speed).alias("Count"),
+         f.avg(col_speed).alias("Avg Speed"),
+         f.grouping(col_type_1),
+         f.grouping(col_type_2)]
+    )
+    for field in result.schema():
+        if field.name.startswith("grouping("):
+            clean = field.name.split(".")[-1].rstrip(")")
+            result = result.with_column_renamed(field.name, f"grouping({clean})")
+    result.sort(
+        col_type_1.sort(ascending=True, nulls_first=True),
+        col_type_2.sort(ascending=True, nulls_first=True)
+    )
+
+Where ``grouping(Type 1)`` is ``0`` the row is a per-``Type 1`` total (and ``Type 2`` is ``null``).
+Where ``grouping(Type 2)`` is ``0`` the row is a per-``Type 2`` total (and ``Type 1`` is ``null``).
+
+
 Aggregate Functions
 -------------------
 
@@ -192,6 +354,7 @@ The available aggregate functions are:
     - :py:func:`datafusion.functions.stddev_pop`
     - :py:func:`datafusion.functions.var_samp`
     - :py:func:`datafusion.functions.var_pop`
+    - :py:func:`datafusion.functions.var_population`
 6. Linear Regression Functions
     - :py:func:`datafusion.functions.regr_count`
     - :py:func:`datafusion.functions.regr_slope`
@@ -208,9 +371,16 @@ The available aggregate functions are:
     - :py:func:`datafusion.functions.nth_value`
 8. String Functions
     - :py:func:`datafusion.functions.string_agg`
-9. Approximation Functions
+9. Percentile Functions
+    - :py:func:`datafusion.functions.percentile_cont`
+    - :py:func:`datafusion.functions.quantile_cont`
     - :py:func:`datafusion.functions.approx_distinct`
     - :py:func:`datafusion.functions.approx_median`
     - :py:func:`datafusion.functions.approx_percentile_cont`
     - :py:func:`datafusion.functions.approx_percentile_cont_with_weight`
+10. Grouping Set Functions
+    - :py:func:`datafusion.functions.grouping`
+    - :py:meth:`datafusion.expr.GroupingSet.rollup`
+    - :py:meth:`datafusion.expr.GroupingSet.cube`
+    - :py:meth:`datafusion.expr.GroupingSet.grouping_sets`
 
diff --git a/docs/source/user-guide/common-operations/joins.rst b/docs/source/user-guide/common-operations/joins.rst
index 1d9d70385..a289c9377 100644
--- a/docs/source/user-guide/common-operations/joins.rst
+++ b/docs/source/user-guide/common-operations/joins.rst
@@ -134,3 +134,36 @@ In contrast to the above example, if we wish to get both columns:
 .. ipython:: python
 
     left.join(right, "id", how="inner", coalesce_duplicate_keys=False)
+
+Disambiguating Columns with ``DataFrame.col()``
+------------------------------------------------
+
+When both DataFrames contain non-key columns with the same name, you can use
+:py:meth:`~datafusion.dataframe.DataFrame.col` on each DataFrame **before** the
+join to create fully qualified column references. These references can then be
+used in the join predicate and when selecting from the result.
+
+This is especially useful with :py:meth:`~datafusion.dataframe.DataFrame.join_on`,
+which accepts expression-based predicates.
+
+.. ipython:: python
+
+    left = ctx.from_pydict(
+        {
+            "id": [1, 2, 3],
+            "val": [10, 20, 30],
+        }
+    )
+
+    right = ctx.from_pydict(
+        {
+            "id": [1, 2, 3],
+            "val": [40, 50, 60],
+        }
+    )
+
+    joined = left.join_on(
+        right, left.col("id") == right.col("id"), how="inner"
+    )
+
+    joined.select(left.col("id"), left.col("val"), right.col("val"))
diff --git a/docs/source/user-guide/common-operations/windows.rst b/docs/source/user-guide/common-operations/windows.rst
index c8fdea8f4..d77881bcf 100644
--- a/docs/source/user-guide/common-operations/windows.rst
+++ b/docs/source/user-guide/common-operations/windows.rst
@@ -175,10 +175,7 @@ it's ``Type 2`` column that are null.
 Aggregate Functions
 -------------------
 
-You can use any :ref:`Aggregation Function<aggregation>` as a window function. Currently
-aggregate functions must use the deprecated
-:py:func:`datafusion.functions.window` API but this should be resolved in
-DataFusion 42.0 (`Issue Link <https://github.com/apache/datafusion-python/issues/833>`_). Here
+You can use any :ref:`Aggregation Function<aggregation>` as a window function. Here
 is an example that shows how to compare each pokemons’s attack power with the average attack
 power in its ``"Type 1"`` using the :py:func:`datafusion.functions.avg` function.
 
@@ -189,10 +186,12 @@ power in its ``"Type 1"`` using the :py:func:`datafusion.functions.avg` function
         col('"Name"'),
         col('"Attack"'),
         col('"Type 1"'),
-        f.window("avg", [col('"Attack"')])
-            .partition_by(col('"Type 1"'))
-            .build()
-            .alias("Average Attack"),
+        f.avg(col('"Attack"')).over(
+            Window(
+                window_frame=WindowFrame("rows", None, None),
+                partition_by=[col('"Type 1"')],
+            )
+        ).alias("Average Attack"),
     )
 
 Available Functions
diff --git a/docs/source/user-guide/data-sources.rst b/docs/source/user-guide/data-sources.rst
index 26f1303c4..48ff4c014 100644
--- a/docs/source/user-guide/data-sources.rst
+++ b/docs/source/user-guide/data-sources.rst
@@ -224,25 +224,37 @@ A common technique for organizing tables is using a three level hierarchical app
 supports this form of organizing using the :py:class:`~datafusion.catalog.Catalog`,
 :py:class:`~datafusion.catalog.Schema`, and :py:class:`~datafusion.catalog.Table`. By default,
 a :py:class:`~datafusion.context.SessionContext` comes with a single Catalog and a single Schema
-with the names ``datafusion`` and ``default``, respectively.
+with the names ``datafusion`` and ``public``, respectively.
 
 The default implementation uses an in-memory approach to the catalog and schema. We have support
-for adding additional in-memory catalogs and schemas. This can be done like in the following
+for adding additional in-memory catalogs and schemas. You can access tables registered in a schema 
+either through the Dataframe API or via sql commands. This can be done like in the following
 example:
 
 .. code-block:: python
 
+    import pyarrow as pa
     from datafusion.catalog import Catalog, Schema
+    from datafusion import SessionContext
+
+    ctx = SessionContext()
 
     my_catalog = Catalog.memory_catalog()
-    my_schema = Schema.memory_schema()
+    my_schema  = Schema.memory_schema()
+    my_catalog.register_schema('my_schema_name', my_schema)
+    ctx.register_catalog_provider('my_catalog_name', my_catalog)
 
-    my_catalog.register_schema("my_schema_name", my_schema)
+    # Create an in-memory table
+    table = pa.table({
+        'name': ['Bulbasaur', 'Charmander', 'Squirtle'],
+        'type': ['Grass',    'Fire',       'Water'],
+        'hp':   [45,          39,           44],
+    })
+    df = ctx.create_dataframe([table.to_batches()], name='pokemon')
 
-    ctx.register_catalog("my_catalog_name", my_catalog)
+    my_schema.register_table('pokemon', df)
 
-You could then register tables in ``my_schema`` and access them either through the DataFrame
-API or via sql commands such as ``"SELECT * from my_catalog_name.my_schema_name.my_table"``.
+    ctx.sql('SELECT * FROM my_catalog_name.my_schema_name.pokemon').show()
 
 User Defined Catalog and Schema
 -------------------------------
diff --git a/docs/source/user-guide/dataframe/execution-metrics.rst b/docs/source/user-guide/dataframe/execution-metrics.rst
new file mode 100644
index 000000000..764fa76ef
--- /dev/null
+++ b/docs/source/user-guide/dataframe/execution-metrics.rst
@@ -0,0 +1,215 @@
+.. Licensed to the Apache Software Foundation (ASF) under one
+.. or more contributor license agreements.  See the NOTICE file
+.. distributed with this work for additional information
+.. regarding copyright ownership.  The ASF licenses this file
+.. to you under the Apache License, Version 2.0 (the
+.. "License"); you may not use this file except in compliance
+.. with the License.  You may obtain a copy of the License at
+
+..   http://www.apache.org/licenses/LICENSE-2.0
+
+.. Unless required by applicable law or agreed to in writing,
+.. software distributed under the License is distributed on an
+.. "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+.. KIND, either express or implied.  See the License for the
+.. specific language governing permissions and limitations
+.. under the License.
+
+.. _execution_metrics:
+
+Execution Metrics
+=================
+
+Overview
+--------
+
+When DataFusion executes a query it compiles the logical plan into a tree of
+*physical plan operators* (e.g. ``FilterExec``, ``ProjectionExec``,
+``HashAggregateExec``). Each operator can record runtime statistics while it
+runs. These statistics are called **execution metrics**.
+
+Typical metrics include:
+
+- **output_rows** – number of rows produced by the operator
+- **elapsed_compute** – total CPU time (nanoseconds) spent inside the operator
+- **spill_count** – number of times the operator spilled data to disk
+- **spilled_bytes** – total bytes written to disk during spills
+- **spilled_rows** – total rows written to disk during spills
+
+Metrics are collected *per-partition*: DataFusion may execute each operator
+in parallel across several partitions. The convenience properties on
+:py:class:`~datafusion.MetricsSet` (e.g. ``output_rows``, ``elapsed_compute``)
+automatically sum the named metric across **all** partitions, giving a single
+aggregate value for the operator as a whole. You can also access the raw
+per-partition :py:class:`~datafusion.Metric` objects via
+:py:meth:`~datafusion.MetricsSet.metrics`.
+
+When Are Metrics Available?
+---------------------------
+
+Some operators (for example ``DataSourceExec``) eagerly create a
+:py:class:`~datafusion.MetricsSet` when the physical plan is built, so
+:py:meth:`~datafusion.ExecutionPlan.metrics` may return a set even before any
+rows have been processed.  However, metric **values** such as ``output_rows``
+are only meaningful **after** the DataFrame has been executed via one of the
+terminal operations:
+
+- :py:meth:`~datafusion.DataFrame.collect`
+- :py:meth:`~datafusion.DataFrame.collect_partitioned`
+- :py:meth:`~datafusion.DataFrame.execute_stream`
+  (metrics are available once the stream has been fully consumed)
+- :py:meth:`~datafusion.DataFrame.execute_stream_partitioned`
+  (metrics are available once all partition streams have been fully consumed)
+
+Before execution, metric values will be ``0`` or ``None``.
+
+.. note::
+
+   **display() does not populate metrics.**
+   When a DataFrame is displayed in a notebook (e.g. via ``display(df)`` or
+   automatic ``repr`` output), DataFusion runs a *limited* internal execution
+   to fetch preview rows.  This internal execution does **not** cache the
+   physical plan used, so :py:meth:`~datafusion.ExecutionPlan.collect_metrics`
+   will not reflect the display execution.  To access metrics you must call
+   one of the terminal operations listed above.
+
+If you call :py:meth:`~datafusion.DataFrame.collect` (or another terminal
+operation) multiple times on the same DataFrame, each call creates a fresh
+physical plan.  Metrics from :py:meth:`~datafusion.DataFrame.execution_plan`
+always reflect the **most recent** execution.
+
+Reading the Physical Plan Tree
+--------------------------------
+
+:py:meth:`~datafusion.DataFrame.execution_plan` returns the root
+:py:class:`~datafusion.ExecutionPlan` node of the physical plan tree. The tree
+mirrors the operator pipeline: the root is typically a projection or
+coalescing node; its children are filters, aggregates, scans, etc.
+
+The ``operator_name`` string returned by
+:py:meth:`~datafusion.ExecutionPlan.collect_metrics` is the *display* name of
+the node, for example ``"FilterExec: column1@0 > 1"``. This is the same string
+you would see when calling ``plan.display()``.
+
+Aggregated vs Per-Partition Metrics
+------------------------------------
+
+DataFusion executes each operator across one or more **partitions** in
+parallel.  The :py:class:`~datafusion.MetricsSet` convenience properties
+(``output_rows``, ``elapsed_compute``, etc.) automatically **sum** the named
+metric across all partitions, giving a single aggregate value.
+
+To inspect individual partitions — for example to detect data skew where one
+partition processes far more rows than others — iterate over the raw
+:py:class:`~datafusion.Metric` objects:
+
+.. code-block:: python
+
+    for metric in metrics_set.metrics():
+        print(f"  partition={metric.partition}  {metric.name}={metric.value}")
+
+The ``partition`` property is a 0-based index (``0``, ``1``, …) identifying
+which parallel slot processed this metric.  It is ``None`` for metrics that
+apply globally (not tied to a specific partition).
+
+Available Metrics
+-----------------
+
+The following metrics are directly accessible as properties on
+:py:class:`~datafusion.MetricsSet`:
+
+.. list-table::
+   :header-rows: 1
+   :widths: 25 75
+
+   * - Property
+     - Description
+   * - ``output_rows``
+     - Number of rows emitted by the operator (summed across partitions).
+   * - ``elapsed_compute``
+     - Wall-clock CPU time **in nanoseconds** spent inside the operator's
+       compute loop, excluding I/O wait.  Useful for identifying which
+       operators are most expensive (summed across partitions).
+   * - ``spill_count``
+     - Number of spill-to-disk events triggered by memory pressure.  This is
+       a unitless count of events, not a measure of data volume (summed across
+       partitions).
+   * - ``spilled_bytes``
+     - Total bytes written to disk during spill events (summed across
+       partitions).
+   * - ``spilled_rows``
+     - Total rows written to disk during spill events (summed across
+       partitions).
+
+Any metric not listed above can be accessed via
+:py:meth:`~datafusion.MetricsSet.sum_by_name`, or by iterating over the raw
+:py:class:`~datafusion.Metric` objects returned by
+:py:meth:`~datafusion.MetricsSet.metrics`.
+
+Labels
+------
+
+A :py:class:`~datafusion.Metric` may carry *labels*: key/value pairs that
+provide additional context.  Labels are operator-specific; most metrics have
+an empty label dict.
+
+Some operators tag their metrics with labels to distinguish variants.  For
+example, a ``HashAggregateExec`` may record separate ``output_rows`` metrics
+for intermediate and final output:
+
+.. code-block:: python
+
+    for metric in metrics_set.metrics():
+        print(metric.name, metric.labels())
+    # output_rows  {'output_type': 'final'}
+    # output_rows  {'output_type': 'intermediate'}
+
+When summing by name (via :py:attr:`~datafusion.MetricsSet.output_rows` or
+:py:meth:`~datafusion.MetricsSet.sum_by_name`), **all** metrics with that
+name are summed regardless of labels.  To filter by label, iterate over the
+raw :py:class:`~datafusion.Metric` objects directly.
+
+End-to-End Example
+------------------
+
+.. code-block:: python
+
+    from datafusion import SessionContext
+
+    ctx = SessionContext()
+    ctx.sql("CREATE TABLE sales AS VALUES (1, 100), (2, 200), (3, 50)")
+
+    df = ctx.sql("SELECT * FROM sales WHERE column1 > 1")
+
+    # Execute the query — this populates the metrics
+    results = df.collect()
+
+    # Retrieve the physical plan with metrics
+    plan = df.execution_plan()
+
+    # Walk every operator and print its metrics
+    for operator_name, ms in plan.collect_metrics():
+        if ms.output_rows is not None:
+            print(f"{operator_name}")
+            print(f"  output_rows    = {ms.output_rows}")
+            print(f"  elapsed_compute = {ms.elapsed_compute} ns")
+
+    # Access raw per-partition metrics
+    for operator_name, ms in plan.collect_metrics():
+        for metric in ms.metrics():
+            print(
+                f"  partition={metric.partition}  "
+                f"{metric.name}={metric.value}  "
+                f"labels={metric.labels()}"
+            )
+
+API Reference
+-------------
+
+- :py:class:`datafusion.ExecutionPlan` — physical plan node
+- :py:meth:`datafusion.ExecutionPlan.collect_metrics` — walk the tree and
+  return ``(operator_name, MetricsSet)`` pairs
+- :py:meth:`datafusion.ExecutionPlan.metrics` — return the
+  :py:class:`~datafusion.MetricsSet` for a single node
+- :py:class:`datafusion.MetricsSet` — aggregated metrics for one operator
+- :py:class:`datafusion.Metric` — a single per-partition metric value
diff --git a/docs/source/user-guide/dataframe/index.rst b/docs/source/user-guide/dataframe/index.rst
index 510bcbc68..8475a7bd7 100644
--- a/docs/source/user-guide/dataframe/index.rst
+++ b/docs/source/user-guide/dataframe/index.rst
@@ -365,7 +365,16 @@ DataFusion provides many built-in functions for data manipulation:
 For a complete list of available functions, see the :py:mod:`datafusion.functions` module documentation.
 
 
+Execution Metrics
+-----------------
+
+After executing a DataFrame (via ``collect()``, ``execute_stream()``, etc.),
+DataFusion populates per-operator runtime statistics such as row counts and
+compute time. See :doc:`execution-metrics` for a full explanation and
+worked example.
+
 .. toctree::
    :maxdepth: 1
 
    rendering
+   execution-metrics
diff --git a/docs/source/user-guide/dataframe/rendering.rst b/docs/source/user-guide/dataframe/rendering.rst
index 9dea948bb..dc61a422f 100644
--- a/docs/source/user-guide/dataframe/rendering.rst
+++ b/docs/source/user-guide/dataframe/rendering.rst
@@ -15,18 +15,18 @@
 .. specific language governing permissions and limitations
 .. under the License.
 
-HTML Rendering in Jupyter
-=========================
+DataFrame Rendering
+===================
 
-When working in Jupyter notebooks or other environments that support rich HTML display, 
-DataFusion DataFrames automatically render as nicely formatted HTML tables. This functionality
-is provided by the ``_repr_html_`` method, which is automatically called by Jupyter to provide
-a richer visualization than plain text output.
+DataFusion provides configurable rendering for DataFrames in both plain text and HTML
+formats. The ``datafusion.dataframe_formatter`` module controls how DataFrames are
+displayed in Jupyter notebooks (via ``_repr_html_``), in the terminal (via ``__repr__``),
+and anywhere else a string or HTML representation is needed.
 
-Basic HTML Rendering
---------------------
+Basic Rendering
+---------------
 
-In a Jupyter environment, simply displaying a DataFrame object will trigger HTML rendering:
+In a Jupyter environment, displaying a DataFrame triggers HTML rendering:
 
 .. code-block:: python
 
@@ -36,74 +36,117 @@ In a Jupyter environment, simply displaying a DataFrame object will trigger HTML
     # Explicit display also uses HTML rendering
     display(df)
 
-Customizing HTML Rendering
----------------------------
+In a terminal or when converting to string, plain text rendering is used:
+
+.. code-block:: python
 
-DataFusion provides extensive customization options for HTML table rendering through the
-``datafusion.html_formatter`` module.
+    # Plain text table output
+    print(df)
 
-Configuring the HTML Formatter
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+Configuring the Formatter
+-------------------------
 
-You can customize how DataFrames are rendered by configuring the formatter:
+You can customize how DataFrames are rendered by configuring the global formatter:
 
 .. code-block:: python
 
-    from datafusion.html_formatter import configure_formatter
-    
-    # Change the default styling
+    from datafusion.dataframe_formatter import configure_formatter
+
     configure_formatter(
-        max_cell_length=25,        # Maximum characters in a cell before truncation
-        max_width=1000,            # Maximum width in pixels
-        max_height=300,            # Maximum height in pixels
-        max_memory_bytes=2097152,  # Maximum memory for rendering (2MB)
-        min_rows=10,               # Minimum number of rows to display
-        max_rows=10,               # Maximum rows to display in __repr__
-        enable_cell_expansion=True,# Allow expanding truncated cells
-        custom_css=None,           # Additional custom CSS
+        max_cell_length=25,           # Maximum characters in a cell before truncation
+        max_width=1000,               # Maximum width in pixels (HTML only)
+        max_height=300,               # Maximum height in pixels (HTML only)
+        max_memory_bytes=2097152,     # Maximum memory for rendering (2MB)
+        min_rows=10,                  # Minimum number of rows to display
+        max_rows=10,                  # Maximum rows to display
+        enable_cell_expansion=True,   # Allow expanding truncated cells (HTML only)
+        custom_css=None,              # Additional custom CSS (HTML only)
         show_truncation_message=True, # Show message when data is truncated
-        style_provider=None,       # Custom styling provider
-        use_shared_styles=True     # Share styles across tables
+        style_provider=None,          # Custom styling provider (HTML only)
+        use_shared_styles=True,       # Share styles across tables (HTML only)
     )
 
 The formatter settings affect all DataFrames displayed after configuration.
 
 Custom Style Providers
------------------------
+----------------------
 
-For advanced styling needs, you can create a custom style provider:
+For HTML styling, you can create a custom style provider that implements the
+``StyleProvider`` protocol:
 
 .. code-block:: python
 
-    from datafusion.html_formatter import StyleProvider, configure_formatter
-    
-    class MyStyleProvider(StyleProvider):
-        def get_table_styles(self):
-            return {
-                "table": "border-collapse: collapse; width: 100%;",
-                "th": "background-color: #007bff; color: white; padding: 8px; text-align: left;",
-                "td": "border: 1px solid #ddd; padding: 8px;",
-                "tr:nth-child(even)": "background-color: #f2f2f2;",
-            }
-            
-        def get_value_styles(self, dtype, value):
-            """Return custom styles for specific values"""
-            if dtype == "float" and value < 0:
-                return "color: red;"
-            return None
-    
+    from datafusion.dataframe_formatter import configure_formatter
+
+    class MyStyleProvider:
+        def get_cell_style(self):
+            """Return CSS style string for table data cells."""
+            return "border: 1px solid #ddd; padding: 8px; text-align: left;"
+
+        def get_header_style(self):
+            """Return CSS style string for table header cells."""
+            return (
+                "background-color: #007bff; color: white; "
+                "padding: 8px; text-align: left;"
+            )
+
     # Apply the custom style provider
     configure_formatter(style_provider=MyStyleProvider())
 
+Custom Cell Formatters
+----------------------
+
+You can register custom formatters for specific Python types. A cell formatter is any
+callable that takes a value and returns a string:
+
+.. code-block:: python
+
+    from datafusion.dataframe_formatter import get_formatter
+
+    formatter = get_formatter()
+
+    # Format floats to 2 decimal places
+    formatter.register_formatter(float, lambda v: f"{v:.2f}")
+
+    # Format dates in a custom way
+    from datetime import date
+    formatter.register_formatter(date, lambda v: v.strftime("%B %d, %Y"))
+
+Custom Cell and Header Builders
+-------------------------------
+
+For full control over the HTML of individual cells or headers, you can set custom
+builder functions:
+
+.. code-block:: python
+
+    from datafusion.dataframe_formatter import get_formatter
+
+    formatter = get_formatter()
+
+    # Custom cell builder receives (value, row, col, table_id) and returns HTML
+    def my_cell_builder(value, row, col, table_id):
+        color = "red" if isinstance(value, (int, float)) and value < 0 else "black"
+        return f"<td style='color: {color}; padding: 8px;'>{value}</td>"
+
+    formatter.set_custom_cell_builder(my_cell_builder)
+
+    # Custom header builder receives a schema field and returns HTML
+    def my_header_builder(field):
+        return f"<th style='background: #333; color: white; padding: 8px;'>{field.name}</th>"
+
+    formatter.set_custom_header_builder(my_header_builder)
+
 Performance Optimization with Shared Styles
 --------------------------------------------
 
-The ``use_shared_styles`` parameter (enabled by default) optimizes performance when displaying 
-multiple DataFrames in notebook environments:
+The ``use_shared_styles`` parameter (enabled by default) optimizes performance when
+displaying multiple DataFrames in notebook environments:
 
 .. code-block:: python
 
-    from datafusion.html_formatter import StyleProvider, configure_formatter
+    from datafusion.dataframe_formatter import configure_formatter
+
     # Default: Use shared styles (recommended for notebooks)
     configure_formatter(use_shared_styles=True)
 
@@ -111,76 +154,48 @@ multiple DataFrames in notebook environments:
     configure_formatter(use_shared_styles=False)
 
 When ``use_shared_styles=True``:
+
 - CSS styles and JavaScript are included only once per notebook session
 - This reduces HTML output size and prevents style duplication
 - Improves rendering performance with many DataFrames
 - Applies consistent styling across all DataFrames
 
-Creating a Custom Formatter
-----------------------------
+Working with the Formatter Directly
+------------------------------------
 
-For complete control over rendering, you can implement a custom formatter:
+You can use ``get_formatter()`` and ``set_formatter()`` for direct access to the global
+formatter instance:
 
 .. code-block:: python
 
-    from datafusion.html_formatter import Formatter, get_formatter
-    
-    class MyFormatter(Formatter):
-        def format_html(self, batches, schema, has_more=False, table_uuid=None):
-            # Create your custom HTML here
-            html = "<div class='my-custom-table'>"
-            # ... formatting logic ...
-            html += "</div>"
-            return html
-    
-    # Set as the global formatter
-    configure_formatter(formatter_class=MyFormatter)
-    
-    # Or use the formatter just for specific operations
+    from datafusion.dataframe_formatter import (
+        DataFrameHtmlFormatter,
+        get_formatter,
+        set_formatter,
+    )
+
+    # Get and modify the current formatter
     formatter = get_formatter()
-    custom_html = formatter.format_html(batches, schema)
+    print(formatter.max_rows)
+    print(formatter.max_cell_length)
 
-Managing Formatters
--------------------
+    # Create and set a fully custom formatter
+    custom_formatter = DataFrameHtmlFormatter(
+        max_cell_length=50,
+        max_rows=20,
+        enable_cell_expansion=False,
+    )
+    set_formatter(custom_formatter)
 
 Reset to default formatting:
 
 .. code-block:: python
 
-    from datafusion.html_formatter import reset_formatter
-    
+    from datafusion.dataframe_formatter import reset_formatter
+
     # Reset to default settings
     reset_formatter()
 
-Get the current formatter settings:
-
-.. code-block:: python
-
-    from datafusion.html_formatter import get_formatter
-    
-    formatter = get_formatter()
-    print(formatter.max_rows)
-    print(formatter.theme)
-
-Contextual Formatting
-----------------------
-
-You can also use a context manager to temporarily change formatting settings:
-
-.. code-block:: python
-
-    from datafusion.html_formatter import formatting_context
-    
-    # Default formatting
-    df.show()
-    
-    # Temporarily use different formatting
-    with formatting_context(max_rows=100, theme="dark"):
-        df.show()  # Will use the temporary settings
-    
-    # Back to default formatting
-    df.show()
-
 Memory and Display Controls
 ---------------------------
 
@@ -188,10 +203,12 @@ You can control how much data is displayed and how much memory is used for rende
 
 .. code-block:: python
 
+    from datafusion.dataframe_formatter import configure_formatter
+
     configure_formatter(
         max_memory_bytes=4 * 1024 * 1024,  # 4MB maximum memory for display
         min_rows=20,                       # Always show at least 20 rows
-        max_rows=50                        # Show up to 50 rows in output
+        max_rows=50,                       # Show up to 50 rows in output
     )
 
 These parameters help balance comprehensive data display against performance considerations.
@@ -216,7 +233,7 @@ Additional Resources
 * :doc:`../io/index` - I/O Guide for reading data from various sources
 * :doc:`../data-sources` - Comprehensive data sources guide
 * :ref:`io_csv` - CSV file reading
-* :ref:`io_parquet` - Parquet file reading  
+* :ref:`io_parquet` - Parquet file reading
 * :ref:`io_json` - JSON file reading
 * :ref:`io_avro` - Avro file reading
 * :ref:`io_custom_table_provider` - Custom table providers
diff --git a/docs/source/user-guide/upgrade-guides.rst b/docs/source/user-guide/upgrade-guides.rst
index a77f60776..2ac7f7703 100644
--- a/docs/source/user-guide/upgrade-guides.rst
+++ b/docs/source/user-guide/upgrade-guides.rst
@@ -18,6 +18,27 @@
 Upgrade Guides
 ==============
 
+DataFusion 53.0.0
+-----------------
+
+This version includes an upgraded version of ``pyo3``, which changed the way to extract an FFI
+object. Example:
+
+Before:
+
+.. code-block:: rust
+
+    let codec = unsafe { capsule.reference::<FFI_LogicalExtensionCodec>() };
+
+Now:
+
+.. code-block:: rust
+
+    let data: NonNull<FFI_LogicalExtensionCodec> = capsule
+        .pointer_checked(Some(c_str!("datafusion_logical_extension_codec")))?
+        .cast();
+    let codec = unsafe { data.as_ref() };
+
 DataFusion 52.0.0
 -----------------
 
@@ -31,8 +52,10 @@ parameter, which is a Python object that can be used to extract the
 ``FFI_LogicalExtensionCodec`` that is necessary.
 
 A complete example can be found in the `FFI example <https://github.com/apache/datafusion-python/tree/main/examples/datafusion-ffi-example>`_.
-Your methods need to be updated to take an additional parameter like in this
-example.
+Your FFI hook methods — ``__datafusion_catalog_provider__``,
+``__datafusion_schema_provider__``, ``__datafusion_table_provider__``, and
+``__datafusion_table_function__`` — need to be updated to accept an additional
+``session: Bound<PyAny>`` parameter, as shown in this example.
 
 .. code-block:: rust
 
diff --git a/examples/datafusion-ffi-example/.cargo/config.toml b/examples/datafusion-ffi-example/.cargo/config.toml
deleted file mode 100644
index af951327f..000000000
--- a/examples/datafusion-ffi-example/.cargo/config.toml
+++ /dev/null
@@ -1,5 +0,0 @@
-[target.x86_64-apple-darwin]
-rustflags = ["-C", "link-arg=-undefined", "-C", "link-arg=dynamic_lookup"]
-
-[target.aarch64-apple-darwin]
-rustflags = ["-C", "link-arg=-undefined", "-C", "link-arg=dynamic_lookup"]
diff --git a/examples/datafusion-ffi-example/Cargo.lock b/examples/datafusion-ffi-example/Cargo.lock
deleted file mode 100644
index 02aa7d9d9..000000000
--- a/examples/datafusion-ffi-example/Cargo.lock
+++ /dev/null
@@ -1,3129 +0,0 @@
-# This file is automatically @generated by Cargo.
-# It is not intended for manual editing.
-version = 4
-
-[[package]]
-name = "abi_stable"
-version = "0.11.3"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "69d6512d3eb05ffe5004c59c206de7f99c34951504056ce23fc953842f12c445"
-dependencies = [
- "abi_stable_derive",
- "abi_stable_shared",
- "const_panic",
- "core_extensions",
- "crossbeam-channel",
- "generational-arena",
- "libloading",
- "lock_api",
- "parking_lot",
- "paste",
- "repr_offset",
- "rustc_version",
- "serde",
- "serde_derive",
- "serde_json",
-]
-
-[[package]]
-name = "abi_stable_derive"
-version = "0.11.3"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "d7178468b407a4ee10e881bc7a328a65e739f0863615cca4429d43916b05e898"
-dependencies = [
- "abi_stable_shared",
- "as_derive_utils",
- "core_extensions",
- "proc-macro2",
- "quote",
- "rustc_version",
- "syn 1.0.109",
- "typed-arena",
-]
-
-[[package]]
-name = "abi_stable_shared"
-version = "0.11.0"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "b2b5df7688c123e63f4d4d649cba63f2967ba7f7861b1664fca3f77d3dad2b63"
-dependencies = [
- "core_extensions",
-]
-
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diff --git a/examples/datafusion-ffi-example/Cargo.toml b/examples/datafusion-ffi-example/Cargo.toml
index 15c11ea49..178dce9f9 100644
--- a/examples/datafusion-ffi-example/Cargo.toml
+++ b/examples/datafusion-ffi-example/Cargo.toml
@@ -17,29 +17,36 @@
 
 [package]
 name = "datafusion-ffi-example"
-version = "0.2.0"
-edition = "2024"
+version.workspace = true
+edition.workspace = true
+license.workspace = true
+description.workspace = true
+homepage.workspace = true
+repository.workspace = true
+publish = false
 
 [dependencies]
-datafusion-catalog = { version = "52", default-features = false }
-datafusion-common = { version = "52", default-features = false }
-datafusion-functions-aggregate = { version = "52" }
-datafusion-functions-window = { version = "52" }
-datafusion-expr = { version = "52" }
-datafusion-ffi = { version = "52" }
+datafusion-catalog = { workspace = true, default-features = false }
+datafusion-common = { workspace = true, default-features = false }
+datafusion-functions-aggregate = { workspace = true }
+datafusion-functions-window = { workspace = true }
+datafusion-expr = { workspace = true }
+datafusion-ffi = { workspace = true }
 
-pyo3 = { version = "0.26", features = [
+arrow = { workspace = true }
+arrow-array = { workspace = true }
+arrow-schema = { workspace = true }
+async-trait = { workspace = true }
+datafusion-python-util.workspace = true
+pyo3 = { workspace = true, features = [
   "extension-module",
   "abi3",
-  "abi3-py39",
+  "abi3-py310",
 ] }
-arrow = { version = "57" }
-arrow-array = { version = "57" }
-arrow-schema = { version = "57" }
-async-trait = "0.1.89"
+pyo3-log = { workspace = true }
 
 [build-dependencies]
-pyo3-build-config = "0.26"
+pyo3-build-config = { workspace = true }
 
 [lib]
 name = "datafusion_ffi_example"
diff --git a/examples/datafusion-ffi-example/python/tests/_test_config.py b/examples/datafusion-ffi-example/python/tests/_test_config.py
new file mode 100644
index 000000000..24d527921
--- /dev/null
+++ b/examples/datafusion-ffi-example/python/tests/_test_config.py
@@ -0,0 +1,35 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+from datafusion import SessionConfig, SessionContext
+from datafusion_ffi_example import MyConfig
+
+
+def test_config_extension_show_set():
+    config = MyConfig()
+    config = SessionConfig(
+        {"datafusion.catalog.information_schema": "true"}
+    ).with_extension(config)
+    config.set("my_config.baz_count", "42")
+    ctx = SessionContext(config)
+
+    result = ctx.sql("SHOW my_config.baz_count;").collect()
+    assert result[0][1][0].as_py() == "42"
+
+    ctx.sql("SET my_config.baz_count=1;")
+    result = ctx.sql("SHOW my_config.baz_count;").collect()
+    assert result[0][1][0].as_py() == "1"
diff --git a/examples/datafusion-ffi-example/python/tests/_test_table_provider_factory.py b/examples/datafusion-ffi-example/python/tests/_test_table_provider_factory.py
new file mode 100644
index 000000000..b1e94ec73
--- /dev/null
+++ b/examples/datafusion-ffi-example/python/tests/_test_table_provider_factory.py
@@ -0,0 +1,41 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+from __future__ import annotations
+
+from datafusion import SessionContext
+from datafusion_ffi_example import MyTableProviderFactory
+
+
+def test_table_provider_factory_ffi() -> None:
+    ctx = SessionContext()
+    table = MyTableProviderFactory()
+
+    ctx.register_table_factory("MY_FORMAT", table)
+
+    # Create a new external table
+    ctx.sql("""
+        CREATE EXTERNAL TABLE
+        foo
+        STORED AS my_format
+        LOCATION '';
+    """).collect()
+
+    # Query the pre-populated table
+    result = ctx.sql("SELECT * FROM foo;").collect()
+    assert len(result) == 2
+    assert result[0].num_columns == 2
diff --git a/examples/datafusion-ffi-example/python/tests/conftest.py b/examples/datafusion-ffi-example/python/tests/conftest.py
new file mode 100644
index 000000000..68f8057af
--- /dev/null
+++ b/examples/datafusion-ffi-example/python/tests/conftest.py
@@ -0,0 +1,42 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+from __future__ import annotations
+
+import logging
+from typing import TYPE_CHECKING
+
+import pytest
+
+if TYPE_CHECKING:
+    from collections.abc import Generator
+    from typing import Any
+
+
+class _FailOnWarning(logging.Handler):
+    def emit(self, record: logging.LogRecord) -> None:
+        if record.levelno >= logging.WARNING:
+            err = f"Unexpected log warning from '{record.name}': {self.format(record)}"
+            raise AssertionError(err)
+
+
+@pytest.fixture(autouse=True)
+def fail_on_log_warnings() -> Generator[None, Any, None]:
+    handler = _FailOnWarning()
+    logging.root.addHandler(handler)
+    yield
+    logging.root.removeHandler(handler)
diff --git a/examples/datafusion-ffi-example/src/aggregate_udf.rs b/examples/datafusion-ffi-example/src/aggregate_udf.rs
index 276ad0275..d5343ff91 100644
--- a/examples/datafusion-ffi-example/src/aggregate_udf.rs
+++ b/examples/datafusion-ffi-example/src/aggregate_udf.rs
@@ -27,7 +27,12 @@ use datafusion_functions_aggregate::sum::Sum;
 use pyo3::types::PyCapsule;
 use pyo3::{Bound, PyResult, Python, pyclass, pymethods};
 
-#[pyclass(name = "MySumUDF", module = "datafusion_ffi_example", subclass)]
+#[pyclass(
+    from_py_object,
+    name = "MySumUDF",
+    module = "datafusion_ffi_example",
+    subclass
+)]
 #[derive(Debug, Clone, Eq, PartialEq, Hash)]
 pub(crate) struct MySumUDF {
     inner: Arc<Sum>,
diff --git a/examples/datafusion-ffi-example/src/catalog_provider.rs b/examples/datafusion-ffi-example/src/catalog_provider.rs
index 3dc111cbc..bd5da1e4d 100644
--- a/examples/datafusion-ffi-example/src/catalog_provider.rs
+++ b/examples/datafusion-ffi-example/src/catalog_provider.rs
@@ -29,11 +29,10 @@ use datafusion_common::error::{DataFusionError, Result};
 use datafusion_ffi::catalog_provider::FFI_CatalogProvider;
 use datafusion_ffi::catalog_provider_list::FFI_CatalogProviderList;
 use datafusion_ffi::schema_provider::FFI_SchemaProvider;
+use datafusion_python_util::ffi_logical_codec_from_pycapsule;
 use pyo3::types::PyCapsule;
 use pyo3::{Bound, PyAny, PyResult, Python, pyclass, pymethods};
 
-use crate::utils::ffi_logical_codec_from_pycapsule;
-
 pub fn my_table() -> Arc<dyn TableProvider + 'static> {
     use arrow::datatypes::{DataType, Field};
     use datafusion_common::record_batch;
@@ -60,6 +59,7 @@ pub fn my_table() -> Arc<dyn TableProvider + 'static> {
 }
 
 #[pyclass(
+    skip_from_py_object,
     name = "FixedSchemaProvider",
     module = "datafusion_ffi_example",
     subclass
@@ -138,6 +138,7 @@ impl SchemaProvider for FixedSchemaProvider {
 /// This catalog provider is intended only for unit tests. It prepopulates with one
 /// schema and only allows for schemas named after four types of fruit.
 #[pyclass(
+    skip_from_py_object,
     name = "MyCatalogProvider",
     module = "datafusion_ffi_example",
     subclass
@@ -208,6 +209,7 @@ impl MyCatalogProvider {
 /// This catalog provider list is intended only for unit tests.
 /// It pre-populates with a single catalog.
 #[pyclass(
+    skip_from_py_object,
     name = "MyCatalogProviderList",
     module = "datafusion_ffi_example",
     subclass
diff --git a/examples/datafusion-ffi-example/src/config.rs b/examples/datafusion-ffi-example/src/config.rs
new file mode 100644
index 000000000..6cdb8aa83
--- /dev/null
+++ b/examples/datafusion-ffi-example/src/config.rs
@@ -0,0 +1,133 @@
+// Licensed to the Apache Software Foundation (ASF) under one
+// or more contributor license agreements.  See the NOTICE file
+// distributed with this work for additional information
+// regarding copyright ownership.  The ASF licenses this file
+// to you under the Apache License, Version 2.0 (the
+// "License"); you may not use this file except in compliance
+// with the License.  You may obtain a copy of the License at
+//
+//   http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing,
+// software distributed under the License is distributed on an
+// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+// KIND, either express or implied.  See the License for the
+// specific language governing permissions and limitations
+// under the License.
+
+use std::any::Any;
+
+use datafusion_common::config::{
+    ConfigEntry, ConfigExtension, ConfigField, ExtensionOptions, Visit,
+};
+use datafusion_common::{DataFusionError, config_err};
+use datafusion_ffi::config::extension_options::FFI_ExtensionOptions;
+use pyo3::exceptions::PyRuntimeError;
+use pyo3::types::PyCapsule;
+use pyo3::{Bound, PyResult, Python, pyclass, pymethods};
+
+/// My own config options.
+#[pyclass(
+    from_py_object,
+    name = "MyConfig",
+    module = "datafusion_ffi_example",
+    subclass
+)]
+#[derive(Clone, Debug)]
+pub struct MyConfig {
+    /// Should "foo" be replaced by "bar"?
+    pub foo_to_bar: bool,
+
+    /// How many "baz" should be created?
+    pub baz_count: usize,
+}
+
+#[pymethods]
+impl MyConfig {
+    #[new]
+    fn new() -> Self {
+        Self::default()
+    }
+
+    fn __datafusion_extension_options__<'py>(
+        &self,
+        py: Python<'py>,
+    ) -> PyResult<Bound<'py, PyCapsule>> {
+        let name = cr"datafusion_extension_options".into();
+
+        let mut config = FFI_ExtensionOptions::default();
+        config
+            .add_config(self)
+            .map_err(|e| PyRuntimeError::new_err(e.to_string()))?;
+
+        PyCapsule::new(py, config, Some(name))
+    }
+}
+
+impl Default for MyConfig {
+    fn default() -> Self {
+        Self {
+            foo_to_bar: true,
+            baz_count: 1337,
+        }
+    }
+}
+
+impl ConfigExtension for MyConfig {
+    const PREFIX: &'static str = "my_config";
+}
+
+impl ExtensionOptions for MyConfig {
+    fn as_any(&self) -> &dyn Any {
+        self
+    }
+
+    fn as_any_mut(&mut self) -> &mut dyn Any {
+        self
+    }
+
+    fn cloned(&self) -> Box<dyn ExtensionOptions> {
+        Box::new(self.clone())
+    }
+
+    fn set(&mut self, key: &str, value: &str) -> datafusion_common::Result<()> {
+        datafusion_common::config::ConfigField::set(self, key, value)
+    }
+
+    fn entries(&self) -> Vec<ConfigEntry> {
+        vec![
+            ConfigEntry {
+                key: "foo_to_bar".to_owned(),
+                value: Some(format!("{}", self.foo_to_bar)),
+                description: "foo to bar",
+            },
+            ConfigEntry {
+                key: "baz_count".to_owned(),
+                value: Some(format!("{}", self.baz_count)),
+                description: "baz count",
+            },
+        ]
+    }
+}
+
+impl ConfigField for MyConfig {
+    fn visit<V: Visit>(&self, v: &mut V, _key: &str, _description: &'static str) {
+        let key = "foo_to_bar";
+        let desc = "foo to bar";
+        self.foo_to_bar.visit(v, key, desc);
+
+        let key = "baz_count";
+        let desc = "baz count";
+        self.baz_count.visit(v, key, desc);
+    }
+
+    fn set(&mut self, key: &str, value: &str) -> Result<(), DataFusionError> {
+        let (key, rem) = key.split_once('.').unwrap_or((key, ""));
+        match key {
+            "foo_to_bar" => self.foo_to_bar.set(rem, value.as_ref()),
+            "baz_count" => self.baz_count.set(rem, value.as_ref()),
+
+            _ => config_err!("Config value \"{}\" not found on MyConfig", key),
+        }
+    }
+}
diff --git a/examples/datafusion-ffi-example/src/lib.rs b/examples/datafusion-ffi-example/src/lib.rs
index 6c64c9fe5..e708c49cc 100644
--- a/examples/datafusion-ffi-example/src/lib.rs
+++ b/examples/datafusion-ffi-example/src/lib.rs
@@ -19,22 +19,28 @@ use pyo3::prelude::*;
 
 use crate::aggregate_udf::MySumUDF;
 use crate::catalog_provider::{FixedSchemaProvider, MyCatalogProvider, MyCatalogProviderList};
+use crate::config::MyConfig;
 use crate::scalar_udf::IsNullUDF;
 use crate::table_function::MyTableFunction;
 use crate::table_provider::MyTableProvider;
+use crate::table_provider_factory::MyTableProviderFactory;
 use crate::window_udf::MyRankUDF;
 
 pub(crate) mod aggregate_udf;
 pub(crate) mod catalog_provider;
+pub(crate) mod config;
 pub(crate) mod scalar_udf;
 pub(crate) mod table_function;
 pub(crate) mod table_provider;
-pub(crate) mod utils;
+pub(crate) mod table_provider_factory;
 pub(crate) mod window_udf;
 
 #[pymodule]
 fn datafusion_ffi_example(m: &Bound<'_, PyModule>) -> PyResult<()> {
+    pyo3_log::init();
+
     m.add_class::<MyTableProvider>()?;
+    m.add_class::<MyTableProviderFactory>()?;
     m.add_class::<MyTableFunction>()?;
     m.add_class::<MyCatalogProvider>()?;
     m.add_class::<MyCatalogProviderList>()?;
@@ -42,5 +48,6 @@ fn datafusion_ffi_example(m: &Bound<'_, PyModule>) -> PyResult<()> {
     m.add_class::<IsNullUDF>()?;
     m.add_class::<MySumUDF>()?;
     m.add_class::<MyRankUDF>()?;
+    m.add_class::<MyConfig>()?;
     Ok(())
 }
diff --git a/examples/datafusion-ffi-example/src/scalar_udf.rs b/examples/datafusion-ffi-example/src/scalar_udf.rs
index 089d32d93..374924781 100644
--- a/examples/datafusion-ffi-example/src/scalar_udf.rs
+++ b/examples/datafusion-ffi-example/src/scalar_udf.rs
@@ -30,7 +30,12 @@ use datafusion_ffi::udf::FFI_ScalarUDF;
 use pyo3::types::PyCapsule;
 use pyo3::{Bound, PyResult, Python, pyclass, pymethods};
 
-#[pyclass(name = "IsNullUDF", module = "datafusion_ffi_example", subclass)]
+#[pyclass(
+    from_py_object,
+    name = "IsNullUDF",
+    module = "datafusion_ffi_example",
+    subclass
+)]
 #[derive(Debug, Clone, PartialEq, Eq, Hash)]
 pub(crate) struct IsNullUDF {
     signature: Signature,
diff --git a/examples/datafusion-ffi-example/src/table_function.rs b/examples/datafusion-ffi-example/src/table_function.rs
index 1cddb9e35..79c13f64d 100644
--- a/examples/datafusion-ffi-example/src/table_function.rs
+++ b/examples/datafusion-ffi-example/src/table_function.rs
@@ -21,13 +21,18 @@ use datafusion_catalog::{TableFunctionImpl, TableProvider};
 use datafusion_common::error::Result as DataFusionResult;
 use datafusion_expr::Expr;
 use datafusion_ffi::udtf::FFI_TableFunction;
+use datafusion_python_util::ffi_logical_codec_from_pycapsule;
 use pyo3::types::PyCapsule;
 use pyo3::{Bound, PyAny, PyResult, Python, pyclass, pymethods};
 
 use crate::table_provider::MyTableProvider;
-use crate::utils::ffi_logical_codec_from_pycapsule;
 
-#[pyclass(name = "MyTableFunction", module = "datafusion_ffi_example", subclass)]
+#[pyclass(
+    from_py_object,
+    name = "MyTableFunction",
+    module = "datafusion_ffi_example",
+    subclass
+)]
 #[derive(Debug, Clone)]
 pub(crate) struct MyTableFunction {}
 
diff --git a/examples/datafusion-ffi-example/src/table_provider.rs b/examples/datafusion-ffi-example/src/table_provider.rs
index 887b2c671..358ef7402 100644
--- a/examples/datafusion-ffi-example/src/table_provider.rs
+++ b/examples/datafusion-ffi-example/src/table_provider.rs
@@ -22,15 +22,19 @@ use arrow_schema::{DataType, Field, Schema};
 use datafusion_catalog::MemTable;
 use datafusion_common::error::{DataFusionError, Result as DataFusionResult};
 use datafusion_ffi::table_provider::FFI_TableProvider;
+use datafusion_python_util::ffi_logical_codec_from_pycapsule;
 use pyo3::exceptions::PyRuntimeError;
 use pyo3::types::PyCapsule;
 use pyo3::{Bound, PyAny, PyResult, Python, pyclass, pymethods};
 
-use crate::utils::ffi_logical_codec_from_pycapsule;
-
 /// In order to provide a test that demonstrates different sized record batches,
 /// the first batch will have num_rows, the second batch num_rows+1, and so on.
-#[pyclass(name = "MyTableProvider", module = "datafusion_ffi_example", subclass)]
+#[pyclass(
+    from_py_object,
+    name = "MyTableProvider",
+    module = "datafusion_ffi_example",
+    subclass
+)]
 #[derive(Clone)]
 pub(crate) struct MyTableProvider {
     num_cols: usize,
diff --git a/examples/datafusion-ffi-example/src/table_provider_factory.rs b/examples/datafusion-ffi-example/src/table_provider_factory.rs
new file mode 100644
index 000000000..53248a905
--- /dev/null
+++ b/examples/datafusion-ffi-example/src/table_provider_factory.rs
@@ -0,0 +1,87 @@
+// Licensed to the Apache Software Foundation (ASF) under one
+// or more contributor license agreements.  See the NOTICE file
+// distributed with this work for additional information
+// regarding copyright ownership.  The ASF licenses this file
+// to you under the Apache License, Version 2.0 (the
+// "License"); you may not use this file except in compliance
+// with the License.  You may obtain a copy of the License at
+//
+//   http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing,
+// software distributed under the License is distributed on an
+// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+// KIND, either express or implied.  See the License for the
+// specific language governing permissions and limitations
+// under the License.
+
+use std::sync::Arc;
+
+use async_trait::async_trait;
+use datafusion_catalog::{Session, TableProvider, TableProviderFactory};
+use datafusion_common::error::Result as DataFusionResult;
+use datafusion_expr::CreateExternalTable;
+use datafusion_ffi::table_provider_factory::FFI_TableProviderFactory;
+use datafusion_python_util::ffi_logical_codec_from_pycapsule;
+use pyo3::types::PyCapsule;
+use pyo3::{Bound, PyAny, PyResult, Python, pyclass, pymethods};
+
+use crate::catalog_provider;
+
+#[derive(Debug)]
+pub(crate) struct ExampleTableProviderFactory {}
+
+impl ExampleTableProviderFactory {
+    fn new() -> Self {
+        Self {}
+    }
+}
+
+#[async_trait]
+impl TableProviderFactory for ExampleTableProviderFactory {
+    async fn create(
+        &self,
+        _state: &dyn Session,
+        _cmd: &CreateExternalTable,
+    ) -> DataFusionResult<Arc<dyn TableProvider>> {
+        Ok(catalog_provider::my_table())
+    }
+}
+
+#[pyclass(
+    name = "MyTableProviderFactory",
+    module = "datafusion_ffi_example",
+    subclass
+)]
+#[derive(Debug)]
+pub struct MyTableProviderFactory {
+    inner: Arc<ExampleTableProviderFactory>,
+}
+
+impl Default for MyTableProviderFactory {
+    fn default() -> Self {
+        let inner = Arc::new(ExampleTableProviderFactory::new());
+        Self { inner }
+    }
+}
+
+#[pymethods]
+impl MyTableProviderFactory {
+    #[new]
+    pub fn new() -> Self {
+        Self::default()
+    }
+
+    pub fn __datafusion_table_provider_factory__<'py>(
+        &self,
+        py: Python<'py>,
+        codec: Bound<PyAny>,
+    ) -> PyResult<Bound<'py, PyCapsule>> {
+        let name = cr"datafusion_table_provider_factory".into();
+        let codec = ffi_logical_codec_from_pycapsule(codec)?;
+        let factory = Arc::clone(&self.inner) as Arc<dyn TableProviderFactory + Send>;
+        let factory = FFI_TableProviderFactory::new_with_ffi_codec(factory, None, codec);
+
+        PyCapsule::new(py, factory, Some(name))
+    }
+}
diff --git a/examples/datafusion-ffi-example/src/utils.rs b/examples/datafusion-ffi-example/src/utils.rs
deleted file mode 100644
index a01d3fe27..000000000
--- a/examples/datafusion-ffi-example/src/utils.rs
+++ /dev/null
@@ -1,58 +0,0 @@
-// Licensed to the Apache Software Foundation (ASF) under one
-// or more contributor license agreements.  See the NOTICE file
-// distributed with this work for additional information
-// regarding copyright ownership.  The ASF licenses this file
-// to you under the Apache License, Version 2.0 (the
-// "License"); you may not use this file except in compliance
-// with the License.  You may obtain a copy of the License at
-//
-//   http://www.apache.org/licenses/LICENSE-2.0
-//
-// Unless required by applicable law or agreed to in writing,
-// software distributed under the License is distributed on an
-// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
-// KIND, either express or implied.  See the License for the
-// specific language governing permissions and limitations
-// under the License.
-
-use datafusion_ffi::proto::logical_extension_codec::FFI_LogicalExtensionCodec;
-use pyo3::exceptions::PyValueError;
-use pyo3::prelude::{PyAnyMethods, PyCapsuleMethods};
-use pyo3::types::PyCapsule;
-use pyo3::{Bound, PyAny, PyResult};
-
-pub(crate) fn ffi_logical_codec_from_pycapsule(
-    obj: Bound<PyAny>,
-) -> PyResult<FFI_LogicalExtensionCodec> {
-    let attr_name = "__datafusion_logical_extension_codec__";
-    let capsule = if obj.hasattr(attr_name)? {
-        obj.getattr(attr_name)?.call0()?
-    } else {
-        obj
-    };
-
-    let capsule = capsule.downcast::<PyCapsule>()?;
-    validate_pycapsule(capsule, "datafusion_logical_extension_codec")?;
-
-    let codec = unsafe { capsule.reference::<FFI_LogicalExtensionCodec>() };
-
-    Ok(codec.clone())
-}
-
-pub(crate) fn validate_pycapsule(capsule: &Bound<PyCapsule>, name: &str) -> PyResult<()> {
-    let capsule_name = capsule.name()?;
-    if capsule_name.is_none() {
-        return Err(PyValueError::new_err(format!(
-            "Expected {name} PyCapsule to have name set."
-        )));
-    }
-
-    let capsule_name = capsule_name.unwrap().to_str()?;
-    if capsule_name != name {
-        return Err(PyValueError::new_err(format!(
-            "Expected name '{name}' in PyCapsule, instead got '{capsule_name}'"
-        )));
-    }
-
-    Ok(())
-}
diff --git a/examples/datafusion-ffi-example/src/window_udf.rs b/examples/datafusion-ffi-example/src/window_udf.rs
index f3f565234..cbf179a86 100644
--- a/examples/datafusion-ffi-example/src/window_udf.rs
+++ b/examples/datafusion-ffi-example/src/window_udf.rs
@@ -27,7 +27,12 @@ use datafusion_functions_window::rank::rank_udwf;
 use pyo3::types::PyCapsule;
 use pyo3::{Bound, PyResult, Python, pyclass, pymethods};
 
-#[pyclass(name = "MyRankUDF", module = "datafusion_ffi_example", subclass)]
+#[pyclass(
+    from_py_object,
+    name = "MyRankUDF",
+    module = "datafusion_ffi_example",
+    subclass
+)]
 #[derive(Debug, Clone, Eq, PartialEq, Hash)]
 pub(crate) struct MyRankUDF {
     inner: Arc<WindowUDF>,
diff --git a/examples/tpch/_tests.py b/examples/tpch/_tests.py
index 780fcf5e5..82dab2974 100644
--- a/examples/tpch/_tests.py
+++ b/examples/tpch/_tests.py
@@ -115,7 +115,7 @@ def test_tpch_query_vs_answer_file(query_code: str, answer_file: str) -> None:
         get_answer_file(answer_file),
         schema=read_schema,
         delimiter="|",
-        file_extension=".out",
+        file_extension=".tbl",
     )
 
     df_expected = df_expected.select(*expected_selections)
diff --git a/examples/tpch/answers_sf1/q1.tbl b/examples/tpch/answers_sf1/q1.tbl
new file mode 100644
index 000000000..03ca993e7
--- /dev/null
+++ b/examples/tpch/answers_sf1/q1.tbl
@@ -0,0 +1,5 @@
+l|l|sum_qty                                  |sum_base_price                           |sum_disc_price                           |sum_charge                               |avg_qty                                  |avg_price                                |avg_disc                                 |count_order           
+A|F|37734107.00|56586554400.73|53758257134.87|55909065222.83|25.52|38273.13|0.05|               1478493
+N|F|991417.00|1487504710.38|1413082168.05|1469649223.19|25.52|38284.47|0.05|                 38854
+N|O|74476040.00|111701729697.74|106118230307.61|110367043872.50|25.50|38249.12|0.05|               2920374
+R|F|37719753.00|56568041380.90|53741292684.60|55889619119.83|25.51|38250.85|0.05|               1478870
diff --git a/examples/tpch/answers_sf1/q10.tbl b/examples/tpch/answers_sf1/q10.tbl
new file mode 100644
index 000000000..95f303907
--- /dev/null
+++ b/examples/tpch/answers_sf1/q10.tbl
@@ -0,0 +1,21 @@
+c_custkey           |c_name                   |revenue                                  |c_acctbal     |n_name                   |c_address                               |c_phone        |c_comment                                                                                                            
+               57040|Customer#000057040       |734235.25|632.87|JAPAN                    |Eioyzjf4pp                              |22-895-641-3466|sits. slyly regular requests sleep alongside of the regular inst                                                     
+              143347|Customer#000143347       |721002.69|2557.47|EGYPT                    |1aReFYv,Kw4                             |14-742-935-3718|ggle carefully enticing requests. final deposits use bold, bold pinto beans. ironic, idle re                         
+               60838|Customer#000060838       |679127.31|2454.77|BRAZIL                   |64EaJ5vMAHWJlBOxJklpNc2RJiWE            |12-913-494-9813| need to boost against the slyly regular account                                                                     
+              101998|Customer#000101998       |637029.57|3790.89|UNITED KINGDOM           |01c9CILnNtfOQYmZj                       |33-593-865-6378|ress foxes wake slyly after the bold excuses. ironic platelets are furiously carefully bold theodolites              
+              125341|Customer#000125341       |633508.09|4983.51|GERMANY                  |S29ODD6bceU8QSuuEJznkNaK                |17-582-695-5962|arefully even depths. blithely even excuses sleep furiously. foxes use except the dependencies. ca                   
+               25501|Customer#000025501       |620269.78|7725.04|ETHIOPIA                 |  W556MXuoiaYCCZamJI,Rn0B4ACUGdkQ8DZ    |15-874-808-6793|he pending instructions wake carefully at the pinto beans. regular, final instructions along the slyly fina          
+              115831|Customer#000115831       |596423.87|5098.10|FRANCE                   |rFeBbEEyk dl ne7zV5fDrmiq1oK09wV7pxqCgIc|16-715-386-3788|l somas sleep. furiously final deposits wake blithely regular pinto b                                                
+               84223|Customer#000084223       |594998.02|528.65|UNITED KINGDOM           |nAVZCs6BaWap rrM27N 2qBnzc5WBauxbA      |33-442-824-8191| slyly final deposits haggle regular, pending dependencies. pending escapades wake                                   
+               54289|Customer#000054289       |585603.39|5583.02|IRAN                     |vXCxoCsU0Bad5JQI ,oobkZ                 |20-834-292-4707|ely special foxes are quickly finally ironic p                                                                       
+               39922|Customer#000039922       |584878.11|7321.11|GERMANY                  |Zgy4s50l2GKN4pLDPBU8m342gIw6R           |17-147-757-8036|y final requests. furiously final foxes cajole blithely special platelets. f                                         
+                6226|Customer#000006226       |576783.76|2230.09|UNITED KINGDOM           |8gPu8,NPGkfyQQ0hcIYUGPIBWc,ybP5g,       |33-657-701-3391|ending platelets along the express deposits cajole carefully final                                                   
+                 922|Customer#000000922       |576767.53|3869.25|GERMANY                  |Az9RFaut7NkPnc5zSD2PwHgVwr4jRzq         |17-945-916-9648|luffily fluffy deposits. packages c                                                                                  
+              147946|Customer#000147946       |576455.13|2030.13|ALGERIA                  |iANyZHjqhyy7Ajah0pTrYyhJ                |10-886-956-3143|ithely ironic deposits haggle blithely ironic requests. quickly regu                                                 
+              115640|Customer#000115640       |569341.19|6436.10|ARGENTINA                |Vtgfia9qI 7EpHgecU1X                    |11-411-543-4901|ost slyly along the patterns; pinto be                                                                               
+               73606|Customer#000073606       |568656.86|1785.67|JAPAN                    |xuR0Tro5yChDfOCrjkd2ol                  |22-437-653-6966|he furiously regular ideas. slowly                                                                                   
+              110246|Customer#000110246       |566842.98|7763.35|VIETNAM                  |7KzflgX MDOq7sOkI                       |31-943-426-9837|egular deposits serve blithely above the fl                                                                          
+              142549|Customer#000142549       |563537.24|5085.99|INDONESIA                |ChqEoK43OysjdHbtKCp6dKqjNyvvi9          |19-955-562-2398|sleep pending courts. ironic deposits against the carefully unusual platelets cajole carefully express accounts.     
+              146149|Customer#000146149       |557254.99|1791.55|ROMANIA                  |s87fvzFQpU                              |29-744-164-6487| of the slyly silent accounts. quickly final accounts across the                                                     
+               52528|Customer#000052528       |556397.35|551.79|ARGENTINA                |NFztyTOR10UOJ                           |11-208-192-3205| deposits hinder. blithely pending asymptotes breach slyly regular re                                                
+               23431|Customer#000023431       |554269.54|3381.86|ROMANIA                  |HgiV0phqhaIa9aydNoIlb                   |29-915-458-2654|nusual, even instructions: furiously stealthy n                                                                      
diff --git a/examples/tpch/answers_sf1/q11.tbl b/examples/tpch/answers_sf1/q11.tbl
new file mode 100644
index 000000000..f48a8989d
--- /dev/null
+++ b/examples/tpch/answers_sf1/q11.tbl
@@ -0,0 +1,1049 @@
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diff --git a/examples/tpch/answers_sf1/q12.tbl b/examples/tpch/answers_sf1/q12.tbl
new file mode 100644
index 000000000..752fbae05
--- /dev/null
+++ b/examples/tpch/answers_sf1/q12.tbl
@@ -0,0 +1,3 @@
+l_shipmode|high_line_count       |low_line_count        
+MAIL      |                  6202|                  9324
+SHIP      |                  6200|                  9262
diff --git a/examples/tpch/answers_sf1/q13.tbl b/examples/tpch/answers_sf1/q13.tbl
new file mode 100644
index 000000000..deecc0d83
--- /dev/null
+++ b/examples/tpch/answers_sf1/q13.tbl
@@ -0,0 +1,43 @@
+c_count               |custdist              
+                     0|                 50005
+                     9|                  6641
+                    10|                  6532
+                    11|                  6014
+                     8|                  5937
+                    12|                  5639
+                    13|                  5024
+                    19|                  4793
+                     7|                  4687
+                    17|                  4587
+                    18|                  4529
+                    20|                  4516
+                    15|                  4505
+                    14|                  4446
+                    16|                  4273
+                    21|                  4190
+                    22|                  3623
+                     6|                  3265
+                    23|                  3225
+                    24|                  2742
+                    25|                  2086
+                     5|                  1948
+                    26|                  1612
+                    27|                  1179
+                     4|                  1007
+                    28|                   893
+                    29|                   593
+                     3|                   415
+                    30|                   376
+                    31|                   226
+                    32|                   148
+                     2|                   134
+                    33|                    75
+                    34|                    50
+                    35|                    37
+                     1|                    17
+                    36|                    14
+                    38|                     5
+                    37|                     5
+                    40|                     4
+                    41|                     2
+                    39|                     1
diff --git a/examples/tpch/answers_sf1/q14.tbl b/examples/tpch/answers_sf1/q14.tbl
new file mode 100644
index 000000000..0e6571a1d
--- /dev/null
+++ b/examples/tpch/answers_sf1/q14.tbl
@@ -0,0 +1,2 @@
+promo_revenue                            
+16.38
diff --git a/examples/tpch/answers_sf1/q15.tbl b/examples/tpch/answers_sf1/q15.tbl
new file mode 100644
index 000000000..ece5d5900
--- /dev/null
+++ b/examples/tpch/answers_sf1/q15.tbl
@@ -0,0 +1,2 @@
+s_suppkey           |s_name                   |s_address                               |s_phone        |total_revenue                            
+                8449|Supplier#000008449       |Wp34zim9qYFbVctdW                       |20-469-856-8873|1772627.21
diff --git a/examples/tpch/answers_sf1/q16.tbl b/examples/tpch/answers_sf1/q16.tbl
new file mode 100644
index 000000000..854a168b7
--- /dev/null
+++ b/examples/tpch/answers_sf1/q16.tbl
@@ -0,0 +1,18315 @@
+p_brand   |p_type                   |p_size              |supplier_cnt          
+Brand#41  |MEDIUM BRUSHED TIN       |                   3|                    28
+Brand#54  |STANDARD BRUSHED COPPER  |                  14|                    27
+Brand#11  |STANDARD BRUSHED TIN     |                  23|                    24
+Brand#11  |STANDARD BURNISHED BRASS |                  36|                    24
+Brand#15  |MEDIUM ANODIZED NICKEL   |                   3|                    24
+Brand#15  |SMALL ANODIZED BRASS     |                  45|                    24
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+Brand#55  |LARGE PLATED BRASS       |                  36|                     4
+Brand#55  |LARGE PLATED BRASS       |                  49|                     4
+Brand#55  |LARGE PLATED COPPER      |                   3|                     4
+Brand#55  |LARGE PLATED COPPER      |                  19|                     4
+Brand#55  |LARGE PLATED COPPER      |                  36|                     4
+Brand#55  |LARGE PLATED NICKEL      |                   3|                     4
+Brand#55  |LARGE PLATED NICKEL      |                  23|                     4
+Brand#55  |LARGE PLATED NICKEL      |                  45|                     4
+Brand#55  |LARGE PLATED NICKEL      |                  49|                     4
+Brand#55  |LARGE PLATED STEEL       |                   9|                     4
+Brand#55  |LARGE PLATED STEEL       |                  45|                     4
+Brand#55  |LARGE PLATED TIN         |                   3|                     4
+Brand#55  |LARGE PLATED TIN         |                  23|                     4
+Brand#55  |LARGE PLATED TIN         |                  49|                     4
+Brand#55  |LARGE POLISHED BRASS     |                   9|                     4
+Brand#55  |LARGE POLISHED BRASS     |                  14|                     4
+Brand#55  |LARGE POLISHED BRASS     |                  19|                     4
+Brand#55  |LARGE POLISHED COPPER    |                   3|                     4
+Brand#55  |LARGE POLISHED COPPER    |                  14|                     4
+Brand#55  |LARGE POLISHED COPPER    |                  19|                     4
+Brand#55  |LARGE POLISHED COPPER    |                  23|                     4
+Brand#55  |LARGE POLISHED COPPER    |                  45|                     4
+Brand#55  |LARGE POLISHED COPPER    |                  49|                     4
+Brand#55  |LARGE POLISHED NICKEL    |                  23|                     4
+Brand#55  |LARGE POLISHED NICKEL    |                  45|                     4
+Brand#55  |LARGE POLISHED STEEL     |                  23|                     4
+Brand#55  |LARGE POLISHED STEEL     |                  36|                     4
+Brand#55  |LARGE POLISHED STEEL     |                  49|                     4
+Brand#55  |LARGE POLISHED TIN       |                   3|                     4
+Brand#55  |LARGE POLISHED TIN       |                  19|                     4
+Brand#55  |LARGE POLISHED TIN       |                  23|                     4
+Brand#55  |LARGE POLISHED TIN       |                  49|                     4
+Brand#55  |MEDIUM ANODIZED BRASS    |                   3|                     4
+Brand#55  |MEDIUM ANODIZED BRASS    |                  14|                     4
+Brand#55  |MEDIUM ANODIZED BRASS    |                  19|                     4
+Brand#55  |MEDIUM ANODIZED BRASS    |                  45|                     4
+Brand#55  |MEDIUM ANODIZED COPPER   |                   9|                     4
+Brand#55  |MEDIUM ANODIZED COPPER   |                  23|                     4
+Brand#55  |MEDIUM ANODIZED COPPER   |                  45|                     4
+Brand#55  |MEDIUM ANODIZED NICKEL   |                   3|                     4
+Brand#55  |MEDIUM ANODIZED NICKEL   |                   9|                     4
+Brand#55  |MEDIUM ANODIZED NICKEL   |                  23|                     4
+Brand#55  |MEDIUM ANODIZED STEEL    |                   9|                     4
+Brand#55  |MEDIUM ANODIZED STEEL    |                  23|                     4
+Brand#55  |MEDIUM ANODIZED STEEL    |                  36|                     4
+Brand#55  |MEDIUM ANODIZED STEEL    |                  45|                     4
+Brand#55  |MEDIUM ANODIZED STEEL    |                  49|                     4
+Brand#55  |MEDIUM ANODIZED TIN      |                   3|                     4
+Brand#55  |MEDIUM ANODIZED TIN      |                   9|                     4
+Brand#55  |MEDIUM ANODIZED TIN      |                  14|                     4
+Brand#55  |MEDIUM ANODIZED TIN      |                  19|                     4
+Brand#55  |MEDIUM ANODIZED TIN      |                  36|                     4
+Brand#55  |MEDIUM BRUSHED BRASS     |                   3|                     4
+Brand#55  |MEDIUM BRUSHED BRASS     |                   9|                     4
+Brand#55  |MEDIUM BRUSHED BRASS     |                  36|                     4
+Brand#55  |MEDIUM BRUSHED BRASS     |                  45|                     4
+Brand#55  |MEDIUM BRUSHED COPPER    |                   9|                     4
+Brand#55  |MEDIUM BRUSHED COPPER    |                  14|                     4
+Brand#55  |MEDIUM BRUSHED COPPER    |                  19|                     4
+Brand#55  |MEDIUM BRUSHED COPPER    |                  36|                     4
+Brand#55  |MEDIUM BRUSHED NICKEL    |                  14|                     4
+Brand#55  |MEDIUM BRUSHED NICKEL    |                  49|                     4
+Brand#55  |MEDIUM BRUSHED STEEL     |                   3|                     4
+Brand#55  |MEDIUM BRUSHED TIN       |                  23|                     4
+Brand#55  |MEDIUM BRUSHED TIN       |                  49|                     4
+Brand#55  |MEDIUM BURNISHED BRASS   |                   9|                     4
+Brand#55  |MEDIUM BURNISHED BRASS   |                  23|                     4
+Brand#55  |MEDIUM BURNISHED BRASS   |                  45|                     4
+Brand#55  |MEDIUM BURNISHED BRASS   |                  49|                     4
+Brand#55  |MEDIUM BURNISHED COPPER  |                   9|                     4
+Brand#55  |MEDIUM BURNISHED COPPER  |                  14|                     4
+Brand#55  |MEDIUM BURNISHED COPPER  |                  19|                     4
+Brand#55  |MEDIUM BURNISHED NICKEL  |                   3|                     4
+Brand#55  |MEDIUM BURNISHED NICKEL  |                   9|                     4
+Brand#55  |MEDIUM BURNISHED NICKEL  |                  14|                     4
+Brand#55  |MEDIUM BURNISHED NICKEL  |                  36|                     4
+Brand#55  |MEDIUM BURNISHED STEEL   |                   9|                     4
+Brand#55  |MEDIUM BURNISHED TIN     |                   3|                     4
+Brand#55  |MEDIUM BURNISHED TIN     |                  23|                     4
+Brand#55  |MEDIUM BURNISHED TIN     |                  49|                     4
+Brand#55  |MEDIUM PLATED BRASS      |                   9|                     4
+Brand#55  |MEDIUM PLATED BRASS      |                  14|                     4
+Brand#55  |MEDIUM PLATED BRASS      |                  36|                     4
+Brand#55  |MEDIUM PLATED BRASS      |                  49|                     4
+Brand#55  |MEDIUM PLATED COPPER     |                  49|                     4
+Brand#55  |MEDIUM PLATED NICKEL     |                   9|                     4
+Brand#55  |MEDIUM PLATED NICKEL     |                  14|                     4
+Brand#55  |MEDIUM PLATED NICKEL     |                  45|                     4
+Brand#55  |MEDIUM PLATED STEEL      |                   9|                     4
+Brand#55  |MEDIUM PLATED STEEL      |                  23|                     4
+Brand#55  |MEDIUM PLATED STEEL      |                  49|                     4
+Brand#55  |MEDIUM PLATED TIN        |                  45|                     4
+Brand#55  |MEDIUM PLATED TIN        |                  49|                     4
+Brand#55  |PROMO ANODIZED BRASS     |                   9|                     4
+Brand#55  |PROMO ANODIZED COPPER    |                  19|                     4
+Brand#55  |PROMO ANODIZED NICKEL    |                  23|                     4
+Brand#55  |PROMO ANODIZED NICKEL    |                  45|                     4
+Brand#55  |PROMO ANODIZED STEEL     |                   9|                     4
+Brand#55  |PROMO ANODIZED STEEL     |                  14|                     4
+Brand#55  |PROMO ANODIZED STEEL     |                  23|                     4
+Brand#55  |PROMO ANODIZED TIN       |                   9|                     4
+Brand#55  |PROMO ANODIZED TIN       |                  23|                     4
+Brand#55  |PROMO BRUSHED BRASS      |                  14|                     4
+Brand#55  |PROMO BRUSHED BRASS      |                  19|                     4
+Brand#55  |PROMO BRUSHED BRASS      |                  49|                     4
+Brand#55  |PROMO BRUSHED COPPER     |                  14|                     4
+Brand#55  |PROMO BRUSHED COPPER     |                  23|                     4
+Brand#55  |PROMO BRUSHED COPPER     |                  36|                     4
+Brand#55  |PROMO BRUSHED COPPER     |                  45|                     4
+Brand#55  |PROMO BRUSHED COPPER     |                  49|                     4
+Brand#55  |PROMO BRUSHED NICKEL     |                   3|                     4
+Brand#55  |PROMO BRUSHED NICKEL     |                  19|                     4
+Brand#55  |PROMO BRUSHED STEEL      |                  14|                     4
+Brand#55  |PROMO BRUSHED STEEL      |                  19|                     4
+Brand#55  |PROMO BRUSHED TIN        |                  19|                     4
+Brand#55  |PROMO BURNISHED BRASS    |                   9|                     4
+Brand#55  |PROMO BURNISHED BRASS    |                  14|                     4
+Brand#55  |PROMO BURNISHED BRASS    |                  19|                     4
+Brand#55  |PROMO BURNISHED COPPER   |                   3|                     4
+Brand#55  |PROMO BURNISHED COPPER   |                  49|                     4
+Brand#55  |PROMO BURNISHED NICKEL   |                  14|                     4
+Brand#55  |PROMO BURNISHED NICKEL   |                  19|                     4
+Brand#55  |PROMO BURNISHED NICKEL   |                  23|                     4
+Brand#55  |PROMO BURNISHED NICKEL   |                  45|                     4
+Brand#55  |PROMO BURNISHED NICKEL   |                  49|                     4
+Brand#55  |PROMO BURNISHED STEEL    |                  19|                     4
+Brand#55  |PROMO BURNISHED STEEL    |                  36|                     4
+Brand#55  |PROMO BURNISHED TIN      |                   3|                     4
+Brand#55  |PROMO BURNISHED TIN      |                  14|                     4
+Brand#55  |PROMO BURNISHED TIN      |                  23|                     4
+Brand#55  |PROMO PLATED BRASS       |                   3|                     4
+Brand#55  |PROMO PLATED BRASS       |                  49|                     4
+Brand#55  |PROMO PLATED COPPER      |                   3|                     4
+Brand#55  |PROMO PLATED COPPER      |                  45|                     4
+Brand#55  |PROMO PLATED NICKEL      |                   3|                     4
+Brand#55  |PROMO PLATED NICKEL      |                  23|                     4
+Brand#55  |PROMO PLATED STEEL       |                   3|                     4
+Brand#55  |PROMO PLATED STEEL       |                  23|                     4
+Brand#55  |PROMO PLATED STEEL       |                  36|                     4
+Brand#55  |PROMO PLATED STEEL       |                  45|                     4
+Brand#55  |PROMO PLATED STEEL       |                  49|                     4
+Brand#55  |PROMO PLATED TIN         |                   3|                     4
+Brand#55  |PROMO PLATED TIN         |                  19|                     4
+Brand#55  |PROMO PLATED TIN         |                  23|                     4
+Brand#55  |PROMO POLISHED BRASS     |                  14|                     4
+Brand#55  |PROMO POLISHED COPPER    |                   3|                     4
+Brand#55  |PROMO POLISHED COPPER    |                  19|                     4
+Brand#55  |PROMO POLISHED COPPER    |                  45|                     4
+Brand#55  |PROMO POLISHED COPPER    |                  49|                     4
+Brand#55  |PROMO POLISHED NICKEL    |                   3|                     4
+Brand#55  |PROMO POLISHED NICKEL    |                  14|                     4
+Brand#55  |PROMO POLISHED NICKEL    |                  19|                     4
+Brand#55  |PROMO POLISHED NICKEL    |                  23|                     4
+Brand#55  |PROMO POLISHED NICKEL    |                  36|                     4
+Brand#55  |PROMO POLISHED STEEL     |                  19|                     4
+Brand#55  |PROMO POLISHED STEEL     |                  45|                     4
+Brand#55  |PROMO POLISHED STEEL     |                  49|                     4
+Brand#55  |PROMO POLISHED TIN       |                   3|                     4
+Brand#55  |PROMO POLISHED TIN       |                   9|                     4
+Brand#55  |PROMO POLISHED TIN       |                  14|                     4
+Brand#55  |PROMO POLISHED TIN       |                  19|                     4
+Brand#55  |PROMO POLISHED TIN       |                  23|                     4
+Brand#55  |PROMO POLISHED TIN       |                  36|                     4
+Brand#55  |PROMO POLISHED TIN       |                  45|                     4
+Brand#55  |PROMO POLISHED TIN       |                  49|                     4
+Brand#55  |SMALL ANODIZED BRASS     |                  23|                     4
+Brand#55  |SMALL ANODIZED BRASS     |                  36|                     4
+Brand#55  |SMALL ANODIZED BRASS     |                  45|                     4
+Brand#55  |SMALL ANODIZED COPPER    |                   9|                     4
+Brand#55  |SMALL ANODIZED COPPER    |                  19|                     4
+Brand#55  |SMALL ANODIZED COPPER    |                  23|                     4
+Brand#55  |SMALL ANODIZED NICKEL    |                   9|                     4
+Brand#55  |SMALL ANODIZED NICKEL    |                  14|                     4
+Brand#55  |SMALL ANODIZED NICKEL    |                  23|                     4
+Brand#55  |SMALL ANODIZED NICKEL    |                  36|                     4
+Brand#55  |SMALL ANODIZED NICKEL    |                  45|                     4
+Brand#55  |SMALL ANODIZED STEEL     |                  36|                     4
+Brand#55  |SMALL ANODIZED TIN       |                   9|                     4
+Brand#55  |SMALL ANODIZED TIN       |                  36|                     4
+Brand#55  |SMALL ANODIZED TIN       |                  45|                     4
+Brand#55  |SMALL ANODIZED TIN       |                  49|                     4
+Brand#55  |SMALL BRUSHED BRASS      |                   9|                     4
+Brand#55  |SMALL BRUSHED BRASS      |                  36|                     4
+Brand#55  |SMALL BRUSHED COPPER     |                   3|                     4
+Brand#55  |SMALL BRUSHED COPPER     |                   9|                     4
+Brand#55  |SMALL BRUSHED COPPER     |                  19|                     4
+Brand#55  |SMALL BRUSHED COPPER     |                  23|                     4
+Brand#55  |SMALL BRUSHED NICKEL     |                   3|                     4
+Brand#55  |SMALL BRUSHED NICKEL     |                   9|                     4
+Brand#55  |SMALL BRUSHED NICKEL     |                  19|                     4
+Brand#55  |SMALL BRUSHED NICKEL     |                  23|                     4
+Brand#55  |SMALL BRUSHED NICKEL     |                  45|                     4
+Brand#55  |SMALL BRUSHED NICKEL     |                  49|                     4
+Brand#55  |SMALL BRUSHED STEEL      |                   3|                     4
+Brand#55  |SMALL BRUSHED STEEL      |                  14|                     4
+Brand#55  |SMALL BRUSHED STEEL      |                  19|                     4
+Brand#55  |SMALL BRUSHED STEEL      |                  23|                     4
+Brand#55  |SMALL BRUSHED STEEL      |                  45|                     4
+Brand#55  |SMALL BRUSHED STEEL      |                  49|                     4
+Brand#55  |SMALL BRUSHED TIN        |                   9|                     4
+Brand#55  |SMALL BRUSHED TIN        |                  49|                     4
+Brand#55  |SMALL BURNISHED BRASS    |                  14|                     4
+Brand#55  |SMALL BURNISHED BRASS    |                  23|                     4
+Brand#55  |SMALL BURNISHED COPPER   |                   3|                     4
+Brand#55  |SMALL BURNISHED COPPER   |                   9|                     4
+Brand#55  |SMALL BURNISHED COPPER   |                  36|                     4
+Brand#55  |SMALL BURNISHED NICKEL   |                   9|                     4
+Brand#55  |SMALL BURNISHED NICKEL   |                  19|                     4
+Brand#55  |SMALL BURNISHED NICKEL   |                  36|                     4
+Brand#55  |SMALL BURNISHED NICKEL   |                  45|                     4
+Brand#55  |SMALL BURNISHED STEEL    |                  14|                     4
+Brand#55  |SMALL BURNISHED TIN      |                   9|                     4
+Brand#55  |SMALL BURNISHED TIN      |                  23|                     4
+Brand#55  |SMALL PLATED COPPER      |                   3|                     4
+Brand#55  |SMALL PLATED COPPER      |                  14|                     4
+Brand#55  |SMALL PLATED COPPER      |                  36|                     4
+Brand#55  |SMALL PLATED COPPER      |                  49|                     4
+Brand#55  |SMALL PLATED NICKEL      |                  14|                     4
+Brand#55  |SMALL PLATED NICKEL      |                  49|                     4
+Brand#55  |SMALL PLATED STEEL       |                   3|                     4
+Brand#55  |SMALL PLATED STEEL       |                  23|                     4
+Brand#55  |SMALL PLATED STEEL       |                  36|                     4
+Brand#55  |SMALL PLATED TIN         |                  36|                     4
+Brand#55  |SMALL PLATED TIN         |                  45|                     4
+Brand#55  |SMALL POLISHED BRASS     |                   9|                     4
+Brand#55  |SMALL POLISHED BRASS     |                  19|                     4
+Brand#55  |SMALL POLISHED BRASS     |                  49|                     4
+Brand#55  |SMALL POLISHED COPPER    |                  19|                     4
+Brand#55  |SMALL POLISHED COPPER    |                  23|                     4
+Brand#55  |SMALL POLISHED COPPER    |                  36|                     4
+Brand#55  |SMALL POLISHED COPPER    |                  45|                     4
+Brand#55  |SMALL POLISHED COPPER    |                  49|                     4
+Brand#55  |SMALL POLISHED NICKEL    |                   9|                     4
+Brand#55  |SMALL POLISHED NICKEL    |                  14|                     4
+Brand#55  |SMALL POLISHED NICKEL    |                  19|                     4
+Brand#55  |SMALL POLISHED NICKEL    |                  23|                     4
+Brand#55  |SMALL POLISHED NICKEL    |                  45|                     4
+Brand#55  |SMALL POLISHED NICKEL    |                  49|                     4
+Brand#55  |SMALL POLISHED STEEL     |                  19|                     4
+Brand#55  |SMALL POLISHED STEEL     |                  45|                     4
+Brand#55  |SMALL POLISHED TIN       |                  14|                     4
+Brand#55  |SMALL POLISHED TIN       |                  23|                     4
+Brand#55  |SMALL POLISHED TIN       |                  45|                     4
+Brand#55  |STANDARD ANODIZED BRASS  |                   9|                     4
+Brand#55  |STANDARD ANODIZED BRASS  |                  23|                     4
+Brand#55  |STANDARD ANODIZED BRASS  |                  49|                     4
+Brand#55  |STANDARD ANODIZED COPPER |                   9|                     4
+Brand#55  |STANDARD ANODIZED COPPER |                  14|                     4
+Brand#55  |STANDARD ANODIZED COPPER |                  45|                     4
+Brand#55  |STANDARD ANODIZED NICKEL |                   3|                     4
+Brand#55  |STANDARD ANODIZED NICKEL |                  14|                     4
+Brand#55  |STANDARD ANODIZED NICKEL |                  45|                     4
+Brand#55  |STANDARD ANODIZED NICKEL |                  49|                     4
+Brand#55  |STANDARD ANODIZED STEEL  |                   3|                     4
+Brand#55  |STANDARD ANODIZED STEEL  |                  14|                     4
+Brand#55  |STANDARD ANODIZED TIN    |                  14|                     4
+Brand#55  |STANDARD ANODIZED TIN    |                  36|                     4
+Brand#55  |STANDARD ANODIZED TIN    |                  45|                     4
+Brand#55  |STANDARD BRUSHED BRASS   |                   9|                     4
+Brand#55  |STANDARD BRUSHED BRASS   |                  19|                     4
+Brand#55  |STANDARD BRUSHED COPPER  |                  14|                     4
+Brand#55  |STANDARD BRUSHED COPPER  |                  19|                     4
+Brand#55  |STANDARD BRUSHED NICKEL  |                   3|                     4
+Brand#55  |STANDARD BRUSHED NICKEL  |                  36|                     4
+Brand#55  |STANDARD BRUSHED STEEL   |                   9|                     4
+Brand#55  |STANDARD BRUSHED STEEL   |                  14|                     4
+Brand#55  |STANDARD BRUSHED STEEL   |                  19|                     4
+Brand#55  |STANDARD BRUSHED STEEL   |                  49|                     4
+Brand#55  |STANDARD BRUSHED TIN     |                  19|                     4
+Brand#55  |STANDARD BRUSHED TIN     |                  49|                     4
+Brand#55  |STANDARD BURNISHED BRASS |                   9|                     4
+Brand#55  |STANDARD BURNISHED BRASS |                  19|                     4
+Brand#55  |STANDARD BURNISHED BRASS |                  23|                     4
+Brand#55  |STANDARD BURNISHED BRASS |                  36|                     4
+Brand#55  |STANDARD BURNISHED COPPER|                   3|                     4
+Brand#55  |STANDARD BURNISHED NICKEL|                   9|                     4
+Brand#55  |STANDARD BURNISHED NICKEL|                  49|                     4
+Brand#55  |STANDARD BURNISHED STEEL |                  19|                     4
+Brand#55  |STANDARD BURNISHED STEEL |                  23|                     4
+Brand#55  |STANDARD BURNISHED STEEL |                  36|                     4
+Brand#55  |STANDARD BURNISHED STEEL |                  45|                     4
+Brand#55  |STANDARD BURNISHED TIN   |                   9|                     4
+Brand#55  |STANDARD BURNISHED TIN   |                  19|                     4
+Brand#55  |STANDARD BURNISHED TIN   |                  36|                     4
+Brand#55  |STANDARD BURNISHED TIN   |                  49|                     4
+Brand#55  |STANDARD PLATED BRASS    |                   9|                     4
+Brand#55  |STANDARD PLATED BRASS    |                  45|                     4
+Brand#55  |STANDARD PLATED BRASS    |                  49|                     4
+Brand#55  |STANDARD PLATED COPPER   |                   9|                     4
+Brand#55  |STANDARD PLATED COPPER   |                  45|                     4
+Brand#55  |STANDARD PLATED NICKEL   |                   3|                     4
+Brand#55  |STANDARD PLATED NICKEL   |                  19|                     4
+Brand#55  |STANDARD PLATED NICKEL   |                  45|                     4
+Brand#55  |STANDARD PLATED STEEL    |                  14|                     4
+Brand#55  |STANDARD PLATED STEEL    |                  23|                     4
+Brand#55  |STANDARD PLATED STEEL    |                  49|                     4
+Brand#55  |STANDARD PLATED TIN      |                   9|                     4
+Brand#55  |STANDARD PLATED TIN      |                  14|                     4
+Brand#55  |STANDARD PLATED TIN      |                  36|                     4
+Brand#55  |STANDARD POLISHED BRASS  |                   3|                     4
+Brand#55  |STANDARD POLISHED BRASS  |                   9|                     4
+Brand#55  |STANDARD POLISHED BRASS  |                  23|                     4
+Brand#55  |STANDARD POLISHED COPPER |                   3|                     4
+Brand#55  |STANDARD POLISHED COPPER |                  23|                     4
+Brand#55  |STANDARD POLISHED COPPER |                  45|                     4
+Brand#55  |STANDARD POLISHED NICKEL |                   3|                     4
+Brand#55  |STANDARD POLISHED NICKEL |                  23|                     4
+Brand#55  |STANDARD POLISHED NICKEL |                  36|                     4
+Brand#55  |STANDARD POLISHED NICKEL |                  45|                     4
+Brand#55  |STANDARD POLISHED NICKEL |                  49|                     4
+Brand#55  |STANDARD POLISHED STEEL  |                  14|                     4
+Brand#55  |STANDARD POLISHED STEEL  |                  23|                     4
+Brand#55  |STANDARD POLISHED TIN    |                   9|                     4
+Brand#55  |STANDARD POLISHED TIN    |                  19|                     4
+Brand#55  |STANDARD POLISHED TIN    |                  36|                     4
+Brand#11  |SMALL BRUSHED TIN        |                  19|                     3
+Brand#15  |LARGE PLATED NICKEL      |                  45|                     3
+Brand#15  |LARGE POLISHED NICKEL    |                   9|                     3
+Brand#21  |PROMO BURNISHED STEEL    |                  45|                     3
+Brand#22  |STANDARD PLATED STEEL    |                  23|                     3
+Brand#25  |LARGE PLATED STEEL       |                  19|                     3
+Brand#32  |STANDARD ANODIZED COPPER |                  23|                     3
+Brand#33  |SMALL ANODIZED BRASS     |                   9|                     3
+Brand#35  |MEDIUM ANODIZED TIN      |                  19|                     3
+Brand#51  |SMALL PLATED BRASS       |                  23|                     3
+Brand#52  |MEDIUM BRUSHED BRASS     |                  45|                     3
+Brand#53  |MEDIUM BRUSHED TIN       |                  45|                     3
+Brand#54  |ECONOMY POLISHED BRASS   |                   9|                     3
+Brand#55  |PROMO PLATED BRASS       |                  19|                     3
+Brand#55  |STANDARD PLATED TIN      |                  49|                     3
diff --git a/examples/tpch/answers_sf1/q17.tbl b/examples/tpch/answers_sf1/q17.tbl
new file mode 100644
index 000000000..c7e570a0f
--- /dev/null
+++ b/examples/tpch/answers_sf1/q17.tbl
@@ -0,0 +1,2 @@
+avg_yearly                               
+348406.02
diff --git a/examples/tpch/answers_sf1/q18.tbl b/examples/tpch/answers_sf1/q18.tbl
new file mode 100644
index 000000000..9e036c6b1
--- /dev/null
+++ b/examples/tpch/answers_sf1/q18.tbl
@@ -0,0 +1,58 @@
+c_name                   |c_custkey           |o_orderkey            |o_orderdat|o_totalprice  |col6                                     
+Customer#000128120       |              128120|               4722021|1994-04-07|544089.09|323.00
+Customer#000144617       |              144617|               3043270|1997-02-12|530604.44|317.00
+Customer#000013940       |               13940|               2232932|1997-04-13|522720.61|304.00
+Customer#000066790       |               66790|               2199712|1996-09-30|515531.82|327.00
+Customer#000046435       |               46435|               4745607|1997-07-03|508047.99|309.00
+Customer#000015272       |               15272|               3883783|1993-07-28|500241.33|302.00
+Customer#000146608       |              146608|               3342468|1994-06-12|499794.58|303.00
+Customer#000096103       |               96103|               5984582|1992-03-16|494398.79|312.00
+Customer#000024341       |               24341|               1474818|1992-11-15|491348.26|302.00
+Customer#000137446       |              137446|               5489475|1997-05-23|487763.25|311.00
+Customer#000107590       |              107590|               4267751|1994-11-04|485141.38|301.00
+Customer#000050008       |               50008|               2366755|1996-12-09|483891.26|302.00
+Customer#000015619       |               15619|               3767271|1996-08-07|480083.96|318.00
+Customer#000077260       |               77260|               1436544|1992-09-12|479499.43|307.00
+Customer#000109379       |              109379|               5746311|1996-10-10|478064.11|302.00
+Customer#000054602       |               54602|               5832321|1997-02-09|471220.08|307.00
+Customer#000105995       |              105995|               2096705|1994-07-03|469692.58|307.00
+Customer#000148885       |              148885|               2942469|1992-05-31|469630.44|313.00
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+Customer#000037729       |               37729|               4134341|1995-06-29|441082.97|309.00
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+Customer#000015631       |               15631|               1845057|1994-05-12|419879.59|302.00
+Customer#000112987       |              112987|               4439686|1996-09-17|418161.49|305.00
+Customer#000012599       |               12599|               4259524|1998-02-12|415200.61|304.00
+Customer#000105410       |              105410|               4478371|1996-03-05|412754.51|302.00
+Customer#000149842       |              149842|               5156581|1994-05-30|411329.35|302.00
+Customer#000010129       |               10129|               5849444|1994-03-21|409129.85|309.00
+Customer#000069904       |               69904|               1742403|1996-10-19|408513.00|305.00
+Customer#000017746       |               17746|                  6882|1997-04-09|408446.93|303.00
+Customer#000013072       |               13072|               1481925|1998-03-15|399195.47|301.00
+Customer#000082441       |               82441|                857959|1994-02-07|382579.74|305.00
+Customer#000088703       |               88703|               2995076|1994-01-30|363812.12|302.00
diff --git a/examples/tpch/answers_sf1/q19.tbl b/examples/tpch/answers_sf1/q19.tbl
new file mode 100644
index 000000000..3711427de
--- /dev/null
+++ b/examples/tpch/answers_sf1/q19.tbl
@@ -0,0 +1,2 @@
+revenue                                  
+3083843.06
diff --git a/examples/tpch/answers_sf1/q2.tbl b/examples/tpch/answers_sf1/q2.tbl
new file mode 100644
index 000000000..487b9fbb9
--- /dev/null
+++ b/examples/tpch/answers_sf1/q2.tbl
@@ -0,0 +1,101 @@
+s_acctbal     |s_name                   |n_name                   |p_partkey           |p_mfgr                   |s_address                               |s_phone        |s_comment                                                                                            
+9938.53|Supplier#000005359       |UNITED KINGDOM           |              185358|Manufacturer#4           |QKuHYh,vZGiwu2FWEJoLDx04                |33-429-790-6131|uriously regular requests hag                                                                        
+9937.84|Supplier#000005969       |ROMANIA                  |              108438|Manufacturer#1           |ANDENSOSmk,miq23Xfb5RWt6dvUcvt6Qa       |29-520-692-3537|efully express instructions. regular requests against the slyly fin                                  
+9936.22|Supplier#000005250       |UNITED KINGDOM           |                 249|Manufacturer#4           |B3rqp0xbSEim4Mpy2RH J                   |33-320-228-2957|etect about the furiously final accounts. slyly ironic pinto beans sleep inside the furiously        
+9923.77|Supplier#000002324       |GERMANY                  |               29821|Manufacturer#4           |y3OD9UywSTOk                            |17-779-299-1839|ackages boost blithely. blithely regular deposits c                                                  
+9871.22|Supplier#000006373       |GERMANY                  |               43868|Manufacturer#5           |J8fcXWsTqM                              |17-813-485-8637|etect blithely bold asymptotes. fluffily ironic platelets wake furiously; blit                       
+9870.78|Supplier#000001286       |GERMANY                  |               81285|Manufacturer#2           |YKA,E2fjiVd7eUrzp2Ef8j1QxGo2DFnosaTEH   |17-516-924-4574| regular accounts. furiously unusual courts above the fi                                             
+9870.78|Supplier#000001286       |GERMANY                  |              181285|Manufacturer#4           |YKA,E2fjiVd7eUrzp2Ef8j1QxGo2DFnosaTEH   |17-516-924-4574| regular accounts. furiously unusual courts above the fi                                             
+9852.52|Supplier#000008973       |RUSSIA                   |               18972|Manufacturer#2           |t5L67YdBYYH6o,Vz24jpDyQ9                |32-188-594-7038|rns wake final foxes. carefully unusual depende                                                      
+9847.83|Supplier#000008097       |RUSSIA                   |              130557|Manufacturer#2           |xMe97bpE69NzdwLoX                       |32-375-640-3593| the special excuses. silent sentiments serve carefully final ac                                     
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+9847.57|Supplier#000006345       |FRANCE                   |              173827|Manufacturer#2           |VSt3rzk3qG698u6ld8HhOByvrTcSTSvQlDQDag  |16-886-766-7945|ges. slyly regular requests are. ruthless, express excuses cajole blithely across the unu            
+9836.93|Supplier#000007342       |RUSSIA                   |                4841|Manufacturer#4           |JOlK7C1,7xrEZSSOw                       |32-399-414-5385|blithely carefully bold theodolites. fur                                                             
+9817.10|Supplier#000002352       |RUSSIA                   |              124815|Manufacturer#2           |4LfoHUZjgjEbAKw TgdKcgOc4D4uCYw         |32-551-831-1437|wake carefully alongside of the carefully final ex                                                   
+9817.10|Supplier#000002352       |RUSSIA                   |              152351|Manufacturer#3           |4LfoHUZjgjEbAKw TgdKcgOc4D4uCYw         |32-551-831-1437|wake carefully alongside of the carefully final ex                                                   
+9739.86|Supplier#000003384       |FRANCE                   |              138357|Manufacturer#2           |o,Z3v4POifevE k9U1b 6J1ucX,I            |16-494-913-5925|s after the furiously bold packages sleep fluffily idly final requests: quickly final                
+9721.95|Supplier#000008757       |UNITED KINGDOM           |              156241|Manufacturer#3           |Atg6GnM4dT2                             |33-821-407-2995|eep furiously sauternes; quickl                                                                      
+9681.33|Supplier#000008406       |RUSSIA                   |               78405|Manufacturer#1           |,qUuXcftUl                              |32-139-873-8571|haggle slyly regular excuses. quic                                                                   
+9643.55|Supplier#000005148       |ROMANIA                  |              107617|Manufacturer#1           |kT4ciVFslx9z4s79p Js825                 |29-252-617-4850|final excuses. final ideas boost quickly furiously speci                                             
+9624.82|Supplier#000001816       |FRANCE                   |               34306|Manufacturer#3           |e7vab91vLJPWxxZnewmnDBpDmxYHrb          |16-392-237-6726|e packages are around the special ideas. special, pending foxes us                                   
+9624.78|Supplier#000009658       |ROMANIA                  |              189657|Manufacturer#1           |oE9uBgEfSS4opIcepXyAYM,x                |29-748-876-2014|ronic asymptotes wake bravely final                                                                  
+9612.94|Supplier#000003228       |ROMANIA                  |              120715|Manufacturer#2           |KDdpNKN3cWu7ZSrbdqp7AfSLxx,qWB          |29-325-784-8187|warhorses. quickly even deposits sublate daringly ironic instructions. slyly blithe t                
+9612.94|Supplier#000003228       |ROMANIA                  |              198189|Manufacturer#4           |KDdpNKN3cWu7ZSrbdqp7AfSLxx,qWB          |29-325-784-8187|warhorses. quickly even deposits sublate daringly ironic instructions. slyly blithe t                
+9571.83|Supplier#000004305       |ROMANIA                  |              179270|Manufacturer#2           |qNHZ7WmCzygwMPRDO9Ps                    |29-973-481-1831|kly carefully express asymptotes. furiou                                                             
+9558.10|Supplier#000003532       |UNITED KINGDOM           |               88515|Manufacturer#4           |EOeuiiOn21OVpTlGguufFDFsbN1p0lhpxHp     |33-152-301-2164| foxes. quickly even excuses use. slyly special foxes nag bl                                         
+9492.79|Supplier#000005975       |GERMANY                  |               25974|Manufacturer#5           |S6mIiCTx82z7lV                          |17-992-579-4839|arefully pending accounts. blithely regular excuses boost carefully carefully ironic p               
+9461.05|Supplier#000002536       |UNITED KINGDOM           |               20033|Manufacturer#1           |8mmGbyzaU 7ZS2wJumTibypncu9pNkDc4FYA    |33-556-973-5522|. slyly regular deposits wake slyly. furiously regular warthogs are.                                 
+9453.01|Supplier#000000802       |ROMANIA                  |              175767|Manufacturer#1           |,6HYXb4uaHITmtMBj4Ak57Pd                |29-342-882-6463|gular frets. permanently special multipliers believe blithely alongs                                 
+9408.65|Supplier#000007772       |UNITED KINGDOM           |              117771|Manufacturer#4           |AiC5YAH,gdu0i7                          |33-152-491-1126|nag against the final requests. furiously unusual packages cajole blit                               
+9359.61|Supplier#000004856       |ROMANIA                  |               62349|Manufacturer#5           |HYogcF3Jb yh1                           |29-334-870-9731|y ironic theodolites. blithely sile                                                                  
+9357.45|Supplier#000006188       |UNITED KINGDOM           |              138648|Manufacturer#1           |g801,ssP8wpTk4Hm                        |33-583-607-1633|ously always regular packages. fluffily even accounts beneath the furiously final pack               
+9352.04|Supplier#000003439       |GERMANY                  |              170921|Manufacturer#4           |qYPDgoiBGhCYxjgC                        |17-128-996-4650| according to the carefully bold ideas                                                               
+9312.97|Supplier#000007807       |RUSSIA                   |               90279|Manufacturer#5           |oGYMPCk9XHGB2PBfKRnHA                   |32-673-872-5854|ecial packages among the pending, even requests use regula                                           
+9312.97|Supplier#000007807       |RUSSIA                   |              100276|Manufacturer#5           |oGYMPCk9XHGB2PBfKRnHA                   |32-673-872-5854|ecial packages among the pending, even requests use regula                                           
+9280.27|Supplier#000007194       |ROMANIA                  |               47193|Manufacturer#3           |zhRUQkBSrFYxIAXTfInj vyGRQjeK           |29-318-454-2133|o beans haggle after the furiously unusual deposits. carefully silent dolphins cajole carefully      
+9274.80|Supplier#000008854       |RUSSIA                   |               76346|Manufacturer#3           |1xhLoOUM7I3mZ1mKnerw OSqdbb4QbGa        |32-524-148-5221|y. courts do wake slyly. carefully ironic platelets haggle above the slyly regular the               
+9249.35|Supplier#000003973       |FRANCE                   |               26466|Manufacturer#1           |d18GiDsL6Wm2IsGXM,RZf1jCsgZAOjNYVThTRP4 |16-722-866-1658|uests are furiously. regular tithes through the regular, final accounts cajole furiously above the q 
+9249.35|Supplier#000003973       |FRANCE                   |               33972|Manufacturer#1           |d18GiDsL6Wm2IsGXM,RZf1jCsgZAOjNYVThTRP4 |16-722-866-1658|uests are furiously. regular tithes through the regular, final accounts cajole furiously above the q 
+9208.70|Supplier#000007769       |ROMANIA                  |               40256|Manufacturer#5           |rsimdze 5o9P Ht7xS                      |29-964-424-9649|lites was quickly above the furiously ironic requests. slyly even foxes against the blithely bold    
+9201.47|Supplier#000009690       |UNITED KINGDOM           |               67183|Manufacturer#5           |CB BnUTlmi5zdeEl7R7                     |33-121-267-9529|e even, even foxes. blithely ironic packages cajole regular packages. slyly final ide                
+9192.10|Supplier#000000115       |UNITED KINGDOM           |               85098|Manufacturer#3           |nJ 2t0f7Ve,wL1,6WzGBJLNBUCKlsV          |33-597-248-1220|es across the carefully express accounts boost caref                                                 
+9189.98|Supplier#000001226       |GERMANY                  |               21225|Manufacturer#4           |qsLCqSvLyZfuXIpjz                       |17-725-903-1381| deposits. blithely bold excuses about the slyly bold forges wake                                    
+9128.97|Supplier#000004311       |RUSSIA                   |              146768|Manufacturer#5           |I8IjnXd7NSJRs594RxsRR0                  |32-155-440-7120|refully. blithely unusual asymptotes haggle                                                          
+9104.83|Supplier#000008520       |GERMANY                  |              150974|Manufacturer#4           |RqRVDgD0ER J9 b41vR2,3                  |17-728-804-1793|ly about the blithely ironic depths. slyly final theodolites among the fluffily bold ideas print     
+9101.00|Supplier#000005791       |ROMANIA                  |              128254|Manufacturer#5           |zub2zCV,jhHPPQqi,P2INAjE1zI n66cOEoXFG  |29-549-251-5384|ts. notornis detect blithely above the carefully bold requests. blithely even package                
+9094.57|Supplier#000004582       |RUSSIA                   |               39575|Manufacturer#1           |WB0XkCSG3r,mnQ n,h9VIxjjr9ARHFvKgMDf    |32-587-577-1351|jole. regular accounts sleep blithely frets. final pinto beans play furiously past the               
+8996.87|Supplier#000004702       |FRANCE                   |              102191|Manufacturer#5           |8XVcQK23akp                             |16-811-269-8946|ickly final packages along the express plat                                                          
+8996.14|Supplier#000009814       |ROMANIA                  |              139813|Manufacturer#2           |af0O5pg83lPU4IDVmEylXZVqYZQzSDlYLAmR    |29-995-571-8781| dependencies boost quickly across the furiously pending requests! unusual dolphins play sl          
+8968.42|Supplier#000010000       |ROMANIA                  |              119999|Manufacturer#5           |aTGLEusCiL4F PDBdv665XBJhPyCOB0i        |29-578-432-2146|ly regular foxes boost slyly. quickly special waters boost carefully ironi                           
+8936.82|Supplier#000007043       |UNITED KINGDOM           |              109512|Manufacturer#1           |FVajceZInZdbJE6Z9XsRUxrUEpiwHDrOXi,1Rz  |33-784-177-8208|efully regular courts. furiousl                                                                      
+8929.42|Supplier#000008770       |FRANCE                   |              173735|Manufacturer#4           |R7cG26TtXrHAP9 HckhfRi                  |16-242-746-9248|cajole furiously unusual requests. quickly stealthy requests are.                                    
+8920.59|Supplier#000003967       |ROMANIA                  |               26460|Manufacturer#1           |eHoAXe62SY9                             |29-194-731-3944|aters. express, pending instructions sleep. brave, r                                                 
+8920.59|Supplier#000003967       |ROMANIA                  |              173966|Manufacturer#2           |eHoAXe62SY9                             |29-194-731-3944|aters. express, pending instructions sleep. brave, r                                                 
+8913.96|Supplier#000004603       |UNITED KINGDOM           |              137063|Manufacturer#2           |OUzlvMUr7n,utLxmPNeYKSf3T24OXskxB5      |33-789-255-7342| haggle slyly above the furiously regular pinto beans. even                                          
+8877.82|Supplier#000007967       |FRANCE                   |              167966|Manufacturer#5           |A3pi1BARM4nx6R,qrwFoRPU                 |16-442-147-9345|ously foxes. express, ironic requests im                                                             
+8862.24|Supplier#000003323       |ROMANIA                  |               73322|Manufacturer#3           |W9 lYcsC9FwBqk3ItL                      |29-736-951-3710|ly pending ideas sleep about the furiously unu                                                       
+8841.59|Supplier#000005750       |ROMANIA                  |              100729|Manufacturer#5           |Erx3lAgu0g62iaHF9x50uMH4EgeN9hEG        |29-344-502-5481|gainst the pinto beans. fluffily unusual dependencies affix slyly even deposits.                     
+8781.71|Supplier#000003121       |ROMANIA                  |               13120|Manufacturer#5           |wNqTogx238ZYCamFb,50v,bj 4IbNFW9Bvw1xP  |29-707-291-5144|s wake quickly ironic ideas                                                                          
+8754.24|Supplier#000009407       |UNITED KINGDOM           |              179406|Manufacturer#4           |CHRCbkaWcf5B                            |33-903-970-9604|e ironic requests. carefully even foxes above the furious                                            
+8691.06|Supplier#000004429       |UNITED KINGDOM           |              126892|Manufacturer#2           |k,BQms5UhoAF1B2Asi,fLib                 |33-964-337-5038|efully express deposits kindle after the deposits. final                                             
+8655.99|Supplier#000006330       |RUSSIA                   |              193810|Manufacturer#2           |UozlaENr0ytKe2w6CeIEWFWn iO3S8Rae7Ou    |32-561-198-3705|symptotes use about the express dolphins. requests use after the express platelets. final, ex        
+8638.36|Supplier#000002920       |RUSSIA                   |               75398|Manufacturer#1           |Je2a8bszf3L                             |32-122-621-7549|ly quickly ironic requests. even requests whithout t                                                 
+8638.36|Supplier#000002920       |RUSSIA                   |              170402|Manufacturer#3           |Je2a8bszf3L                             |32-122-621-7549|ly quickly ironic requests. even requests whithout t                                                 
+8607.69|Supplier#000006003       |UNITED KINGDOM           |               76002|Manufacturer#2           |EH9wADcEiuenM0NR08zDwMidw,52Y2RyILEiA   |33-416-807-5206|ar, pending accounts. pending depende                                                                
+8569.52|Supplier#000005936       |RUSSIA                   |                5935|Manufacturer#5           |jXaNZ6vwnEWJ2ksLZJpjtgt0bY2a3AU         |32-644-251-7916|. regular foxes nag carefully atop the regular, silent deposits. quickly regular packages            
+8564.12|Supplier#000000033       |GERMANY                  |              110032|Manufacturer#1           |gfeKpYw3400L0SDywXA6Ya1Qmq1w6YB9f3R     |17-138-897-9374|n sauternes along the regular asymptotes are regularly along the                                     
+8553.82|Supplier#000003979       |ROMANIA                  |              143978|Manufacturer#4           |BfmVhCAnCMY3jzpjUMy4CNWs9 HzpdQR7INJU   |29-124-646-4897|ic requests wake against the blithely unusual accounts. fluffily r                                   
+8517.23|Supplier#000009529       |RUSSIA                   |               37025|Manufacturer#5           |e44R8o7JAIS9iMcr                        |32-565-297-8775|ove the even courts. furiously special platelets                                                     
+8517.23|Supplier#000009529       |RUSSIA                   |               59528|Manufacturer#2           |e44R8o7JAIS9iMcr                        |32-565-297-8775|ove the even courts. furiously special platelets                                                     
+8503.70|Supplier#000006830       |RUSSIA                   |               44325|Manufacturer#4           |BC4WFCYRUZyaIgchU 4S                    |32-147-878-5069|pades cajole. furious packages among the carefully express excuses boost furiously across th         
+8457.09|Supplier#000009456       |UNITED KINGDOM           |               19455|Manufacturer#1           |7SBhZs8gP1cJjT0Qf433YBk                 |33-858-440-4349|cing requests along the furiously unusual deposits promise among the furiously unus                  
+8441.40|Supplier#000003817       |FRANCE                   |              141302|Manufacturer#2           |hU3fz3xL78                              |16-339-356-5115|ely even ideas. ideas wake slyly furiously unusual instructions. pinto beans sleep ag                
+8432.89|Supplier#000003990       |RUSSIA                   |              191470|Manufacturer#1           |wehBBp1RQbfxAYDASS75MsywmsKHRVdkrvNe6m  |32-839-509-9301|ep furiously. packages should have to haggle slyly across the deposits. furiously regu               
+8431.40|Supplier#000002675       |ROMANIA                  |                5174|Manufacturer#1           |HJFStOu9R5NGPOegKhgbzBdyvrG2yh8w        |29-474-643-1443|ithely express pinto beans. blithely even foxes haggle. furiously regular theodol                    
+8407.04|Supplier#000005406       |RUSSIA                   |              162889|Manufacturer#4           |j7 gYF5RW8DC5UrjKC                      |32-626-152-4621|r the blithely regular packages. slyly ironic theodoli                                               
+8386.08|Supplier#000008518       |FRANCE                   |               36014|Manufacturer#3           |2jqzqqAVe9crMVGP,n9nTsQXulNLTUYoJjEDcqWV|16-618-780-7481|blithely bold pains are carefully platelets. finally regular pinto beans sleep carefully special     
+8376.52|Supplier#000005306       |UNITED KINGDOM           |              190267|Manufacturer#5           |9t8Y8 QqSIsoADPt6NLdk,TP5zyRx41oBUlgoGc9|33-632-514-7931|ly final accounts sleep special, regular requests. furiously regular                                 
+8348.74|Supplier#000008851       |FRANCE                   |               66344|Manufacturer#4           |nWxi7GwEbjhw1                           |16-796-240-2472| boldly final deposits. regular, even instructions detect slyly. fluffily unusual pinto bea          
+8338.58|Supplier#000007269       |FRANCE                   |               17268|Manufacturer#4           |ZwhJSwABUoiB04,3                        |16-267-277-4365|iously final accounts. even pinto beans cajole slyly regular                                         
+8328.46|Supplier#000001744       |ROMANIA                  |               69237|Manufacturer#5           |oLo3fV64q2,FKHa3p,qHnS7Yzv,ps8          |29-330-728-5873|ep carefully-- even, careful packages are slyly along t                                              
+8307.93|Supplier#000003142       |GERMANY                  |               18139|Manufacturer#1           |dqblvV8dCNAorGlJ                        |17-595-447-6026|olites wake furiously regular decoys. final requests nod                                             
+8231.61|Supplier#000009558       |RUSSIA                   |              192000|Manufacturer#2           |mcdgen,yT1iJDHDS5fV                     |32-762-137-5858| foxes according to the furi                                                                         
+8152.61|Supplier#000002731       |ROMANIA                  |               15227|Manufacturer#4           | nluXJCuY1tu                            |29-805-463-2030| special requests. even, regular warhorses affix among the final gr                                  
+8109.09|Supplier#000009186       |FRANCE                   |               99185|Manufacturer#1           |wgfosrVPexl9pEXWywaqlBMDYYf             |16-668-570-1402|tions haggle slyly about the sil                                                                     
+8102.62|Supplier#000003347       |UNITED KINGDOM           |               18344|Manufacturer#5           |m CtXS2S16i                             |33-454-274-8532|egrate with the slyly bold instructions. special foxes haggle silently among the                     
+8046.07|Supplier#000008780       |FRANCE                   |              191222|Manufacturer#3           |AczzuE0UK9osj ,Lx0Jmh                   |16-473-215-6395|onic platelets cajole after the regular instructions. permanently bold excuses                       
+8042.09|Supplier#000003245       |RUSSIA                   |              135705|Manufacturer#4           |Dh8Ikg39onrbOL4DyTfGw8a9oKUX3d9Y        |32-836-132-8872|osits. packages cajole slyly. furiously regular deposits cajole slyly. q                             
+8042.09|Supplier#000003245       |RUSSIA                   |              150729|Manufacturer#1           |Dh8Ikg39onrbOL4DyTfGw8a9oKUX3d9Y        |32-836-132-8872|osits. packages cajole slyly. furiously regular deposits cajole slyly. q                             
+7992.40|Supplier#000006108       |FRANCE                   |              118574|Manufacturer#1           |8tBydnTDwUqfBfFV4l3                     |16-974-998-8937| ironic ideas? fluffily even instructions wake. blithel                                              
+7980.65|Supplier#000001288       |FRANCE                   |               13784|Manufacturer#4           |zE,7HgVPrCn                             |16-646-464-8247|ully bold courts. escapades nag slyly. furiously fluffy theodo                                       
+7950.37|Supplier#000008101       |GERMANY                  |               33094|Manufacturer#5           |kkYvL6IuvojJgTNG IKkaXQDYgx8ILohj       |17-627-663-8014|arefully unusual requests x-ray above the quickly final deposits.                                    
+7937.93|Supplier#000009012       |ROMANIA                  |               83995|Manufacturer#2           |iUiTziH,Ek3i4lwSgunXMgrcTzwdb           |29-250-925-9690|to the blithely ironic deposits nag sly                                                              
+7914.45|Supplier#000001013       |RUSSIA                   |              125988|Manufacturer#2           |riRcntps4KEDtYScjpMIWeYF6mNnR           |32-194-698-3365| busily bold packages are dolphi                                                                     
+7912.91|Supplier#000004211       |GERMANY                  |              159180|Manufacturer#5           |2wQRVovHrm3,v03IKzfTd,1PYsFXQFFOG       |17-266-947-7315|ay furiously regular platelets. cou                                                                  
+7912.91|Supplier#000004211       |GERMANY                  |              184210|Manufacturer#4           |2wQRVovHrm3,v03IKzfTd,1PYsFXQFFOG       |17-266-947-7315|ay furiously regular platelets. cou                                                                  
+7894.56|Supplier#000007981       |GERMANY                  |               85472|Manufacturer#4           |NSJ96vMROAbeXP                          |17-963-404-3760|ic platelets affix after the furiously                                                               
+7887.08|Supplier#000009792       |GERMANY                  |              164759|Manufacturer#3           |Y28ITVeYriT3kIGdV2K8fSZ V2UqT5H1Otz     |17-988-938-4296|ckly around the carefully fluffy theodolites. slyly ironic pack                                      
+7871.50|Supplier#000007206       |RUSSIA                   |              104695|Manufacturer#1           |3w fNCnrVmvJjE95sgWZzvW                 |32-432-452-7731|ironic requests. furiously final theodolites cajole. final, express packages sleep. quickly reg      
+7852.45|Supplier#000005864       |RUSSIA                   |                8363|Manufacturer#4           |WCNfBPZeSXh3h,c                         |32-454-883-3821|usly unusual pinto beans. brave ideas sleep carefully quickly ironi                                  
+7850.66|Supplier#000001518       |UNITED KINGDOM           |               86501|Manufacturer#1           |ONda3YJiHKJOC                           |33-730-383-3892|ifts haggle fluffily pending pai                                                                     
+7843.52|Supplier#000006683       |FRANCE                   |               11680|Manufacturer#4           |2Z0JGkiv01Y00oCFwUGfviIbhzCdy           |16-464-517-8943| express, final pinto beans x-ray slyly asymptotes. unusual, unusual                                 
diff --git a/examples/tpch/answers_sf1/q20.tbl b/examples/tpch/answers_sf1/q20.tbl
new file mode 100644
index 000000000..41e0dbc4c
--- /dev/null
+++ b/examples/tpch/answers_sf1/q20.tbl
@@ -0,0 +1,187 @@
+s_name                   |s_address                               
+Supplier#000000020       |iybAE,RmTymrZVYaFZva2SH,j               
+Supplier#000000091       |YV45D7TkfdQanOOZ7q9QxkyGUapU1oOWU6q3    
+Supplier#000000205       |rF uV8d0JNEk                            
+Supplier#000000285       |Br7e1nnt1yxrw6ImgpJ7YdhFDjuBf           
+Supplier#000000287       |7a9SP7qW5Yku5PvSg                       
+Supplier#000000354       |w8fOo5W,aS                              
+Supplier#000000378       |FfbhyCxWvcPrO8ltp9                      
+Supplier#000000402       |i9Sw4DoyMhzhKXCH9By,AYSgmD              
+Supplier#000000530       |0qwCMwobKY OcmLyfRXlagA8ukENJv,         
+Supplier#000000555       |TfB,a5bfl3Ah 3Z 74GqnNs6zKVGM           
+Supplier#000000640       |mvvtlQKsTOsJj5Ihk7,cq                   
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+Supplier#000000887       |urEaTejH5POADP2ARrf                     
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+Supplier#000001263       |rQWr6nf8ZhB2TAiIDIvo5Io                 
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+Supplier#000001602       |uKNWIeafaM644                           
+Supplier#000001626       |UhxNRzUu1dtFmp0                         
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+Supplier#000001700       |7hMlCof1Y5zLFg                          
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+Supplier#000001806       |M934fuZSnLW                             
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+Supplier#000002218       |nODZw5q4dx kp0K5                        
+Supplier#000002243       |nSOEV3JeOU79                            
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+Supplier#000003894       |vvGC rameLOk                            
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+Supplier#000004346       |S3076LEOwo                              
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+Supplier#000004975       |GPq5PMKY6Wy                             
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+Supplier#000005257       |f9g8SEHB7obMj3QXAjXS2vfYY22             
+Supplier#000005300       |gXG28YqpxU                              
+Supplier#000005323       |tMCkdqbDoyNo8vMIkzjBqYexoRAuv,T6 qzcu   
+Supplier#000005386       |Ub6AAfHpWLWP                            
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+Supplier#000005505       |d2sbjG43KwMPX                           
+Supplier#000005506       |On f5ypzoWgB                            
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+Supplier#000005736       |2dq XTYhtYWSfp                          
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+Supplier#000006099       |aZilwQKYDTVPoK                          
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+Supplier#000006478       |bQYPnj9lpmW3U                           
+Supplier#000006521       |b9 2zjHzxR                              
+Supplier#000006642       |N,CUclSqRLJcS8zQ                        
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+Supplier#000006669       |NQ4Yryj624p7K53                         
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+Supplier#000006946       |To6Slo0GJTqcIvD                         
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+Supplier#000007098       |G3j8g0KC4OcbAu2OVoPHrXQWMCUdjq8wgCHOExu 
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+Supplier#000007398       |V8eE6oZ00OFNU,                          
+Supplier#000007402       |4UVv58ery1rjmqSR5                       
+Supplier#000007448       |yhhpWiJi7EJ6Q5VCaQ                      
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+Supplier#000007561       |rMcFg2530VC                             
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+Supplier#000007760       |JsPE18PvcdFTK                           
+Supplier#000007801       |69fi,U1r6enUb                           
+Supplier#000007865       |5cDGCS,T6N                              
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+Supplier#000007926       |ErzCF80K9Uy                             
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+Supplier#000008224       |TWxt9f,LVER                             
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+Supplier#000008243       |2AyePMkDqmzVzjGTizXthFLo8h EiudCMxOmIIG 
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+Supplier#000009278       |RqYTzgxj93CLX 0mcYfCENOefD              
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+Supplier#000009430       |igRqmneFt                               
+Supplier#000009549       |h3RVchUf8MzY46IzbZ0ng09                 
+Supplier#000009601       |51m637bO,Rw5DnHWFUvLacRx9               
+Supplier#000009709       |rRnCbHYgDgl9PZYnyWKVYSUW0vKg            
+Supplier#000009753       |wLhVEcRmd7PkJF4FBnGK7Z                  
+Supplier#000009799       | 4wNjXGa4OKWl                           
+Supplier#000009811       |E3iuyq7UnZxU7oPZIe2Gu6                  
+Supplier#000009812       |APFRMy3lCbgFga53n5t9DxzFPQPgnjrGt32     
+Supplier#000009846       |57sNwJJ3PtBDu,hMPP5QvpcOcSNRXn3PypJJrh  
+Supplier#000009899       |7XdpAHrzr1t,UQFZE                       
+Supplier#000009974       |7wJ,J5DKcxSU4Kp1cQLpbcAvB5AsvKT         
diff --git a/examples/tpch/answers_sf1/q21.tbl b/examples/tpch/answers_sf1/q21.tbl
new file mode 100644
index 000000000..f944ca656
--- /dev/null
+++ b/examples/tpch/answers_sf1/q21.tbl
@@ -0,0 +1,101 @@
+s_name                   |numwait               
+Supplier#000002829       |                    20
+Supplier#000005808       |                    18
+Supplier#000000262       |                    17
+Supplier#000000496       |                    17
+Supplier#000002160       |                    17
+Supplier#000002301       |                    17
+Supplier#000002540       |                    17
+Supplier#000003063       |                    17
+Supplier#000005178       |                    17
+Supplier#000008331       |                    17
+Supplier#000002005       |                    16
+Supplier#000002095       |                    16
+Supplier#000005799       |                    16
+Supplier#000005842       |                    16
+Supplier#000006450       |                    16
+Supplier#000006939       |                    16
+Supplier#000009200       |                    16
+Supplier#000009727       |                    16
+Supplier#000000486       |                    15
+Supplier#000000565       |                    15
+Supplier#000001046       |                    15
+Supplier#000001047       |                    15
+Supplier#000001161       |                    15
+Supplier#000001336       |                    15
+Supplier#000001435       |                    15
+Supplier#000003075       |                    15
+Supplier#000003335       |                    15
+Supplier#000005649       |                    15
+Supplier#000006027       |                    15
+Supplier#000006795       |                    15
+Supplier#000006800       |                    15
+Supplier#000006824       |                    15
+Supplier#000007131       |                    15
+Supplier#000007382       |                    15
+Supplier#000008913       |                    15
+Supplier#000009787       |                    15
+Supplier#000000633       |                    14
+Supplier#000001960       |                    14
+Supplier#000002323       |                    14
+Supplier#000002490       |                    14
+Supplier#000002993       |                    14
+Supplier#000003101       |                    14
+Supplier#000004489       |                    14
+Supplier#000005435       |                    14
+Supplier#000005583       |                    14
+Supplier#000005774       |                    14
+Supplier#000007579       |                    14
+Supplier#000008180       |                    14
+Supplier#000008695       |                    14
+Supplier#000009224       |                    14
+Supplier#000000357       |                    13
+Supplier#000000436       |                    13
+Supplier#000000610       |                    13
+Supplier#000000788       |                    13
+Supplier#000000889       |                    13
+Supplier#000001062       |                    13
+Supplier#000001498       |                    13
+Supplier#000002056       |                    13
+Supplier#000002312       |                    13
+Supplier#000002344       |                    13
+Supplier#000002596       |                    13
+Supplier#000002615       |                    13
+Supplier#000002978       |                    13
+Supplier#000003048       |                    13
+Supplier#000003234       |                    13
+Supplier#000003727       |                    13
+Supplier#000003806       |                    13
+Supplier#000004472       |                    13
+Supplier#000005236       |                    13
+Supplier#000005906       |                    13
+Supplier#000006241       |                    13
+Supplier#000006326       |                    13
+Supplier#000006384       |                    13
+Supplier#000006394       |                    13
+Supplier#000006624       |                    13
+Supplier#000006629       |                    13
+Supplier#000006682       |                    13
+Supplier#000006737       |                    13
+Supplier#000006825       |                    13
+Supplier#000007021       |                    13
+Supplier#000007417       |                    13
+Supplier#000007497       |                    13
+Supplier#000007602       |                    13
+Supplier#000008134       |                    13
+Supplier#000008234       |                    13
+Supplier#000009435       |                    13
+Supplier#000009436       |                    13
+Supplier#000009564       |                    13
+Supplier#000009896       |                    13
+Supplier#000000379       |                    12
+Supplier#000000673       |                    12
+Supplier#000000762       |                    12
+Supplier#000000811       |                    12
+Supplier#000000821       |                    12
+Supplier#000001337       |                    12
+Supplier#000001916       |                    12
+Supplier#000001925       |                    12
+Supplier#000002039       |                    12
+Supplier#000002357       |                    12
+Supplier#000002483       |                    12
diff --git a/examples/tpch/answers_sf1/q22.tbl b/examples/tpch/answers_sf1/q22.tbl
new file mode 100644
index 000000000..de4bb472c
--- /dev/null
+++ b/examples/tpch/answers_sf1/q22.tbl
@@ -0,0 +1,8 @@
+cntrycode      |numcust               |totacctbal                               
+13             |                   888|6737713.99
+17             |                   861|6460573.72
+18             |                   964|7236687.40
+23             |                   892|6701457.95
+29             |                   948|7158866.63
+30             |                   909|6808436.13
+31             |                   922|6806670.18
diff --git a/examples/tpch/answers_sf1/q3.tbl b/examples/tpch/answers_sf1/q3.tbl
new file mode 100644
index 000000000..69771b8be
--- /dev/null
+++ b/examples/tpch/answers_sf1/q3.tbl
@@ -0,0 +1,11 @@
+l_orderkey            |revenue                                  |o_orderdat|o_shippriority      
+               2456423|406181.01|1995-03-05|                   0
+               3459808|405838.70|1995-03-04|                   0
+                492164|390324.06|1995-02-19|                   0
+               1188320|384537.94|1995-03-09|                   0
+               2435712|378673.06|1995-02-26|                   0
+               4878020|378376.80|1995-03-12|                   0
+               5521732|375153.92|1995-03-13|                   0
+               2628192|373133.31|1995-02-22|                   0
+                993600|371407.46|1995-03-05|                   0
+               2300070|367371.15|1995-03-13|                   0
diff --git a/examples/tpch/answers_sf1/q4.tbl b/examples/tpch/answers_sf1/q4.tbl
new file mode 100644
index 000000000..91bc1da24
--- /dev/null
+++ b/examples/tpch/answers_sf1/q4.tbl
@@ -0,0 +1,6 @@
+o_orderpriority|order_count           
+1-URGENT       |                 10594
+2-HIGH         |                 10476
+3-MEDIUM       |                 10410
+4-NOT SPECIFIED|                 10556
+5-LOW          |                 10487
diff --git a/examples/tpch/answers_sf1/q5.tbl b/examples/tpch/answers_sf1/q5.tbl
new file mode 100644
index 000000000..5dac463df
--- /dev/null
+++ b/examples/tpch/answers_sf1/q5.tbl
@@ -0,0 +1,6 @@
+n_name                   |revenue                                  
+INDONESIA                |55502041.17
+VIETNAM                  |55295087.00
+CHINA                    |53724494.26
+INDIA                    |52035512.00
+JAPAN                    |45410175.70
diff --git a/examples/tpch/answers_sf1/q6.tbl b/examples/tpch/answers_sf1/q6.tbl
new file mode 100644
index 000000000..703a8084c
--- /dev/null
+++ b/examples/tpch/answers_sf1/q6.tbl
@@ -0,0 +1,2 @@
+revenue                                  
+123141078.23
diff --git a/examples/tpch/answers_sf1/q7.tbl b/examples/tpch/answers_sf1/q7.tbl
new file mode 100644
index 000000000..7164bfac2
--- /dev/null
+++ b/examples/tpch/answers_sf1/q7.tbl
@@ -0,0 +1,5 @@
+supp_nation              |cust_nation              |l_year              |revenue                                  
+FRANCE                   |GERMANY                  |                1995|54639732.73
+FRANCE                   |GERMANY                  |                1996|54633083.31
+GERMANY                  |FRANCE                   |                1995|52531746.67
+GERMANY                  |FRANCE                   |                1996|52520549.02
diff --git a/examples/tpch/answers_sf1/q8.tbl b/examples/tpch/answers_sf1/q8.tbl
new file mode 100644
index 000000000..618439d1a
--- /dev/null
+++ b/examples/tpch/answers_sf1/q8.tbl
@@ -0,0 +1,3 @@
+o_year              |mkt_share                                
+                1995|0.03
+                1996|0.04
diff --git a/examples/tpch/answers_sf1/q9.tbl b/examples/tpch/answers_sf1/q9.tbl
new file mode 100644
index 000000000..16ab17f13
--- /dev/null
+++ b/examples/tpch/answers_sf1/q9.tbl
@@ -0,0 +1,176 @@
+nation                   |o_year              |sum_profit                               
+ALGERIA                  |                1998|27136900.18
+ALGERIA                  |                1997|48611833.50
+ALGERIA                  |                1996|48285482.68
+ALGERIA                  |                1995|44402273.60
+ALGERIA                  |                1994|48694008.07
+ALGERIA                  |                1993|46044207.78
+ALGERIA                  |                1992|45636849.49
+ARGENTINA                |                1998|28341663.78
+ARGENTINA                |                1997|47143964.12
+ARGENTINA                |                1996|45255278.60
+ARGENTINA                |                1995|45631769.21
+ARGENTINA                |                1994|48268856.35
+ARGENTINA                |                1993|48605593.62
+ARGENTINA                |                1992|46654240.75
+BRAZIL                   |                1998|26527736.40
+BRAZIL                   |                1997|45640660.77
+BRAZIL                   |                1996|45090647.16
+BRAZIL                   |                1995|44015888.51
+BRAZIL                   |                1994|44854218.89
+BRAZIL                   |                1993|45766603.74
+BRAZIL                   |                1992|45280216.80
+CANADA                   |                1998|26828985.39
+CANADA                   |                1997|44849954.32
+CANADA                   |                1996|46307936.11
+CANADA                   |                1995|47311993.04
+CANADA                   |                1994|46691491.96
+CANADA                   |                1993|46634791.11
+CANADA                   |                1992|45873849.69
+CHINA                    |                1998|27510180.17
+CHINA                    |                1997|46123865.41
+CHINA                    |                1996|49532807.06
+CHINA                    |                1995|46734651.48
+CHINA                    |                1994|46397896.61
+CHINA                    |                1993|49634673.95
+CHINA                    |                1992|46949457.64
+EGYPT                    |                1998|28401491.80
+EGYPT                    |                1997|47674857.68
+EGYPT                    |                1996|47745727.55
+EGYPT                    |                1995|45897160.68
+EGYPT                    |                1994|47194895.23
+EGYPT                    |                1993|49133627.65
+EGYPT                    |                1992|47000574.50
+ETHIOPIA                 |                1998|25135046.14
+ETHIOPIA                 |                1997|43010596.08
+ETHIOPIA                 |                1996|43636287.19
+ETHIOPIA                 |                1995|43575757.33
+ETHIOPIA                 |                1994|41597208.53
+ETHIOPIA                 |                1993|42622804.16
+ETHIOPIA                 |                1992|44385735.68
+FRANCE                   |                1998|26210392.28
+FRANCE                   |                1997|42392969.47
+FRANCE                   |                1996|43306317.97
+FRANCE                   |                1995|46377408.43
+FRANCE                   |                1994|43447352.99
+FRANCE                   |                1993|43729961.06
+FRANCE                   |                1992|44052308.43
+GERMANY                  |                1998|25991257.11
+GERMANY                  |                1997|43968355.81
+GERMANY                  |                1996|45882074.80
+GERMANY                  |                1995|43314338.31
+GERMANY                  |                1994|44616995.44
+GERMANY                  |                1993|45126645.91
+GERMANY                  |                1992|44361141.21
+INDIA                    |                1998|29626417.24
+INDIA                    |                1997|51386111.34
+INDIA                    |                1996|47571018.51
+INDIA                    |                1995|49344062.28
+INDIA                    |                1994|50106952.43
+INDIA                    |                1993|48112766.70
+INDIA                    |                1992|47914303.12
+INDONESIA                |                1998|27734909.68
+INDONESIA                |                1997|44593812.99
+INDONESIA                |                1996|44746729.81
+INDONESIA                |                1995|45593622.70
+INDONESIA                |                1994|45988483.88
+INDONESIA                |                1993|46147963.79
+INDONESIA                |                1992|45185777.07
+IRAN                     |                1998|26661608.93
+IRAN                     |                1997|45019114.17
+IRAN                     |                1996|45891397.10
+IRAN                     |                1995|44414285.23
+IRAN                     |                1994|43696360.48
+IRAN                     |                1993|45362775.81
+IRAN                     |                1992|43052338.41
+IRAQ                     |                1998|31188498.19
+IRAQ                     |                1997|48585307.52
+IRAQ                     |                1996|50036593.84
+IRAQ                     |                1995|48774801.73
+IRAQ                     |                1994|48795847.23
+IRAQ                     |                1993|47435691.51
+IRAQ                     |                1992|47562355.66
+JAPAN                    |                1998|24694102.17
+JAPAN                    |                1997|42377052.35
+JAPAN                    |                1996|40267778.91
+JAPAN                    |                1995|40925317.47
+JAPAN                    |                1994|41159518.31
+JAPAN                    |                1993|39589074.28
+JAPAN                    |                1992|39113493.91
+JORDAN                   |                1998|23489867.79
+JORDAN                   |                1997|41615962.66
+JORDAN                   |                1996|41860855.47
+JORDAN                   |                1995|39931672.09
+JORDAN                   |                1994|40707555.46
+JORDAN                   |                1993|39060405.47
+JORDAN                   |                1992|41657604.27
+KENYA                    |                1998|25566337.43
+KENYA                    |                1997|43108847.90
+KENYA                    |                1996|43482953.54
+KENYA                    |                1995|42517988.98
+KENYA                    |                1994|43612479.45
+KENYA                    |                1993|42724038.76
+KENYA                    |                1992|43217106.21
+MOROCCO                  |                1998|24915496.88
+MOROCCO                  |                1997|42698382.85
+MOROCCO                  |                1996|42986113.50
+MOROCCO                  |                1995|42316089.16
+MOROCCO                  |                1994|43458604.60
+MOROCCO                  |                1993|42672288.07
+MOROCCO                  |                1992|42800781.64
+MOZAMBIQUE               |                1998|28279876.03
+MOZAMBIQUE               |                1997|51159216.23
+MOZAMBIQUE               |                1996|48072525.06
+MOZAMBIQUE               |                1995|48905200.60
+MOZAMBIQUE               |                1994|46092076.28
+MOZAMBIQUE               |                1993|48555926.27
+MOZAMBIQUE               |                1992|47809075.12
+PERU                     |                1998|26713966.27
+PERU                     |                1997|48324008.60
+PERU                     |                1996|50310008.86
+PERU                     |                1995|49647080.96
+PERU                     |                1994|46420910.28
+PERU                     |                1993|51536906.25
+PERU                     |                1992|47711665.31
+ROMANIA                  |                1998|27271993.10
+ROMANIA                  |                1997|45063059.20
+ROMANIA                  |                1996|47492335.03
+ROMANIA                  |                1995|45710636.29
+ROMANIA                  |                1994|46088041.11
+ROMANIA                  |                1993|47515092.56
+ROMANIA                  |                1992|44111439.80
+RUSSIA                   |                1998|27935323.73
+RUSSIA                   |                1997|48222347.29
+RUSSIA                   |                1996|47553559.49
+RUSSIA                   |                1995|46755990.10
+RUSSIA                   |                1994|48000515.62
+RUSSIA                   |                1993|48569624.51
+RUSSIA                   |                1992|47672831.53
+SAUDI ARABIA             |                1998|27113516.84
+SAUDI ARABIA             |                1997|46690468.96
+SAUDI ARABIA             |                1996|47775782.67
+SAUDI ARABIA             |                1995|46657107.83
+SAUDI ARABIA             |                1994|48181672.81
+SAUDI ARABIA             |                1993|45692556.44
+SAUDI ARABIA             |                1992|48924913.27
+UNITED KINGDOM           |                1998|26366682.88
+UNITED KINGDOM           |                1997|44518130.19
+UNITED KINGDOM           |                1996|45539729.62
+UNITED KINGDOM           |                1995|46845879.34
+UNITED KINGDOM           |                1994|43081609.57
+UNITED KINGDOM           |                1993|44770146.76
+UNITED KINGDOM           |                1992|44123402.55
+UNITED STATES            |                1998|27826593.68
+UNITED STATES            |                1997|46638572.36
+UNITED STATES            |                1996|46688280.55
+UNITED STATES            |                1995|48951591.62
+UNITED STATES            |                1994|45099092.06
+UNITED STATES            |                1993|46181600.53
+UNITED STATES            |                1992|46168214.09
+VIETNAM                  |                1998|27281931.00
+VIETNAM                  |                1997|48735914.18
+VIETNAM                  |                1996|47824595.90
+VIETNAM                  |                1995|48235135.80
+VIETNAM                  |                1994|47729256.33
+VIETNAM                  |                1993|45352676.87
+VIETNAM                  |                1992|47846355.65
diff --git a/examples/tpch/q02_minimum_cost_supplier.py b/examples/tpch/q02_minimum_cost_supplier.py
index 7390d0892..47961d2ef 100644
--- a/examples/tpch/q02_minimum_cost_supplier.py
+++ b/examples/tpch/q02_minimum_cost_supplier.py
@@ -32,6 +32,7 @@
 import datafusion
 from datafusion import SessionContext, col, lit
 from datafusion import functions as F
+from datafusion.expr import Window
 from util import get_data_path
 
 # This is the part we're looking for. Values selected here differ from the spec in order to run
@@ -106,11 +107,8 @@
 window_frame = datafusion.WindowFrame("rows", None, None)
 df = df.with_column(
     "min_cost",
-    F.window(
-        "min",
-        [col("ps_supplycost")],
-        partition_by=[col("ps_partkey")],
-        window_frame=window_frame,
+    F.min(col("ps_supplycost")).over(
+        Window(partition_by=[col("ps_partkey")], window_frame=window_frame)
     ),
 )
 
diff --git a/examples/tpch/q11_important_stock_identification.py b/examples/tpch/q11_important_stock_identification.py
index 22829ab7c..de309fa64 100644
--- a/examples/tpch/q11_important_stock_identification.py
+++ b/examples/tpch/q11_important_stock_identification.py
@@ -29,6 +29,7 @@
 
 from datafusion import SessionContext, WindowFrame, col, lit
 from datafusion import functions as F
+from datafusion.expr import Window
 from util import get_data_path
 
 NATION = "GERMANY"
@@ -71,7 +72,7 @@
 window_frame = WindowFrame("rows", None, None)
 
 df = df.with_column(
-    "total_value", F.window("sum", [col("value")], window_frame=window_frame)
+    "total_value", F.sum(col("value")).over(Window(window_frame=window_frame))
 )
 
 # Limit to the parts for which there is a significant value based on the fraction of the total
diff --git a/examples/tpch/q15_top_supplier.py b/examples/tpch/q15_top_supplier.py
index c321048f2..5128937a7 100644
--- a/examples/tpch/q15_top_supplier.py
+++ b/examples/tpch/q15_top_supplier.py
@@ -31,6 +31,7 @@
 import pyarrow as pa
 from datafusion import SessionContext, WindowFrame, col, lit
 from datafusion import functions as F
+from datafusion.expr import Window
 from util import get_data_path
 
 DATE = "1996-01-01"
@@ -70,7 +71,8 @@
 # Use a window function to find the maximum revenue across the entire dataframe
 window_frame = WindowFrame("rows", None, None)
 df = df.with_column(
-    "max_revenue", F.window("max", [col("total_revenue")], window_frame=window_frame)
+    "max_revenue",
+    F.max(col("total_revenue")).over(Window(window_frame=window_frame)),
 )
 
 # Find all suppliers whose total revenue is the same as the maximum
diff --git a/examples/tpch/q17_small_quantity_order.py b/examples/tpch/q17_small_quantity_order.py
index 6d76fe506..5ccb38422 100644
--- a/examples/tpch/q17_small_quantity_order.py
+++ b/examples/tpch/q17_small_quantity_order.py
@@ -30,6 +30,7 @@
 
 from datafusion import SessionContext, WindowFrame, col, lit
 from datafusion import functions as F
+from datafusion.expr import Window
 from util import get_data_path
 
 BRAND = "Brand#23"
@@ -58,11 +59,8 @@
 window_frame = WindowFrame("rows", None, None)
 df = df.with_column(
     "avg_quantity",
-    F.window(
-        "avg",
-        [col("l_quantity")],
-        window_frame=window_frame,
-        partition_by=[col("l_partkey")],
+    F.avg(col("l_quantity")).over(
+        Window(partition_by=[col("l_partkey")], window_frame=window_frame)
     ),
 )
 
diff --git a/examples/tpch/q21_suppliers_kept_orders_waiting.py b/examples/tpch/q21_suppliers_kept_orders_waiting.py
index 619c4406b..4ee9d3733 100644
--- a/examples/tpch/q21_suppliers_kept_orders_waiting.py
+++ b/examples/tpch/q21_suppliers_kept_orders_waiting.py
@@ -81,16 +81,12 @@
     [col("o_orderkey")],
     [
         F.array_agg(col("l_suppkey"), distinct=True).alias("all_suppliers"),
-        F.array_agg(col("failed_supp"), distinct=True).alias("failed_suppliers"),
+        F.array_agg(
+            col("failed_supp"), filter=col("failed_supp").is_not_null(), distinct=True
+        ).alias("failed_suppliers"),
     ],
 )
 
-# Remove the null entries that will get returned by array_agg so we can test to see where we only
-# have a single failed supplier in a multiple supplier order
-df = df.with_column(
-    "failed_suppliers", F.array_remove(col("failed_suppliers"), lit(None))
-)
-
 # This is the check described above which will identify single failed supplier in a multiple
 # supplier order.
 df = df.filter(F.array_length(col("failed_suppliers")) == lit(1)).filter(
diff --git a/examples/tpch/q22_global_sales_opportunity.py b/examples/tpch/q22_global_sales_opportunity.py
index c4d115b74..a2d41b215 100644
--- a/examples/tpch/q22_global_sales_opportunity.py
+++ b/examples/tpch/q22_global_sales_opportunity.py
@@ -28,6 +28,7 @@
 
 from datafusion import SessionContext, WindowFrame, col, lit
 from datafusion import functions as F
+from datafusion.expr import Window
 from util import get_data_path
 
 NATION_CODES = [13, 31, 23, 29, 30, 18, 17]
@@ -55,7 +56,8 @@
 # current row. We want our frame to cover the entire data frame.
 window_frame = WindowFrame("rows", None, None)
 df = df.with_column(
-    "avg_balance", F.window("avg", [col("c_acctbal")], window_frame=window_frame)
+    "avg_balance",
+    F.avg(col("c_acctbal")).over(Window(window_frame=window_frame)),
 )
 
 df.show()
diff --git a/examples/tpch/util.py b/examples/tpch/util.py
index ec53bcd15..0b52c4e09 100644
--- a/examples/tpch/util.py
+++ b/examples/tpch/util.py
@@ -31,4 +31,4 @@ def get_data_path(filename: str) -> Path:
 def get_answer_file(answer_file: str) -> Path:
     path = Path(__file__).resolve().parent
 
-    return path / "../../benchmarks/tpch/data/answers" / f"{answer_file}.out"
+    return path / "answers_sf1" / f"{answer_file}.tbl"
diff --git a/pyproject.toml b/pyproject.toml
index 5a5128a2f..327199d1a 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -25,7 +25,7 @@ description = "Build and run queries against data"
 readme = "README.md"
 license = { file = "LICENSE.txt" }
 requires-python = ">=3.10"
-keywords = ["datafusion", "dataframe", "rust", "query-engine"]
+keywords = ["dataframe", "datafusion", "query-engine", "rust"]
 classifiers = [
   "Development Status :: 2 - Pre-Alpha",
   "Intended Audience :: Developers",
@@ -59,10 +59,11 @@ repository = "https://github.com/apache/datafusion-python"
 profile = "black"
 
 [tool.maturin]
+manifest-path = "crates/core/Cargo.toml"
 python-source = "python"
 module-name = "datafusion._internal"
 include = [{ path = "Cargo.lock", format = "sdist" }]
-exclude = [".github/**", "ci/**", ".asf.yaml"]
+exclude = [".asf.yaml", ".github/**", "ci/**"]
 # Require Cargo.lock is up to date
 locked = true
 features = ["substrait"]
@@ -70,6 +71,9 @@ features = ["substrait"]
 [tool.pytest.ini_options]
 asyncio_mode = "auto"
 asyncio_default_fixture_loop_scope = "function"
+addopts = "--doctest-modules"
+doctest_optionflags = ["NORMALIZE_WHITESPACE", "ELLIPSIS"]
+testpaths = ["python/tests", "python/datafusion"]
 
 # Enable docstring linting using the google style guide
 [tool.ruff.lint]
@@ -77,19 +81,18 @@ select = ["ALL"]
 ignore = [
   "A001",    # Allow using words like min as variable names
   "A002",    # Allow using words like filter as variable names
+  "A005",    # Allow module named io
   "ANN401",  # Allow Any for wrapper classes
   "COM812",  # Recommended to ignore these rules when using with ruff-format
-  "FIX002",  # Allow TODO lines - consider removing at some point
   "FBT001",  # Allow boolean positional args
   "FBT002",  # Allow boolean positional args
+  "FIX002",  # Allow TODO lines - consider removing at some point
   "ISC001",  # Recommended to ignore these rules when using with ruff-format
+  "N812",    # Allow importing functions as `F`
+  "PLR0913", # Allow many arguments in function definition
   "SLF001",  # Allow accessing private members
   "TD002",   # Do not require author names in TODO statements
   "TD003",   # Allow TODO lines
-  "PLR0913", # Allow many arguments in function definition
-  "PD901",   # Allow variable name df
-  "N812",    # Allow importing functions as `F`
-  "A005",    # Allow module named io
 ]
 
 [tool.ruff.lint.pydocstyle]
@@ -99,7 +102,7 @@ convention = "google"
 max-doc-length = 88
 
 [tool.ruff.lint.flake8-boolean-trap]
-extend-allowed-calls = ["lit", "datafusion.lit"]
+extend-allowed-calls = ["datafusion.lit", "lit"]
 
 # Disable docstring checking for these directories
 [tool.ruff.lint.per-file-ignores]
@@ -108,68 +111,77 @@ extend-allowed-calls = ["lit", "datafusion.lit"]
   "ARG",
   "BLE001",
   "D",
-  "S101",
-  "SLF",
   "PD",
+  "PLC0415",
+  "PLR0913",
   "PLR2004",
+  "PT004",
   "PT011",
   "RUF015",
+  "S101",
   "S608",
-  "PLR0913",
-  "PT004",
+  "SLF",
 ]
 "examples/*" = [
-  "D",
-  "W505",
-  "E501",
-  "T201",
-  "S101",
-  "PLR2004",
   "ANN001",
   "ANN202",
-  "INP001",
+  "D",
   "DTZ007",
+  "E501",
+  "INP001",
+  "PLR2004",
   "RUF015",
+  "S101",
+  "T201",
+  "W505",
 ]
 "dev/*" = [
+  "ANN001",
+  "C",
   "D",
   "E",
-  "T",
-  "S",
+  "ERA001",
+  "EXE",
+  "N817",
   "PLR",
-  "C",
+  "S",
   "SIM",
+  "T",
   "UP",
-  "EXE",
-  "N817",
-  "ERA001",
-  "ANN001",
 ]
 "benchmarks/*" = [
+  "ANN001",
+  "BLE",
   "D",
+  "E",
+  "ERA001",
+  "EXE",
   "F",
-  "T",
-  "BLE",
   "FURB",
+  "INP001",
   "PLR",
-  "E",
-  "TD",
-  "TRY",
   "S",
   "SIM",
-  "EXE",
+  "T",
+  "TD",
+  "TRY",
   "UP",
-  "ERA001",
-  "ANN001",
-  "INP001",
 ]
 "docs/*" = ["D"]
-"docs/source/conf.py" = ["ERA001", "ANN001", "INP001"]
+"docs/source/conf.py" = ["ANN001", "ERA001", "INP001"]
 
+# CI and pre-commit invoke codespell with different paths, so we have a little
+# redundancy here, and we intentionally drop python in the path.
 [tool.codespell]
-skip = ["./target", "uv.lock", "./python/tests/test_functions.py"]
+skip = [
+  "*/tests/test_functions.py",
+  "*/target",
+  "./uv.lock",
+  "uv.lock",
+  "*/tpch/answers_sf1/*",
+]
 count = true
-ignore-words-list = ["ans", "IST"]
+ignore-words-list = ["IST", "ans"]
 
 [dependency-groups]
 dev = [
@@ -182,10 +194,10 @@ dev = [
   "pre-commit>=4.3.0",
   "pyarrow>=19.0.0",
   "pygithub==2.5.0",
-  "pytest>=7.4.4",
   "pytest-asyncio>=0.23.3",
+  "pytest>=7.4.4",
   "pyyaml>=6.0.3",
-  "ruff>=0.9.1",
+  "ruff>=0.15.1",
   "toml>=0.10.2",
 ]
 docs = [
@@ -196,6 +208,6 @@ docs = [
   "pickleshare>=0.7.5",
   "pydata-sphinx-theme==0.8.0",
   "setuptools>=75.3.0",
-  "sphinx>=7.1.2",
   "sphinx-autoapi>=3.4.0",
+  "sphinx>=7.1.2",
 ]
diff --git a/python/datafusion/__init__.py b/python/datafusion/__init__.py
index 2e6f81166..80dfa2fab 100644
--- a/python/datafusion/__init__.py
+++ b/python/datafusion/__init__.py
@@ -35,7 +35,7 @@
 
 # The following imports are okay to remain as opaque to the user.
 from ._internal import Config
-from .catalog import Catalog, Database, Table
+from .catalog import Catalog, Table
 from .col import col, column
 from .common import DFSchema
 from .context import (
@@ -47,6 +47,7 @@
 from .dataframe import (
     DataFrame,
     DataFrameWriteOptions,
+    ExplainFormat,
     InsertOp,
     ParquetColumnOptions,
     ParquetWriterOptions,
@@ -55,7 +56,7 @@
 from .expr import Expr, WindowFrame
 from .io import read_avro, read_csv, read_json, read_parquet
 from .options import CsvReadOptions
-from .plan import ExecutionPlan, LogicalPlan
+from .plan import ExecutionPlan, LogicalPlan, Metric, MetricsSet
 from .record_batch import RecordBatch, RecordBatchStream
 from .user_defined import (
     Accumulator,
@@ -80,11 +81,13 @@
     "DFSchema",
     "DataFrame",
     "DataFrameWriteOptions",
-    "Database",
     "ExecutionPlan",
+    "ExplainFormat",
     "Expr",
     "InsertOp",
     "LogicalPlan",
+    "Metric",
+    "MetricsSet",
     "ParquetColumnOptions",
     "ParquetWriterOptions",
     "RecordBatch",
diff --git a/python/datafusion/catalog.py b/python/datafusion/catalog.py
index bc43cf349..20da5e671 100644
--- a/python/datafusion/catalog.py
+++ b/python/datafusion/catalog.py
@@ -29,6 +29,7 @@
 
     from datafusion import DataFrame, SessionContext
     from datafusion.context import TableProviderExportable
+    from datafusion.expr import CreateExternalTable
 
 try:
     from warnings import deprecated  # Python 3.13+
@@ -128,11 +129,6 @@ def schema(self, name: str = "public") -> Schema:
             else schema
         )
 
-    @deprecated("Use `schema` instead.")
-    def database(self, name: str = "public") -> Schema:
-        """Returns the database with the given ``name`` from this catalog."""
-        return self.schema(name)
-
     def register_schema(
         self,
         name: str,
@@ -194,11 +190,6 @@ def table_exist(self, name: str) -> bool:
         return self._raw_schema.table_exist(name)
 
 
-@deprecated("Use `Schema` instead.")
-class Database(Schema):
-    """See `Schema`."""
-
-
 class Table:
     """A DataFusion table.
 
@@ -243,6 +234,24 @@ def kind(self) -> str:
         return self._inner.kind
 
 
+class TableProviderFactory(ABC):
+    """Abstract class for defining a Python based Table Provider Factory."""
+
+    @abstractmethod
+    def create(self, cmd: CreateExternalTable) -> Table:
+        """Create a table using the :class:`CreateExternalTable`."""
+        ...
+
+
+class TableProviderFactoryExportable(Protocol):
+    """Type hint for object that has __datafusion_table_provider_factory__ PyCapsule.
+
+    https://docs.rs/datafusion/latest/datafusion/catalog/trait.TableProviderFactory.html
+    """
+
+    def __datafusion_table_provider_factory__(self, session: Any) -> object: ...
+
+
 class CatalogProviderList(ABC):
     """Abstract class for defining a Python based Catalog Provider List."""
 
diff --git a/python/datafusion/context.py b/python/datafusion/context.py
index 0d8259774..c3f94cc16 100644
--- a/python/datafusion/context.py
+++ b/python/datafusion/context.py
@@ -37,6 +37,8 @@
     CatalogProviderExportable,
     CatalogProviderList,
     CatalogProviderListExportable,
+    TableProviderFactory,
+    TableProviderFactoryExportable,
 )
 from datafusion.dataframe import DataFrame
 from datafusion.expr import sort_list_to_raw_sort_list
@@ -61,7 +63,8 @@
     import polars as pl  # type: ignore[import]
 
     from datafusion.catalog import CatalogProvider, Table
-    from datafusion.expr import SortKey
+    from datafusion.common import DFSchema
+    from datafusion.expr import Expr, SortKey
     from datafusion.plan import ExecutionPlan, LogicalPlan
     from datafusion.user_defined import (
         AggregateUDF,
@@ -294,6 +297,19 @@ def set(self, key: str, value: str) -> SessionConfig:
         self.config_internal = self.config_internal.set(key, value)
         return self
 
+    def with_extension(self, extension: Any) -> SessionConfig:
+        """Create a new configuration using an extension.
+
+        Args:
+            extension: A custom configuration extension object. These are
+            shared from another DataFusion extension library.
+
+        Returns:
+            A new :py:class:`SessionConfig` object with the updated setting.
+        """
+        self.config_internal = self.config_internal.with_extension(extension)
+        return self
+
 
 class RuntimeEnvBuilder:
     """Runtime configuration options."""
@@ -369,9 +385,8 @@ def with_fair_spill_pool(self, size: int) -> RuntimeEnvBuilder:
         Returns:
             A new :py:class:`RuntimeEnvBuilder` object with the updated setting.
 
-        Examples usage::
-
-            config = RuntimeEnvBuilder().with_fair_spill_pool(1024)
+        Examples:
+            >>> config = dfn.RuntimeEnvBuilder().with_fair_spill_pool(1024)
         """
         self.config_internal = self.config_internal.with_fair_spill_pool(size)
         return self
@@ -389,9 +404,8 @@ def with_greedy_memory_pool(self, size: int) -> RuntimeEnvBuilder:
         Returns:
             A new :py:class:`RuntimeEnvBuilder` object with the updated setting.
 
-        Example usage::
-
-            config = RuntimeEnvBuilder().with_greedy_memory_pool(1024)
+        Examples:
+            >>> config = dfn.RuntimeEnvBuilder().with_greedy_memory_pool(1024)
         """
         self.config_internal = self.config_internal.with_greedy_memory_pool(size)
         return self
@@ -405,19 +419,13 @@ def with_temp_file_path(self, path: str | pathlib.Path) -> RuntimeEnvBuilder:
         Returns:
             A new :py:class:`RuntimeEnvBuilder` object with the updated setting.
 
-        Example usage::
-
-            config = RuntimeEnvBuilder().with_temp_file_path("/tmp")
+        Examples:
+            >>> config = dfn.RuntimeEnvBuilder().with_temp_file_path("/tmp")
         """
         self.config_internal = self.config_internal.with_temp_file_path(str(path))
         return self
 
 
-@deprecated("Use `RuntimeEnvBuilder` instead.")
-class RuntimeConfig(RuntimeEnvBuilder):
-    """See `RuntimeEnvBuilder`."""
-
-
 class SQLOptions:
     """Options to be used when performing SQL queries."""
 
@@ -442,9 +450,8 @@ def with_allow_ddl(self, allow: bool = True) -> SQLOptions:
         Returns:
             A new :py:class:`SQLOptions` object with the updated setting.
 
-        Example usage::
-
-            options = SQLOptions().with_allow_ddl(True)
+        Examples:
+            >>> options = dfn.SQLOptions().with_allow_ddl(True)
         """
         self.options_internal = self.options_internal.with_allow_ddl(allow)
         return self
@@ -460,9 +467,8 @@ def with_allow_dml(self, allow: bool = True) -> SQLOptions:
         Returns:
             A new :py:class:`SQLOptions` object with the updated setting.
 
-        Example usage::
-
-            options = SQLOptions().with_allow_dml(True)
+        Examples:
+            >>> options = dfn.SQLOptions().with_allow_dml(True)
         """
         self.options_internal = self.options_internal.with_allow_dml(allow)
         return self
@@ -476,9 +482,8 @@ def with_allow_statements(self, allow: bool = True) -> SQLOptions:
         Returns:
             A new :py:class:SQLOptions` object with the updated setting.
 
-        Example usage::
-
-            options = SQLOptions().with_allow_statements(True)
+        Examples:
+            >>> options = dfn.SQLOptions().with_allow_statements(True)
         """
         self.options_internal = self.options_internal.with_allow_statements(allow)
         return self
@@ -559,6 +564,15 @@ def register_object_store(
         """
         self.ctx.register_object_store(schema, store, host)
 
+    def deregister_object_store(self, schema: str, host: str | None = None) -> None:
+        """Remove an object store from the session.
+
+        Args:
+            schema: The data source schema (e.g. ``"s3://"``).
+            host: URL for the host (e.g. bucket name).
+        """
+        self.ctx.deregister_object_store(schema, host)
+
     def register_listing_table(
         self,
         name: str,
@@ -766,14 +780,6 @@ def from_arrow(
         """
         return DataFrame(self.ctx.from_arrow(data, name))
 
-    @deprecated("Use ``from_arrow`` instead.")
-    def from_arrow_table(self, data: pa.Table, name: str | None = None) -> DataFrame:
-        """Create a :py:class:`~datafusion.dataframe.DataFrame` from an Arrow table.
-
-        This is an alias for :py:func:`from_arrow`.
-        """
-        return self.from_arrow(data, name)
-
     def from_pandas(self, data: pd.DataFrame, name: str | None = None) -> DataFrame:
         """Create a :py:class:`~datafusion.dataframe.DataFrame` from a Pandas DataFrame.
 
@@ -830,6 +836,22 @@ def deregister_table(self, name: str) -> None:
         """Remove a table from the session."""
         self.ctx.deregister_table(name)
 
+    def register_table_factory(
+        self,
+        format: str,
+        factory: TableProviderFactory | TableProviderFactoryExportable,
+    ) -> None:
+        """Register a :py:class:`~datafusion.TableProviderFactoryExportable`.
+
+        The registered factory can be referenced from SQL DDL statements executed
+        against this context.
+
+        Args:
+            format: The value to be used in `STORED AS ${format}` clause.
+            factory: A PyCapsule that implements :class:`TableProviderFactoryExportable`
+        """
+        self.ctx.register_table_factory(format, factory)
+
     def catalog_names(self) -> set[str]:
         """Returns the list of catalogs in this context."""
         return self.ctx.catalog_names()
@@ -869,6 +891,35 @@ def register_udtf(self, func: TableFunction) -> None:
         """Register a user defined table function."""
         self.ctx.register_udtf(func._udtf)
 
+    def register_batch(self, name: str, batch: pa.RecordBatch) -> None:
+        """Register a single :py:class:`pa.RecordBatch` as a table.
+
+        Args:
+            name: Name of the resultant table.
+            batch: Record batch to register as a table.
+
+        Examples:
+            >>> ctx = dfn.SessionContext()
+            >>> batch = pa.RecordBatch.from_pydict({"a": [1, 2, 3]})
+            >>> ctx.register_batch("batch_tbl", batch)
+            >>> ctx.sql("SELECT * FROM batch_tbl").collect()[0].column(0)
+            <pyarrow.lib.Int64Array object at ...>
+            [
+              1,
+              2,
+              3
+            ]
+        """
+        self.ctx.register_batch(name, batch)
+
+    def deregister_udtf(self, name: str) -> None:
+        """Remove a user-defined table function from the session.
+
+        Args:
+            name: Name of the UDTF to deregister.
+        """
+        self.ctx.deregister_udtf(name)
+
     def register_record_batches(
         self, name: str, partitions: list[list[pa.RecordBatch]]
     ) -> None:
@@ -1067,6 +1118,86 @@ def register_avro(
             name, str(path), schema, file_extension, table_partition_cols
         )
 
+    def register_arrow(
+        self,
+        name: str,
+        path: str | pathlib.Path,
+        schema: pa.Schema | None = None,
+        file_extension: str = ".arrow",
+        table_partition_cols: list[tuple[str, str | pa.DataType]] | None = None,
+    ) -> None:
+        """Register an Arrow IPC file as a table.
+
+        The registered table can be referenced from SQL statements executed
+        against this context.
+
+        Args:
+            name: Name of the table to register.
+            path: Path to the Arrow IPC file.
+            schema: The data source schema.
+            file_extension: File extension to select.
+            table_partition_cols: Partition columns.
+
+        Examples:
+            >>> import tempfile, os
+            >>> ctx = dfn.SessionContext()
+            >>> table = pa.table({"x": [10, 20, 30]})
+            >>> with tempfile.TemporaryDirectory() as tmpdir:
+            ...     path = os.path.join(tmpdir, "data.arrow")
+            ...     with pa.ipc.new_file(path, table.schema) as writer:
+            ...         writer.write_table(table)
+            ...     ctx.register_arrow("arrow_tbl", path)
+            ...     ctx.sql("SELECT * FROM arrow_tbl").collect()[0].column(0)
+            <pyarrow.lib.Int64Array object at ...>
+            [
+              10,
+              20,
+              30
+            ]
+
+            Provide an explicit ``schema`` to override schema inference:
+
+            >>> with tempfile.TemporaryDirectory() as tmpdir:
+            ...     path = os.path.join(tmpdir, "data.arrow")
+            ...     with pa.ipc.new_file(path, table.schema) as writer:
+            ...         writer.write_table(table)
+            ...     ctx.register_arrow(
+            ...         "arrow_schema",
+            ...         path,
+            ...         schema=pa.schema([("x", pa.int64())]),
+            ...     )
+            ...     ctx.sql("SELECT * FROM arrow_schema").collect()[0].column(0)
+            <pyarrow.lib.Int64Array object at ...>
+            [
+              10,
+              20,
+              30
+            ]
+
+            Use ``file_extension`` to read files with a non-default extension:
+
+            >>> with tempfile.TemporaryDirectory() as tmpdir:
+            ...     path = os.path.join(tmpdir, "data.ipc")
+            ...     with pa.ipc.new_file(path, table.schema) as writer:
+            ...         writer.write_table(table)
+            ...     ctx.register_arrow(
+            ...         "arrow_ipc", path, file_extension=".ipc"
+            ...     )
+            ...     ctx.sql("SELECT * FROM arrow_ipc").collect()[0].column(0)
+            <pyarrow.lib.Int64Array object at ...>
+            [
+              10,
+              20,
+              30
+            ]
+        """
+        if table_partition_cols is None:
+            table_partition_cols = []
+        table_partition_cols = _convert_table_partition_cols(table_partition_cols)
+        self.ctx.register_arrow(
+            name, str(path), schema, file_extension, table_partition_cols
+        )
+
     def register_dataset(self, name: str, dataset: pa.dataset.Dataset) -> None:
         """Register a :py:class:`pa.dataset.Dataset` as a table.
 
@@ -1080,26 +1211,42 @@ def register_udf(self, udf: ScalarUDF) -> None:
         """Register a user-defined function (UDF) with the context."""
         self.ctx.register_udf(udf._udf)
 
+    def deregister_udf(self, name: str) -> None:
+        """Remove a user-defined scalar function from the session.
+
+        Args:
+            name: Name of the UDF to deregister.
+        """
+        self.ctx.deregister_udf(name)
+
     def register_udaf(self, udaf: AggregateUDF) -> None:
         """Register a user-defined aggregation function (UDAF) with the context."""
         self.ctx.register_udaf(udaf._udaf)
 
+    def deregister_udaf(self, name: str) -> None:
+        """Remove a user-defined aggregate function from the session.
+
+        Args:
+            name: Name of the UDAF to deregister.
+        """
+        self.ctx.deregister_udaf(name)
+
     def register_udwf(self, udwf: WindowUDF) -> None:
         """Register a user-defined window function (UDWF) with the context."""
         self.ctx.register_udwf(udwf._udwf)
 
+    def deregister_udwf(self, name: str) -> None:
+        """Remove a user-defined window function from the session.
+
+        Args:
+            name: Name of the UDWF to deregister.
+        """
+        self.ctx.deregister_udwf(name)
+
     def catalog(self, name: str = "datafusion") -> Catalog:
         """Retrieve a catalog by name."""
         return Catalog(self.ctx.catalog(name))
 
-    @deprecated(
-        "Use the catalog provider interface ``SessionContext.Catalog`` to "
-        "examine available catalogs, schemas and tables"
-    )
-    def tables(self) -> set[str]:
-        """Deprecated."""
-        return self.ctx.tables()
-
     def table(self, name: str) -> DataFrame:
         """Retrieve a previously registered table by name."""
         return DataFrame(self.ctx.table(name))
@@ -1116,6 +1263,121 @@ def session_id(self) -> str:
         """Return an id that uniquely identifies this :py:class:`SessionContext`."""
         return self.ctx.session_id()
 
+    def session_start_time(self) -> str:
+        """Return the session start time as an RFC 3339 formatted string.
+
+        Examples:
+            >>> ctx = SessionContext()
+            >>> ctx.session_start_time()  # doctest: +SKIP
+            '2026-01-01T12:34:56.123456789+00:00'
+        """
+        return self.ctx.session_start_time()
+
+    def enable_ident_normalization(self) -> bool:
+        """Return whether identifier normalization (lowercasing) is enabled.
+
+        Examples:
+            >>> ctx = SessionContext()
+            >>> ctx.enable_ident_normalization()
+            True
+        """
+        return self.ctx.enable_ident_normalization()
+
+    def parse_sql_expr(self, sql: str, schema: DFSchema) -> Expr:
+        """Parse a SQL expression string into a logical expression.
+
+        Args:
+            sql: SQL expression string.
+            schema: Schema to use for resolving column references.
+
+        Returns:
+            Parsed expression.
+
+        Examples:
+            >>> from datafusion.common import DFSchema
+            >>> ctx = SessionContext()
+            >>> schema = DFSchema.empty()
+            >>> ctx.parse_sql_expr("1 + 2", schema=schema)
+            Expr(Int64(1) + Int64(2))
+        """
+        from datafusion.expr import Expr  # noqa: PLC0415
+
+        return Expr(self.ctx.parse_sql_expr(sql, schema))
+
+    def execute_logical_plan(self, plan: LogicalPlan) -> DataFrame:
+        """Execute a :py:class:`~datafusion.plan.LogicalPlan` and return a DataFrame.
+
+        Args:
+            plan: Logical plan to execute.
+
+        Returns:
+            DataFrame resulting from the execution.
+
+        Examples:
+            >>> ctx = SessionContext()
+            >>> df = ctx.from_pydict({"a": [1, 2, 3]})
+            >>> plan = df.logical_plan()
+            >>> df2 = ctx.execute_logical_plan(plan)
+            >>> df2.collect()[0].column(0)
+            <pyarrow.lib.Int64Array object at ...>
+            [
+              1,
+              2,
+              3
+            ]
+        """
+        return DataFrame(self.ctx.execute_logical_plan(plan._raw_plan))
+
+    def refresh_catalogs(self) -> None:
+        """Refresh catalog metadata.
+
+        Examples:
+            >>> ctx = SessionContext()
+            >>> ctx.refresh_catalogs()
+        """
+        self.ctx.refresh_catalogs()
+
+    def remove_optimizer_rule(self, name: str) -> bool:
+        """Remove an optimizer rule by name.
+
+        Args:
+            name: Name of the optimizer rule to remove.
+
+        Returns:
+            True if a rule with the given name was found and removed.
+
+        Examples:
+            >>> ctx = SessionContext()
+            >>> ctx.remove_optimizer_rule("nonexistent_rule")
+            False
+        """
+        return self.ctx.remove_optimizer_rule(name)
+
+    def table_provider(self, name: str) -> Table:
+        """Return the :py:class:`~datafusion.catalog.Table` for the given table name.
+
+        Args:
+            name: Name of the table.
+
+        Returns:
+            The table provider.
+
+        Raises:
+            KeyError: If the table is not found.
+
+        Examples:
+            >>> import pyarrow as pa
+            >>> ctx = SessionContext()
+            >>> batch = pa.RecordBatch.from_pydict({"x": [1, 2]})
+            >>> ctx.register_record_batches("my_table", [[batch]])
+            >>> tbl = ctx.table_provider("my_table")
+            >>> tbl.schema
+            x: int64
+        """
+        from datafusion.catalog import Table  # noqa: PLC0415
+
+        return Table(self.ctx.table_provider(name))
+
     def read_json(
         self,
         path: str | pathlib.Path,
@@ -1303,6 +1565,86 @@ def read_avro(
             self.ctx.read_avro(str(path), schema, file_partition_cols, file_extension)
         )
 
+    def read_arrow(
+        self,
+        path: str | pathlib.Path,
+        schema: pa.Schema | None = None,
+        file_extension: str = ".arrow",
+        file_partition_cols: list[tuple[str, str | pa.DataType]] | None = None,
+    ) -> DataFrame:
+        """Create a :py:class:`DataFrame` for reading an Arrow IPC data source.
+
+        Args:
+            path: Path to the Arrow IPC file.
+            schema: The data source schema.
+            file_extension: File extension to select.
+            file_partition_cols: Partition columns.
+
+        Returns:
+            DataFrame representation of the read Arrow IPC file.
+
+        Examples:
+            >>> import tempfile, os
+            >>> ctx = dfn.SessionContext()
+            >>> table = pa.table({"a": [1, 2, 3]})
+            >>> with tempfile.TemporaryDirectory() as tmpdir:
+            ...     path = os.path.join(tmpdir, "data.arrow")
+            ...     with pa.ipc.new_file(path, table.schema) as writer:
+            ...         writer.write_table(table)
+            ...     df = ctx.read_arrow(path)
+            ...     df.collect()[0].column(0)
+            <pyarrow.lib.Int64Array object at ...>
+            [
+              1,
+              2,
+              3
+            ]
+
+            Provide an explicit ``schema`` to override schema inference:
+
+            >>> with tempfile.TemporaryDirectory() as tmpdir:
+            ...     path = os.path.join(tmpdir, "data.arrow")
+            ...     with pa.ipc.new_file(path, table.schema) as writer:
+            ...         writer.write_table(table)
+            ...     df = ctx.read_arrow(path, schema=pa.schema([("a", pa.int64())]))
+            ...     df.collect()[0].column(0)
+            <pyarrow.lib.Int64Array object at ...>
+            [
+              1,
+              2,
+              3
+            ]
+
+            Use ``file_extension`` to read files with a non-default extension:
+
+            >>> with tempfile.TemporaryDirectory() as tmpdir:
+            ...     path = os.path.join(tmpdir, "data.ipc")
+            ...     with pa.ipc.new_file(path, table.schema) as writer:
+            ...         writer.write_table(table)
+            ...     df = ctx.read_arrow(path, file_extension=".ipc")
+            ...     df.collect()[0].column(0)
+            <pyarrow.lib.Int64Array object at ...>
+            [
+              1,
+              2,
+              3
+            ]
+        """
+        if file_partition_cols is None:
+            file_partition_cols = []
+        file_partition_cols = _convert_table_partition_cols(file_partition_cols)
+        return DataFrame(
+            self.ctx.read_arrow(str(path), schema, file_extension, file_partition_cols)
+        )
+
+    def read_empty(self) -> DataFrame:
+        """Create an empty :py:class:`DataFrame` with no columns or rows.
+
+        See Also:
+            This is an alias for :meth:`empty_table`.
+        """
+        return self.empty_table()
+
     def read_table(
         self, table: Table | TableProviderExportable | DataFrame | pa.dataset.Dataset
     ) -> DataFrame:
diff --git a/python/datafusion/dataframe.py b/python/datafusion/dataframe.py
index d302c12a5..c00c85fdb 100644
--- a/python/datafusion/dataframe.py
+++ b/python/datafusion/dataframe.py
@@ -44,6 +44,7 @@
     Expr,
     SortExpr,
     SortKey,
+    _to_raw_expr,
     ensure_expr,
     ensure_expr_list,
     expr_list_to_raw_expr_list,
@@ -65,6 +66,25 @@
 from enum import Enum
 
 
+class ExplainFormat(Enum):
+    """Output format for explain plans.
+
+    Controls how the query plan is rendered in :py:meth:`DataFrame.explain`.
+    """
+
+    INDENT = "indent"
+    """Default indented text format."""
+
+    TREE = "tree"
+    """Tree-style visual format with box-drawing characters."""
+
+    PGJSON = "pgjson"
+    """PostgreSQL-compatible JSON format for use with visualization tools."""
+
+    GRAPHVIZ = "graphviz"
+    """Graphviz DOT format for graph rendering."""
+
+
 # excerpt from deltalake
 # https://github.com/apache/datafusion-python/pull/981#discussion_r1905619163
 class Compression(Enum):
@@ -327,10 +347,11 @@ def into_view(self, temporary: bool = False) -> Table:
             >>> df = ctx.sql("SELECT 1 AS value")
             >>> view = df.into_view()
             >>> ctx.register_table("values_view", view)
-            >>> df.collect()  # The DataFrame is still usable
-            >>> ctx.sql("SELECT value FROM values_view").collect()
+            >>> result = ctx.sql("SELECT value FROM values_view").collect()
+            >>> result[0].column("value").to_pylist()
+            [1]
         """
-        from datafusion.catalog import Table as _Table
+        from datafusion.catalog import Table as _Table  # noqa: PLC0415
 
         return _Table(self.df.into_view(temporary))
 
@@ -394,16 +415,79 @@ def schema(self) -> pa.Schema:
         """
         return self.df.schema()
 
-    @deprecated(
-        "select_columns() is deprecated. Use :py:meth:`~DataFrame.select` instead"
-    )
-    def select_columns(self, *args: str) -> DataFrame:
-        """Filter the DataFrame by columns.
+    def column(self, name: str) -> Expr:
+        """Return a fully qualified column expression for ``name``.
+
+        Resolves an unqualified column name against this DataFrame's schema
+        and returns an :py:class:`Expr` whose underlying column reference
+        includes the table qualifier. This is especially useful after joins,
+        where the same column name may appear in multiple relations.
+
+        Args:
+            name: Unqualified column name to look up.
 
         Returns:
-            DataFrame only containing the specified columns.
+            A fully qualified column expression.
+
+        Raises:
+            Exception: If the column is not found or is ambiguous (exists in
+                multiple relations).
+
+        Examples:
+            Resolve a column from a simple DataFrame:
+
+            >>> ctx = dfn.SessionContext()
+            >>> df = ctx.from_pydict({"a": [1, 2], "b": [3, 4]})
+            >>> expr = df.column("a")
+            >>> df.select(expr).to_pydict()
+            {'a': [1, 2]}
+
+            Resolve qualified columns after a join:
+
+            >>> left = ctx.from_pydict({"id": [1, 2], "x": [10, 20]})
+            >>> right = ctx.from_pydict({"id": [1, 2], "y": [30, 40]})
+            >>> joined = left.join(right, on="id", how="inner")
+            >>> expr = joined.column("y")
+            >>> joined.select("id", expr).sort("id").to_pydict()
+            {'id': [1, 2], 'y': [30, 40]}
         """
-        return self.select(*args)
+        return self.find_qualified_columns(name)[0]
+
+    def col(self, name: str) -> Expr:
+        """Alias for :py:meth:`column`.
+
+        See Also:
+            :py:meth:`column`
+        """
+        return self.column(name)
+
+    def find_qualified_columns(self, *names: str) -> list[Expr]:
+        """Return fully qualified column expressions for the given names.
+
+        This is a batch version of :py:meth:`column` — it resolves each
+        unqualified name against the DataFrame's schema and returns a list
+        of qualified column expressions.
+
+        Args:
+            names: Unqualified column names to look up.
+
+        Returns:
+            List of fully qualified column expressions, one per name.
+
+        Raises:
+            Exception: If any column is not found or is ambiguous.
+
+        Examples:
+            Resolve multiple columns at once:
+
+            >>> ctx = dfn.SessionContext()
+            >>> df = ctx.from_pydict({"a": [1, 2], "b": [3, 4], "c": [5, 6]})
+            >>> exprs = df.find_qualified_columns("a", "c")
+            >>> df.select(*exprs).to_pydict()
+            {'a': [1, 2], 'c': [5, 6]}
+        """
+        raw_exprs = self.df.find_qualified_columns(list(names))
+        return [Expr(e) for e in raw_exprs]
 
     def select_exprs(self, *args: str) -> DataFrame:
         """Project arbitrary list of expression strings into a new DataFrame.
@@ -441,30 +525,61 @@ def select(self, *exprs: Expr | str) -> DataFrame:
     def drop(self, *columns: str) -> DataFrame:
         """Drop arbitrary amount of columns.
 
-        Column names are case-sensitive and do not require double quotes like
-        other operations such as `select`. Leading and trailing double quotes
-        are allowed and will be automatically stripped if present.
+        Column names are case-sensitive and require double quotes to be dropped
+        if the original name is not strictly lower case.
 
         Args:
-            columns: Column names to drop from the dataframe. Both ``column_name``
-                    and ``"column_name"`` are accepted.
+            columns: Column names to drop from the dataframe.
 
         Returns:
             DataFrame with those columns removed in the projection.
 
-        Example Usage::
+        Examples:
+            To drop a lower-cased column 'a'
 
-            df.drop('ID_For_Students')      # Works
-            df.drop('"ID_For_Students"')    # Also works (quotes stripped)
+            >>> ctx = dfn.SessionContext()
+            >>> df = ctx.from_pydict({"a": [1, 2], "b": [3, 4]})
+            >>> df.drop("a").schema().names
+            ['b']
+
+            Or to drop an upper-cased column 'A'
+
+            >>> ctx = dfn.SessionContext()
+            >>> df = ctx.from_pydict({"A": [1, 2], "b": [3, 4]})
+            >>> df.drop('"A"').schema().names
+            ['b']
         """
-        normalized_columns = []
-        for col in columns:
-            if col.startswith('"') and col.endswith('"'):
-                normalized_columns.append(col.strip('"'))  # Strip double quotes
-            else:
-                normalized_columns.append(col)
+        return DataFrame(self.df.drop(*columns))
 
-        return DataFrame(self.df.drop(*normalized_columns))
+    def window(self, *exprs: Expr) -> DataFrame:
+        """Add window function columns to the DataFrame.
+
+        Applies the given window function expressions and appends the results
+        as new columns.
+
+        Args:
+            exprs: Window function expressions to evaluate.
+
+        Returns:
+            DataFrame with new window function columns appended.
+
+        Examples:
+            Add a row number within each group:
+
+            >>> import datafusion.functions as f
+            >>> from datafusion import col
+            >>> ctx = dfn.SessionContext()
+            >>> df = ctx.from_pydict({"a": [1, 2, 3], "b": ["x", "x", "y"]})
+            >>> df = df.window(
+            ...     f.row_number(
+            ...         partition_by=[col("b")], order_by=[col("a")]
+            ...     ).alias("rn")
+            ... )
+            >>> "rn" in df.schema().names
+            True
+        """
+        raw = expr_list_to_raw_expr_list(exprs)
+        return DataFrame(self.df.window(*raw))
 
     def filter(self, *predicates: Expr | str) -> DataFrame:
         """Return a DataFrame for which ``predicate`` evaluates to ``True``.
@@ -477,11 +592,13 @@ def filter(self, *predicates: Expr | str) -> DataFrame:
         that will be parsed against the DataFrame schema. If more complex logic is
         required, see the logical operations in :py:mod:`~datafusion.functions`.
 
-        Example::
-
-            from datafusion import col, lit
-            df.filter(col("a") > lit(1))
-            df.filter("a > 1")
+        Examples:
+            >>> ctx = dfn.SessionContext()
+            >>> df = ctx.from_pydict({"a": [1, 2, 3]})
+            >>> df.filter(col("a") > lit(1)).to_pydict()
+            {'a': [2, 3]}
+            >>> df.filter("a > 1").to_pydict()
+            {'a': [2, 3]}
 
         Args:
             predicates: Predicate expression(s) or SQL strings to filter the DataFrame.
@@ -504,14 +621,12 @@ def parse_sql_expr(self, expr: str) -> Expr:
 
         The expression is created and processed against the current schema.
 
-        Example::
-
-            from datafusion import col, lit
-            df.parse_sql_expr("a > 1")
-
-            should produce:
-
-            col("a") > lit(1)
+        Examples:
+            >>> ctx = dfn.SessionContext()
+            >>> df = ctx.from_pydict({"a": [1, 2, 3]})
+            >>> expr = df.parse_sql_expr("a > 1")
+            >>> df.filter(expr).to_pydict()
+            {'a': [2, 3]}
 
         Args:
             expr: Expression string to be converted to datafusion expression
@@ -528,10 +643,11 @@ def with_column(self, name: str, expr: Expr | str) -> DataFrame:
         :func:`datafusion.col` or :func:`datafusion.lit`, or a SQL expression
         string that will be parsed against the DataFrame schema.
 
-        Example::
-
-            from datafusion import col, lit
-            df.with_column("b", col("a") + lit(1))
+        Examples:
+            >>> ctx = dfn.SessionContext()
+            >>> df = ctx.from_pydict({"a": [1, 2]})
+            >>> df.with_column("b", col("a") + lit(10)).to_pydict()
+            {'a': [1, 2], 'b': [11, 12]}
 
         Args:
             name: Name of the column to add.
@@ -630,8 +746,22 @@ def aggregate(
     ) -> DataFrame:
         """Aggregates the rows of the current DataFrame.
 
+        By default each unique combination of the ``group_by`` columns
+        produces one row. To get multiple levels of subtotals in a
+        single pass, pass a
+        :py:class:`~datafusion.expr.GroupingSet` expression
+        (created via
+        :py:meth:`~datafusion.expr.GroupingSet.rollup`,
+        :py:meth:`~datafusion.expr.GroupingSet.cube`, or
+        :py:meth:`~datafusion.expr.GroupingSet.grouping_sets`)
+        as the ``group_by`` argument.  See the
+        :ref:`aggregation` user guide for detailed examples.
+
         Args:
-            group_by: Sequence of expressions or column names to group by.
+            group_by: Sequence of expressions or column names to group
+                by. A :py:class:`~datafusion.expr.GroupingSet`
+                expression may be included to produce multiple grouping
+                levels (rollup, cube, or explicit grouping sets).
             aggs: Sequence of expressions to aggregate.
 
         Returns:
@@ -820,7 +950,13 @@ def join(
     ) -> DataFrame:
         """Join this :py:class:`DataFrame` with another :py:class:`DataFrame`.
 
-        `on` has to be provided or both `left_on` and `right_on` in conjunction.
+        ``on`` has to be provided or both ``left_on`` and ``right_on`` in
+        conjunction.
+
+        When non-key columns share the same name in both DataFrames, use
+        :py:meth:`DataFrame.col` on each DataFrame **before** the join to
+        obtain fully qualified column references that can disambiguate them.
+        See :py:meth:`join_on` for an example.
 
         Args:
             right: Other DataFrame to join with.
@@ -894,10 +1030,33 @@ def join_on(
         built with :func:`datafusion.col`. On expressions are used to support
         in-equality predicates. Equality predicates are correctly optimized.
 
-        Example::
+        Use :py:meth:`DataFrame.col` on each DataFrame **before** the join to
+        obtain fully qualified column references. These qualified references
+        can then be used in the join predicate and to disambiguate columns
+        with the same name when selecting from the result.
 
-            from datafusion import col
-            df.join_on(other_df, col("id") == col("other_id"))
+        Examples:
+            Join with unique column names:
+
+            >>> ctx = dfn.SessionContext()
+            >>> left = ctx.from_pydict({"a": [1, 2], "x": ["a", "b"]})
+            >>> right = ctx.from_pydict({"b": [1, 2], "y": ["c", "d"]})
+            >>> left.join_on(
+            ...     right, col("a") == col("b")
+            ... ).sort(col("x")).to_pydict()
+            {'a': [1, 2], 'x': ['a', 'b'], 'b': [1, 2], 'y': ['c', 'd']}
+
+            Use :py:meth:`col` to disambiguate shared column names:
+
+            >>> left = ctx.from_pydict({"id": [1, 2], "val": [10, 20]})
+            >>> right = ctx.from_pydict({"id": [1, 2], "val": [30, 40]})
+            >>> joined = left.join_on(
+            ...     right, left.col("id") == right.col("id"), how="inner"
+            ... )
+            >>> joined.select(
+            ...     left.col("id"), left.col("val"), right.col("val").alias("rval")
+            ... ).sort(left.col("id")).to_pydict()
+            {'id': [1, 2], 'val': [10, 20], 'rval': [30, 40]}
 
         Args:
             right: Other DataFrame to join with.
@@ -911,7 +1070,12 @@ def join_on(
         exprs = [ensure_expr(expr) for expr in on_exprs]
         return DataFrame(self.df.join_on(right.df, exprs, how))
 
-    def explain(self, verbose: bool = False, analyze: bool = False) -> None:
+    def explain(
+        self,
+        verbose: bool = False,
+        analyze: bool = False,
+        format: ExplainFormat | None = None,
+    ) -> None:
         """Print an explanation of the DataFrame's plan so far.
 
         If ``analyze`` is specified, runs the plan and reports metrics.
@@ -919,8 +1083,23 @@ def explain(self, verbose: bool = False, analyze: bool = False) -> None:
         Args:
             verbose: If ``True``, more details will be included.
             analyze: If ``True``, the plan will run and metrics reported.
+            format: Output format for the plan. Defaults to
+                :py:attr:`ExplainFormat.INDENT`.
+
+        Examples:
+            Show the plan in tree format:
+
+            >>> from datafusion import ExplainFormat
+            >>> ctx = dfn.SessionContext()
+            >>> df = ctx.from_pydict({"a": [1, 2, 3]})
+            >>> df.explain(format=ExplainFormat.TREE)  # doctest: +SKIP
+
+            Show plan with runtime metrics:
+
+            >>> df.explain(analyze=True)  # doctest: +SKIP
         """
-        self.df.explain(verbose, analyze)
+        fmt = format.value if format is not None else None
+        self.df.explain(verbose, analyze, fmt)
 
     def logical_plan(self) -> LogicalPlan:
         """Return the unoptimized ``LogicalPlan``.
@@ -989,45 +1168,170 @@ def union(self, other: DataFrame, distinct: bool = False) -> DataFrame:
         """
         return DataFrame(self.df.union(other.df, distinct))
 
+    @deprecated(
+        "union_distinct() is deprecated. Use union(other, distinct=True) instead."
+    )
     def union_distinct(self, other: DataFrame) -> DataFrame:
         """Calculate the distinct union of two :py:class:`DataFrame`.
 
+        See Also:
+            :py:meth:`union`
+        """
+        return self.union(other, distinct=True)
+
+    def intersect(self, other: DataFrame, distinct: bool = False) -> DataFrame:
+        """Calculate the intersection of two :py:class:`DataFrame`.
+
         The two :py:class:`DataFrame` must have exactly the same schema.
-        Any duplicate rows are discarded.
 
         Args:
-            other: DataFrame to union with.
+            other: DataFrame to intersect with.
+            distinct: If ``True``, duplicate rows are removed from the result.
 
         Returns:
-            DataFrame after union.
+            DataFrame after intersection.
+
+        Examples:
+            Find rows common to both DataFrames:
+
+            >>> ctx = dfn.SessionContext()
+            >>> df1 = ctx.from_pydict({"a": [1, 2, 3], "b": [10, 20, 30]})
+            >>> df2 = ctx.from_pydict({"a": [1, 4], "b": [10, 40]})
+            >>> df1.intersect(df2).to_pydict()
+            {'a': [1], 'b': [10]}
+
+            Intersect with deduplication:
+
+            >>> df1 = ctx.from_pydict({"a": [1, 1, 2], "b": [10, 10, 20]})
+            >>> df2 = ctx.from_pydict({"a": [1, 1], "b": [10, 10]})
+            >>> df1.intersect(df2, distinct=True).to_pydict()
+            {'a': [1], 'b': [10]}
         """
-        return DataFrame(self.df.union_distinct(other.df))
+        return DataFrame(self.df.intersect(other.df, distinct))
 
-    def intersect(self, other: DataFrame) -> DataFrame:
-        """Calculate the intersection of two :py:class:`DataFrame`.
+    def except_all(self, other: DataFrame, distinct: bool = False) -> DataFrame:
+        """Calculate the set difference of two :py:class:`DataFrame`.
+
+        Returns rows that are in this DataFrame but not in ``other``.
 
         The two :py:class:`DataFrame` must have exactly the same schema.
 
         Args:
-            other:  DataFrame to intersect with.
+            other: DataFrame to calculate exception with.
+            distinct: If ``True``, duplicate rows are removed from the result.
 
         Returns:
-            DataFrame after intersection.
+            DataFrame after set difference.
+
+        Examples:
+            Remove rows present in ``df2``:
+
+            >>> ctx = dfn.SessionContext()
+            >>> df1 = ctx.from_pydict({"a": [1, 2, 3], "b": [10, 20, 30]})
+            >>> df2 = ctx.from_pydict({"a": [1, 2], "b": [10, 20]})
+            >>> df1.except_all(df2).sort("a").to_pydict()
+            {'a': [3], 'b': [30]}
+
+            Remove rows present in ``df2`` and deduplicate:
+
+            >>> df1.except_all(df2, distinct=True).sort("a").to_pydict()
+            {'a': [3], 'b': [30]}
         """
-        return DataFrame(self.df.intersect(other.df))
+        return DataFrame(self.df.except_all(other.df, distinct))
 
-    def except_all(self, other: DataFrame) -> DataFrame:
-        """Calculate the exception of two :py:class:`DataFrame`.
+    def union_by_name(self, other: DataFrame, distinct: bool = False) -> DataFrame:
+        """Union two :py:class:`DataFrame` matching columns by name.
 
-        The two :py:class:`DataFrame` must have exactly the same schema.
+        Unlike :py:meth:`union` which matches columns by position, this method
+        matches columns by their names, allowing DataFrames with different
+        column orders to be combined.
 
         Args:
-            other: DataFrame to calculate exception with.
+            other: DataFrame to union with.
+            distinct: If ``True``, duplicate rows are removed from the result.
 
         Returns:
-            DataFrame after exception.
+            DataFrame after union by name.
+
+        Examples:
+            Combine DataFrames with different column orders:
+
+            >>> ctx = dfn.SessionContext()
+            >>> df1 = ctx.from_pydict({"a": [1], "b": [10]})
+            >>> df2 = ctx.from_pydict({"b": [20], "a": [2]})
+            >>> df1.union_by_name(df2).sort("a").to_pydict()
+            {'a': [1, 2], 'b': [10, 20]}
+
+            Union by name with deduplication:
+
+            >>> df1 = ctx.from_pydict({"a": [1, 1], "b": [10, 10]})
+            >>> df2 = ctx.from_pydict({"b": [10], "a": [1]})
+            >>> df1.union_by_name(df2, distinct=True).to_pydict()
+            {'a': [1], 'b': [10]}
         """
-        return DataFrame(self.df.except_all(other.df))
+        return DataFrame(self.df.union_by_name(other.df, distinct))
+
+    def distinct_on(
+        self,
+        on_expr: list[Expr],
+        select_expr: list[Expr],
+        sort_expr: list[SortKey] | None = None,
+    ) -> DataFrame:
+        """Deduplicate rows based on specific columns.
+
+        Returns a new DataFrame with one row per unique combination of the
+        ``on_expr`` columns, keeping the first row per group as determined by
+        ``sort_expr``.
+
+        Args:
+            on_expr: Expressions that determine uniqueness.
+            select_expr: Expressions to include in the output.
+            sort_expr: Optional sort expressions to determine which row to keep.
+
+        Returns:
+            DataFrame after deduplication.
+
+        Examples:
+            Keep the row with the smallest ``b`` for each unique ``a``:
+
+            >>> from datafusion import col
+            >>> ctx = dfn.SessionContext()
+            >>> df = ctx.from_pydict({"a": [1, 1, 2, 2], "b": [10, 20, 30, 40]})
+            >>> df.distinct_on(
+            ...     [col("a")],
+            ...     [col("a"), col("b")],
+            ...     [col("a").sort(ascending=True), col("b").sort(ascending=True)],
+            ... ).sort("a").to_pydict()
+            {'a': [1, 2], 'b': [10, 30]}
+        """
+        on_raw = expr_list_to_raw_expr_list(on_expr)
+        select_raw = expr_list_to_raw_expr_list(select_expr)
+        sort_raw = sort_list_to_raw_sort_list(sort_expr) if sort_expr else None
+        return DataFrame(self.df.distinct_on(on_raw, select_raw, sort_raw))
+
+    def sort_by(self, *exprs: Expr | str) -> DataFrame:
+        """Sort the DataFrame by column expressions in ascending order.
+
+        This is a convenience method that sorts the DataFrame by the given
+        expressions in ascending order with nulls last. For more control over
+        sort direction and null ordering, use :py:meth:`sort` instead.
+
+        Args:
+            exprs: Expressions or column names to sort by.
+
+        Returns:
+            DataFrame after sorting.
+
+        Examples:
+            Sort by a single column:
+
+            >>> ctx = dfn.SessionContext()
+            >>> df = ctx.from_pydict({"a": [3, 1, 2]})
+            >>> df.sort_by("a").to_pydict()
+            {'a': [1, 2, 3]}
+        """
+        raw = [_to_raw_expr(e) for e in exprs]
+        return DataFrame(self.df.sort_by(raw))
 
     def write_csv(
         self,
@@ -1288,24 +1592,44 @@ def count(self) -> int:
         """
         return self.df.count()
 
-    @deprecated("Use :py:func:`unnest_columns` instead.")
-    def unnest_column(self, column: str, preserve_nulls: bool = True) -> DataFrame:
-        """See :py:func:`unnest_columns`."""
-        return DataFrame(self.df.unnest_column(column, preserve_nulls=preserve_nulls))
-
-    def unnest_columns(self, *columns: str, preserve_nulls: bool = True) -> DataFrame:
+    def unnest_columns(
+        self,
+        *columns: str,
+        preserve_nulls: bool = True,
+        recursions: list[tuple[str, str, int]] | None = None,
+    ) -> DataFrame:
         """Expand columns of arrays into a single row per array element.
 
         Args:
             columns: Column names to perform unnest operation on.
             preserve_nulls: If False, rows with null entries will not be
                 returned.
+            recursions: Optional list of ``(input_column, output_column, depth)``
+                tuples that control how deeply nested columns are unnested. Any
+                column not mentioned here is unnested with depth 1.
 
         Returns:
             A DataFrame with the columns expanded.
+
+        Examples:
+            Unnest an array column:
+
+            >>> ctx = dfn.SessionContext()
+            >>> df = ctx.from_pydict({"a": [[1, 2], [3]], "b": ["x", "y"]})
+            >>> df.unnest_columns("a").to_pydict()
+            {'a': [1, 2, 3], 'b': ['x', 'x', 'y']}
+
+            With explicit recursion depth:
+
+            >>> df.unnest_columns("a", recursions=[("a", "a", 1)]).to_pydict()
+            {'a': [1, 2, 3], 'b': ['x', 'x', 'y']}
         """
         columns = list(columns)
-        return DataFrame(self.df.unnest_columns(columns, preserve_nulls=preserve_nulls))
+        return DataFrame(
+            self.df.unnest_columns(
+                columns, preserve_nulls=preserve_nulls, recursions=recursions
+            )
+        )
 
     def __arrow_c_stream__(self, requested_schema: object | None = None) -> object:
         """Export the DataFrame as an Arrow C Stream.
@@ -1359,15 +1683,17 @@ def __aiter__(self) -> AsyncIterator[RecordBatch]:
     def transform(self, func: Callable[..., DataFrame], *args: Any) -> DataFrame:
         """Apply a function to the current DataFrame which returns another DataFrame.
 
-        This is useful for chaining together multiple functions. For example::
+        This is useful for chaining together multiple functions.
 
-            def add_3(df: DataFrame) -> DataFrame:
-                return df.with_column("modified", lit(3))
-
-            def within_limit(df: DataFrame, limit: int) -> DataFrame:
-                return df.filter(col("a") < lit(limit)).distinct()
-
-            df = df.transform(modify_df).transform(within_limit, 4)
+        Examples:
+            >>> ctx = dfn.SessionContext()
+            >>> df = ctx.from_pydict({"a": [1, 2, 3]})
+            >>> def add_3(df):
+            ...     return df.with_column("modified", dfn.lit(3))
+            >>> def within_limit(df: DataFrame, limit: int) -> DataFrame:
+            ...     return df.filter(col("a") < lit(limit)).distinct()
+            >>> df.transform(add_3).transform(within_limit, 4).sort("a").to_pydict()
+            {'a': [1, 2, 3], 'modified': [3, 3, 3]}
 
         Args:
             func: A callable function that takes a DataFrame as it's first argument
@@ -1389,9 +1715,12 @@ def fill_null(self, value: Any, subset: list[str] | None = None) -> DataFrame:
             DataFrame with null values replaced where type casting is possible
 
         Examples:
-            >>> df = df.fill_null(0)  # Fill all nulls with 0 where possible
-            >>> # Fill nulls in specific string columns
-            >>> df = df.fill_null("missing", subset=["name", "category"])
+            >>> from datafusion import SessionContext, col
+            >>> ctx = SessionContext()
+            >>> df = ctx.from_pydict({"a": [1, None, 3], "b": [None, 5, 6]})
+            >>> filled = df.fill_null(0)
+            >>> filled.sort(col("a")).collect()[0].column("a").to_pylist()
+            [0, 1, 3]
 
         Notes:
             - Only fills nulls in columns where the value can be cast to the column type
diff --git a/python/datafusion/dataframe_formatter.py b/python/datafusion/dataframe_formatter.py
index b8af45a1b..fd2da99f0 100644
--- a/python/datafusion/dataframe_formatter.py
+++ b/python/datafusion/dataframe_formatter.py
@@ -748,7 +748,7 @@ def get_formatter() -> DataFrameHtmlFormatter:
         The global HTML formatter instance
 
     Example:
-        >>> from datafusion.html_formatter import get_formatter
+        >>> from datafusion.dataframe_formatter import get_formatter
         >>> formatter = get_formatter()
         >>> formatter.max_cell_length = 50  # Increase cell length
     """
@@ -762,7 +762,7 @@ def set_formatter(formatter: DataFrameHtmlFormatter) -> None:
         formatter: The formatter instance to use globally
 
     Example:
-        >>> from datafusion.html_formatter import get_formatter, set_formatter
+        >>> from datafusion.dataframe_formatter import get_formatter, set_formatter
         >>> custom_formatter = DataFrameHtmlFormatter(max_cell_length=100)
         >>> set_formatter(custom_formatter)
     """
@@ -783,7 +783,7 @@ def configure_formatter(**kwargs: Any) -> None:
         ValueError: If any invalid parameters are provided
 
     Example:
-        >>> from datafusion.html_formatter import configure_formatter
+        >>> from datafusion.dataframe_formatter import configure_formatter
         >>> configure_formatter(
         ...     max_cell_length=50,
         ...     max_height=500,
@@ -827,7 +827,7 @@ def reset_formatter() -> None:
     and sets it as the global formatter for all DataFrames.
 
     Example:
-        >>> from datafusion.html_formatter import reset_formatter
+        >>> from datafusion.dataframe_formatter import reset_formatter
         >>> reset_formatter()  # Reset formatter to default settings
     """
     formatter = DataFrameHtmlFormatter()
diff --git a/python/datafusion/expr.py b/python/datafusion/expr.py
index 9df58f52a..32004656f 100644
--- a/python/datafusion/expr.py
+++ b/python/datafusion/expr.py
@@ -20,16 +20,13 @@
 See :ref:`Expressions` in the online documentation for more details.
 """
 
+# ruff: noqa: PLC0415
+
 from __future__ import annotations
 
 from collections.abc import Iterable, Sequence
 from typing import TYPE_CHECKING, Any, ClassVar
 
-try:
-    from warnings import deprecated  # Python 3.13+
-except ImportError:
-    from typing_extensions import deprecated  # Python 3.12
-
 import pyarrow as pa
 
 from ._internal import expr as expr_internal
@@ -89,7 +86,6 @@
 Extension = expr_internal.Extension
 FileType = expr_internal.FileType
 Filter = expr_internal.Filter
-GroupingSet = expr_internal.GroupingSet
 Join = expr_internal.Join
 ILike = expr_internal.ILike
 InList = expr_internal.InList
@@ -340,7 +336,7 @@ def sort_list_to_raw_sort_list(
     return raw_sort_list
 
 
-class Expr:
+class Expr:  # noqa: PLW1641
     """Expression object.
 
     Expressions are one of the core concepts in DataFusion. See
@@ -355,16 +351,6 @@ def to_variant(self) -> Any:
         """Convert this expression into a python object if possible."""
         return self.expr.to_variant()
 
-    @deprecated(
-        "display_name() is deprecated. Use :py:meth:`~Expr.schema_name` instead"
-    )
-    def display_name(self) -> str:
-        """Returns the name of this expression as it should appear in a schema.
-
-        This name will not include any CAST expressions.
-        """
-        return self.schema_name()
-
     def schema_name(self) -> str:
         """Returns the name of this expression as it should appear in a schema.
 
@@ -497,6 +483,8 @@ def __eq__(self, rhs: object) -> Expr:
 
         Accepts either an expression or any valid PyArrow scalar literal value.
         """
+        if rhs is None:
+            return self.is_null()
         if not isinstance(rhs, Expr):
             rhs = Expr.literal(rhs)
         return Expr(self.expr.__eq__(rhs.expr))
@@ -506,6 +494,8 @@ def __ne__(self, rhs: object) -> Expr:
 
         Accepts either an expression or any valid PyArrow scalar literal value.
         """
+        if rhs is None:
+            return self.is_not_null()
         if not isinstance(rhs, Expr):
             rhs = Expr.literal(rhs)
         return Expr(self.expr.__ne__(rhs.expr))
@@ -1365,16 +1355,18 @@ def is_unbounded(self) -> bool:
 class CaseBuilder:
     """Builder class for constructing case statements.
 
-    An example usage would be as follows::
-
-        import datafusion.functions as f
-        from datafusion import lit, col
-        df.select(
-            f.case(col("column_a"))
-            .when(lit(1), lit("One"))
-            .when(lit(2), lit("Two"))
-            .otherwise(lit("Unknown"))
-        )
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1, 2, 3]})
+        >>> result = df.select(
+        ...     dfn.functions.case(dfn.col("a"))
+        ...     .when(dfn.lit(1), dfn.lit("One"))
+        ...     .when(dfn.lit(2), dfn.lit("Two"))
+        ...     .otherwise(dfn.lit("Other"))
+        ...     .alias("label")
+        ... )
+        >>> result.to_pydict()
+        {'label': ['One', 'Two', 'Other']}
     """
 
     def __init__(self, case_builder: expr_internal.CaseBuilder) -> None:
@@ -1426,3 +1418,129 @@ def __repr__(self) -> str:
 
 
 SortKey = Expr | SortExpr | str
+
+
+class GroupingSet:
+    """Factory for creating grouping set expressions.
+
+    Grouping sets control how
+    :py:meth:`~datafusion.dataframe.DataFrame.aggregate` groups rows.
+    Instead of a single ``GROUP BY``, they produce multiple grouping
+    levels in one pass — subtotals, cross-tabulations, or arbitrary
+    column subsets.
+
+    Use :py:func:`~datafusion.functions.grouping` in the aggregate list
+    to tell which columns are aggregated across in each result row.
+    """
+
+    @staticmethod
+    def rollup(*exprs: Expr | str) -> Expr:
+        """Create a ``ROLLUP`` grouping set for use with ``aggregate()``.
+
+        ``ROLLUP`` generates all prefixes of the given column list as
+        grouping sets. For example, ``rollup(a, b)`` produces grouping
+        sets ``(a, b)``, ``(a)``, and ``()`` (grand total).
+
+        This is equivalent to ``GROUP BY ROLLUP(a, b)`` in SQL.
+
+        Args:
+            *exprs: Column expressions or column name strings to
+                include in the rollup.
+
+        Examples:
+            >>> from datafusion.expr import GroupingSet
+            >>> ctx = dfn.SessionContext()
+            >>> df = ctx.from_pydict({"a": [1, 1, 2], "b": [10, 20, 30]})
+            >>> result = df.aggregate(
+            ...     [GroupingSet.rollup(dfn.col("a"))],
+            ...     [dfn.functions.sum(dfn.col("b")).alias("s"),
+            ...      dfn.functions.grouping(dfn.col("a"))],
+            ... ).sort(dfn.col("a").sort(nulls_first=False))
+            >>> result.collect_column("s").to_pylist()
+            [30, 30, 60]
+
+        See Also:
+            :py:meth:`cube`, :py:meth:`grouping_sets`,
+            :py:func:`~datafusion.functions.grouping`
+        """
+        args = [_to_raw_expr(e) for e in exprs]
+        return Expr(expr_internal.GroupingSet.rollup(*args))
+
+    @staticmethod
+    def cube(*exprs: Expr | str) -> Expr:
+        """Create a ``CUBE`` grouping set for use with ``aggregate()``.
+
+        ``CUBE`` generates all possible subsets of the given column list
+        as grouping sets. For example, ``cube(a, b)`` produces grouping
+        sets ``(a, b)``, ``(a)``, ``(b)``, and ``()`` (grand total).
+
+        This is equivalent to ``GROUP BY CUBE(a, b)`` in SQL.
+
+        Args:
+            *exprs: Column expressions or column name strings to
+                include in the cube.
+
+        Examples:
+            With a single column, ``cube`` behaves identically to
+            :py:meth:`rollup`:
+
+            >>> from datafusion.expr import GroupingSet
+            >>> ctx = dfn.SessionContext()
+            >>> df = ctx.from_pydict({"a": [1, 1, 2], "b": [10, 20, 30]})
+            >>> result = df.aggregate(
+            ...     [GroupingSet.cube(dfn.col("a"))],
+            ...     [dfn.functions.sum(dfn.col("b")).alias("s"),
+            ...      dfn.functions.grouping(dfn.col("a"))],
+            ... ).sort(dfn.col("a").sort(nulls_first=False))
+            >>> result.collect_column("s").to_pylist()
+            [30, 30, 60]
+
+        See Also:
+            :py:meth:`rollup`, :py:meth:`grouping_sets`,
+            :py:func:`~datafusion.functions.grouping`
+        """
+        args = [_to_raw_expr(e) for e in exprs]
+        return Expr(expr_internal.GroupingSet.cube(*args))
+
+    @staticmethod
+    def grouping_sets(*expr_lists: list[Expr | str]) -> Expr:
+        """Create explicit grouping sets for use with ``aggregate()``.
+
+        Each argument is a list of column expressions or column name
+        strings representing one grouping set. For example,
+        ``grouping_sets([a], [b])`` groups by ``a`` alone and by ``b``
+        alone in a single query.
+
+        This is equivalent to ``GROUP BY GROUPING SETS ((a), (b))`` in
+        SQL.
+
+        Args:
+            *expr_lists: Each positional argument is a list of
+                expressions or column name strings forming one
+                grouping set.
+
+        Examples:
+            >>> from datafusion.expr import GroupingSet
+            >>> ctx = dfn.SessionContext()
+            >>> df = ctx.from_pydict(
+            ...     {"a": ["x", "x", "y"], "b": ["m", "n", "m"],
+            ...      "c": [1, 2, 3]})
+            >>> result = df.aggregate(
+            ...     [GroupingSet.grouping_sets(
+            ...         [dfn.col("a")], [dfn.col("b")])],
+            ...     [dfn.functions.sum(dfn.col("c")).alias("s"),
+            ...      dfn.functions.grouping(dfn.col("a")),
+            ...      dfn.functions.grouping(dfn.col("b"))],
+            ... ).sort(
+            ...     dfn.col("a").sort(nulls_first=False),
+            ...     dfn.col("b").sort(nulls_first=False),
+            ... )
+            >>> result.collect_column("s").to_pylist()
+            [3, 3, 4, 2]
+
+        See Also:
+            :py:meth:`rollup`, :py:meth:`cube`,
+            :py:func:`~datafusion.functions.grouping`
+        """
+        raw_lists = [[_to_raw_expr(e) for e in lst] for lst in expr_lists]
+        return Expr(expr_internal.GroupingSet.grouping_sets(*raw_lists))
diff --git a/python/datafusion/functions.py b/python/datafusion/functions.py
index 431afcc30..841cd9c0b 100644
--- a/python/datafusion/functions.py
+++ b/python/datafusion/functions.py
@@ -18,7 +18,7 @@
 
 from __future__ import annotations
 
-from typing import TYPE_CHECKING, Any
+from typing import Any
 
 import pyarrow as pa
 
@@ -29,20 +29,11 @@
     Expr,
     SortExpr,
     SortKey,
-    WindowFrame,
     expr_list_to_raw_expr_list,
     sort_list_to_raw_sort_list,
     sort_or_default,
 )
 
-try:
-    from warnings import deprecated  # Python 3.13+
-except ImportError:
-    from typing_extensions import deprecated  # Python 3.12
-
-if TYPE_CHECKING:
-    from datafusion.context import SessionContext
-
 __all__ = [
     "abs",
     "acos",
@@ -54,10 +45,13 @@
     "approx_percentile_cont_with_weight",
     "array",
     "array_agg",
+    "array_any_value",
     "array_append",
     "array_cat",
     "array_concat",
+    "array_contains",
     "array_dims",
+    "array_distance",
     "array_distinct",
     "array_element",
     "array_empty",
@@ -70,6 +64,8 @@
     "array_intersect",
     "array_join",
     "array_length",
+    "array_max",
+    "array_min",
     "array_ndims",
     "array_pop_back",
     "array_pop_front",
@@ -86,11 +82,15 @@
     "array_replace_all",
     "array_replace_n",
     "array_resize",
+    "array_reverse",
     "array_slice",
     "array_sort",
     "array_to_string",
     "array_union",
+    "arrays_overlap",
+    "arrays_zip",
     "arrow_cast",
+    "arrow_metadata",
     "arrow_typeof",
     "ascii",
     "asin",
@@ -117,6 +117,7 @@
     "col",
     "concat",
     "concat_ws",
+    "contains",
     "corr",
     "cos",
     "cosh",
@@ -129,7 +130,9 @@
     "cume_dist",
     "current_date",
     "current_time",
+    "current_timestamp",
     "date_bin",
+    "date_format",
     "date_part",
     "date_trunc",
     "datepart",
@@ -138,6 +141,7 @@
     "degrees",
     "dense_rank",
     "digest",
+    "element_at",
     "empty",
     "encode",
     "ends_with",
@@ -150,6 +154,12 @@
     "floor",
     "from_unixtime",
     "gcd",
+    "gen_series",
+    "generate_series",
+    "get_field",
+    "greatest",
+    "grouping",
+    "ifnull",
     "in_list",
     "initcap",
     "isnan",
@@ -158,22 +168,35 @@
     "last_value",
     "lcm",
     "lead",
+    "least",
     "left",
     "length",
     "levenshtein",
+    "list_any_value",
     "list_append",
     "list_cat",
     "list_concat",
+    "list_contains",
     "list_dims",
+    "list_distance",
     "list_distinct",
     "list_element",
+    "list_empty",
     "list_except",
     "list_extract",
+    "list_has",
+    "list_has_all",
+    "list_has_any",
     "list_indexof",
     "list_intersect",
     "list_join",
     "list_length",
+    "list_max",
+    "list_min",
     "list_ndims",
+    "list_overlap",
+    "list_pop_back",
+    "list_pop_front",
     "list_position",
     "list_positions",
     "list_prepend",
@@ -187,10 +210,12 @@
     "list_replace_all",
     "list_replace_n",
     "list_resize",
+    "list_reverse",
     "list_slice",
     "list_sort",
     "list_to_string",
     "list_union",
+    "list_zip",
     "ln",
     "log",
     "log2",
@@ -201,6 +226,12 @@
     "make_array",
     "make_date",
     "make_list",
+    "make_map",
+    "make_time",
+    "map_entries",
+    "map_extract",
+    "map_keys",
+    "map_values",
     "max",
     "md5",
     "mean",
@@ -213,13 +244,16 @@
     "ntile",
     "nullif",
     "nvl",
+    "nvl2",
     "octet_length",
     "order_by",
     "overlay",
     "percent_rank",
+    "percentile_cont",
     "pi",
     "pow",
     "power",
+    "quantile_cont",
     "radians",
     "random",
     "range",
@@ -243,6 +277,7 @@
     "reverse",
     "right",
     "round",
+    "row",
     "row_number",
     "rpad",
     "rtrim",
@@ -260,6 +295,8 @@
     "stddev_pop",
     "stddev_samp",
     "string_agg",
+    "string_to_array",
+    "string_to_list",
     "strpos",
     "struct",
     "substr",
@@ -268,30 +305,45 @@
     "sum",
     "tan",
     "tanh",
+    "to_char",
+    "to_date",
     "to_hex",
+    "to_local_time",
+    "to_time",
     "to_timestamp",
     "to_timestamp_micros",
     "to_timestamp_millis",
     "to_timestamp_nanos",
     "to_timestamp_seconds",
     "to_unixtime",
+    "today",
     "translate",
     "trim",
     "trunc",
+    "union_extract",
+    "union_tag",
     "upper",
     "uuid",
     "var",
     "var_pop",
+    "var_population",
     "var_samp",
     "var_sample",
+    "version",
     "when",
-    # Window Functions
-    "window",
 ]
 
 
 def isnan(expr: Expr) -> Expr:
-    """Returns true if a given number is +NaN or -NaN otherwise returns false."""
+    """Returns true if a given number is +NaN or -NaN otherwise returns false.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1.0, np.nan]})
+        >>> result = df.select(dfn.functions.isnan(dfn.col("a")).alias("isnan"))
+        >>> result.collect_column("isnan")[1].as_py()
+        True
+    """
     return Expr(f.isnan(expr.expr))
 
 
@@ -299,29 +351,65 @@ def nullif(expr1: Expr, expr2: Expr) -> Expr:
     """Returns NULL if expr1 equals expr2; otherwise it returns expr1.
 
     This can be used to perform the inverse operation of the COALESCE expression.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1, 2], "b": [1, 3]})
+        >>> result = df.select(
+        ...     dfn.functions.nullif(dfn.col("a"), dfn.col("b")).alias("nullif"))
+        >>> result.collect_column("nullif").to_pylist()
+        [None, 2]
     """
     return Expr(f.nullif(expr1.expr, expr2.expr))
 
 
 def encode(expr: Expr, encoding: Expr) -> Expr:
-    """Encode the ``input``, using the ``encoding``. encoding can be base64 or hex."""
+    """Encode the ``input``, using the ``encoding``. encoding can be base64 or hex.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["hello"]})
+        >>> result = df.select(
+        ...     dfn.functions.encode(dfn.col("a"), dfn.lit("base64")).alias("enc"))
+        >>> result.collect_column("enc")[0].as_py()
+        'aGVsbG8'
+    """
     return Expr(f.encode(expr.expr, encoding.expr))
 
 
 def decode(expr: Expr, encoding: Expr) -> Expr:
-    """Decode the ``input``, using the ``encoding``. encoding can be base64 or hex."""
+    """Decode the ``input``, using the ``encoding``. encoding can be base64 or hex.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["aGVsbG8="]})
+        >>> result = df.select(
+        ...     dfn.functions.decode(dfn.col("a"), dfn.lit("base64")).alias("dec"))
+        >>> result.collect_column("dec")[0].as_py()
+        b'hello'
+    """
     return Expr(f.decode(expr.expr, encoding.expr))
 
 
 def array_to_string(expr: Expr, delimiter: Expr) -> Expr:
-    """Converts each element to its text representation."""
+    """Converts each element to its text representation.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [[1, 2, 3]]})
+        >>> result = df.select(
+        ...     dfn.functions.array_to_string(dfn.col("a"), dfn.lit(",")).alias("s"))
+        >>> result.collect_column("s")[0].as_py()
+        '1,2,3'
+    """
     return Expr(f.array_to_string(expr.expr, delimiter.expr.cast(pa.string())))
 
 
 def array_join(expr: Expr, delimiter: Expr) -> Expr:
     """Converts each element to its text representation.
 
-    This is an alias for :py:func:`array_to_string`.
+    See Also:
+        This is an alias for :py:func:`array_to_string`.
     """
     return array_to_string(expr, delimiter)
 
@@ -329,7 +417,8 @@ def array_join(expr: Expr, delimiter: Expr) -> Expr:
 def list_to_string(expr: Expr, delimiter: Expr) -> Expr:
     """Converts each element to its text representation.
 
-    This is an alias for :py:func:`array_to_string`.
+    See Also:
+        This is an alias for :py:func:`array_to_string`.
     """
     return array_to_string(expr, delimiter)
 
@@ -337,13 +426,35 @@ def list_to_string(expr: Expr, delimiter: Expr) -> Expr:
 def list_join(expr: Expr, delimiter: Expr) -> Expr:
     """Converts each element to its text representation.
 
-    This is an alias for :py:func:`array_to_string`.
+    See Also:
+        This is an alias for :py:func:`array_to_string`.
     """
     return array_to_string(expr, delimiter)
 
 
 def in_list(arg: Expr, values: list[Expr], negated: bool = False) -> Expr:
-    """Returns whether the argument is contained within the list ``values``."""
+    """Returns whether the argument is contained within the list ``values``.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1, 2, 3]})
+        >>> result = df.select(
+        ...     dfn.functions.in_list(
+        ...         dfn.col("a"), [dfn.lit(1), dfn.lit(3)]
+        ...     ).alias("in")
+        ... )
+        >>> result.collect_column("in").to_pylist()
+        [True, False, True]
+
+        >>> result = df.select(
+        ...     dfn.functions.in_list(
+        ...         dfn.col("a"), [dfn.lit(1), dfn.lit(3)],
+        ...         negated=True,
+        ...     ).alias("not_in")
+        ... )
+        >>> result.collect_column("not_in").to_pylist()
+        [False, True, False]
+    """
     values = [v.expr for v in values]
     return Expr(f.in_list(arg.expr, values, negated))
 
@@ -353,14 +464,45 @@ def digest(value: Expr, method: Expr) -> Expr:
 
     Standard algorithms are md5, sha224, sha256, sha384, sha512, blake2s,
     blake2b, and blake3.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["hello"]})
+        >>> result = df.select(
+        ...     dfn.functions.digest(dfn.col("a"), dfn.lit("md5")).alias("d"))
+        >>> len(result.collect_column("d")[0].as_py()) > 0
+        True
     """
     return Expr(f.digest(value.expr, method.expr))
 
 
+def contains(string: Expr, search_str: Expr) -> Expr:
+    """Returns true if ``search_str`` is found within ``string`` (case-sensitive).
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["the quick brown fox"]})
+        >>> result = df.select(
+        ...     dfn.functions.contains(dfn.col("a"), dfn.lit("brown")).alias("c"))
+        >>> result.collect_column("c")[0].as_py()
+        True
+    """
+    return Expr(f.contains(string.expr, search_str.expr))
+
+
 def concat(*args: Expr) -> Expr:
     """Concatenates the text representations of all the arguments.
 
     NULL arguments are ignored.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["hello"], "b": [" world"]})
+        >>> result = df.select(
+        ...     dfn.functions.concat(dfn.col("a"), dfn.col("b")).alias("c")
+        ... )
+        >>> result.collect_column("c")[0].as_py()
+        'hello world'
     """
     args = [arg.expr for arg in args]
     return Expr(f.concat(args))
@@ -370,13 +512,33 @@ def concat_ws(separator: str, *args: Expr) -> Expr:
     """Concatenates the list ``args`` with the separator.
 
     ``NULL`` arguments are ignored. ``separator`` should not be ``NULL``.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["hello"], "b": ["world"]})
+        >>> result = df.select(
+        ...     dfn.functions.concat_ws("-", dfn.col("a"), dfn.col("b")).alias("c"))
+        >>> result.collect_column("c")[0].as_py()
+        'hello-world'
     """
     args = [arg.expr for arg in args]
     return Expr(f.concat_ws(separator, args))
 
 
 def order_by(expr: Expr, ascending: bool = True, nulls_first: bool = True) -> SortExpr:
-    """Creates a new sort expression."""
+    """Creates a new sort expression.
+
+    Examples:
+        >>> sort_expr = dfn.functions.order_by(
+        ...     dfn.col("a"), ascending=False)
+        >>> sort_expr.ascending()
+        False
+
+        >>> sort_expr = dfn.functions.order_by(
+        ...     dfn.col("a"), ascending=True, nulls_first=False)
+        >>> sort_expr.nulls_first()
+        False
+    """
     return SortExpr(expr, ascending=ascending, nulls_first=nulls_first)
 
 
@@ -388,14 +550,39 @@ def alias(expr: Expr, name: str, metadata: dict[str, str] | None = None) -> Expr
         name: The alias name
         metadata: Optional metadata to attach to the column
 
-    Returns:
-        An expression with the given alias
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1, 2]})
+        >>> result = df.select(
+        ...     dfn.functions.alias(
+        ...         dfn.col("a"), "b"
+        ...     )
+        ... )
+        >>> result.collect_column("b")[0].as_py()
+        1
+
+        >>> result = df.select(
+        ...     dfn.functions.alias(
+        ...         dfn.col("a"), "b", metadata={"info": "test"}
+        ...     )
+        ... )
+        >>> result.schema()
+        b: int64
+          -- field metadata --
+          info: 'test'
     """
     return Expr(f.alias(expr.expr, name, metadata))
 
 
 def col(name: str) -> Expr:
-    """Creates a column reference expression."""
+    """Creates a column reference expression.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1, 2, 3]})
+        >>> df.select(dfn.functions.col("a")).collect_column("a")[0].as_py()
+        1
+    """
     return Expr(f.col(name))
 
 
@@ -409,6 +596,22 @@ def count_star(filter: Expr | None = None) -> Expr:
 
     Args:
         filter: If provided, only count rows for which the filter is True
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1, 2, 3]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.count_star(
+        ...     ).alias("cnt")])
+        >>> result.collect_column("cnt")[0].as_py()
+        3
+
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.count_star(
+        ...         filter=dfn.col("a") > dfn.lit(1)
+        ...     ).alias("cnt")])
+        >>> result.collect_column("cnt")[0].as_py()
+        2
     """
     return count(Expr.literal(1), filter=filter)
 
@@ -419,6 +622,15 @@ def case(expr: Expr) -> CaseBuilder:
     Create a :py:class:`~datafusion.expr.CaseBuilder` to match cases for the
     expression ``expr``. See :py:class:`~datafusion.expr.CaseBuilder` for
     detailed usage.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1, 2, 3]})
+        >>> result = df.select(
+        ...     dfn.functions.case(dfn.col("a")).when(dfn.lit(1),
+        ...     dfn.lit("one")).otherwise(dfn.lit("other")).alias("c"))
+        >>> result.collect_column("c")[0].as_py()
+        'one'
     """
     return CaseBuilder(f.case(expr.expr))
 
@@ -429,61 +641,29 @@ def when(when: Expr, then: Expr) -> CaseBuilder:
     Create a :py:class:`~datafusion.expr.CaseBuilder` to match cases for the
     expression ``expr``. See :py:class:`~datafusion.expr.CaseBuilder` for
     detailed usage.
-    """
-    return CaseBuilder(f.when(when.expr, then.expr))
 
-
-@deprecated("Prefer to call Expr.over() instead")
-def window(
-    name: str,
-    args: list[Expr],
-    partition_by: list[Expr] | Expr | None = None,
-    order_by: list[SortKey] | SortKey | None = None,
-    window_frame: WindowFrame | None = None,
-    filter: Expr | None = None,
-    distinct: bool = False,
-    ctx: SessionContext | None = None,
-) -> Expr:
-    """Creates a new Window function expression.
-
-    This interface will soon be deprecated. Instead of using this interface,
-    users should call the window functions directly. For example, to perform a
-    lag use::
-
-        df.select(functions.lag(col("a")).partition_by(col("b")).build())
-
-    The ``order_by`` parameter accepts column names or expressions, e.g.::
-
-        window("lag", [col("a")], order_by="ts")
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1, 2, 3]})
+        >>> result = df.select(
+        ...     dfn.functions.when(dfn.col("a") > dfn.lit(2),
+        ...     dfn.lit("big")).otherwise(dfn.lit("small")).alias("c"))
+        >>> result.collect_column("c")[2].as_py()
+        'big'
     """
-    args = [a.expr for a in args]
-    partition_by_raw = expr_list_to_raw_expr_list(partition_by)
-    order_by_raw = sort_list_to_raw_sort_list(order_by)
-    window_frame = window_frame.window_frame if window_frame is not None else None
-    ctx = ctx.ctx if ctx is not None else None
-    filter_raw = filter.expr if filter is not None else None
-    return Expr(
-        f.window(
-            name,
-            args,
-            partition_by=partition_by_raw,
-            order_by=order_by_raw,
-            window_frame=window_frame,
-            ctx=ctx,
-            filter=filter_raw,
-            distinct=distinct,
-        )
-    )
+    return CaseBuilder(f.when(when.expr, then.expr))
 
 
 # scalar functions
 def abs(arg: Expr) -> Expr:
     """Return the absolute value of a given number.
 
-    Returns:
-    --------
-    Expr
-        A new expression representing the absolute value of the input expression.
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [-1, 0, 1]})
+        >>> result = df.select(dfn.functions.abs(dfn.col("a")).alias("abs"))
+        >>> result.collect_column("abs")[0].as_py()
+        1
     """
     return Expr(f.abs(arg.expr))
 
@@ -491,127 +671,323 @@ def abs(arg: Expr) -> Expr:
 def acos(arg: Expr) -> Expr:
     """Returns the arc cosine or inverse cosine of a number.
 
-    Returns:
-    --------
-    Expr
-        A new expression representing the arc cosine of the input expression.
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1.0]})
+        >>> result = df.select(dfn.functions.acos(dfn.col("a")).alias("acos"))
+        >>> result.collect_column("acos")[0].as_py()
+        0.0
     """
     return Expr(f.acos(arg.expr))
 
 
 def acosh(arg: Expr) -> Expr:
-    """Returns inverse hyperbolic cosine."""
+    """Returns inverse hyperbolic cosine.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1.0]})
+        >>> result = df.select(dfn.functions.acosh(dfn.col("a")).alias("acosh"))
+        >>> result.collect_column("acosh")[0].as_py()
+        0.0
+    """
     return Expr(f.acosh(arg.expr))
 
 
 def ascii(arg: Expr) -> Expr:
-    """Returns the numeric code of the first character of the argument."""
+    """Returns the numeric code of the first character of the argument.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["a","b","c"]})
+        >>> ascii_df = df.select(dfn.functions.ascii(dfn.col("a")).alias("ascii"))
+        >>> ascii_df.collect_column("ascii")[0].as_py()
+        97
+    """
     return Expr(f.ascii(arg.expr))
 
 
 def asin(arg: Expr) -> Expr:
-    """Returns the arc sine or inverse sine of a number."""
+    """Returns the arc sine or inverse sine of a number.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [0.0]})
+        >>> result = df.select(dfn.functions.asin(dfn.col("a")).alias("asin"))
+        >>> result.collect_column("asin")[0].as_py()
+        0.0
+    """
     return Expr(f.asin(arg.expr))
 
 
 def asinh(arg: Expr) -> Expr:
-    """Returns inverse hyperbolic sine."""
+    """Returns inverse hyperbolic sine.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [0.0]})
+        >>> result = df.select(dfn.functions.asinh(dfn.col("a")).alias("asinh"))
+        >>> result.collect_column("asinh")[0].as_py()
+        0.0
+    """
     return Expr(f.asinh(arg.expr))
 
 
 def atan(arg: Expr) -> Expr:
-    """Returns inverse tangent of a number."""
+    """Returns inverse tangent of a number.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [0.0]})
+        >>> result = df.select(dfn.functions.atan(dfn.col("a")).alias("atan"))
+        >>> result.collect_column("atan")[0].as_py()
+        0.0
+    """
     return Expr(f.atan(arg.expr))
 
 
 def atanh(arg: Expr) -> Expr:
-    """Returns inverse hyperbolic tangent."""
+    """Returns inverse hyperbolic tangent.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [0.0]})
+        >>> result = df.select(dfn.functions.atanh(dfn.col("a")).alias("atanh"))
+        >>> result.collect_column("atanh")[0].as_py()
+        0.0
+    """
     return Expr(f.atanh(arg.expr))
 
 
 def atan2(y: Expr, x: Expr) -> Expr:
-    """Returns inverse tangent of a division given in the argument."""
+    """Returns inverse tangent of a division given in the argument.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"y": [0.0], "x": [1.0]})
+        >>> result = df.select(
+        ...     dfn.functions.atan2(dfn.col("y"), dfn.col("x")).alias("atan2"))
+        >>> result.collect_column("atan2")[0].as_py()
+        0.0
+    """
     return Expr(f.atan2(y.expr, x.expr))
 
 
 def bit_length(arg: Expr) -> Expr:
-    """Returns the number of bits in the string argument."""
+    """Returns the number of bits in the string argument.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["a","b","c"]})
+        >>> bit_df = df.select(dfn.functions.bit_length(dfn.col("a")).alias("bit_len"))
+        >>> bit_df.collect_column("bit_len")[0].as_py()
+        8
+    """
     return Expr(f.bit_length(arg.expr))
 
 
 def btrim(arg: Expr) -> Expr:
-    """Removes all characters, spaces by default, from both sides of a string."""
+    """Removes all characters, spaces by default, from both sides of a string.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [" a  "]})
+        >>> trim_df = df.select(dfn.functions.btrim(dfn.col("a")).alias("trimmed"))
+        >>> trim_df.collect_column("trimmed")[0].as_py()
+        'a'
+    """
     return Expr(f.btrim(arg.expr))
 
 
 def cbrt(arg: Expr) -> Expr:
-    """Returns the cube root of a number."""
+    """Returns the cube root of a number.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [27]})
+        >>> cbrt_df = df.select(dfn.functions.cbrt(dfn.col("a")).alias("cbrt"))
+        >>> cbrt_df.collect_column("cbrt")[0].as_py()
+        3.0
+    """
     return Expr(f.cbrt(arg.expr))
 
 
 def ceil(arg: Expr) -> Expr:
-    """Returns the nearest integer greater than or equal to argument."""
+    """Returns the nearest integer greater than or equal to argument.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1.9]})
+        >>> ceil_df = df.select(dfn.functions.ceil(dfn.col("a")).alias("ceil"))
+        >>> ceil_df.collect_column("ceil")[0].as_py()
+        2.0
+    """
     return Expr(f.ceil(arg.expr))
 
 
 def character_length(arg: Expr) -> Expr:
-    """Returns the number of characters in the argument."""
+    """Returns the number of characters in the argument.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["abc","b","c"]})
+        >>> char_len_df = df.select(
+        ...     dfn.functions.character_length(dfn.col("a")).alias("char_len"))
+        >>> char_len_df.collect_column("char_len")[0].as_py()
+        3
+    """
     return Expr(f.character_length(arg.expr))
 
 
 def length(string: Expr) -> Expr:
-    """The number of characters in the ``string``."""
+    """The number of characters in the ``string``.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["hello"]})
+        >>> result = df.select(dfn.functions.length(dfn.col("a")).alias("len"))
+        >>> result.collect_column("len")[0].as_py()
+        5
+    """
     return Expr(f.length(string.expr))
 
 
 def char_length(string: Expr) -> Expr:
-    """The number of characters in the ``string``."""
+    """The number of characters in the ``string``.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["hello"]})
+        >>> result = df.select(dfn.functions.char_length(dfn.col("a")).alias("len"))
+        >>> result.collect_column("len")[0].as_py()
+        5
+    """
     return Expr(f.char_length(string.expr))
 
 
 def chr(arg: Expr) -> Expr:
-    """Converts the Unicode code point to a UTF8 character."""
+    """Converts the Unicode code point to a UTF8 character.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [65]})
+        >>> result = df.select(dfn.functions.chr(dfn.col("a")).alias("chr"))
+        >>> result.collect_column("chr")[0].as_py()
+        'A'
+    """
     return Expr(f.chr(arg.expr))
 
 
 def coalesce(*args: Expr) -> Expr:
-    """Returns the value of the first expr in ``args`` which is not NULL."""
+    """Returns the value of the first expr in ``args`` which is not NULL.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [None, 1], "b": [2, 3]})
+        >>> result = df.select(
+        ...     dfn.functions.coalesce(dfn.col("a"), dfn.col("b")).alias("c"))
+        >>> result.collect_column("c")[0].as_py()
+        2
+    """
     args = [arg.expr for arg in args]
     return Expr(f.coalesce(*args))
 
 
 def cos(arg: Expr) -> Expr:
-    """Returns the cosine of the argument."""
+    """Returns the cosine of the argument.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [0,-1,1]})
+        >>> cos_df = df.select(dfn.functions.cos(dfn.col("a")).alias("cos"))
+        >>> cos_df.collect_column("cos")[0].as_py()
+        1.0
+    """
     return Expr(f.cos(arg.expr))
 
 
 def cosh(arg: Expr) -> Expr:
-    """Returns the hyperbolic cosine of the argument."""
+    """Returns the hyperbolic cosine of the argument.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [0,-1,1]})
+        >>> cosh_df = df.select(dfn.functions.cosh(dfn.col("a")).alias("cosh"))
+        >>> cosh_df.collect_column("cosh")[0].as_py()
+        1.0
+    """
     return Expr(f.cosh(arg.expr))
 
 
 def cot(arg: Expr) -> Expr:
-    """Returns the cotangent of the argument."""
+    """Returns the cotangent of the argument.
+
+    Examples:
+        >>> from math import pi
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [pi / 4]})
+        >>> result = df.select(
+        ...     dfn.functions.cot(dfn.col("a")).alias("cot")
+        ... )
+        >>> result.collect_column("cot")[0].as_py()
+        1.0...
+    """
     return Expr(f.cot(arg.expr))
 
 
 def degrees(arg: Expr) -> Expr:
-    """Converts the argument from radians to degrees."""
+    """Converts the argument from radians to degrees.
+
+    Examples:
+        >>> from math import pi
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [0,pi,2*pi]})
+        >>> deg_df = df.select(dfn.functions.degrees(dfn.col("a")).alias("deg"))
+        >>> deg_df.collect_column("deg")[2].as_py()
+        360.0
+    """
     return Expr(f.degrees(arg.expr))
 
 
 def ends_with(arg: Expr, suffix: Expr) -> Expr:
-    """Returns true if the ``string`` ends with the ``suffix``, false otherwise."""
+    """Returns true if the ``string`` ends with the ``suffix``, false otherwise.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["abc","b","c"]})
+        >>> ends_with_df = df.select(
+        ...     dfn.functions.ends_with(dfn.col("a"), dfn.lit("c")).alias("ends_with"))
+        >>> ends_with_df.collect_column("ends_with")[0].as_py()
+        True
+    """
     return Expr(f.ends_with(arg.expr, suffix.expr))
 
 
 def exp(arg: Expr) -> Expr:
-    """Returns the exponential of the argument."""
+    """Returns the exponential of the argument.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [0.0]})
+        >>> result = df.select(dfn.functions.exp(dfn.col("a")).alias("exp"))
+        >>> result.collect_column("exp")[0].as_py()
+        1.0
+    """
     return Expr(f.exp(arg.expr))
 
 
 def factorial(arg: Expr) -> Expr:
-    """Returns the factorial of the argument."""
+    """Returns the factorial of the argument.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [3]})
+        >>> result = df.select(
+        ...     dfn.functions.factorial(dfn.col("a")).alias("factorial")
+        ... )
+        >>> result.collect_column("factorial")[0].as_py()
+        6
+    """
     return Expr(f.factorial(arg.expr))
 
 
@@ -622,25 +998,86 @@ def find_in_set(string: Expr, string_list: Expr) -> Expr:
     ``string_list`` consisting of N substrings.
 
     The string list is a string composed of substrings separated by ``,`` characters.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["b"]})
+        >>> result = df.select(
+        ...     dfn.functions.find_in_set(dfn.col("a"), dfn.lit("a,b,c")).alias("pos"))
+        >>> result.collect_column("pos")[0].as_py()
+        2
     """
     return Expr(f.find_in_set(string.expr, string_list.expr))
 
 
 def floor(arg: Expr) -> Expr:
-    """Returns the nearest integer less than or equal to the argument."""
+    """Returns the nearest integer less than or equal to the argument.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1.9]})
+        >>> floor_df = df.select(dfn.functions.floor(dfn.col("a")).alias("floor"))
+        >>> floor_df.collect_column("floor")[0].as_py()
+        1.0
+    """
     return Expr(f.floor(arg.expr))
 
 
 def gcd(x: Expr, y: Expr) -> Expr:
-    """Returns the greatest common divisor."""
+    """Returns the greatest common divisor.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [12], "b": [8]})
+        >>> result = df.select(
+        ...     dfn.functions.gcd(dfn.col("a"), dfn.col("b")).alias("gcd")
+        ... )
+        >>> result.collect_column("gcd")[0].as_py()
+        4
+    """
     return Expr(f.gcd(x.expr, y.expr))
 
 
+def greatest(*args: Expr) -> Expr:
+    """Returns the greatest value from a list of expressions.
+
+    Returns NULL if all expressions are NULL.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1, 3], "b": [2, 1]})
+        >>> result = df.select(
+        ...     dfn.functions.greatest(dfn.col("a"), dfn.col("b")).alias("greatest"))
+        >>> result.collect_column("greatest")[0].as_py()
+        2
+        >>> result.collect_column("greatest")[1].as_py()
+        3
+    """
+    exprs = [arg.expr for arg in args]
+    return Expr(f.greatest(*exprs))
+
+
+def ifnull(x: Expr, y: Expr) -> Expr:
+    """Returns ``x`` if ``x`` is not NULL. Otherwise returns ``y``.
+
+    See Also:
+        This is an alias for :py:func:`nvl`.
+    """
+    return nvl(x, y)
+
+
 def initcap(string: Expr) -> Expr:
     """Set the initial letter of each word to capital.
 
     Converts the first letter of each word in ``string`` to uppercase and the remaining
     characters to lowercase.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["the cat"]})
+        >>> cap_df = df.select(dfn.functions.initcap(dfn.col("a")).alias("cap"))
+        >>> cap_df.collect_column("cap")[0].as_py()
+        'The Cat'
     """
     return Expr(f.initcap(string.expr))
 
@@ -648,53 +1085,151 @@ def initcap(string: Expr) -> Expr:
 def instr(string: Expr, substring: Expr) -> Expr:
     """Finds the position from where the ``substring`` matches the ``string``.
 
-    This is an alias for :py:func:`strpos`.
+    See Also:
+        This is an alias for :py:func:`strpos`.
     """
     return strpos(string, substring)
 
 
 def iszero(arg: Expr) -> Expr:
-    """Returns true if a given number is +0.0 or -0.0 otherwise returns false."""
+    """Returns true if a given number is +0.0 or -0.0 otherwise returns false.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [0.0, 1.0]})
+        >>> result = df.select(dfn.functions.iszero(dfn.col("a")).alias("iz"))
+        >>> result.collect_column("iz")[0].as_py()
+        True
+    """
     return Expr(f.iszero(arg.expr))
 
 
 def lcm(x: Expr, y: Expr) -> Expr:
-    """Returns the least common multiple."""
+    """Returns the least common multiple.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [4], "b": [6]})
+        >>> result = df.select(
+        ...     dfn.functions.lcm(dfn.col("a"), dfn.col("b")).alias("lcm")
+        ... )
+        >>> result.collect_column("lcm")[0].as_py()
+        12
+    """
     return Expr(f.lcm(x.expr, y.expr))
 
 
+def least(*args: Expr) -> Expr:
+    """Returns the least value from a list of expressions.
+
+    Returns NULL if all expressions are NULL.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1, 3], "b": [2, 1]})
+        >>> result = df.select(
+        ...     dfn.functions.least(dfn.col("a"), dfn.col("b")).alias("least"))
+        >>> result.collect_column("least")[0].as_py()
+        1
+        >>> result.collect_column("least")[1].as_py()
+        1
+    """
+    exprs = [arg.expr for arg in args]
+    return Expr(f.least(*exprs))
+
+
 def left(string: Expr, n: Expr) -> Expr:
-    """Returns the first ``n`` characters in the ``string``."""
+    """Returns the first ``n`` characters in the ``string``.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["the cat"]})
+        >>> left_df = df.select(
+        ...     dfn.functions.left(dfn.col("a"), dfn.lit(3)).alias("left"))
+        >>> left_df.collect_column("left")[0].as_py()
+        'the'
+    """
     return Expr(f.left(string.expr, n.expr))
 
 
 def levenshtein(string1: Expr, string2: Expr) -> Expr:
-    """Returns the Levenshtein distance between the two given strings."""
+    """Returns the Levenshtein distance between the two given strings.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["kitten"]})
+        >>> result = df.select(
+        ...     dfn.functions.levenshtein(dfn.col("a"), dfn.lit("sitting")).alias("d"))
+        >>> result.collect_column("d")[0].as_py()
+        3
+    """
     return Expr(f.levenshtein(string1.expr, string2.expr))
 
 
 def ln(arg: Expr) -> Expr:
-    """Returns the natural logarithm (base e) of the argument."""
+    """Returns the natural logarithm (base e) of the argument.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1.0]})
+        >>> result = df.select(dfn.functions.ln(dfn.col("a")).alias("ln"))
+        >>> result.collect_column("ln")[0].as_py()
+        0.0
+    """
     return Expr(f.ln(arg.expr))
 
 
 def log(base: Expr, num: Expr) -> Expr:
-    """Returns the logarithm of a number for a particular ``base``."""
+    """Returns the logarithm of a number for a particular ``base``.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [100.0]})
+        >>> result = df.select(
+        ...     dfn.functions.log(dfn.lit(10.0), dfn.col("a")).alias("log")
+        ... )
+        >>> result.collect_column("log")[0].as_py()
+        2.0
+    """
     return Expr(f.log(base.expr, num.expr))
 
 
 def log10(arg: Expr) -> Expr:
-    """Base 10 logarithm of the argument."""
+    """Base 10 logarithm of the argument.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [100.0]})
+        >>> result = df.select(dfn.functions.log10(dfn.col("a")).alias("log10"))
+        >>> result.collect_column("log10")[0].as_py()
+        2.0
+    """
     return Expr(f.log10(arg.expr))
 
 
 def log2(arg: Expr) -> Expr:
-    """Base 2 logarithm of the argument."""
+    """Base 2 logarithm of the argument.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [8.0]})
+        >>> result = df.select(dfn.functions.log2(dfn.col("a")).alias("log2"))
+        >>> result.collect_column("log2")[0].as_py()
+        3.0
+    """
     return Expr(f.log2(arg.expr))
 
 
 def lower(arg: Expr) -> Expr:
-    """Converts a string to lowercase."""
+    """Converts a string to lowercase.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["THE CaT"]})
+        >>> lower_df = df.select(dfn.functions.lower(dfn.col("a")).alias("lower"))
+        >>> lower_df.collect_column("lower")[0].as_py()
+        'the cat'
+    """
     return Expr(f.lower(arg.expr))
 
 
@@ -704,33 +1239,117 @@ def lpad(string: Expr, count: Expr, characters: Expr | None = None) -> Expr:
     Extends the string to length length by prepending the characters fill (a
     space by default). If the string is already longer than length then it is
     truncated (on the right).
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["the cat", "a hat"]})
+        >>> lpad_df = df.select(
+        ...     dfn.functions.lpad(
+        ...         dfn.col("a"), dfn.lit(6)
+        ...     ).alias("lpad"))
+        >>> lpad_df.collect_column("lpad")[0].as_py()
+        'the ca'
+        >>> lpad_df.collect_column("lpad")[1].as_py()
+        ' a hat'
+
+        >>> result = df.select(
+        ...     dfn.functions.lpad(
+        ...         dfn.col("a"), dfn.lit(10), characters=dfn.lit(".")
+        ...     ).alias("lpad"))
+        >>> result.collect_column("lpad")[0].as_py()
+        '...the cat'
     """
     characters = characters if characters is not None else Expr.literal(" ")
     return Expr(f.lpad(string.expr, count.expr, characters.expr))
 
 
 def ltrim(arg: Expr) -> Expr:
-    """Removes all characters, spaces by default, from the beginning of a string."""
+    """Removes all characters, spaces by default, from the beginning of a string.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [" a  "]})
+        >>> trim_df = df.select(dfn.functions.ltrim(dfn.col("a")).alias("trimmed"))
+        >>> trim_df.collect_column("trimmed")[0].as_py()
+        'a  '
+    """
     return Expr(f.ltrim(arg.expr))
 
 
 def md5(arg: Expr) -> Expr:
-    """Computes an MD5 128-bit checksum for a string expression."""
+    """Computes an MD5 128-bit checksum for a string expression.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["hello"]})
+        >>> result = df.select(dfn.functions.md5(dfn.col("a")).alias("md5"))
+        >>> result.collect_column("md5")[0].as_py()
+        '5d41402abc4b2a76b9719d911017c592'
+    """
     return Expr(f.md5(arg.expr))
 
 
 def nanvl(x: Expr, y: Expr) -> Expr:
-    """Returns ``x`` if ``x`` is not ``NaN``. Otherwise returns ``y``."""
+    """Returns ``x`` if ``x`` is not ``NaN``. Otherwise returns ``y``.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [np.nan, 1.0], "b": [0.0, 0.0]})
+        >>> nanvl_df = df.select(
+        ...     dfn.functions.nanvl(dfn.col("a"), dfn.col("b")).alias("nanvl"))
+        >>> nanvl_df.collect_column("nanvl")[0].as_py()
+        0.0
+        >>> nanvl_df.collect_column("nanvl")[1].as_py()
+        1.0
+    """
     return Expr(f.nanvl(x.expr, y.expr))
 
 
 def nvl(x: Expr, y: Expr) -> Expr:
-    """Returns ``x`` if ``x`` is not ``NULL``. Otherwise returns ``y``."""
+    """Returns ``x`` if ``x`` is not ``NULL``. Otherwise returns ``y``.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [None, 1], "b": [0, 0]})
+        >>> nvl_df = df.select(
+        ...     dfn.functions.nvl(dfn.col("a"), dfn.col("b")).alias("nvl")
+        ... )
+        >>> nvl_df.collect_column("nvl")[0].as_py()
+        0
+        >>> nvl_df.collect_column("nvl")[1].as_py()
+        1
+    """
     return Expr(f.nvl(x.expr, y.expr))
 
 
+def nvl2(x: Expr, y: Expr, z: Expr) -> Expr:
+    """Returns ``y`` if ``x`` is not NULL. Otherwise returns ``z``.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [None, 1], "b": [10, 20], "c": [30, 40]})
+        >>> result = df.select(
+        ...     dfn.functions.nvl2(
+        ...         dfn.col("a"), dfn.col("b"), dfn.col("c")).alias("nvl2")
+        ... )
+        >>> result.collect_column("nvl2")[0].as_py()
+        30
+        >>> result.collect_column("nvl2")[1].as_py()
+        20
+    """
+    return Expr(f.nvl2(x.expr, y.expr, z.expr))
+
+
 def octet_length(arg: Expr) -> Expr:
-    """Returns the number of bytes of a string."""
+    """Returns the number of bytes of a string.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["hello"]})
+        >>> result = df.select(dfn.functions.octet_length(dfn.col("a")).alias("len"))
+        >>> result.collect_column("len")[0].as_py()
+        5
+    """
     return Expr(f.octet_length(arg.expr))
 
 
@@ -741,6 +1360,15 @@ def overlay(
 
     Replace the substring of string that starts at the ``start``'th character and
     extends for ``length`` characters with new substring.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["abcdef"]})
+        >>> result = df.select(
+        ...     dfn.functions.overlay(dfn.col("a"), dfn.lit("XY"), dfn.lit(3),
+        ...     dfn.lit(2)).alias("o"))
+        >>> result.collect_column("o")[0].as_py()
+        'abXYef'
     """
     if length is None:
         return Expr(f.overlay(string.expr, substring.expr, start.expr))
@@ -748,41 +1376,97 @@ def overlay(
 
 
 def pi() -> Expr:
-    """Returns an approximate value of π."""
+    """Returns an approximate value of π.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1]})
+        >>> from math import pi
+        >>> result = df.select(
+        ...     dfn.functions.pi().alias("pi")
+        ... )
+        >>> result.collect_column("pi")[0].as_py() == pi
+        True
+    """
     return Expr(f.pi())
 
 
 def position(string: Expr, substring: Expr) -> Expr:
     """Finds the position from where the ``substring`` matches the ``string``.
 
-    This is an alias for :py:func:`strpos`.
+    See Also:
+        This is an alias for :py:func:`strpos`.
     """
     return strpos(string, substring)
 
 
 def power(base: Expr, exponent: Expr) -> Expr:
-    """Returns ``base`` raised to the power of ``exponent``."""
+    """Returns ``base`` raised to the power of ``exponent``.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [2.0]})
+        >>> result = df.select(
+        ...     dfn.functions.power(dfn.col("a"), dfn.lit(3.0)).alias("pow")
+        ... )
+        >>> result.collect_column("pow")[0].as_py()
+        8.0
+    """
     return Expr(f.power(base.expr, exponent.expr))
 
 
 def pow(base: Expr, exponent: Expr) -> Expr:
     """Returns ``base`` raised to the power of ``exponent``.
 
-    This is an alias of :py:func:`power`.
+    See Also:
+        This is an alias of :py:func:`power`.
     """
     return power(base, exponent)
 
 
 def radians(arg: Expr) -> Expr:
-    """Converts the argument from degrees to radians."""
+    """Converts the argument from degrees to radians.
+
+    Examples:
+        >>> from math import pi
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [180.0]})
+        >>> result = df.select(
+        ...     dfn.functions.radians(dfn.col("a")).alias("rad")
+        ... )
+        >>> result.collect_column("rad")[0].as_py() == pi
+        True
+    """
     return Expr(f.radians(arg.expr))
 
 
 def regexp_like(string: Expr, regex: Expr, flags: Expr | None = None) -> Expr:
-    """Find if any regular expression (regex) matches exist.
+    r"""Find if any regular expression (regex) matches exist.
 
     Tests a string using a regular expression returning true if at least one match,
     false otherwise.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["hello123"]})
+        >>> result = df.select(
+        ...     dfn.functions.regexp_like(
+        ...         dfn.col("a"), dfn.lit("\\d+")
+        ...     ).alias("m")
+        ... )
+        >>> result.collect_column("m")[0].as_py()
+        True
+
+        Use ``flags`` for case-insensitive matching:
+
+        >>> result = df.select(
+        ...     dfn.functions.regexp_like(
+        ...         dfn.col("a"), dfn.lit("HELLO"),
+        ...         flags=dfn.lit("i"),
+        ...     ).alias("m")
+        ... )
+        >>> result.collect_column("m")[0].as_py()
+        True
     """
     if flags is not None:
         flags = flags.expr
@@ -790,10 +1474,32 @@ def regexp_like(string: Expr, regex: Expr, flags: Expr | None = None) -> Expr:
 
 
 def regexp_match(string: Expr, regex: Expr, flags: Expr | None = None) -> Expr:
-    """Perform regular expression (regex) matching.
+    r"""Perform regular expression (regex) matching.
 
     Returns an array with each element containing the leftmost-first match of the
     corresponding index in ``regex`` to string in ``string``.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["hello 42 world"]})
+        >>> result = df.select(
+        ...     dfn.functions.regexp_match(
+        ...         dfn.col("a"), dfn.lit("(\\d+)")
+        ...     ).alias("m")
+        ... )
+        >>> result.collect_column("m")[0].as_py()
+        ['42']
+
+        Use ``flags`` for case-insensitive matching:
+
+        >>> result = df.select(
+        ...     dfn.functions.regexp_match(
+        ...         dfn.col("a"), dfn.lit("(HELLO)"),
+        ...         flags=dfn.lit("i"),
+        ...     ).alias("m")
+        ... )
+        >>> result.collect_column("m")[0].as_py()
+        ['hello']
     """
     if flags is not None:
         flags = flags.expr
@@ -803,13 +1509,37 @@ def regexp_match(string: Expr, regex: Expr, flags: Expr | None = None) -> Expr:
 def regexp_replace(
     string: Expr, pattern: Expr, replacement: Expr, flags: Expr | None = None
 ) -> Expr:
-    """Replaces substring(s) matching a PCRE-like regular expression.
+    r"""Replaces substring(s) matching a PCRE-like regular expression.
 
     The full list of supported features and syntax can be found at
     <https://docs.rs/regex/latest/regex/#syntax>
 
     Supported flags with the addition of 'g' can be found at
     <https://docs.rs/regex/latest/regex/#grouping-and-flags>
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["hello 42"]})
+        >>> result = df.select(
+        ...     dfn.functions.regexp_replace(
+        ...         dfn.col("a"), dfn.lit("\\d+"),
+        ...         dfn.lit("XX")
+        ...     ).alias("r")
+        ... )
+        >>> result.collect_column("r")[0].as_py()
+        'hello XX'
+
+        Use the ``g`` flag to replace all occurrences:
+
+        >>> df = ctx.from_pydict({"a": ["a1 b2 c3"]})
+        >>> result = df.select(
+        ...     dfn.functions.regexp_replace(
+        ...         dfn.col("a"), dfn.lit("\\d+"),
+        ...         dfn.lit("X"), flags=dfn.lit("g"),
+        ...     ).alias("r")
+        ... )
+        >>> result.collect_column("r")[0].as_py()
+        'aX bX cX'
     """
     if flags is not None:
         flags = flags.expr
@@ -823,6 +1553,27 @@ def regexp_count(
 
     Optional start position (the first position is 1) to search for the regular
     expression.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["abcabc"]})
+        >>> result = df.select(
+        ...     dfn.functions.regexp_count(
+        ...         dfn.col("a"), dfn.lit("abc")
+        ...     ).alias("c"))
+        >>> result.collect_column("c")[0].as_py()
+        2
+
+        Use ``start`` to begin searching from a position, and
+        ``flags`` for case-insensitive matching:
+
+        >>> result = df.select(
+        ...     dfn.functions.regexp_count(
+        ...         dfn.col("a"), dfn.lit("ABC"),
+        ...         start=dfn.lit(4), flags=dfn.lit("i"),
+        ...     ).alias("c"))
+        >>> result.collect_column("c")[0].as_py()
+        1
     """
     if flags is not None:
         flags = flags.expr
@@ -838,12 +1589,51 @@ def regexp_instr(
     flags: Expr | None = None,
     sub_expr: Expr | None = None,
 ) -> Expr:
-    """Returns the position of a regular expression match in a string.
+    r"""Returns the position of a regular expression match in a string.
 
-    Searches ``values`` for the ``n``-th occurrence of ``regex``, starting at position
-    ``start`` (the first position is 1). Returns the starting or ending position based
-    on ``end_position``. Use ``flags`` to control regex behavior and ``sub_expr`` to
-    return the position of a specific capture group instead of the entire match.
+    Args:
+        values: Data to search for the regular expression match.
+        regex: Regular expression to search for.
+        start: Optional position to start the search (the first position is 1).
+        n: Optional occurrence of the match to find (the first occurrence is 1).
+        flags: Optional regular expression flags to control regex behavior.
+        sub_expr: Optionally capture group position instead of the entire match.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["hello 42 world"]})
+        >>> result = df.select(
+        ...     dfn.functions.regexp_instr(
+        ...         dfn.col("a"), dfn.lit("\\d+")
+        ...     ).alias("pos")
+        ... )
+        >>> result.collect_column("pos")[0].as_py()
+        7
+
+        Use ``start`` to search from a position, ``n`` for the
+        nth occurrence, and ``flags`` for case-insensitive mode:
+
+        >>> df = ctx.from_pydict({"a": ["abc ABC abc"]})
+        >>> result = df.select(
+        ...     dfn.functions.regexp_instr(
+        ...         dfn.col("a"), dfn.lit("abc"),
+        ...         start=dfn.lit(2), n=dfn.lit(1),
+        ...         flags=dfn.lit("i"),
+        ...     ).alias("pos")
+        ... )
+        >>> result.collect_column("pos")[0].as_py()
+        5
+
+        Use ``sub_expr`` to get the position of a capture group:
+
+        >>> result = df.select(
+        ...     dfn.functions.regexp_instr(
+        ...         dfn.col("a"), dfn.lit("(abc)"),
+        ...         sub_expr=dfn.lit(1),
+        ...     ).alias("pos")
+        ... )
+        >>> result.collect_column("pos")[0].as_py()
+        1
     """
     start = start.expr if start is not None else None
     n = n.expr if n is not None else None
@@ -863,22 +1653,57 @@ def regexp_instr(
 
 
 def repeat(string: Expr, n: Expr) -> Expr:
-    """Repeats the ``string`` to ``n`` times."""
+    """Repeats the ``string`` to ``n`` times.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["ha"]})
+        >>> result = df.select(
+        ...     dfn.functions.repeat(dfn.col("a"), dfn.lit(3)).alias("r"))
+        >>> result.collect_column("r")[0].as_py()
+        'hahaha'
+    """
     return Expr(f.repeat(string.expr, n.expr))
 
 
 def replace(string: Expr, from_val: Expr, to_val: Expr) -> Expr:
-    """Replaces all occurrences of ``from_val`` with ``to_val`` in the ``string``."""
+    """Replaces all occurrences of ``from_val`` with ``to_val`` in the ``string``.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["hello world"]})
+        >>> result = df.select(
+        ...     dfn.functions.replace(dfn.col("a"), dfn.lit("world"),
+        ...     dfn.lit("there")).alias("r"))
+        >>> result.collect_column("r")[0].as_py()
+        'hello there'
+    """
     return Expr(f.replace(string.expr, from_val.expr, to_val.expr))
 
 
 def reverse(arg: Expr) -> Expr:
-    """Reverse the string argument."""
+    """Reverse the string argument.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["hello"]})
+        >>> result = df.select(dfn.functions.reverse(dfn.col("a")).alias("r"))
+        >>> result.collect_column("r")[0].as_py()
+        'olleh'
+    """
     return Expr(f.reverse(arg.expr))
 
 
 def right(string: Expr, n: Expr) -> Expr:
-    """Returns the last ``n`` characters in the ``string``."""
+    """Returns the last ``n`` characters in the ``string``.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["hello"]})
+        >>> result = df.select(dfn.functions.right(dfn.col("a"), dfn.lit(3)).alias("r"))
+        >>> result.collect_column("r")[0].as_py()
+        'llo'
+    """
     return Expr(f.right(string.expr, n.expr))
 
 
@@ -888,6 +1713,13 @@ def round(value: Expr, decimal_places: Expr | None = None) -> Expr:
     If the optional ``decimal_places`` is specified, round to the nearest number of
     decimal places. You can specify a negative number of decimal places. For example
     ``round(lit(125.2345), lit(-2))`` would yield a value of ``100.0``.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1.567]})
+        >>> result = df.select(dfn.functions.round(dfn.col("a"), dfn.lit(2)).alias("r"))
+        >>> result.collect_column("r")[0].as_py()
+        1.57
     """
     if decimal_places is None:
         decimal_places = Expr.literal(0)
@@ -899,48 +1731,128 @@ def rpad(string: Expr, count: Expr, characters: Expr | None = None) -> Expr:
 
     Extends the string to length length by appending the characters fill (a space
     by default). If the string is already longer than length then it is truncated.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["hi"]})
+        >>> result = df.select(
+        ...     dfn.functions.rpad(dfn.col("a"), dfn.lit(5), dfn.lit("!")).alias("r"))
+        >>> result.collect_column("r")[0].as_py()
+        'hi!!!'
     """
     characters = characters if characters is not None else Expr.literal(" ")
     return Expr(f.rpad(string.expr, count.expr, characters.expr))
 
 
 def rtrim(arg: Expr) -> Expr:
-    """Removes all characters, spaces by default, from the end of a string."""
+    """Removes all characters, spaces by default, from the end of a string.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [" a  "]})
+        >>> trim_df = df.select(dfn.functions.rtrim(dfn.col("a")).alias("trimmed"))
+        >>> trim_df.collect_column("trimmed")[0].as_py()
+        ' a'
+    """
     return Expr(f.rtrim(arg.expr))
 
 
 def sha224(arg: Expr) -> Expr:
-    """Computes the SHA-224 hash of a binary string."""
+    """Computes the SHA-224 hash of a binary string.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["hello"]})
+        >>> result = df.select(
+        ...     dfn.functions.sha224(dfn.col("a")).alias("h")
+        ... )
+        >>> result.collect_column("h")[0].as_py().hex()
+        'ea09ae9cc6768c50fcee903ed054556e5bfc8347907f12598aa24193'
+    """
     return Expr(f.sha224(arg.expr))
 
 
 def sha256(arg: Expr) -> Expr:
-    """Computes the SHA-256 hash of a binary string."""
+    """Computes the SHA-256 hash of a binary string.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["hello"]})
+        >>> result = df.select(
+        ...     dfn.functions.sha256(dfn.col("a")).alias("h")
+        ... )
+        >>> result.collect_column("h")[0].as_py().hex()
+        '2cf24dba5fb0a30e26e83b2ac5b9e29e1b161e5c1fa7425e73043362938b9824'
+    """
     return Expr(f.sha256(arg.expr))
 
 
 def sha384(arg: Expr) -> Expr:
-    """Computes the SHA-384 hash of a binary string."""
+    """Computes the SHA-384 hash of a binary string.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["hello"]})
+        >>> result = df.select(
+        ...     dfn.functions.sha384(dfn.col("a")).alias("h")
+        ... )
+        >>> result.collect_column("h")[0].as_py().hex()
+        '59e1748777448c69de6b800d7a33bbfb9ff1b...
+    """
     return Expr(f.sha384(arg.expr))
 
 
 def sha512(arg: Expr) -> Expr:
-    """Computes the SHA-512 hash of a binary string."""
+    """Computes the SHA-512 hash of a binary string.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["hello"]})
+        >>> result = df.select(
+        ...     dfn.functions.sha512(dfn.col("a")).alias("h")
+        ... )
+        >>> result.collect_column("h")[0].as_py().hex()
+        '9b71d224bd62f3785d96d46ad3ea3d73319bfb...
+    """
     return Expr(f.sha512(arg.expr))
 
 
 def signum(arg: Expr) -> Expr:
-    """Returns the sign of the argument (-1, 0, +1)."""
+    """Returns the sign of the argument (-1, 0, +1).
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [-5.0, 0.0, 5.0]})
+        >>> result = df.select(dfn.functions.signum(dfn.col("a")).alias("s"))
+        >>> result.collect_column("s").to_pylist()
+        [-1.0, 0.0, 1.0]
+    """
     return Expr(f.signum(arg.expr))
 
 
 def sin(arg: Expr) -> Expr:
-    """Returns the sine of the argument."""
+    """Returns the sine of the argument.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [0.0]})
+        >>> result = df.select(dfn.functions.sin(dfn.col("a")).alias("sin"))
+        >>> result.collect_column("sin")[0].as_py()
+        0.0
+    """
     return Expr(f.sin(arg.expr))
 
 
 def sinh(arg: Expr) -> Expr:
-    """Returns the hyperbolic sine of the argument."""
+    """Returns the hyperbolic sine of the argument.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [0.0]})
+        >>> result = df.select(dfn.functions.sinh(dfn.col("a")).alias("sinh"))
+        >>> result.collect_column("sinh")[0].as_py()
+        0.0
+    """
     return Expr(f.sinh(arg.expr))
 
 
@@ -949,27 +1861,72 @@ def split_part(string: Expr, delimiter: Expr, index: Expr) -> Expr:
 
     Splits a string based on a delimiter and picks out the desired field based
     on the index.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["a,b,c"]})
+        >>> result = df.select(
+        ...     dfn.functions.split_part(
+        ...         dfn.col("a"), dfn.lit(","), dfn.lit(2)
+        ...     ).alias("s"))
+        >>> result.collect_column("s")[0].as_py()
+        'b'
     """
     return Expr(f.split_part(string.expr, delimiter.expr, index.expr))
 
 
 def sqrt(arg: Expr) -> Expr:
-    """Returns the square root of the argument."""
+    """Returns the square root of the argument.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [9.0]})
+        >>> result = df.select(dfn.functions.sqrt(dfn.col("a")).alias("sqrt"))
+        >>> result.collect_column("sqrt")[0].as_py()
+        3.0
+    """
     return Expr(f.sqrt(arg.expr))
 
 
 def starts_with(string: Expr, prefix: Expr) -> Expr:
-    """Returns true if string starts with prefix."""
+    """Returns true if string starts with prefix.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["hello_from_datafusion"]})
+        >>> result = df.select(
+        ...     dfn.functions.starts_with(dfn.col("a"), dfn.lit("hello")).alias("sw"))
+        >>> result.collect_column("sw")[0].as_py()
+        True
+    """
     return Expr(f.starts_with(string.expr, prefix.expr))
 
 
 def strpos(string: Expr, substring: Expr) -> Expr:
-    """Finds the position from where the ``substring`` matches the ``string``."""
+    """Finds the position from where the ``substring`` matches the ``string``.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["hello"]})
+        >>> result = df.select(
+        ...     dfn.functions.strpos(dfn.col("a"), dfn.lit("llo")).alias("pos"))
+        >>> result.collect_column("pos")[0].as_py()
+        3
+    """
     return Expr(f.strpos(string.expr, substring.expr))
 
 
 def substr(string: Expr, position: Expr) -> Expr:
-    """Substring from the ``position`` to the end."""
+    """Substring from the ``position`` to the end.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["hello"]})
+        >>> result = df.select(
+        ...     dfn.functions.substr(dfn.col("a"), dfn.lit(3)).alias("s"))
+        >>> result.collect_column("s")[0].as_py()
+        'llo'
+    """
     return Expr(f.substr(string.expr, position.expr))
 
 
@@ -978,27 +1935,71 @@ def substr_index(string: Expr, delimiter: Expr, count: Expr) -> Expr:
 
     The return will be the ``string`` from before ``count`` occurrences of
     ``delimiter``.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["a.b.c"]})
+        >>> result = df.select(
+        ...     dfn.functions.substr_index(dfn.col("a"), dfn.lit("."),
+        ...     dfn.lit(2)).alias("s"))
+        >>> result.collect_column("s")[0].as_py()
+        'a.b'
     """
     return Expr(f.substr_index(string.expr, delimiter.expr, count.expr))
 
 
 def substring(string: Expr, position: Expr, length: Expr) -> Expr:
-    """Substring from the ``position`` with ``length`` characters."""
+    """Substring from the ``position`` with ``length`` characters.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["hello world"]})
+        >>> result = df.select(
+        ...     dfn.functions.substring(
+        ...         dfn.col("a"), dfn.lit(1), dfn.lit(5)
+        ...     ).alias("s"))
+        >>> result.collect_column("s")[0].as_py()
+        'hello'
+    """
     return Expr(f.substring(string.expr, position.expr, length.expr))
 
 
 def tan(arg: Expr) -> Expr:
-    """Returns the tangent of the argument."""
+    """Returns the tangent of the argument.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [0.0]})
+        >>> result = df.select(dfn.functions.tan(dfn.col("a")).alias("tan"))
+        >>> result.collect_column("tan")[0].as_py()
+        0.0
+    """
     return Expr(f.tan(arg.expr))
 
 
 def tanh(arg: Expr) -> Expr:
-    """Returns the hyperbolic tangent of the argument."""
+    """Returns the hyperbolic tangent of the argument.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [0.0]})
+        >>> result = df.select(dfn.functions.tanh(dfn.col("a")).alias("tanh"))
+        >>> result.collect_column("tanh")[0].as_py()
+        0.0
+    """
     return Expr(f.tanh(arg.expr))
 
 
 def to_hex(arg: Expr) -> Expr:
-    """Converts an integer to a hexadecimal string."""
+    """Converts an integer to a hexadecimal string.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [255]})
+        >>> result = df.select(dfn.functions.to_hex(dfn.col("a")).alias("hex"))
+        >>> result.collect_column("hex")[0].as_py()
+        'ff'
+    """
     return Expr(f.to_hex(arg.expr))
 
 
@@ -1006,144 +2007,457 @@ def now() -> Expr:
     """Returns the current timestamp in nanoseconds.
 
     This will use the same value for all instances of now() in same statement.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1]})
+        >>> result = df.select(
+        ...     dfn.functions.now().alias("now")
+        ... )
+
+        Use .value instead of .as_py() because nanosecond timestamps
+        require pandas to convert to Python datetime objects.
+
+        >>> result.collect_column("now")[0].value > 0
+        True
     """
     return Expr(f.now())
 
 
+def current_timestamp() -> Expr:
+    """Returns the current timestamp in nanoseconds.
+
+    See Also:
+        This is an alias for :py:func:`now`.
+    """
+    return now()
+
+
+def to_char(arg: Expr, formatter: Expr) -> Expr:
+    """Returns a string representation of a date, time, timestamp or duration.
+
+    For usage of ``formatter`` see the rust chrono package ``strftime`` package.
+
+    [Documentation here.](https://docs.rs/chrono/latest/chrono/format/strftime/index.html)
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["2021-01-01T00:00:00"]})
+        >>> result = df.select(
+        ...     dfn.functions.to_char(
+        ...         dfn.functions.to_timestamp(dfn.col("a")),
+        ...         dfn.lit("%Y/%m/%d"),
+        ...     ).alias("formatted")
+        ... )
+        >>> result.collect_column("formatted")[0].as_py()
+        '2021/01/01'
+    """
+    return Expr(f.to_char(arg.expr, formatter.expr))
+
+
+def date_format(arg: Expr, formatter: Expr) -> Expr:
+    """Returns a string representation of a date, time, timestamp or duration.
+
+    See Also:
+        This is an alias for :py:func:`to_char`.
+    """
+    return to_char(arg, formatter)
+
+
+def _unwrap_exprs(args: tuple[Expr, ...]) -> list:
+    return [arg.expr for arg in args]
+
+
+def to_date(arg: Expr, *formatters: Expr) -> Expr:
+    """Converts a value to a date (YYYY-MM-DD).
+
+    Supports strings, numeric and timestamp types as input.
+    Integers and doubles are interpreted as days since the unix epoch.
+    Strings are parsed as YYYY-MM-DD (e.g. '2023-07-20')
+    if ``formatters`` are not provided.
+
+    For usage of ``formatters`` see the rust chrono package ``strftime`` package.
+
+    [Documentation here.](https://docs.rs/chrono/latest/chrono/format/strftime/index.html)
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["2021-07-20"]})
+        >>> result = df.select(
+        ...     dfn.functions.to_date(dfn.col("a")).alias("dt"))
+        >>> str(result.collect_column("dt")[0].as_py())
+        '2021-07-20'
+    """
+    return Expr(f.to_date(arg.expr, *_unwrap_exprs(formatters)))
+
+
+def to_local_time(*args: Expr) -> Expr:
+    """Converts a timestamp with a timezone to a timestamp without a timezone.
+
+    This function handles daylight saving time changes.
+    """
+    return Expr(f.to_local_time(*_unwrap_exprs(args)))
+
+
+def to_time(arg: Expr, *formatters: Expr) -> Expr:
+    """Converts a value to a time. Supports strings and timestamps as input.
+
+    If ``formatters`` is not provided strings are parsed as HH:MM:SS, HH:MM or
+    HH:MM:SS.nnnnnnnnn;
+
+    For usage of ``formatters`` see the rust chrono package ``strftime`` package.
+
+    [Documentation here.](https://docs.rs/chrono/latest/chrono/format/strftime/index.html)
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["14:30:00"]})
+        >>> result = df.select(
+        ...     dfn.functions.to_time(dfn.col("a")).alias("t"))
+        >>> str(result.collect_column("t")[0].as_py())
+        '14:30:00'
+    """
+    return Expr(f.to_time(arg.expr, *_unwrap_exprs(formatters)))
+
+
 def to_timestamp(arg: Expr, *formatters: Expr) -> Expr:
     """Converts a string and optional formats to a ``Timestamp`` in nanoseconds.
 
     For usage of ``formatters`` see the rust chrono package ``strftime`` package.
 
     [Documentation here.](https://docs.rs/chrono/latest/chrono/format/strftime/index.html)
-    """
-    if formatters is None:
-        return f.to_timestamp(arg.expr)
 
-    formatters = [f.expr for f in formatters]
-    return Expr(f.to_timestamp(arg.expr, *formatters))
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["2021-01-01T00:00:00"]})
+        >>> result = df.select(
+        ...     dfn.functions.to_timestamp(
+        ...         dfn.col("a")
+        ...     ).alias("ts")
+        ... )
+        >>> str(result.collect_column("ts")[0].as_py())
+        '2021-01-01 00:00:00'
+    """
+    return Expr(f.to_timestamp(arg.expr, *_unwrap_exprs(formatters)))
 
 
 def to_timestamp_millis(arg: Expr, *formatters: Expr) -> Expr:
     """Converts a string and optional formats to a ``Timestamp`` in milliseconds.
 
     See :py:func:`to_timestamp` for a description on how to use formatters.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["2021-01-01T00:00:00"]})
+        >>> result = df.select(
+        ...     dfn.functions.to_timestamp_millis(
+        ...         dfn.col("a")
+        ...     ).alias("ts")
+        ... )
+        >>> str(result.collect_column("ts")[0].as_py())
+        '2021-01-01 00:00:00'
     """
-    formatters = [f.expr for f in formatters]
-    return Expr(f.to_timestamp_millis(arg.expr, *formatters))
+    return Expr(f.to_timestamp_millis(arg.expr, *_unwrap_exprs(formatters)))
 
 
 def to_timestamp_micros(arg: Expr, *formatters: Expr) -> Expr:
     """Converts a string and optional formats to a ``Timestamp`` in microseconds.
 
     See :py:func:`to_timestamp` for a description on how to use formatters.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["2021-01-01T00:00:00"]})
+        >>> result = df.select(
+        ...     dfn.functions.to_timestamp_micros(
+        ...         dfn.col("a")
+        ...     ).alias("ts")
+        ... )
+        >>> str(result.collect_column("ts")[0].as_py())
+        '2021-01-01 00:00:00'
     """
-    formatters = [f.expr for f in formatters]
-    return Expr(f.to_timestamp_micros(arg.expr, *formatters))
+    return Expr(f.to_timestamp_micros(arg.expr, *_unwrap_exprs(formatters)))
 
 
 def to_timestamp_nanos(arg: Expr, *formatters: Expr) -> Expr:
     """Converts a string and optional formats to a ``Timestamp`` in nanoseconds.
 
     See :py:func:`to_timestamp` for a description on how to use formatters.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["2021-01-01T00:00:00"]})
+        >>> result = df.select(
+        ...     dfn.functions.to_timestamp_nanos(
+        ...         dfn.col("a")
+        ...     ).alias("ts")
+        ... )
+        >>> str(result.collect_column("ts")[0].as_py())
+        '2021-01-01 00:00:00'
     """
-    formatters = [f.expr for f in formatters]
-    return Expr(f.to_timestamp_nanos(arg.expr, *formatters))
+    return Expr(f.to_timestamp_nanos(arg.expr, *_unwrap_exprs(formatters)))
 
 
 def to_timestamp_seconds(arg: Expr, *formatters: Expr) -> Expr:
     """Converts a string and optional formats to a ``Timestamp`` in seconds.
 
     See :py:func:`to_timestamp` for a description on how to use formatters.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["2021-01-01T00:00:00"]})
+        >>> result = df.select(
+        ...     dfn.functions.to_timestamp_seconds(
+        ...         dfn.col("a")
+        ...     ).alias("ts")
+        ... )
+        >>> str(result.collect_column("ts")[0].as_py())
+        '2021-01-01 00:00:00'
     """
-    formatters = [f.expr for f in formatters]
-    return Expr(f.to_timestamp_seconds(arg.expr, *formatters))
+    return Expr(f.to_timestamp_seconds(arg.expr, *_unwrap_exprs(formatters)))
 
 
 def to_unixtime(string: Expr, *format_arguments: Expr) -> Expr:
-    """Converts a string and optional formats to a Unixtime."""
-    args = [f.expr for f in format_arguments]
-    return Expr(f.to_unixtime(string.expr, *args))
+    """Converts a string and optional formats to a Unixtime.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["1970-01-01T00:00:00"]})
+        >>> result = df.select(dfn.functions.to_unixtime(dfn.col("a")).alias("u"))
+        >>> result.collect_column("u")[0].as_py()
+        0
+    """
+    return Expr(f.to_unixtime(string.expr, *_unwrap_exprs(format_arguments)))
 
 
 def current_date() -> Expr:
-    """Returns current UTC date as a Date32 value."""
+    """Returns current UTC date as a Date32 value.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1]})
+        >>> result = df.select(
+        ...     dfn.functions.current_date().alias("d")
+        ... )
+        >>> result.collect_column("d")[0].as_py() is not None
+        True
+    """
     return Expr(f.current_date())
 
 
+today = current_date
+
+
 def current_time() -> Expr:
-    """Returns current UTC time as a Time64 value."""
+    """Returns current UTC time as a Time64 value.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1]})
+        >>> result = df.select(
+        ...     dfn.functions.current_time().alias("t")
+        ... )
+
+        Use .value instead of .as_py() because nanosecond timestamps
+        require pandas to convert to Python datetime objects.
+
+        >>> result.collect_column("t")[0].value > 0
+        True
+    """
     return Expr(f.current_time())
 
 
 def datepart(part: Expr, date: Expr) -> Expr:
     """Return a specified part of a date.
 
-    This is an alias for :py:func:`date_part`.
+    See Also:
+        This is an alias for :py:func:`date_part`.
     """
     return date_part(part, date)
 
 
 def date_part(part: Expr, date: Expr) -> Expr:
-    """Extracts a subfield from the date."""
+    """Extracts a subfield from the date.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["2021-07-15T00:00:00"]})
+        >>> df = df.select(dfn.functions.to_timestamp(dfn.col("a")).alias("a"))
+        >>> result = df.select(
+        ...     dfn.functions.date_part(dfn.lit("year"), dfn.col("a")).alias("y"))
+        >>> result.collect_column("y")[0].as_py()
+        2021
+    """
     return Expr(f.date_part(part.expr, date.expr))
 
 
 def extract(part: Expr, date: Expr) -> Expr:
     """Extracts a subfield from the date.
 
-    This is an alias for :py:func:`date_part`.
+    See Also:
+        This is an alias for :py:func:`date_part`.
     """
     return date_part(part, date)
 
 
 def date_trunc(part: Expr, date: Expr) -> Expr:
-    """Truncates the date to a specified level of precision."""
+    """Truncates the date to a specified level of precision.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["2021-07-15T12:34:56"]})
+        >>> df = df.select(dfn.functions.to_timestamp(dfn.col("a")).alias("a"))
+        >>> result = df.select(
+        ...     dfn.functions.date_trunc(
+        ...         dfn.lit("month"), dfn.col("a")
+        ...     ).alias("t")
+        ... )
+        >>> str(result.collect_column("t")[0].as_py())
+        '2021-07-01 00:00:00'
+    """
     return Expr(f.date_trunc(part.expr, date.expr))
 
 
 def datetrunc(part: Expr, date: Expr) -> Expr:
     """Truncates the date to a specified level of precision.
 
-    This is an alias for :py:func:`date_trunc`.
+    See Also:
+        This is an alias for :py:func:`date_trunc`.
     """
     return date_trunc(part, date)
 
 
 def date_bin(stride: Expr, source: Expr, origin: Expr) -> Expr:
-    """Coerces an arbitrary timestamp to the start of the nearest specified interval."""
+    """Coerces an arbitrary timestamp to the start of the nearest specified interval.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"timestamp": ['2021-07-15 12:34:56', '2021-01-01']})
+        >>> result = df.select(
+        ...     dfn.functions.date_bin(
+        ...         dfn.string_literal("15 minutes"),
+        ...         dfn.col("timestamp"),
+        ...         dfn.string_literal("2001-01-01 00:00:00")
+        ...     ).alias("b")
+        ... )
+        >>> str(result.collect_column("b")[0].as_py())
+        '2021-07-15 12:30:00'
+        >>> str(result.collect_column("b")[1].as_py())
+        '2021-01-01 00:00:00'
+    """
     return Expr(f.date_bin(stride.expr, source.expr, origin.expr))
 
 
 def make_date(year: Expr, month: Expr, day: Expr) -> Expr:
-    """Make a date from year, month and day component parts."""
+    """Make a date from year, month and day component parts.
+
+    Examples:
+        >>> from datetime import date
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"y": [2024], "m": [1], "d": [15]})
+        >>> result = df.select(
+        ...     dfn.functions.make_date(dfn.col("y"), dfn.col("m"),
+        ...     dfn.col("d")).alias("dt"))
+        >>> result.collect_column("dt")[0].as_py()
+        datetime.date(2024, 1, 15)
+    """
     return Expr(f.make_date(year.expr, month.expr, day.expr))
 
 
+def make_time(hour: Expr, minute: Expr, second: Expr) -> Expr:
+    """Make a time from hour, minute and second component parts.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"h": [12], "m": [30], "s": [0]})
+        >>> result = df.select(
+        ...     dfn.functions.make_time(dfn.col("h"), dfn.col("m"),
+        ...     dfn.col("s")).alias("t"))
+        >>> result.collect_column("t")[0].as_py()
+        datetime.time(12, 30)
+    """
+    return Expr(f.make_time(hour.expr, minute.expr, second.expr))
+
+
 def translate(string: Expr, from_val: Expr, to_val: Expr) -> Expr:
-    """Replaces the characters in ``from_val`` with the counterpart in ``to_val``."""
+    """Replaces the characters in ``from_val`` with the counterpart in ``to_val``.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["hello"]})
+        >>> result = df.select(
+        ...     dfn.functions.translate(dfn.col("a"), dfn.lit("helo"),
+        ...     dfn.lit("HELO")).alias("t"))
+        >>> result.collect_column("t")[0].as_py()
+        'HELLO'
+    """
     return Expr(f.translate(string.expr, from_val.expr, to_val.expr))
 
 
 def trim(arg: Expr) -> Expr:
-    """Removes all characters, spaces by default, from both sides of a string."""
+    """Removes all characters, spaces by default, from both sides of a string.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["  hello  "]})
+        >>> result = df.select(dfn.functions.trim(dfn.col("a")).alias("t"))
+        >>> result.collect_column("t")[0].as_py()
+        'hello'
+    """
     return Expr(f.trim(arg.expr))
 
 
 def trunc(num: Expr, precision: Expr | None = None) -> Expr:
-    """Truncate the number toward zero with optional precision."""
+    """Truncate the number toward zero with optional precision.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1.567]})
+        >>> result = df.select(
+        ...     dfn.functions.trunc(
+        ...         dfn.col("a")
+        ...     ).alias("t"))
+        >>> result.collect_column("t")[0].as_py()
+        1.0
+
+        >>> result = df.select(
+        ...     dfn.functions.trunc(
+        ...         dfn.col("a"), precision=dfn.lit(2)
+        ...     ).alias("t"))
+        >>> result.collect_column("t")[0].as_py()
+        1.56
+    """
     if precision is not None:
         return Expr(f.trunc(num.expr, precision.expr))
     return Expr(f.trunc(num.expr))
 
 
 def upper(arg: Expr) -> Expr:
-    """Converts a string to uppercase."""
+    """Converts a string to uppercase.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["hello"]})
+        >>> result = df.select(dfn.functions.upper(dfn.col("a")).alias("u"))
+        >>> result.collect_column("u")[0].as_py()
+        'HELLO'
+    """
     return Expr(f.upper(arg.expr))
 
 
 def make_array(*args: Expr) -> Expr:
-    """Returns an array using the specified input expressions."""
+    """Returns an array using the specified input expressions.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1]})
+        >>> result = df.select(
+        ...     dfn.functions.make_array(
+        ...         dfn.lit(1), dfn.lit(2), dfn.lit(3)
+        ...     ).alias("arr"))
+        >>> result.collect_column("arr")[0].as_py()
+        [1, 2, 3]
+    """
     args = [arg.expr for arg in args]
     return Expr(f.make_array(args))
 
@@ -1151,7 +2465,8 @@ def make_array(*args: Expr) -> Expr:
 def make_list(*args: Expr) -> Expr:
     """Returns an array using the specified input expressions.
 
-    This is an alias for :py:func:`make_array`.
+    See Also:
+        This is an alias for :py:func:`make_array`.
     """
     return make_array(*args)
 
@@ -1159,29 +2474,77 @@ def make_list(*args: Expr) -> Expr:
 def array(*args: Expr) -> Expr:
     """Returns an array using the specified input expressions.
 
-    This is an alias for :py:func:`make_array`.
+    See Also:
+        This is an alias for :py:func:`make_array`.
     """
     return make_array(*args)
 
 
 def range(start: Expr, stop: Expr, step: Expr) -> Expr:
-    """Create a list of values in the range between start and stop."""
+    """Create a list of values in the range between start and stop.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1]})
+        >>> result = df.select(
+        ...     dfn.functions.range(dfn.lit(0), dfn.lit(5), dfn.lit(2)).alias("r"))
+        >>> result.collect_column("r")[0].as_py()
+        [0, 2, 4]
+    """
     return Expr(f.range(start.expr, stop.expr, step.expr))
 
 
 def uuid() -> Expr:
-    """Returns uuid v4 as a string value."""
+    """Returns uuid v4 as a string value.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1]})
+        >>> result = df.select(
+        ...     dfn.functions.uuid().alias("u")
+        ... )
+        >>> len(result.collect_column("u")[0].as_py()) == 36
+        True
+    """
     return Expr(f.uuid())
 
 
 def struct(*args: Expr) -> Expr:
-    """Returns a struct with the given arguments."""
+    """Returns a struct with the given arguments.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1], "b": [2]})
+        >>> result = df.select(
+        ...     dfn.functions.struct(
+        ...         dfn.col("a"), dfn.col("b")
+        ...     ).alias("s")
+        ... )
+
+        Children in the new struct will always be `c0`, ..., `cN-1`
+        for `N` children.
+
+        >>> result.collect_column("s")[0].as_py() == {"c0": 1, "c1": 2}
+        True
+    """
     args = [arg.expr for arg in args]
     return Expr(f.struct(*args))
 
 
 def named_struct(name_pairs: list[tuple[str, Expr]]) -> Expr:
-    """Returns a struct with the given names and arguments pairs."""
+    """Returns a struct with the given names and arguments pairs.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1]})
+        >>> result = df.select(
+        ...     dfn.functions.named_struct(
+        ...         [("x", dfn.lit(10)), ("y", dfn.lit(20))]
+        ...     ).alias("s")
+        ... )
+        >>> result.collect_column("s")[0].as_py() == {"x": 10, "y": 20}
+        True
+    """
     name_pair_exprs = [
         [Expr.literal(pa.scalar(pair[0], type=pa.string())), pair[1]]
         for pair in name_pairs
@@ -1193,34 +2556,244 @@ def named_struct(name_pairs: list[tuple[str, Expr]]) -> Expr:
 
 
 def from_unixtime(arg: Expr) -> Expr:
-    """Converts an integer to RFC3339 timestamp format string."""
+    """Converts an integer to RFC3339 timestamp format string.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [0]})
+        >>> result = df.select(
+        ...     dfn.functions.from_unixtime(
+        ...         dfn.col("a")
+        ...     ).alias("ts")
+        ... )
+        >>> str(result.collect_column("ts")[0].as_py())
+        '1970-01-01 00:00:00'
+    """
     return Expr(f.from_unixtime(arg.expr))
 
 
 def arrow_typeof(arg: Expr) -> Expr:
-    """Returns the Arrow type of the expression."""
+    """Returns the Arrow type of the expression.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1]})
+        >>> result = df.select(dfn.functions.arrow_typeof(dfn.col("a")).alias("t"))
+        >>> result.collect_column("t")[0].as_py()
+        'Int64'
+    """
     return Expr(f.arrow_typeof(arg.expr))
 
 
-def arrow_cast(expr: Expr, data_type: Expr) -> Expr:
-    """Casts an expression to a specified data type."""
+def arrow_cast(expr: Expr, data_type: Expr | str | pa.DataType) -> Expr:
+    """Casts an expression to a specified data type.
+
+    The ``data_type`` can be a string, a ``pyarrow.DataType``, or an
+    ``Expr``. For simple types, :py:meth:`Expr.cast()
+    <datafusion.expr.Expr.cast>` is more concise
+    (e.g., ``col("a").cast(pa.float64())``). Use ``arrow_cast`` when
+    you want to specify the target type as a string using DataFusion's
+    type syntax, which can be more readable for complex types like
+    ``"Timestamp(Nanosecond, None)"``.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1]})
+        >>> result = df.select(
+        ...     dfn.functions.arrow_cast(dfn.col("a"), "Float64").alias("c")
+        ... )
+        >>> result.collect_column("c")[0].as_py()
+        1.0
+
+        >>> result = df.select(
+        ...     dfn.functions.arrow_cast(
+        ...         dfn.col("a"), data_type=pa.float64()
+        ...     ).alias("c")
+        ... )
+        >>> result.collect_column("c")[0].as_py()
+        1.0
+    """
+    if isinstance(data_type, pa.DataType):
+        return expr.cast(data_type)
+    if isinstance(data_type, str):
+        data_type = Expr.string_literal(data_type)
     return Expr(f.arrow_cast(expr.expr, data_type.expr))
 
 
+def arrow_metadata(expr: Expr, key: Expr | str | None = None) -> Expr:
+    """Returns the metadata of the input expression.
+
+    If called with one argument, returns a Map of all metadata key-value pairs.
+    If called with two arguments, returns the value for the specified metadata key.
+
+    Examples:
+        >>> field = pa.field("val", pa.int64(), metadata={"k": "v"})
+        >>> schema = pa.schema([field])
+        >>> batch = pa.RecordBatch.from_arrays([pa.array([1])], schema=schema)
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.create_dataframe([[batch]])
+        >>> result = df.select(
+        ...     dfn.functions.arrow_metadata(dfn.col("val")).alias("meta")
+        ... )
+        >>> ("k", "v") in result.collect_column("meta")[0].as_py()
+        True
+
+        >>> result = df.select(
+        ...     dfn.functions.arrow_metadata(
+        ...         dfn.col("val"), key="k"
+        ...     ).alias("meta_val")
+        ... )
+        >>> result.collect_column("meta_val")[0].as_py()
+        'v'
+    """
+    if key is None:
+        return Expr(f.arrow_metadata(expr.expr))
+    if isinstance(key, str):
+        key = Expr.string_literal(key)
+    return Expr(f.arrow_metadata(expr.expr, key.expr))
+
+
+def get_field(expr: Expr, name: Expr | str) -> Expr:
+    """Extracts a field from a struct or map by name.
+
+    When the field name is a static string, the bracket operator
+    ``expr["field"]`` is a convenient shorthand. Use ``get_field``
+    when the field name is a dynamic expression.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1], "b": [2]})
+        >>> df = df.with_column(
+        ...     "s",
+        ...     dfn.functions.named_struct(
+        ...         [("x", dfn.col("a")), ("y", dfn.col("b"))]
+        ...     ),
+        ... )
+        >>> result = df.select(
+        ...     dfn.functions.get_field(dfn.col("s"), "x").alias("x_val")
+        ... )
+        >>> result.collect_column("x_val")[0].as_py()
+        1
+
+        Equivalent using bracket syntax:
+
+        >>> result = df.select(
+        ...     dfn.col("s")["x"].alias("x_val")
+        ... )
+        >>> result.collect_column("x_val")[0].as_py()
+        1
+    """
+    if isinstance(name, str):
+        name = Expr.string_literal(name)
+    return Expr(f.get_field(expr.expr, name.expr))
+
+
+def union_extract(union_expr: Expr, field_name: Expr | str) -> Expr:
+    """Extracts a value from a union type by field name.
+
+    Returns the value of the named field if it is the currently selected
+    variant, otherwise returns NULL.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> types = pa.array([0, 1, 0], type=pa.int8())
+        >>> offsets = pa.array([0, 0, 1], type=pa.int32())
+        >>> arr = pa.UnionArray.from_dense(
+        ...     types, offsets, [pa.array([1, 2]), pa.array(["hi"])],
+        ...     ["int", "str"], [0, 1],
+        ... )
+        >>> batch = pa.RecordBatch.from_arrays([arr], names=["u"])
+        >>> df = ctx.create_dataframe([[batch]])
+        >>> result = df.select(
+        ...     dfn.functions.union_extract(dfn.col("u"), "int").alias("val")
+        ... )
+        >>> result.collect_column("val").to_pylist()
+        [1, None, 2]
+    """
+    if isinstance(field_name, str):
+        field_name = Expr.string_literal(field_name)
+    return Expr(f.union_extract(union_expr.expr, field_name.expr))
+
+
+def union_tag(union_expr: Expr) -> Expr:
+    """Returns the tag (active field name) of a union type.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> types = pa.array([0, 1, 0], type=pa.int8())
+        >>> offsets = pa.array([0, 0, 1], type=pa.int32())
+        >>> arr = pa.UnionArray.from_dense(
+        ...     types, offsets, [pa.array([1, 2]), pa.array(["hi"])],
+        ...     ["int", "str"], [0, 1],
+        ... )
+        >>> batch = pa.RecordBatch.from_arrays([arr], names=["u"])
+        >>> df = ctx.create_dataframe([[batch]])
+        >>> result = df.select(
+        ...     dfn.functions.union_tag(dfn.col("u")).alias("tag")
+        ... )
+        >>> result.collect_column("tag").to_pylist()
+        ['int', 'str', 'int']
+    """
+    return Expr(f.union_tag(union_expr.expr))
+
+
+def version() -> Expr:
+    """Returns the DataFusion version string.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.empty_table()
+        >>> result = df.select(dfn.functions.version().alias("v"))
+        >>> "Apache DataFusion" in result.collect_column("v")[0].as_py()
+        True
+    """
+    return Expr(f.version())
+
+
+def row(*args: Expr) -> Expr:
+    """Returns a struct with the given arguments.
+
+    See Also:
+        This is an alias for :py:func:`struct`.
+    """
+    return struct(*args)
+
+
 def random() -> Expr:
-    """Returns a random value in the range ``0.0 <= x < 1.0``."""
+    """Returns a random value in the range ``0.0 <= x < 1.0``.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1]})
+        >>> result = df.select(
+        ...     dfn.functions.random().alias("r")
+        ... )
+        >>> val = result.collect_column("r")[0].as_py()
+        >>> 0.0 <= val < 1.0
+        True
+    """
     return Expr(f.random())
 
 
 def array_append(array: Expr, element: Expr) -> Expr:
-    """Appends an element to the end of an array."""
+    """Appends an element to the end of an array.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [[1, 2, 3]]})
+        >>> result = df.select(
+        ...     dfn.functions.array_append(dfn.col("a"), dfn.lit(4)).alias("result"))
+        >>> result.collect_column("result")[0].as_py()
+        [1, 2, 3, 4]
+    """
     return Expr(f.array_append(array.expr, element.expr))
 
 
 def array_push_back(array: Expr, element: Expr) -> Expr:
     """Appends an element to the end of an array.
 
-    This is an alias for :py:func:`array_append`.
+    See Also:
+        This is an alias for :py:func:`array_append`.
     """
     return array_append(array, element)
 
@@ -1228,7 +2801,8 @@ def array_push_back(array: Expr, element: Expr) -> Expr:
 def list_append(array: Expr, element: Expr) -> Expr:
     """Appends an element to the end of an array.
 
-    This is an alias for :py:func:`array_append`.
+    See Also:
+        This is an alias for :py:func:`array_append`.
     """
     return array_append(array, element)
 
@@ -1236,13 +2810,23 @@ def list_append(array: Expr, element: Expr) -> Expr:
 def list_push_back(array: Expr, element: Expr) -> Expr:
     """Appends an element to the end of an array.
 
-    This is an alias for :py:func:`array_append`.
+    See Also:
+        This is an alias for :py:func:`array_append`.
     """
     return array_append(array, element)
 
 
 def array_concat(*args: Expr) -> Expr:
-    """Concatenates the input arrays."""
+    """Concatenates the input arrays.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [[1, 2]], "b": [[3, 4]]})
+        >>> result = df.select(
+        ...     dfn.functions.array_concat(dfn.col("a"), dfn.col("b")).alias("result"))
+        >>> result.collect_column("result")[0].as_py()
+        [1, 2, 3, 4]
+    """
     args = [arg.expr for arg in args]
     return Expr(f.array_concat(args))
 
@@ -1250,25 +2834,49 @@ def array_concat(*args: Expr) -> Expr:
 def array_cat(*args: Expr) -> Expr:
     """Concatenates the input arrays.
 
-    This is an alias for :py:func:`array_concat`.
+    See Also:
+        This is an alias for :py:func:`array_concat`.
     """
     return array_concat(*args)
 
 
 def array_dims(array: Expr) -> Expr:
-    """Returns an array of the array's dimensions."""
+    """Returns an array of the array's dimensions.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [[1, 2, 3]]})
+        >>> result = df.select(dfn.functions.array_dims(dfn.col("a")).alias("result"))
+        >>> result.collect_column("result")[0].as_py()
+        [3]
+    """
     return Expr(f.array_dims(array.expr))
 
 
 def array_distinct(array: Expr) -> Expr:
-    """Returns distinct values from the array after removing duplicates."""
+    """Returns distinct values from the array after removing duplicates.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [[1, 1, 2, 3]]})
+        >>> result = df.select(
+        ...     dfn.functions.array_distinct(
+        ...         dfn.col("a")
+        ...     ).alias("result")
+        ... )
+        >>> sorted(
+        ...     result.collect_column("result")[0].as_py()
+        ... )
+        [1, 2, 3]
+    """
     return Expr(f.array_distinct(array.expr))
 
 
 def list_cat(*args: Expr) -> Expr:
     """Concatenates the input arrays.
 
-    This is an alias for :py:func:`array_concat`, :py:func:`array_cat`.
+    See Also:
+        This is an alias for :py:func:`array_concat`, :py:func:`array_cat`.
     """
     return array_concat(*args)
 
@@ -1276,7 +2884,8 @@ def list_cat(*args: Expr) -> Expr:
 def list_concat(*args: Expr) -> Expr:
     """Concatenates the input arrays.
 
-    This is an alias for :py:func:`array_concat`, :py:func:`array_cat`.
+    See Also:
+        This is an alias for :py:func:`array_concat`, :py:func:`array_cat`.
     """
     return array_concat(*args)
 
@@ -1284,7 +2893,8 @@ def list_concat(*args: Expr) -> Expr:
 def list_distinct(array: Expr) -> Expr:
     """Returns distinct values from the array after removing duplicates.
 
-    This is an alias for :py:func:`array_distinct`.
+    See Also:
+        This is an alias for :py:func:`array_distinct`.
     """
     return array_distinct(array)
 
@@ -1292,25 +2902,53 @@ def list_distinct(array: Expr) -> Expr:
 def list_dims(array: Expr) -> Expr:
     """Returns an array of the array's dimensions.
 
-    This is an alias for :py:func:`array_dims`.
+    See Also:
+        This is an alias for :py:func:`array_dims`.
     """
     return array_dims(array)
 
 
 def array_element(array: Expr, n: Expr) -> Expr:
-    """Extracts the element with the index n from the array."""
+    """Extracts the element with the index n from the array.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [[10, 20, 30]]})
+        >>> result = df.select(
+        ...     dfn.functions.array_element(dfn.col("a"), dfn.lit(2)).alias("result"))
+        >>> result.collect_column("result")[0].as_py()
+        20
+    """
     return Expr(f.array_element(array.expr, n.expr))
 
 
 def array_empty(array: Expr) -> Expr:
-    """Returns a boolean indicating whether the array is empty."""
+    """Returns a boolean indicating whether the array is empty.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [[1, 2]]})
+        >>> result = df.select(dfn.functions.array_empty(dfn.col("a")).alias("result"))
+        >>> result.collect_column("result")[0].as_py()
+        False
+    """
     return Expr(f.array_empty(array.expr))
 
 
+def list_empty(array: Expr) -> Expr:
+    """Returns a boolean indicating whether the array is empty.
+
+    See Also:
+        This is an alias for :py:func:`array_empty`.
+    """
+    return array_empty(array)
+
+
 def array_extract(array: Expr, n: Expr) -> Expr:
     """Extracts the element with the index n from the array.
 
-    This is an alias for :py:func:`array_element`.
+    See Also:
+        This is an alias for :py:func:`array_element`.
     """
     return array_element(array, n)
 
@@ -1318,7 +2956,8 @@ def array_extract(array: Expr, n: Expr) -> Expr:
 def list_element(array: Expr, n: Expr) -> Expr:
     """Extracts the element with the index n from the array.
 
-    This is an alias for :py:func:`array_element`.
+    See Also:
+        This is an alias for :py:func:`array_element`.
     """
     return array_element(array, n)
 
@@ -1326,56 +2965,176 @@ def list_element(array: Expr, n: Expr) -> Expr:
 def list_extract(array: Expr, n: Expr) -> Expr:
     """Extracts the element with the index n from the array.
 
-    This is an alias for :py:func:`array_element`.
+    See Also:
+        This is an alias for :py:func:`array_element`.
     """
     return array_element(array, n)
 
 
 def array_length(array: Expr) -> Expr:
-    """Returns the length of the array."""
+    """Returns the length of the array.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [[1, 2, 3]]})
+        >>> result = df.select(dfn.functions.array_length(dfn.col("a")).alias("result"))
+        >>> result.collect_column("result")[0].as_py()
+        3
+    """
     return Expr(f.array_length(array.expr))
 
 
 def list_length(array: Expr) -> Expr:
     """Returns the length of the array.
 
-    This is an alias for :py:func:`array_length`.
+    See Also:
+        This is an alias for :py:func:`array_length`.
     """
     return array_length(array)
 
 
 def array_has(first_array: Expr, second_array: Expr) -> Expr:
-    """Returns true if the element appears in the first array, otherwise false."""
+    """Returns true if the element appears in the first array, otherwise false.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [[1, 2, 3]]})
+        >>> result = df.select(
+        ...     dfn.functions.array_has(dfn.col("a"), dfn.lit(2)).alias("result"))
+        >>> result.collect_column("result")[0].as_py()
+        True
+    """
     return Expr(f.array_has(first_array.expr, second_array.expr))
 
 
-def array_has_all(first_array: Expr, second_array: Expr) -> Expr:
-    """Determines if there is complete overlap ``second_array`` in ``first_array``.
+def array_has_all(first_array: Expr, second_array: Expr) -> Expr:
+    """Determines if there is complete overlap ``second_array`` in ``first_array``.
+
+    Returns true if each element of the second array appears in the first array.
+    Otherwise, it returns false.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [[1, 2, 3]], "b": [[1, 2]]})
+        >>> result = df.select(
+        ...     dfn.functions.array_has_all(dfn.col("a"), dfn.col("b")).alias("result"))
+        >>> result.collect_column("result")[0].as_py()
+        True
+    """
+    return Expr(f.array_has_all(first_array.expr, second_array.expr))
+
+
+def array_has_any(first_array: Expr, second_array: Expr) -> Expr:
+    """Determine if there is an overlap between ``first_array`` and ``second_array``.
+
+    Returns true if at least one element of the second array appears in the first
+    array. Otherwise, it returns false.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [[1, 2, 3]], "b": [[2, 5]]})
+        >>> result = df.select(
+        ...     dfn.functions.array_has_any(dfn.col("a"), dfn.col("b")).alias("result"))
+        >>> result.collect_column("result")[0].as_py()
+        True
+    """
+    return Expr(f.array_has_any(first_array.expr, second_array.expr))
+
+
+def array_contains(array: Expr, element: Expr) -> Expr:
+    """Returns true if the element appears in the array, otherwise false.
+
+    See Also:
+        This is an alias for :py:func:`array_has`.
+    """
+    return array_has(array, element)
+
+
+def list_has(array: Expr, element: Expr) -> Expr:
+    """Returns true if the element appears in the array, otherwise false.
+
+    See Also:
+        This is an alias for :py:func:`array_has`.
+    """
+    return array_has(array, element)
+
+
+def list_has_all(first_array: Expr, second_array: Expr) -> Expr:
+    """Determines if there is complete overlap ``second_array`` in ``first_array``.
+
+    See Also:
+        This is an alias for :py:func:`array_has_all`.
+    """
+    return array_has_all(first_array, second_array)
+
+
+def list_has_any(first_array: Expr, second_array: Expr) -> Expr:
+    """Determine if there is an overlap between ``first_array`` and ``second_array``.
+
+    See Also:
+        This is an alias for :py:func:`array_has_any`.
+    """
+    return array_has_any(first_array, second_array)
+
+
+def arrays_overlap(first_array: Expr, second_array: Expr) -> Expr:
+    """Returns true if any element appears in both arrays.
+
+    See Also:
+        This is an alias for :py:func:`array_has_any`.
+    """
+    return array_has_any(first_array, second_array)
+
+
+def list_overlap(first_array: Expr, second_array: Expr) -> Expr:
+    """Returns true if any element appears in both arrays.
 
-    Returns true if each element of the second array appears in the first array.
-    Otherwise, it returns false.
+    See Also:
+        This is an alias for :py:func:`array_has_any`.
     """
-    return Expr(f.array_has_all(first_array.expr, second_array.expr))
+    return array_has_any(first_array, second_array)
 
 
-def array_has_any(first_array: Expr, second_array: Expr) -> Expr:
-    """Determine if there is an overlap between ``first_array`` and ``second_array``.
+def list_contains(array: Expr, element: Expr) -> Expr:
+    """Returns true if the element appears in the array, otherwise false.
 
-    Returns true if at least one element of the second array appears in the first
-    array. Otherwise, it returns false.
+    See Also:
+        This is an alias for :py:func:`array_has`.
     """
-    return Expr(f.array_has_any(first_array.expr, second_array.expr))
+    return array_has(array, element)
 
 
 def array_position(array: Expr, element: Expr, index: int | None = 1) -> Expr:
-    """Return the position of the first occurrence of ``element`` in ``array``."""
+    """Return the position of the first occurrence of ``element`` in ``array``.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [[10, 20, 30]]})
+        >>> result = df.select(
+        ...     dfn.functions.array_position(
+        ...         dfn.col("a"), dfn.lit(20)
+        ...     ).alias("result"))
+        >>> result.collect_column("result")[0].as_py()
+        2
+
+        Use ``index`` to start searching from a given position:
+
+        >>> df = ctx.from_pydict({"a": [[10, 20, 10, 20]]})
+        >>> result = df.select(
+        ...     dfn.functions.array_position(
+        ...         dfn.col("a"), dfn.lit(20), index=3,
+        ...     ).alias("result"))
+        >>> result.collect_column("result")[0].as_py()
+        4
+    """
     return Expr(f.array_position(array.expr, element.expr, index))
 
 
 def array_indexof(array: Expr, element: Expr, index: int | None = 1) -> Expr:
     """Return the position of the first occurrence of ``element`` in ``array``.
 
-    This is an alias for :py:func:`array_position`.
+    See Also:
+        This is an alias for :py:func:`array_position`.
     """
     return array_position(array, element, index)
 
@@ -1383,7 +3142,8 @@ def array_indexof(array: Expr, element: Expr, index: int | None = 1) -> Expr:
 def list_position(array: Expr, element: Expr, index: int | None = 1) -> Expr:
     """Return the position of the first occurrence of ``element`` in ``array``.
 
-    This is an alias for :py:func:`array_position`.
+    See Also:
+        This is an alias for :py:func:`array_position`.
     """
     return array_position(array, element, index)
 
@@ -1391,46 +3151,76 @@ def list_position(array: Expr, element: Expr, index: int | None = 1) -> Expr:
 def list_indexof(array: Expr, element: Expr, index: int | None = 1) -> Expr:
     """Return the position of the first occurrence of ``element`` in ``array``.
 
-    This is an alias for :py:func:`array_position`.
+    See Also:
+        This is an alias for :py:func:`array_position`.
     """
     return array_position(array, element, index)
 
 
 def array_positions(array: Expr, element: Expr) -> Expr:
-    """Searches for an element in the array and returns all occurrences."""
+    """Searches for an element in the array and returns all occurrences.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [[1, 2, 1]]})
+        >>> result = df.select(
+        ...     dfn.functions.array_positions(dfn.col("a"), dfn.lit(1)).alias("result"))
+        >>> result.collect_column("result")[0].as_py()
+        [1, 3]
+    """
     return Expr(f.array_positions(array.expr, element.expr))
 
 
 def list_positions(array: Expr, element: Expr) -> Expr:
     """Searches for an element in the array and returns all occurrences.
 
-    This is an alias for :py:func:`array_positions`.
+    See Also:
+        This is an alias for :py:func:`array_positions`.
     """
     return array_positions(array, element)
 
 
 def array_ndims(array: Expr) -> Expr:
-    """Returns the number of dimensions of the array."""
+    """Returns the number of dimensions of the array.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [[1, 2, 3]]})
+        >>> result = df.select(dfn.functions.array_ndims(dfn.col("a")).alias("result"))
+        >>> result.collect_column("result")[0].as_py()
+        1
+    """
     return Expr(f.array_ndims(array.expr))
 
 
 def list_ndims(array: Expr) -> Expr:
     """Returns the number of dimensions of the array.
 
-    This is an alias for :py:func:`array_ndims`.
+    See Also:
+        This is an alias for :py:func:`array_ndims`.
     """
     return array_ndims(array)
 
 
 def array_prepend(element: Expr, array: Expr) -> Expr:
-    """Prepends an element to the beginning of an array."""
+    """Prepends an element to the beginning of an array.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [[1, 2]]})
+        >>> result = df.select(
+        ...     dfn.functions.array_prepend(dfn.lit(0), dfn.col("a")).alias("result"))
+        >>> result.collect_column("result")[0].as_py()
+        [0, 1, 2]
+    """
     return Expr(f.array_prepend(element.expr, array.expr))
 
 
 def array_push_front(element: Expr, array: Expr) -> Expr:
     """Prepends an element to the beginning of an array.
 
-    This is an alias for :py:func:`array_prepend`.
+    See Also:
+        This is an alias for :py:func:`array_prepend`.
     """
     return array_prepend(element, array)
 
@@ -1438,7 +3228,8 @@ def array_push_front(element: Expr, array: Expr) -> Expr:
 def list_prepend(element: Expr, array: Expr) -> Expr:
     """Prepends an element to the beginning of an array.
 
-    This is an alias for :py:func:`array_prepend`.
+    See Also:
+        This is an alias for :py:func:`array_prepend`.
     """
     return array_prepend(element, array)
 
@@ -1446,82 +3237,173 @@ def list_prepend(element: Expr, array: Expr) -> Expr:
 def list_push_front(element: Expr, array: Expr) -> Expr:
     """Prepends an element to the beginning of an array.
 
-    This is an alias for :py:func:`array_prepend`.
+    See Also:
+        This is an alias for :py:func:`array_prepend`.
     """
     return array_prepend(element, array)
 
 
 def array_pop_back(array: Expr) -> Expr:
-    """Returns the array without the last element."""
+    """Returns the array without the last element.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [[1, 2, 3]]})
+        >>> result = df.select(
+        ...     dfn.functions.array_pop_back(dfn.col("a")).alias("result"))
+        >>> result.collect_column("result")[0].as_py()
+        [1, 2]
+    """
     return Expr(f.array_pop_back(array.expr))
 
 
 def array_pop_front(array: Expr) -> Expr:
-    """Returns the array without the first element."""
+    """Returns the array without the first element.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [[1, 2, 3]]})
+        >>> result = df.select(
+        ...     dfn.functions.array_pop_front(dfn.col("a")).alias("result"))
+        >>> result.collect_column("result")[0].as_py()
+        [2, 3]
+    """
     return Expr(f.array_pop_front(array.expr))
 
 
+def list_pop_back(array: Expr) -> Expr:
+    """Returns the array without the last element.
+
+    See Also:
+        This is an alias for :py:func:`array_pop_back`.
+    """
+    return array_pop_back(array)
+
+
+def list_pop_front(array: Expr) -> Expr:
+    """Returns the array without the first element.
+
+    See Also:
+        This is an alias for :py:func:`array_pop_front`.
+    """
+    return array_pop_front(array)
+
+
 def array_remove(array: Expr, element: Expr) -> Expr:
-    """Removes the first element from the array equal to the given value."""
+    """Removes the first element from the array equal to the given value.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [[1, 2, 1]]})
+        >>> result = df.select(
+        ...     dfn.functions.array_remove(dfn.col("a"), dfn.lit(1)).alias("result"))
+        >>> result.collect_column("result")[0].as_py()
+        [2, 1]
+    """
     return Expr(f.array_remove(array.expr, element.expr))
 
 
 def list_remove(array: Expr, element: Expr) -> Expr:
     """Removes the first element from the array equal to the given value.
 
-    This is an alias for :py:func:`array_remove`.
+    See Also:
+        This is an alias for :py:func:`array_remove`.
     """
     return array_remove(array, element)
 
 
 def array_remove_n(array: Expr, element: Expr, max: Expr) -> Expr:
-    """Removes the first ``max`` elements from the array equal to the given value."""
+    """Removes the first ``max`` elements from the array equal to the given value.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [[1, 2, 1, 1]]})
+        >>> result = df.select(
+        ...     dfn.functions.array_remove_n(dfn.col("a"), dfn.lit(1),
+        ...     dfn.lit(2)).alias("result"))
+        >>> result.collect_column("result")[0].as_py()
+        [2, 1]
+    """
     return Expr(f.array_remove_n(array.expr, element.expr, max.expr))
 
 
 def list_remove_n(array: Expr, element: Expr, max: Expr) -> Expr:
     """Removes the first ``max`` elements from the array equal to the given value.
 
-    This is an alias for :py:func:`array_remove_n`.
+    See Also:
+        This is an alias for :py:func:`array_remove_n`.
     """
     return array_remove_n(array, element, max)
 
 
 def array_remove_all(array: Expr, element: Expr) -> Expr:
-    """Removes all elements from the array equal to the given value."""
+    """Removes all elements from the array equal to the given value.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [[1, 2, 1]]})
+        >>> result = df.select(
+        ...     dfn.functions.array_remove_all(
+        ...         dfn.col("a"), dfn.lit(1)
+        ...     ).alias("result"))
+        >>> result.collect_column("result")[0].as_py()
+        [2]
+    """
     return Expr(f.array_remove_all(array.expr, element.expr))
 
 
 def list_remove_all(array: Expr, element: Expr) -> Expr:
     """Removes all elements from the array equal to the given value.
 
-    This is an alias for :py:func:`array_remove_all`.
+    See Also:
+        This is an alias for :py:func:`array_remove_all`.
     """
     return array_remove_all(array, element)
 
 
 def array_repeat(element: Expr, count: Expr) -> Expr:
-    """Returns an array containing ``element`` ``count`` times."""
+    """Returns an array containing ``element`` ``count`` times.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1]})
+        >>> result = df.select(
+        ...     dfn.functions.array_repeat(dfn.lit(3), dfn.lit(3)).alias("result"))
+        >>> result.collect_column("result")[0].as_py()
+        [3, 3, 3]
+    """
     return Expr(f.array_repeat(element.expr, count.expr))
 
 
 def list_repeat(element: Expr, count: Expr) -> Expr:
     """Returns an array containing ``element`` ``count`` times.
 
-    This is an alias for :py:func:`array_repeat`.
+    See Also:
+        This is an alias for :py:func:`array_repeat`.
     """
     return array_repeat(element, count)
 
 
 def array_replace(array: Expr, from_val: Expr, to_val: Expr) -> Expr:
-    """Replaces the first occurrence of ``from_val`` with ``to_val``."""
+    """Replaces the first occurrence of ``from_val`` with ``to_val``.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [[1, 2, 1]]})
+        >>> result = df.select(
+        ...     dfn.functions.array_replace(dfn.col("a"), dfn.lit(1),
+        ...     dfn.lit(9)).alias("result"))
+        >>> result.collect_column("result")[0].as_py()
+        [9, 2, 1]
+    """
     return Expr(f.array_replace(array.expr, from_val.expr, to_val.expr))
 
 
 def list_replace(array: Expr, from_val: Expr, to_val: Expr) -> Expr:
     """Replaces the first occurrence of ``from_val`` with ``to_val``.
 
-    This is an alias for :py:func:`array_replace`.
+    See Also:
+        This is an alias for :py:func:`array_replace`.
     """
     return array_replace(array, from_val, to_val)
 
@@ -1531,6 +3413,15 @@ def array_replace_n(array: Expr, from_val: Expr, to_val: Expr, max: Expr) -> Exp
 
     Replaces the first ``max`` occurrences of the specified element with another
     specified element.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [[1, 2, 1, 1]]})
+        >>> result = df.select(
+        ...     dfn.functions.array_replace_n(dfn.col("a"), dfn.lit(1), dfn.lit(9),
+        ...     dfn.lit(2)).alias("result"))
+        >>> result.collect_column("result")[0].as_py()
+        [9, 2, 9, 1]
     """
     return Expr(f.array_replace_n(array.expr, from_val.expr, to_val.expr, max.expr))
 
@@ -1541,20 +3432,32 @@ def list_replace_n(array: Expr, from_val: Expr, to_val: Expr, max: Expr) -> Expr
     Replaces the first ``max`` occurrences of the specified element with another
     specified element.
 
-    This is an alias for :py:func:`array_replace_n`.
+    See Also:
+        This is an alias for :py:func:`array_replace_n`.
     """
     return array_replace_n(array, from_val, to_val, max)
 
 
 def array_replace_all(array: Expr, from_val: Expr, to_val: Expr) -> Expr:
-    """Replaces all occurrences of ``from_val`` with ``to_val``."""
+    """Replaces all occurrences of ``from_val`` with ``to_val``.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [[1, 2, 1]]})
+        >>> result = df.select(
+        ...     dfn.functions.array_replace_all(dfn.col("a"), dfn.lit(1),
+        ...     dfn.lit(9)).alias("result"))
+        >>> result.collect_column("result")[0].as_py()
+        [9, 2, 9]
+    """
     return Expr(f.array_replace_all(array.expr, from_val.expr, to_val.expr))
 
 
 def list_replace_all(array: Expr, from_val: Expr, to_val: Expr) -> Expr:
     """Replaces all occurrences of ``from_val`` with ``to_val``.
 
-    This is an alias for :py:func:`array_replace_all`.
+    See Also:
+        This is an alias for :py:func:`array_replace_all`.
     """
     return array_replace_all(array, from_val, to_val)
 
@@ -1566,6 +3469,24 @@ def array_sort(array: Expr, descending: bool = False, null_first: bool = False)
         array: The input array to sort.
         descending: If True, sorts in descending order.
         null_first: If True, nulls will be returned at the beginning of the array.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [[3, 1, 2]]})
+        >>> result = df.select(
+        ...     dfn.functions.array_sort(
+        ...         dfn.col("a")
+        ...     ).alias("result"))
+        >>> result.collect_column("result")[0].as_py()
+        [1, 2, 3]
+
+        >>> df = ctx.from_pydict({"a": [[3, None, 1]]})
+        >>> result = df.select(
+        ...     dfn.functions.array_sort(
+        ...         dfn.col("a"), descending=True, null_first=True,
+        ...     ).alias("result"))
+        >>> result.collect_column("result")[0].as_py()
+        [None, 3, 1]
     """
     desc = "DESC" if descending else "ASC"
     nulls_first = "NULLS FIRST" if null_first else "NULLS LAST"
@@ -1579,14 +3500,39 @@ def array_sort(array: Expr, descending: bool = False, null_first: bool = False)
 
 
 def list_sort(array: Expr, descending: bool = False, null_first: bool = False) -> Expr:
-    """This is an alias for :py:func:`array_sort`."""
+    """Sorts the array.
+
+    See Also:
+        This is an alias for :py:func:`array_sort`.
+    """
     return array_sort(array, descending=descending, null_first=null_first)
 
 
 def array_slice(
     array: Expr, begin: Expr, end: Expr, stride: Expr | None = None
 ) -> Expr:
-    """Returns a slice of the array."""
+    """Returns a slice of the array.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [[1, 2, 3, 4]]})
+        >>> result = df.select(
+        ...     dfn.functions.array_slice(
+        ...         dfn.col("a"), dfn.lit(2), dfn.lit(3)
+        ...     ).alias("result"))
+        >>> result.collect_column("result")[0].as_py()
+        [2, 3]
+
+        Use ``stride`` to skip elements:
+
+        >>> result = df.select(
+        ...     dfn.functions.array_slice(
+        ...         dfn.col("a"), dfn.lit(1), dfn.lit(4),
+        ...         stride=dfn.lit(2),
+        ...     ).alias("result"))
+        >>> result.collect_column("result")[0].as_py()
+        [1, 3]
+    """
     if stride is not None:
         stride = stride.expr
     return Expr(f.array_slice(array.expr, begin.expr, end.expr, stride))
@@ -1595,20 +3541,36 @@ def array_slice(
 def list_slice(array: Expr, begin: Expr, end: Expr, stride: Expr | None = None) -> Expr:
     """Returns a slice of the array.
 
-    This is an alias for :py:func:`array_slice`.
+    See Also:
+        This is an alias for :py:func:`array_slice`.
     """
     return array_slice(array, begin, end, stride)
 
 
 def array_intersect(array1: Expr, array2: Expr) -> Expr:
-    """Returns the intersection of ``array1`` and ``array2``."""
+    """Returns the intersection of ``array1`` and ``array2``.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [[1, 2, 3]], "b": [[2, 3, 4]]})
+        >>> result = df.select(
+        ...     dfn.functions.array_intersect(
+        ...         dfn.col("a"), dfn.col("b")
+        ...     ).alias("result")
+        ... )
+        >>> sorted(
+        ...     result.collect_column("result")[0].as_py()
+        ... )
+        [2, 3]
+    """
     return Expr(f.array_intersect(array1.expr, array2.expr))
 
 
 def list_intersect(array1: Expr, array2: Expr) -> Expr:
     """Returns an the intersection of ``array1`` and ``array2``.
 
-    This is an alias for :py:func:`array_intersect`.
+    See Also:
+        This is an alias for :py:func:`array_intersect`.
     """
     return array_intersect(array1, array2)
 
@@ -1617,6 +3579,19 @@ def array_union(array1: Expr, array2: Expr) -> Expr:
     """Returns an array of the elements in the union of array1 and array2.
 
     Duplicate rows will not be returned.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [[1, 2, 3]], "b": [[2, 3, 4]]})
+        >>> result = df.select(
+        ...     dfn.functions.array_union(
+        ...         dfn.col("a"), dfn.col("b")
+        ...     ).alias("result")
+        ... )
+        >>> sorted(
+        ...     result.collect_column("result")[0].as_py()
+        ... )
+        [1, 2, 3, 4]
     """
     return Expr(f.array_union(array1.expr, array2.expr))
 
@@ -1626,20 +3601,31 @@ def list_union(array1: Expr, array2: Expr) -> Expr:
 
     Duplicate rows will not be returned.
 
-    This is an alias for :py:func:`array_union`.
+    See Also:
+        This is an alias for :py:func:`array_union`.
     """
     return array_union(array1, array2)
 
 
 def array_except(array1: Expr, array2: Expr) -> Expr:
-    """Returns the elements that appear in ``array1`` but not in ``array2``."""
+    """Returns the elements that appear in ``array1`` but not in ``array2``.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [[1, 2, 3]], "b": [[2, 3, 4]]})
+        >>> result = df.select(
+        ...     dfn.functions.array_except(dfn.col("a"), dfn.col("b")).alias("result"))
+        >>> result.collect_column("result")[0].as_py()
+        [1]
+    """
     return Expr(f.array_except(array1.expr, array2.expr))
 
 
 def list_except(array1: Expr, array2: Expr) -> Expr:
     """Returns the elements that appear in ``array1`` but not in the ``array2``.
 
-    This is an alias for :py:func:`array_except`.
+    See Also:
+        This is an alias for :py:func:`array_except`.
     """
     return array_except(array1, array2)
 
@@ -1649,6 +3635,15 @@ def array_resize(array: Expr, size: Expr, value: Expr) -> Expr:
 
     If ``size`` is greater than the ``array`` length, the additional entries will
     be filled with the given ``value``.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [[1, 2]]})
+        >>> result = df.select(
+        ...     dfn.functions.array_resize(dfn.col("a"), dfn.lit(4),
+        ...     dfn.lit(0)).alias("result"))
+        >>> result.collect_column("result")[0].as_py()
+        [1, 2, 0, 0]
     """
     return Expr(f.array_resize(array.expr, size.expr, value.expr))
 
@@ -1657,26 +3652,422 @@ def list_resize(array: Expr, size: Expr, value: Expr) -> Expr:
     """Returns an array with the specified size filled.
 
     If ``size`` is greater than the ``array`` length, the additional entries will be
-    filled with the given ``value``. This is an alias for :py:func:`array_resize`.
+    filled with the given ``value``.
+
+    See Also:
+        This is an alias for :py:func:`array_resize`.
     """
     return array_resize(array, size, value)
 
 
+def array_any_value(array: Expr) -> Expr:
+    """Returns the first non-null element in the array.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [[None, 2, 3]]})
+        >>> result = df.select(
+        ...     dfn.functions.array_any_value(dfn.col("a")).alias("result"))
+        >>> result.collect_column("result")[0].as_py()
+        2
+    """
+    return Expr(f.array_any_value(array.expr))
+
+
+def list_any_value(array: Expr) -> Expr:
+    """Returns the first non-null element in the array.
+
+    See Also:
+        This is an alias for :py:func:`array_any_value`.
+    """
+    return array_any_value(array)
+
+
+def array_distance(array1: Expr, array2: Expr) -> Expr:
+    """Returns the Euclidean distance between two numeric arrays.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [[1.0, 2.0]], "b": [[1.0, 4.0]]})
+        >>> result = df.select(
+        ...     dfn.functions.array_distance(
+        ...         dfn.col("a"), dfn.col("b"),
+        ...     ).alias("result"))
+        >>> result.collect_column("result")[0].as_py()
+        2.0
+    """
+    return Expr(f.array_distance(array1.expr, array2.expr))
+
+
+def list_distance(array1: Expr, array2: Expr) -> Expr:
+    """Returns the Euclidean distance between two numeric arrays.
+
+    See Also:
+        This is an alias for :py:func:`array_distance`.
+    """
+    return array_distance(array1, array2)
+
+
+def array_max(array: Expr) -> Expr:
+    """Returns the maximum value in the array.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [[1, 2, 3]]})
+        >>> result = df.select(
+        ...     dfn.functions.array_max(dfn.col("a")).alias("result"))
+        >>> result.collect_column("result")[0].as_py()
+        3
+    """
+    return Expr(f.array_max(array.expr))
+
+
+def list_max(array: Expr) -> Expr:
+    """Returns the maximum value in the array.
+
+    See Also:
+        This is an alias for :py:func:`array_max`.
+    """
+    return array_max(array)
+
+
+def array_min(array: Expr) -> Expr:
+    """Returns the minimum value in the array.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [[1, 2, 3]]})
+        >>> result = df.select(
+        ...     dfn.functions.array_min(dfn.col("a")).alias("result"))
+        >>> result.collect_column("result")[0].as_py()
+        1
+    """
+    return Expr(f.array_min(array.expr))
+
+
+def list_min(array: Expr) -> Expr:
+    """Returns the minimum value in the array.
+
+    See Also:
+        This is an alias for :py:func:`array_min`.
+    """
+    return array_min(array)
+
+
+def array_reverse(array: Expr) -> Expr:
+    """Reverses the order of elements in the array.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [[1, 2, 3]]})
+        >>> result = df.select(
+        ...     dfn.functions.array_reverse(dfn.col("a")).alias("result"))
+        >>> result.collect_column("result")[0].as_py()
+        [3, 2, 1]
+    """
+    return Expr(f.array_reverse(array.expr))
+
+
+def list_reverse(array: Expr) -> Expr:
+    """Reverses the order of elements in the array.
+
+    See Also:
+        This is an alias for :py:func:`array_reverse`.
+    """
+    return array_reverse(array)
+
+
+def arrays_zip(*arrays: Expr) -> Expr:
+    """Combines multiple arrays into a single array of structs.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [[1, 2]], "b": [[3, 4]]})
+        >>> result = df.select(
+        ...     dfn.functions.arrays_zip(dfn.col("a"), dfn.col("b")).alias("result"))
+        >>> result.collect_column("result")[0].as_py()
+        [{'c0': 1, 'c1': 3}, {'c0': 2, 'c1': 4}]
+    """
+    args = [a.expr for a in arrays]
+    return Expr(f.arrays_zip(args))
+
+
+def list_zip(*arrays: Expr) -> Expr:
+    """Combines multiple arrays into a single array of structs.
+
+    See Also:
+        This is an alias for :py:func:`arrays_zip`.
+    """
+    return arrays_zip(*arrays)
+
+
+def string_to_array(
+    string: Expr, delimiter: Expr, null_string: Expr | None = None
+) -> Expr:
+    """Splits a string based on a delimiter and returns an array of parts.
+
+    Any parts matching the optional ``null_string`` will be replaced with ``NULL``.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["hello,world"]})
+        >>> result = df.select(
+        ...     dfn.functions.string_to_array(
+        ...         dfn.col("a"), dfn.lit(","),
+        ...     ).alias("result"))
+        >>> result.collect_column("result")[0].as_py()
+        ['hello', 'world']
+
+        Replace parts matching a ``null_string`` with ``NULL``:
+
+        >>> result = df.select(
+        ...     dfn.functions.string_to_array(
+        ...         dfn.col("a"), dfn.lit(","), null_string=dfn.lit("world"),
+        ...     ).alias("result"))
+        >>> result.collect_column("result")[0].as_py()
+        ['hello', None]
+    """
+    null_expr = null_string.expr if null_string is not None else None
+    return Expr(f.string_to_array(string.expr, delimiter.expr, null_expr))
+
+
+def string_to_list(
+    string: Expr, delimiter: Expr, null_string: Expr | None = None
+) -> Expr:
+    """Splits a string based on a delimiter and returns an array of parts.
+
+    See Also:
+        This is an alias for :py:func:`string_to_array`.
+    """
+    return string_to_array(string, delimiter, null_string)
+
+
+def gen_series(start: Expr, stop: Expr, step: Expr | None = None) -> Expr:
+    """Creates a list of values in the range between start and stop.
+
+    Unlike :py:func:`range`, this includes the upper bound.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [0]})
+        >>> result = df.select(
+        ...     dfn.functions.gen_series(
+        ...         dfn.lit(1), dfn.lit(5),
+        ...     ).alias("result"))
+        >>> result.collect_column("result")[0].as_py()
+        [1, 2, 3, 4, 5]
+
+        Specify a custom ``step``:
+
+        >>> result = df.select(
+        ...     dfn.functions.gen_series(
+        ...         dfn.lit(1), dfn.lit(10), step=dfn.lit(3),
+        ...     ).alias("result"))
+        >>> result.collect_column("result")[0].as_py()
+        [1, 4, 7, 10]
+    """
+    step_expr = step.expr if step is not None else None
+    return Expr(f.gen_series(start.expr, stop.expr, step_expr))
+
+
+def generate_series(start: Expr, stop: Expr, step: Expr | None = None) -> Expr:
+    """Creates a list of values in the range between start and stop.
+
+    Unlike :py:func:`range`, this includes the upper bound.
+
+    See Also:
+        This is an alias for :py:func:`gen_series`.
+    """
+    return gen_series(start, stop, step)
+
+
 def flatten(array: Expr) -> Expr:
-    """Flattens an array of arrays into a single array."""
+    """Flattens an array of arrays into a single array.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [[[1, 2], [3, 4]]]})
+        >>> result = df.select(dfn.functions.flatten(dfn.col("a")).alias("result"))
+        >>> result.collect_column("result")[0].as_py()
+        [1, 2, 3, 4]
+    """
     return Expr(f.flatten(array.expr))
 
 
 def cardinality(array: Expr) -> Expr:
-    """Returns the total number of elements in the array."""
+    """Returns the total number of elements in the array.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [[1, 2, 3]]})
+        >>> result = df.select(dfn.functions.cardinality(dfn.col("a")).alias("result"))
+        >>> result.collect_column("result")[0].as_py()
+        3
+    """
     return Expr(f.cardinality(array.expr))
 
 
 def empty(array: Expr) -> Expr:
-    """This is an alias for :py:func:`array_empty`."""
+    """Returns true if the array is empty.
+
+    See Also:
+        This is an alias for :py:func:`array_empty`.
+    """
     return array_empty(array)
 
 
+# map functions
+
+
+def make_map(*args: Any) -> Expr:
+    """Returns a map expression.
+
+    Supports three calling conventions:
+
+    - ``make_map({"a": 1, "b": 2})`` — from a Python dictionary.
+    - ``make_map([keys], [values])`` — from a list of keys and a list of
+      their associated values.  Both lists must be the same length.
+    - ``make_map(k1, v1, k2, v2, ...)`` — from alternating keys and their
+      associated values.
+
+    Keys and values that are not already :py:class:`~datafusion.expr.Expr`
+    are automatically converted to literal expressions.
+
+    Examples:
+        From a dictionary:
+
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1]})
+        >>> result = df.select(
+        ...     dfn.functions.make_map({"a": 1, "b": 2}).alias("m"))
+        >>> result.collect_column("m")[0].as_py()
+        [('a', 1), ('b', 2)]
+
+        From two lists:
+
+        >>> df = ctx.from_pydict({"key": ["x", "y"], "val": [10, 20]})
+        >>> df = df.select(
+        ...     dfn.functions.make_map(
+        ...         [dfn.col("key")], [dfn.col("val")]
+        ...     ).alias("m"))
+        >>> df.collect_column("m")[0].as_py()
+        [('x', 10)]
+
+        From alternating keys and values:
+
+        >>> df = ctx.from_pydict({"a": [1]})
+        >>> result = df.select(
+        ...     dfn.functions.make_map("x", 1, "y", 2).alias("m"))
+        >>> result.collect_column("m")[0].as_py()
+        [('x', 1), ('y', 2)]
+    """
+    if len(args) == 1 and isinstance(args[0], dict):
+        key_list = list(args[0].keys())
+        value_list = list(args[0].values())
+    elif (
+        len(args) == 2  # noqa: PLR2004
+        and isinstance(args[0], list)
+        and isinstance(args[1], list)
+    ):
+        if len(args[0]) != len(args[1]):
+            msg = "make_map requires key and value lists to be the same length"
+            raise ValueError(msg)
+        key_list = args[0]
+        value_list = args[1]
+    elif len(args) >= 2 and len(args) % 2 == 0:  # noqa: PLR2004
+        key_list = list(args[0::2])
+        value_list = list(args[1::2])
+    else:
+        msg = (
+            "make_map expects a dict, two lists, or an even number of "
+            "key-value arguments"
+        )
+        raise ValueError(msg)
+
+    key_exprs = [k if isinstance(k, Expr) else Expr.literal(k) for k in key_list]
+    val_exprs = [v if isinstance(v, Expr) else Expr.literal(v) for v in value_list]
+    return Expr(f.make_map([k.expr for k in key_exprs], [v.expr for v in val_exprs]))
+
+
+def map_keys(map: Expr) -> Expr:
+    """Returns a list of all keys in the map.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1]})
+        >>> df = df.select(
+        ...     dfn.functions.make_map({"x": 1, "y": 2}).alias("m"))
+        >>> result = df.select(
+        ...     dfn.functions.map_keys(dfn.col("m")).alias("keys"))
+        >>> result.collect_column("keys")[0].as_py()
+        ['x', 'y']
+    """
+    return Expr(f.map_keys(map.expr))
+
+
+def map_values(map: Expr) -> Expr:
+    """Returns a list of all values in the map.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1]})
+        >>> df = df.select(
+        ...     dfn.functions.make_map({"x": 1, "y": 2}).alias("m"))
+        >>> result = df.select(
+        ...     dfn.functions.map_values(dfn.col("m")).alias("vals"))
+        >>> result.collect_column("vals")[0].as_py()
+        [1, 2]
+    """
+    return Expr(f.map_values(map.expr))
+
+
+def map_extract(map: Expr, key: Expr) -> Expr:
+    """Returns the value for a given key in the map.
+
+    Returns ``[None]`` if the key is absent.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1]})
+        >>> df = df.select(
+        ...     dfn.functions.make_map({"x": 1, "y": 2}).alias("m"))
+        >>> result = df.select(
+        ...     dfn.functions.map_extract(
+        ...         dfn.col("m"), dfn.lit("x")
+        ...     ).alias("val"))
+        >>> result.collect_column("val")[0].as_py()
+        [1]
+    """
+    return Expr(f.map_extract(map.expr, key.expr))
+
+
+def map_entries(map: Expr) -> Expr:
+    """Returns a list of all entries (key-value struct pairs) in the map.
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1]})
+        >>> df = df.select(
+        ...     dfn.functions.make_map({"x": 1, "y": 2}).alias("m"))
+        >>> result = df.select(
+        ...     dfn.functions.map_entries(dfn.col("m")).alias("entries"))
+        >>> result.collect_column("entries")[0].as_py()
+        [{'key': 'x', 'value': 1}, {'key': 'y', 'value': 2}]
+    """
+    return Expr(f.map_entries(map.expr))
+
+
+def element_at(map: Expr, key: Expr) -> Expr:
+    """Returns the value for a given key in the map.
+
+    Returns ``[None]`` if the key is absent.
+
+    See Also:
+        This is an alias for :py:func:`map_extract`.
+    """
+    return map_extract(map, key)
+
+
 # aggregate functions
 def approx_distinct(
     expression: Expr,
@@ -1694,6 +4085,24 @@ def approx_distinct(
     Args:
         expression: Values to check for distinct entries
         filter: If provided, only compute against rows for which the filter is True
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1, 1, 2, 3]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.approx_distinct(
+        ...         dfn.col("a")
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py() == 3
+        True
+
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.approx_distinct(
+        ...         dfn.col("a"),
+        ...         filter=dfn.col("a") > dfn.lit(1)
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py() == 2
+        True
     """
     filter_raw = filter.expr if filter is not None else None
 
@@ -1712,6 +4121,24 @@ def approx_median(expression: Expr, filter: Expr | None = None) -> Expr:
     Args:
         expression: Values to find the median for
         filter: If provided, only compute against rows for which the filter is True
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1.0, 2.0, 3.0]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.approx_median(
+        ...         dfn.col("a")
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        2.0
+
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.approx_median(
+        ...         dfn.col("a"),
+        ...         filter=dfn.col("a") > dfn.lit(1.0)
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        2.5
     """
     filter_raw = filter.expr if filter is not None else None
     return Expr(f.approx_median(expression.expr, filter=filter_raw))
@@ -1743,6 +4170,25 @@ def approx_percentile_cont(
         percentile: This must be between 0.0 and 1.0, inclusive
         num_centroids: Max bin size for the t-digest algorithm
         filter: If provided, only compute against rows for which the filter is True
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1.0, 2.0, 3.0, 4.0, 5.0]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.approx_percentile_cont(
+        ...         dfn.col("a"), 0.5
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        3.0
+
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.approx_percentile_cont(
+        ...         dfn.col("a"), 0.5,
+        ...         num_centroids=10,
+        ...         filter=dfn.col("a") > dfn.lit(1.0),
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        3.5
     """
     sort_expr_raw = sort_or_default(sort_expression)
     filter_raw = filter.expr if filter is not None else None
@@ -1775,6 +4221,24 @@ def approx_percentile_cont_with_weight(
         num_centroids: Max bin size for the t-digest algorithm
         filter: If provided, only compute against rows for which the filter is True
 
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1.0, 2.0, 3.0], "w": [1.0, 1.0, 1.0]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.approx_percentile_cont_with_weight(
+        ...         dfn.col("a"), dfn.col("w"), 0.5
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        2.0
+
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.approx_percentile_cont_with_weight(
+        ...         dfn.col("a"), dfn.col("w"), 0.5,
+        ...         num_centroids=10,
+        ...         filter=dfn.col("a") > dfn.lit(1.0),
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        2.5
     """
     sort_expr_raw = sort_or_default(sort_expression)
     filter_raw = filter.expr if filter is not None else None
@@ -1789,6 +4253,60 @@ def approx_percentile_cont_with_weight(
     )
 
 
+def percentile_cont(
+    sort_expression: Expr | SortExpr,
+    percentile: float,
+    filter: Expr | None = None,
+) -> Expr:
+    """Computes the exact percentile of input values using continuous interpolation.
+
+    Unlike :py:func:`approx_percentile_cont`, this function computes the exact
+    percentile value rather than an approximation.
+
+    If using the builder functions described in ref:`_aggregation` this function ignores
+    the options ``order_by``, ``null_treatment``, and ``distinct``.
+
+    Args:
+        sort_expression: Values for which to find the percentile
+        percentile: This must be between 0.0 and 1.0, inclusive
+        filter: If provided, only compute against rows for which the filter is True
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1.0, 2.0, 3.0, 4.0, 5.0]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.percentile_cont(
+        ...         dfn.col("a"), 0.5
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        3.0
+
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.percentile_cont(
+        ...         dfn.col("a"), 0.5,
+        ...         filter=dfn.col("a") > dfn.lit(1.0),
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        3.5
+    """
+    sort_expr_raw = sort_or_default(sort_expression)
+    filter_raw = filter.expr if filter is not None else None
+    return Expr(f.percentile_cont(sort_expr_raw, percentile, filter=filter_raw))
+
+
+def quantile_cont(
+    sort_expression: Expr | SortExpr,
+    percentile: float,
+    filter: Expr | None = None,
+) -> Expr:
+    """Computes the exact percentile of input values using continuous interpolation.
+
+    See Also:
+        This is an alias for :py:func:`percentile_cont`.
+    """
+    return percentile_cont(sort_expression, percentile, filter)
+
+
 def array_agg(
     expression: Expr,
     distinct: bool = False,
@@ -1810,9 +4328,32 @@ def array_agg(
         filter: If provided, only compute against rows for which the filter is True
         order_by: Order the resultant array values. Accepts column names or expressions.
 
-    For example::
-
-        df.aggregate([], array_agg(col("a"), order_by="b"))
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1, 2, 3]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.array_agg(
+        ...         dfn.col("a")
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        [1, 2, 3]
+
+        >>> df = ctx.from_pydict({"a": [3, 1, 2, 1]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.array_agg(
+        ...         dfn.col("a"), distinct=True,
+        ...     ).alias("v")])
+        >>> sorted(result.collect_column("v")[0].as_py())
+        [1, 2, 3]
+
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.array_agg(
+        ...         dfn.col("a"),
+        ...         filter=dfn.col("a") > dfn.lit(1),
+        ...         order_by="a",
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        [2, 3]
     """
     order_by_raw = sort_list_to_raw_sort_list(order_by)
     filter_raw = filter.expr if filter is not None else None
@@ -1824,6 +4365,65 @@ def array_agg(
     )
 
 
+def grouping(
+    expression: Expr,
+    distinct: bool = False,
+    filter: Expr | None = None,
+) -> Expr:
+    """Indicates whether a column is aggregated across in the current row.
+
+    Returns 0 when the column is part of the grouping key for that row
+    (i.e., the row contains per-group results for that column). Returns 1
+    when the column is *not* part of the grouping key (i.e., the row's
+    aggregate spans all values of that column).
+
+    This function is meaningful with
+    :py:meth:`GroupingSet.rollup <datafusion.expr.GroupingSet.rollup>`,
+    :py:meth:`GroupingSet.cube <datafusion.expr.GroupingSet.cube>`, or
+    :py:meth:`GroupingSet.grouping_sets <datafusion.expr.GroupingSet.grouping_sets>`,
+    where different rows are grouped by different subsets of columns. In a
+    default aggregation without grouping sets every column is always part
+    of the key, so ``grouping()`` always returns 0.
+
+    .. warning::
+
+        Due to an upstream DataFusion limitation
+        (`#21411 <https://github.com/apache/datafusion/issues/21411>`_),
+        ``.alias()`` cannot be applied directly to a ``grouping()``
+        expression. Doing so will raise an error at execution time. To
+        rename the column, use
+        :py:meth:`~datafusion.dataframe.DataFrame.with_column_renamed`
+        on the result DataFrame instead.
+
+    Args:
+        expression: The column to check grouping status for
+        distinct: If True, compute on distinct values only
+        filter: If provided, only compute against rows for which the filter is True
+
+    Examples:
+        With :py:meth:`~datafusion.expr.GroupingSet.rollup`, the result
+        includes both per-group rows (``grouping(a) = 0``) and a
+        grand-total row where ``a`` is aggregated across
+        (``grouping(a) = 1``):
+
+        >>> from datafusion.expr import GroupingSet
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1, 1, 2], "b": [10, 20, 30]})
+        >>> result = df.aggregate(
+        ...     [GroupingSet.rollup(dfn.col("a"))],
+        ...     [dfn.functions.sum(dfn.col("b")).alias("s"),
+        ...      dfn.functions.grouping(dfn.col("a"))],
+        ... ).sort(dfn.col("a").sort(nulls_first=False))
+        >>> result.collect_column("s").to_pylist()
+        [30, 30, 60]
+
+    See Also:
+        :py:class:`~datafusion.expr.GroupingSet`
+    """
+    filter_raw = filter.expr if filter is not None else None
+    return Expr(f.grouping(expression.expr, distinct=distinct, filter=filter_raw))
+
+
 def avg(
     expression: Expr,
     filter: Expr | None = None,
@@ -1838,6 +4438,24 @@ def avg(
     Args:
         expression: Values to combine into an array
         filter: If provided, only compute against rows for which the filter is True
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1.0, 2.0, 3.0]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.avg(
+        ...         dfn.col("a")
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        2.0
+
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.avg(
+        ...         dfn.col("a"),
+        ...         filter=dfn.col("a") > dfn.lit(1.0)
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        2.5
     """
     filter_raw = filter.expr if filter is not None else None
     return Expr(f.avg(expression.expr, filter=filter_raw))
@@ -1855,6 +4473,24 @@ def corr(value_y: Expr, value_x: Expr, filter: Expr | None = None) -> Expr:
         value_y: The dependent variable for correlation
         value_x: The independent variable for correlation
         filter: If provided, only compute against rows for which the filter is True
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1.0, 2.0, 3.0], "b": [1.0, 2.0, 3.0]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.corr(
+        ...         dfn.col("a"), dfn.col("b")
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        1.0
+
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.corr(
+        ...         dfn.col("a"), dfn.col("b"),
+        ...         filter=dfn.col("a") > dfn.lit(1.0)
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        1.0
     """
     filter_raw = filter.expr if filter is not None else None
     return Expr(f.corr(value_y.expr, value_x.expr, filter=filter_raw))
@@ -1876,6 +4512,25 @@ def count(
         expressions: Argument to perform bitwise calculation on
         distinct: If True, a single entry for each distinct value will be in the result
         filter: If provided, only compute against rows for which the filter is True
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1, 2, 3]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.count(
+        ...         dfn.col("a")
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        3
+
+        >>> df = ctx.from_pydict({"a": [1, 1, 2, 3]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.count(
+        ...         dfn.col("a"), distinct=True,
+        ...         filter=dfn.col("a") > dfn.lit(1),
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        2
     """
     filter_raw = filter.expr if filter is not None else None
 
@@ -1901,6 +4556,30 @@ def covar_pop(value_y: Expr, value_x: Expr, filter: Expr | None = None) -> Expr:
         value_y: The dependent variable for covariance
         value_x: The independent variable for covariance
         filter: If provided, only compute against rows for which the filter is True
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1.0, 5.0, 10.0], "b": [1.0, 2.0, 3.0]})
+        >>> result = df.aggregate(
+        ...     [],
+        ...     [dfn.functions.covar_pop(
+        ...         dfn.col("a"), dfn.col("b")
+        ...     ).alias("v")]
+        ... )
+        >>> result.collect_column("v")[0].as_py()
+        3.0
+
+        >>> df = ctx.from_pydict(
+        ...     {"a": [0.0, 1.0, 3.0], "b": [0.0, 1.0, 3.0]})
+        >>> result = df.aggregate(
+        ...     [],
+        ...     [dfn.functions.covar_pop(
+        ...         dfn.col("a"), dfn.col("b"),
+        ...         filter=dfn.col("a") > dfn.lit(0.0)
+        ...     ).alias("v")]
+        ... )
+        >>> result.collect_column("v")[0].as_py()
+        1.0
     """
     filter_raw = filter.expr if filter is not None else None
     return Expr(f.covar_pop(value_y.expr, value_x.expr, filter=filter_raw))
@@ -1918,6 +4597,24 @@ def covar_samp(value_y: Expr, value_x: Expr, filter: Expr | None = None) -> Expr
         value_y: The dependent variable for covariance
         value_x: The independent variable for covariance
         filter: If provided, only compute against rows for which the filter is True
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1.0, 2.0, 3.0], "b": [4.0, 5.0, 6.0]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.covar_samp(
+        ...         dfn.col("a"), dfn.col("b")
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        1.0
+
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.covar_samp(
+        ...         dfn.col("a"), dfn.col("b"),
+        ...         filter=dfn.col("a") > dfn.lit(1.0)
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        0.5
     """
     filter_raw = filter.expr if filter is not None else None
     return Expr(f.covar_samp(value_y.expr, value_x.expr, filter=filter_raw))
@@ -1926,7 +4623,8 @@ def covar_samp(value_y: Expr, value_x: Expr, filter: Expr | None = None) -> Expr
 def covar(value_y: Expr, value_x: Expr, filter: Expr | None = None) -> Expr:
     """Computes the sample covariance.
 
-    This is an alias for :py:func:`covar_samp`.
+    See Also:
+        This is an alias for :py:func:`covar_samp`.
     """
     return covar_samp(value_y, value_x, filter)
 
@@ -1940,6 +4638,24 @@ def max(expression: Expr, filter: Expr | None = None) -> Expr:
     Args:
         expression: The value to find the maximum of
         filter: If provided, only compute against rows for which the filter is True
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1, 2, 3]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.max(
+        ...         dfn.col("a")
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        3
+
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.max(
+        ...         dfn.col("a"),
+        ...         filter=dfn.col("a") < dfn.lit(3)
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        2
     """
     filter_raw = filter.expr if filter is not None else None
     return Expr(f.max(expression.expr, filter=filter_raw))
@@ -1948,7 +4664,8 @@ def max(expression: Expr, filter: Expr | None = None) -> Expr:
 def mean(expression: Expr, filter: Expr | None = None) -> Expr:
     """Returns the average (mean) value of the argument.
 
-    This is an alias for :py:func:`avg`.
+    See Also:
+        This is an alias for :py:func:`avg`.
     """
     return avg(expression, filter)
 
@@ -1968,6 +4685,25 @@ def median(
         expression: The value to compute the median of
         distinct: If True, a single entry for each distinct value will be in the result
         filter: If provided, only compute against rows for which the filter is True
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1.0, 2.0, 3.0]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.median(
+        ...         dfn.col("a")
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        2.0
+
+        >>> df = ctx.from_pydict({"a": [1.0, 1.0, 2.0, 3.0]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.median(
+        ...         dfn.col("a"), distinct=True,
+        ...         filter=dfn.col("a") < dfn.lit(3.0),
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        1.5
     """
     filter_raw = filter.expr if filter is not None else None
     return Expr(f.median(expression.expr, distinct=distinct, filter=filter_raw))
@@ -1982,6 +4718,24 @@ def min(expression: Expr, filter: Expr | None = None) -> Expr:
     Args:
         expression: The value to find the minimum of
         filter: If provided, only compute against rows for which the filter is True
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1, 2, 3]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.min(
+        ...         dfn.col("a")
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        1
+
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.min(
+        ...         dfn.col("a"),
+        ...         filter=dfn.col("a") > dfn.lit(1)
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        2
     """
     filter_raw = filter.expr if filter is not None else None
     return Expr(f.min(expression.expr, filter=filter_raw))
@@ -2001,6 +4755,24 @@ def sum(
     Args:
         expression: Values to combine into an array
         filter: If provided, only compute against rows for which the filter is True
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1, 2, 3]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.sum(
+        ...         dfn.col("a")
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        6
+
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.sum(
+        ...         dfn.col("a"),
+        ...         filter=dfn.col("a") > dfn.lit(1)
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        5
     """
     filter_raw = filter.expr if filter is not None else None
     return Expr(f.sum(expression.expr, filter=filter_raw))
@@ -2015,6 +4787,24 @@ def stddev(expression: Expr, filter: Expr | None = None) -> Expr:
     Args:
         expression: The value to find the minimum of
         filter: If provided, only compute against rows for which the filter is True
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [2.0, 4.0, 6.0]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.stddev(
+        ...         dfn.col("a")
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        2.0
+
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.stddev(
+        ...         dfn.col("a"),
+        ...         filter=dfn.col("a") > dfn.lit(2.0)
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        1.41...
     """
     filter_raw = filter.expr if filter is not None else None
     return Expr(f.stddev(expression.expr, filter=filter_raw))
@@ -2029,6 +4819,27 @@ def stddev_pop(expression: Expr, filter: Expr | None = None) -> Expr:
     Args:
         expression: The value to find the minimum of
         filter: If provided, only compute against rows for which the filter is True
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [0.0, 1.0, 3.0]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.stddev_pop(
+        ...         dfn.col("a")
+        ...     ).alias("v")]
+        ... )
+        >>> result.collect_column("v")[0].as_py()
+        1.247...
+
+        >>> df = ctx.from_pydict({"a": [0.0, 1.0, 3.0]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.stddev_pop(
+        ...         dfn.col("a"),
+        ...         filter=dfn.col("a") > dfn.lit(0.0)
+        ...     ).alias("v")]
+        ... )
+        >>> result.collect_column("v")[0].as_py()
+        1.0
     """
     filter_raw = filter.expr if filter is not None else None
     return Expr(f.stddev_pop(expression.expr, filter=filter_raw))
@@ -2037,7 +4848,8 @@ def stddev_pop(expression: Expr, filter: Expr | None = None) -> Expr:
 def stddev_samp(arg: Expr, filter: Expr | None = None) -> Expr:
     """Computes the sample standard deviation of the argument.
 
-    This is an alias for :py:func:`stddev`.
+    See Also:
+        This is an alias for :py:func:`stddev`.
     """
     return stddev(arg, filter=filter)
 
@@ -2045,7 +4857,8 @@ def stddev_samp(arg: Expr, filter: Expr | None = None) -> Expr:
 def var(expression: Expr, filter: Expr | None = None) -> Expr:
     """Computes the sample variance of the argument.
 
-    This is an alias for :py:func:`var_samp`.
+    See Also:
+        This is an alias for :py:func:`var_samp`.
     """
     return var_samp(expression, filter)
 
@@ -2059,11 +4872,38 @@ def var_pop(expression: Expr, filter: Expr | None = None) -> Expr:
     Args:
         expression: The variable to compute the variance for
         filter: If provided, only compute against rows for which the filter is True
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [-1.0, 0.0, 2.0]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.var_pop(
+        ...         dfn.col("a")
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        1.555...
+
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.var_pop(
+        ...         dfn.col("a"),
+        ...         filter=dfn.col("a") > dfn.lit(-1.0)
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        1.0
     """
     filter_raw = filter.expr if filter is not None else None
     return Expr(f.var_pop(expression.expr, filter=filter_raw))
 
 
+def var_population(expression: Expr, filter: Expr | None = None) -> Expr:
+    """Computes the population variance of the argument.
+
+    See Also:
+        This is an alias for :py:func:`var_pop`.
+    """
+    return var_pop(expression, filter)
+
+
 def var_samp(expression: Expr, filter: Expr | None = None) -> Expr:
     """Computes the sample variance of the argument.
 
@@ -2073,6 +4913,24 @@ def var_samp(expression: Expr, filter: Expr | None = None) -> Expr:
     Args:
         expression: The variable to compute the variance for
         filter: If provided, only compute against rows for which the filter is True
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1.0, 2.0, 3.0]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.var_samp(
+        ...         dfn.col("a")
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        1.0
+
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.var_samp(
+        ...         dfn.col("a"),
+        ...         filter=dfn.col("a") > dfn.lit(1.0)
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        0.5
     """
     filter_raw = filter.expr if filter is not None else None
     return Expr(f.var_sample(expression.expr, filter=filter_raw))
@@ -2081,7 +4939,8 @@ def var_samp(expression: Expr, filter: Expr | None = None) -> Expr:
 def var_sample(expression: Expr, filter: Expr | None = None) -> Expr:
     """Computes the sample variance of the argument.
 
-    This is an alias for :py:func:`var_samp`.
+    See Also:
+        This is an alias for :py:func:`var_samp`.
     """
     return var_samp(expression, filter)
 
@@ -2103,6 +4962,24 @@ def regr_avgx(
         y: The linear regression dependent variable
         x: The linear regression independent variable
         filter: If provided, only compute against rows for which the filter is True
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"y": [1.0, 2.0, 3.0], "x": [4.0, 5.0, 6.0]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.regr_avgx(
+        ...         dfn.col("y"), dfn.col("x")
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        5.0
+
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.regr_avgx(
+        ...         dfn.col("y"), dfn.col("x"),
+        ...         filter=dfn.col("y") > dfn.lit(1.0)
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        5.5
     """
     filter_raw = filter.expr if filter is not None else None
 
@@ -2126,6 +5003,24 @@ def regr_avgy(
         y: The linear regression dependent variable
         x: The linear regression independent variable
         filter: If provided, only compute against rows for which the filter is True
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"y": [1.0, 2.0, 3.0], "x": [4.0, 5.0, 6.0]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.regr_avgy(
+        ...         dfn.col("y"), dfn.col("x")
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        2.0
+
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.regr_avgy(
+        ...         dfn.col("y"), dfn.col("x"),
+        ...         filter=dfn.col("y") > dfn.lit(1.0)
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        2.5
     """
     filter_raw = filter.expr if filter is not None else None
 
@@ -2149,6 +5044,24 @@ def regr_count(
         y: The linear regression dependent variable
         x: The linear regression independent variable
         filter: If provided, only compute against rows for which the filter is True
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"y": [1.0, 2.0, 3.0], "x": [4.0, 5.0, 6.0]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.regr_count(
+        ...         dfn.col("y"), dfn.col("x")
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        3
+
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.regr_count(
+        ...         dfn.col("y"), dfn.col("x"),
+        ...         filter=dfn.col("y") > dfn.lit(1.0)
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        2
     """
     filter_raw = filter.expr if filter is not None else None
 
@@ -2172,6 +5085,26 @@ def regr_intercept(
         y: The linear regression dependent variable
         x: The linear regression independent variable
         filter: If provided, only compute against rows for which the filter is True
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"y": [2.0, 4.0, 6.0], "x": [4.0, 16.0, 36.0]})
+        >>> result = df.aggregate(
+        ...     [],
+        ...     [dfn.functions.regr_intercept(
+        ...         dfn.col("y"), dfn.col("x")
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        1.714...
+
+        >>> result = df.aggregate(
+        ...     [],
+        ...     [dfn.functions.regr_intercept(
+        ...         dfn.col("y"), dfn.col("x"),
+        ...         filter=dfn.col("y") > dfn.lit(2.0)
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        2.4
     """
     filter_raw = filter.expr if filter is not None else None
 
@@ -2195,6 +5128,24 @@ def regr_r2(
         y: The linear regression dependent variable
         x: The linear regression independent variable
         filter: If provided, only compute against rows for which the filter is True
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"y": [2.0, 4.0, 6.0], "x": [4.0, 16.0, 36.0]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.regr_r2(
+        ...         dfn.col("y"), dfn.col("x")
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        0.9795...
+
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.regr_r2(
+        ...         dfn.col("y"), dfn.col("x"),
+        ...         filter=dfn.col("y") > dfn.lit(2.0)
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        1.0
     """
     filter_raw = filter.expr if filter is not None else None
 
@@ -2218,6 +5169,24 @@ def regr_slope(
         y: The linear regression dependent variable
         x: The linear regression independent variable
         filter: If provided, only compute against rows for which the filter is True
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"y": [2.0, 4.0, 6.0], "x": [4.0, 16.0, 36.0]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.regr_slope(
+        ...         dfn.col("y"), dfn.col("x")
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        0.122...
+
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.regr_slope(
+        ...         dfn.col("y"), dfn.col("x"),
+        ...         filter=dfn.col("y") > dfn.lit(2.0)
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        0.1
     """
     filter_raw = filter.expr if filter is not None else None
 
@@ -2241,6 +5210,24 @@ def regr_sxx(
         y: The linear regression dependent variable
         x: The linear regression independent variable
         filter: If provided, only compute against rows for which the filter is True
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"y": [1.0, 2.0, 3.0], "x": [1.0, 2.0, 3.0]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.regr_sxx(
+        ...         dfn.col("y"), dfn.col("x")
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        2.0
+
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.regr_sxx(
+        ...         dfn.col("y"), dfn.col("x"),
+        ...         filter=dfn.col("y") > dfn.lit(1.0)
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        0.5
     """
     filter_raw = filter.expr if filter is not None else None
 
@@ -2264,6 +5251,24 @@ def regr_sxy(
         y: The linear regression dependent variable
         x: The linear regression independent variable
         filter: If provided, only compute against rows for which the filter is True
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"y": [1.0, 2.0, 3.0], "x": [1.0, 2.0, 3.0]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.regr_sxy(
+        ...         dfn.col("y"), dfn.col("x")
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        2.0
+
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.regr_sxy(
+        ...         dfn.col("y"), dfn.col("x"),
+        ...         filter=dfn.col("y") > dfn.lit(1.0)
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        0.5
     """
     filter_raw = filter.expr if filter is not None else None
 
@@ -2287,6 +5292,24 @@ def regr_syy(
         y: The linear regression dependent variable
         x: The linear regression independent variable
         filter: If provided, only compute against rows for which the filter is True
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"y": [1.0, 2.0, 3.0], "x": [1.0, 2.0, 3.0]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.regr_syy(
+        ...         dfn.col("y"), dfn.col("x")
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        2.0
+
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.regr_syy(
+        ...         dfn.col("y"), dfn.col("x"),
+        ...         filter=dfn.col("y") > dfn.lit(1.0)
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        0.5
     """
     filter_raw = filter.expr if filter is not None else None
 
@@ -2313,9 +5336,28 @@ def first_value(
             column names or expressions.
         null_treatment: Assign whether to respect or ignore null values.
 
-    For example::
-
-        df.aggregate([], first_value(col("a"), order_by="ts"))
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [10, 20, 30]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.first_value(
+        ...         dfn.col("a")
+        ...     ).alias("v")]
+        ... )
+        >>> result.collect_column("v")[0].as_py()
+        10
+
+        >>> df = ctx.from_pydict({"a": [None, 20, 10]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.first_value(
+        ...         dfn.col("a"),
+        ...         filter=dfn.col("a") > dfn.lit(10),
+        ...         order_by="a",
+        ...         null_treatment=dfn.common.NullTreatment.IGNORE_NULLS,
+        ...     ).alias("v")]
+        ... )
+        >>> result.collect_column("v")[0].as_py()
+        20
     """
     order_by_raw = sort_list_to_raw_sort_list(order_by)
     filter_raw = filter.expr if filter is not None else None
@@ -2350,9 +5392,28 @@ def last_value(
             column names or expressions.
         null_treatment: Assign whether to respect or ignore null values.
 
-    For example::
-
-        df.aggregate([], last_value(col("a"), order_by="ts"))
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [10, 20, 30]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.last_value(
+        ...         dfn.col("a")
+        ...     ).alias("v")]
+        ... )
+        >>> result.collect_column("v")[0].as_py()
+        30
+
+        >>> df = ctx.from_pydict({"a": [None, 20, 10]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.last_value(
+        ...         dfn.col("a"),
+        ...         filter=dfn.col("a") > dfn.lit(10),
+        ...         order_by="a",
+        ...         null_treatment=dfn.common.NullTreatment.IGNORE_NULLS,
+        ...     ).alias("v")]
+        ... )
+        >>> result.collect_column("v")[0].as_py()
+        20
     """
     order_by_raw = sort_list_to_raw_sort_list(order_by)
     filter_raw = filter.expr if filter is not None else None
@@ -2389,9 +5450,27 @@ def nth_value(
             column names or expressions.
         null_treatment: Assign whether to respect or ignore null values.
 
-    For example::
-
-        df.aggregate([], nth_value(col("a"), 2, order_by="ts"))
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [10, 20, 30]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.nth_value(
+        ...         dfn.col("a"), 1
+        ...     ).alias("v")]
+        ... )
+        >>> result.collect_column("v")[0].as_py()
+        10
+
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.nth_value(
+        ...         dfn.col("a"), 1,
+        ...         filter=dfn.col("a") > dfn.lit(10),
+        ...         order_by="a",
+        ...         null_treatment=dfn.common.NullTreatment.IGNORE_NULLS,
+        ...     ).alias("v")]
+        ... )
+        >>> result.collect_column("v")[0].as_py()
+        20
     """
     order_by_raw = sort_list_to_raw_sort_list(order_by)
     filter_raw = filter.expr if filter is not None else None
@@ -2418,6 +5497,25 @@ def bit_and(expression: Expr, filter: Expr | None = None) -> Expr:
     Args:
         expression: Argument to perform bitwise calculation on
         filter: If provided, only compute against rows for which the filter is True
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [7, 3]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.bit_and(
+        ...         dfn.col("a")
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        3
+
+        >>> df = ctx.from_pydict({"a": [7, 5, 3]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.bit_and(
+        ...         dfn.col("a"),
+        ...         filter=dfn.col("a") > dfn.lit(3)
+        ...     ).alias("v")])
+        >>> result.collect_column("v")[0].as_py()
+        5
     """
     filter_raw = filter.expr if filter is not None else None
     return Expr(f.bit_and(expression.expr, filter=filter_raw))
@@ -2434,6 +5532,27 @@ def bit_or(expression: Expr, filter: Expr | None = None) -> Expr:
     Args:
         expression: Argument to perform bitwise calculation on
         filter: If provided, only compute against rows for which the filter is True
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1, 2]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.bit_or(
+        ...         dfn.col("a")
+        ...     ).alias("v")]
+        ... )
+        >>> result.collect_column("v")[0].as_py()
+        3
+
+        >>> df = ctx.from_pydict({"a": [1, 2, 4]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.bit_or(
+        ...         dfn.col("a"),
+        ...         filter=dfn.col("a") > dfn.lit(1)
+        ...     ).alias("v")]
+        ... )
+        >>> result.collect_column("v")[0].as_py()
+        6
     """
     filter_raw = filter.expr if filter is not None else None
     return Expr(f.bit_or(expression.expr, filter=filter_raw))
@@ -2453,6 +5572,27 @@ def bit_xor(
         expression: Argument to perform bitwise calculation on
         distinct: If True, evaluate each unique value of expression only once
         filter: If provided, only compute against rows for which the filter is True
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [5, 3]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.bit_xor(
+        ...         dfn.col("a")
+        ...     ).alias("v")]
+        ... )
+        >>> result.collect_column("v")[0].as_py()
+        6
+
+        >>> df = ctx.from_pydict({"a": [5, 5, 3]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.bit_xor(
+        ...         dfn.col("a"), distinct=True,
+        ...         filter=dfn.col("a") > dfn.lit(3),
+        ...     ).alias("v")]
+        ... )
+        >>> result.collect_column("v")[0].as_py()
+        5
     """
     filter_raw = filter.expr if filter is not None else None
     return Expr(f.bit_xor(expression.expr, distinct=distinct, filter=filter_raw))
@@ -2470,6 +5610,28 @@ def bool_and(expression: Expr, filter: Expr | None = None) -> Expr:
     Args:
         expression: Argument to perform calculation on
         filter: If provided, only compute against rows for which the filter is True
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [True, True, False]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.bool_and(
+        ...         dfn.col("a")
+        ...     ).alias("v")]
+        ... )
+        >>> result.collect_column("v")[0].as_py()
+        False
+
+        >>> df = ctx.from_pydict(
+        ...     {"a": [True, True, False], "b": [1, 2, 3]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.bool_and(
+        ...         dfn.col("a"),
+        ...         filter=dfn.col("b") < dfn.lit(3)
+        ...     ).alias("v")]
+        ... )
+        >>> result.collect_column("v")[0].as_py()
+        True
     """
     filter_raw = filter.expr if filter is not None else None
     return Expr(f.bool_and(expression.expr, filter=filter_raw))
@@ -2487,6 +5649,28 @@ def bool_or(expression: Expr, filter: Expr | None = None) -> Expr:
     Args:
         expression: Argument to perform calculation on
         filter: If provided, only compute against rows for which the filter is True
+
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [False, False, True]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.bool_or(
+        ...         dfn.col("a")
+        ...     ).alias("v")]
+        ... )
+        >>> result.collect_column("v")[0].as_py()
+        True
+
+        >>> df = ctx.from_pydict(
+        ...     {"a": [False, False, True], "b": [1, 2, 3]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.bool_or(
+        ...         dfn.col("a"),
+        ...         filter=dfn.col("b") < dfn.lit(3)
+        ...     ).alias("v")]
+        ... )
+        >>> result.collect_column("v")[0].as_py()
+        False
     """
     filter_raw = filter.expr if filter is not None else None
     return Expr(f.bool_or(expression.expr, filter=filter_raw))
@@ -2529,9 +5713,27 @@ def lead(
         order_by: Set ordering within the window frame. Accepts
             column names or expressions.
 
-    For example::
-
-        lead(col("b"), order_by="ts")
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1, 2, 3]})
+        >>> result = df.select(
+        ...     dfn.col("a"),
+        ...     dfn.functions.lead(
+        ...         dfn.col("a"), shift_offset=1,
+        ...         default_value=0, order_by="a"
+        ...     ).alias("lead"))
+        >>> result.sort(dfn.col("a")).collect_column("lead").to_pylist()
+        [2, 3, 0]
+
+        >>> df = ctx.from_pydict({"g": ["a", "a", "b"], "v": [1, 2, 3]})
+        >>> result = df.select(
+        ...     dfn.col("g"), dfn.col("v"),
+        ...     dfn.functions.lead(
+        ...         dfn.col("v"), shift_offset=1, default_value=0,
+        ...         partition_by=dfn.col("g"), order_by="v",
+        ...     ).alias("lead"))
+        >>> result.sort(dfn.col("g"), dfn.col("v")).collect_column("lead").to_pylist()
+        [2, 0, 0]
     """
     if not isinstance(default_value, pa.Scalar) and default_value is not None:
         default_value = pa.scalar(default_value)
@@ -2584,9 +5786,27 @@ def lag(
         order_by: Set ordering within the window frame. Accepts
             column names or expressions.
 
-    For example::
-
-        lag(col("b"), order_by="ts")
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1, 2, 3]})
+        >>> result = df.select(
+        ...     dfn.col("a"),
+        ...     dfn.functions.lag(
+        ...         dfn.col("a"), shift_offset=1,
+        ...         default_value=0, order_by="a"
+        ...     ).alias("lag"))
+        >>> result.sort(dfn.col("a")).collect_column("lag").to_pylist()
+        [0, 1, 2]
+
+        >>> df = ctx.from_pydict({"g": ["a", "a", "b"], "v": [1, 2, 3]})
+        >>> result = df.select(
+        ...     dfn.col("g"), dfn.col("v"),
+        ...     dfn.functions.lag(
+        ...         dfn.col("v"), shift_offset=1, default_value=0,
+        ...         partition_by=dfn.col("g"), order_by="v",
+        ...     ).alias("lag"))
+        >>> result.sort(dfn.col("g"), dfn.col("v")).collect_column("lag").to_pylist()
+        [0, 1, 0]
     """
     if not isinstance(default_value, pa.Scalar):
         default_value = pa.scalar(default_value)
@@ -2629,9 +5849,26 @@ def row_number(
         order_by: Set ordering within the window frame. Accepts
             column names or expressions.
 
-    For example::
-
-        row_number(order_by="points")
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [10, 20, 30]})
+        >>> result = df.select(
+        ...     dfn.col("a"),
+        ...     dfn.functions.row_number(
+        ...         order_by="a"
+        ...     ).alias("rn"))
+        >>> result.sort(dfn.col("a")).collect_column("rn").to_pylist()
+        [1, 2, 3]
+
+        >>> df = ctx.from_pydict(
+        ...     {"g": ["a", "a", "b", "b"], "v": [1, 2, 3, 4]})
+        >>> result = df.select(
+        ...     dfn.col("g"), dfn.col("v"),
+        ...     dfn.functions.row_number(
+        ...         partition_by=dfn.col("g"), order_by="v",
+        ...     ).alias("rn"))
+        >>> result.sort(dfn.col("g"), dfn.col("v")).collect_column("rn").to_pylist()
+        [1, 2, 1, 2]
     """
     partition_by_raw = expr_list_to_raw_expr_list(partition_by)
     order_by_raw = sort_list_to_raw_sort_list(order_by)
@@ -2673,9 +5910,27 @@ def rank(
         order_by: Set ordering within the window frame. Accepts
             column names or expressions.
 
-    For example::
-
-        rank(order_by="points")
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [10, 10, 20]})
+        >>> result = df.select(
+        ...     dfn.col("a"),
+        ...     dfn.functions.rank(
+        ...         order_by="a"
+        ...     ).alias("rnk")
+        ... )
+        >>> result.sort(dfn.col("a")).collect_column("rnk").to_pylist()
+        [1, 1, 3]
+
+        >>> df = ctx.from_pydict(
+        ...     {"g": ["a", "a", "b", "b"], "v": [1, 1, 2, 3]})
+        >>> result = df.select(
+        ...     dfn.col("g"), dfn.col("v"),
+        ...     dfn.functions.rank(
+        ...         partition_by=dfn.col("g"), order_by="v",
+        ...     ).alias("rnk"))
+        >>> result.sort(dfn.col("g"), dfn.col("v")).collect_column("rnk").to_pylist()
+        [1, 1, 1, 2]
     """
     partition_by_raw = expr_list_to_raw_expr_list(partition_by)
     order_by_raw = sort_list_to_raw_sort_list(order_by)
@@ -2712,9 +5967,26 @@ def dense_rank(
         order_by: Set ordering within the window frame. Accepts
             column names or expressions.
 
-    For example::
-
-        dense_rank(order_by="points")
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [10, 10, 20]})
+        >>> result = df.select(
+        ...     dfn.col("a"),
+        ...     dfn.functions.dense_rank(
+        ...         order_by="a"
+        ...     ).alias("dr"))
+        >>> result.sort(dfn.col("a")).collect_column("dr").to_pylist()
+        [1, 1, 2]
+
+        >>> df = ctx.from_pydict(
+        ...     {"g": ["a", "a", "b", "b"], "v": [1, 1, 2, 3]})
+        >>> result = df.select(
+        ...     dfn.col("g"), dfn.col("v"),
+        ...     dfn.functions.dense_rank(
+        ...         partition_by=dfn.col("g"), order_by="v",
+        ...     ).alias("dr"))
+        >>> result.sort(dfn.col("g"), dfn.col("v")).collect_column("dr").to_pylist()
+        [1, 1, 1, 2]
     """
     partition_by_raw = expr_list_to_raw_expr_list(partition_by)
     order_by_raw = sort_list_to_raw_sort_list(order_by)
@@ -2752,9 +6024,27 @@ def percent_rank(
         order_by: Set ordering within the window frame. Accepts
             column names or expressions.
 
-    For example::
 
-        percent_rank(order_by="points")
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [10, 20, 30]})
+        >>> result = df.select(
+        ...     dfn.col("a"),
+        ...     dfn.functions.percent_rank(
+        ...         order_by="a"
+        ...     ).alias("pr"))
+        >>> result.sort(dfn.col("a")).collect_column("pr").to_pylist()
+        [0.0, 0.5, 1.0]
+
+        >>> df = ctx.from_pydict(
+        ...     {"g": ["a", "a", "a", "b", "b"], "v": [1, 2, 3, 4, 5]})
+        >>> result = df.select(
+        ...     dfn.col("g"), dfn.col("v"),
+        ...     dfn.functions.percent_rank(
+        ...         partition_by=dfn.col("g"), order_by="v",
+        ...     ).alias("pr"))
+        >>> result.sort(dfn.col("g"), dfn.col("v")).collect_column("pr").to_pylist()
+        [0.0, 0.5, 1.0, 0.0, 1.0]
     """
     partition_by_raw = expr_list_to_raw_expr_list(partition_by)
     order_by_raw = sort_list_to_raw_sort_list(order_by)
@@ -2792,9 +6082,27 @@ def cume_dist(
         order_by: Set ordering within the window frame. Accepts
             column names or expressions.
 
-    For example::
-
-        cume_dist(order_by="points")
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [1., 2., 2., 3.]})
+        >>> result = df.select(
+        ...     dfn.col("a"),
+        ...     dfn.functions.cume_dist(
+        ...         order_by="a"
+        ...     ).alias("cd")
+        ... )
+        >>> result.collect_column("cd").to_pylist()
+        [0.25..., 0.75..., 0.75..., 1.0...]
+
+        >>> df = ctx.from_pydict(
+        ...     {"g": ["a", "a", "b", "b"], "v": [1, 2, 3, 4]})
+        >>> result = df.select(
+        ...     dfn.col("g"), dfn.col("v"),
+        ...     dfn.functions.cume_dist(
+        ...         partition_by=dfn.col("g"), order_by="v",
+        ...     ).alias("cd"))
+        >>> result.sort(dfn.col("g"), dfn.col("v")).collect_column("cd").to_pylist()
+        [0.5, 1.0, 0.5, 1.0]
     """
     partition_by_raw = expr_list_to_raw_expr_list(partition_by)
     order_by_raw = sort_list_to_raw_sort_list(order_by)
@@ -2836,9 +6144,26 @@ def ntile(
         order_by: Set ordering within the window frame. Accepts
             column names or expressions.
 
-    For example::
-
-        ntile(3, order_by="points")
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": [10, 20, 30, 40]})
+        >>> result = df.select(
+        ...     dfn.col("a"),
+        ...     dfn.functions.ntile(
+        ...         2, order_by="a"
+        ...     ).alias("nt"))
+        >>> result.sort(dfn.col("a")).collect_column("nt").to_pylist()
+        [1, 1, 2, 2]
+
+        >>> df = ctx.from_pydict(
+        ...     {"g": ["a", "a", "b", "b"], "v": [1, 2, 3, 4]})
+        >>> result = df.select(
+        ...     dfn.col("g"), dfn.col("v"),
+        ...     dfn.functions.ntile(
+        ...         2, partition_by=dfn.col("g"), order_by="v",
+        ...     ).alias("nt"))
+        >>> result.sort(dfn.col("g"), dfn.col("v")).collect_column("nt").to_pylist()
+        [1, 2, 1, 2]
     """
     partition_by_raw = expr_list_to_raw_expr_list(partition_by)
     order_by_raw = sort_list_to_raw_sort_list(order_by)
@@ -2874,9 +6199,24 @@ def string_agg(
         order_by: Set the ordering of the expression to evaluate. Accepts
             column names or expressions.
 
-    For example::
-
-        df.aggregate([], string_agg(col("a"), ",", order_by="b"))
+    Examples:
+        >>> ctx = dfn.SessionContext()
+        >>> df = ctx.from_pydict({"a": ["x", "y", "z"]})
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.string_agg(
+        ...         dfn.col("a"), ",", order_by="a"
+        ...     ).alias("s")])
+        >>> result.collect_column("s")[0].as_py()
+        'x,y,z'
+
+        >>> result = df.aggregate(
+        ...     [], [dfn.functions.string_agg(
+        ...         dfn.col("a"), ",",
+        ...         filter=dfn.col("a") > dfn.lit("x"),
+        ...         order_by="a",
+        ...     ).alias("s")])
+        >>> result.collect_column("s")[0].as_py()
+        'y,z'
     """
     order_by_raw = sort_list_to_raw_sort_list(order_by)
     filter_raw = filter.expr if filter is not None else None
diff --git a/python/datafusion/input/location.py b/python/datafusion/input/location.py
index b804ac18b..779d94d23 100644
--- a/python/datafusion/input/location.py
+++ b/python/datafusion/input/location.py
@@ -46,7 +46,7 @@ def build_table(
         num_rows = 0  # Total number of rows in the file. Used for statistics
         columns = []
         if file_format == "parquet":
-            import pyarrow.parquet as pq
+            import pyarrow.parquet as pq  # noqa: PLC0415
 
             # Read the Parquet metadata
             metadata = pq.read_metadata(input_item)
@@ -61,7 +61,7 @@ def build_table(
             ]
 
         elif format == "csv":
-            import csv
+            import csv  # noqa: PLC0415
 
             # Consume header row and count number of rows for statistics.
             # TODO: Possibly makes sense to have the eager number of rows
diff --git a/python/datafusion/plan.py b/python/datafusion/plan.py
index fb54fd624..c0cfd523f 100644
--- a/python/datafusion/plan.py
+++ b/python/datafusion/plan.py
@@ -24,15 +24,19 @@
 import datafusion._internal as df_internal
 
 if TYPE_CHECKING:
+    import datetime
+
     from datafusion.context import SessionContext
 
 __all__ = [
     "ExecutionPlan",
     "LogicalPlan",
+    "Metric",
+    "MetricsSet",
 ]
 
 
-class LogicalPlan:
+class LogicalPlan:  # noqa: PLW1641
     """Logical Plan.
 
     A `LogicalPlan` is a node in a tree of relational operators (such as
@@ -151,3 +155,176 @@ def to_proto(self) -> bytes:
         Tables created in memory from record batches are currently not supported.
         """
         return self._raw_plan.to_proto()
+
+    def metrics(self) -> MetricsSet | None:
+        """Return metrics for this plan node, or None if this plan has no MetricsSet.
+
+        Some operators (e.g. DataSourceExec) eagerly initialize a MetricsSet
+        when the plan is created, so this may return a set even before
+        execution.  Metric *values* (such as ``output_rows``) are only
+        meaningful after the DataFrame has been executed.
+        """
+        raw = self._raw_plan.metrics()
+        if raw is None:
+            return None
+        return MetricsSet(raw)
+
+    def collect_metrics(self) -> list[tuple[str, MetricsSet]]:
+        """Return runtime statistics for each step of the query execution.
+
+        DataFusion executes a query as a pipeline of operators — for example a
+        data source scan, followed by a filter, followed by a projection. After
+        the DataFrame has been executed (via
+        :py:meth:`~datafusion.DataFrame.collect`,
+        :py:meth:`~datafusion.DataFrame.execute_stream`, etc.), each operator
+        records statistics such as how many rows it produced and how much CPU
+        time it consumed.
+
+        Each entry in the returned list corresponds to one operator that
+        recorded metrics. The first element of the tuple is the operator's
+        description string — the same text shown by
+        :py:meth:`display_indent` — which identifies both the operator type
+        and its key parameters, for example ``"FilterExec: column1@0 > 1"``
+        or ``"DataSourceExec: partitions=1"``.
+
+        Returns:
+            A list of ``(description, MetricsSet)`` tuples ordered from the
+            outermost operator (top of the execution tree) down to the
+            data-source leaves. Only operators that recorded at least one
+            metric are included. Returns an empty list if called before the
+            DataFrame has been executed.
+        """
+        result: list[tuple[str, MetricsSet]] = []
+
+        def _walk(node: ExecutionPlan) -> None:
+            ms = node.metrics()
+            if ms is not None:
+                result.append((node.display(), ms))
+            for child in node.children():
+                _walk(child)
+
+        _walk(self)
+        return result
+
+
+class MetricsSet:
+    """A set of metrics for a single execution plan operator.
+
+    A physical plan operator runs independently across one or more partitions.
+    :py:meth:`metrics` returns the raw per-partition :py:class:`Metric` objects.
+    The convenience properties (:py:attr:`output_rows`, :py:attr:`elapsed_compute`,
+    etc.) automatically sum the named metric across *all* partitions, giving a
+    single aggregate value for the operator as a whole.
+    """
+
+    def __init__(self, raw: df_internal.MetricsSet) -> None:
+        """This constructor should not be called by the end user."""
+        self._raw = raw
+
+    def metrics(self) -> list[Metric]:
+        """Return all individual metrics in this set."""
+        return [Metric(m) for m in self._raw.metrics()]
+
+    @property
+    def output_rows(self) -> int | None:
+        """Sum of output_rows across all partitions."""
+        return self._raw.output_rows()
+
+    @property
+    def elapsed_compute(self) -> int | None:
+        """Total CPU time (in nanoseconds) spent inside this operator's execute loop.
+
+        Summed across all partitions. Returns ``None`` if no ``elapsed_compute``
+        metric was recorded.
+        """
+        return self._raw.elapsed_compute()
+
+    @property
+    def spill_count(self) -> int | None:
+        """Number of times this operator spilled data to disk due to memory pressure.
+
+        This is a count of spill events, not a byte count. Summed across all
+        partitions. Returns ``None`` if no ``spill_count`` metric was recorded.
+        """
+        return self._raw.spill_count()
+
+    @property
+    def spilled_bytes(self) -> int | None:
+        """Sum of spilled_bytes across all partitions."""
+        return self._raw.spilled_bytes()
+
+    @property
+    def spilled_rows(self) -> int | None:
+        """Sum of spilled_rows across all partitions."""
+        return self._raw.spilled_rows()
+
+    def sum_by_name(self, name: str) -> int | None:
+        """Sum the named metric across all partitions.
+
+        Useful for accessing any metric not exposed as a first-class property.
+        Returns ``None`` if no metric with the given name was recorded.
+
+        Args:
+            name: The metric name, e.g. ``"output_rows"`` or ``"elapsed_compute"``.
+        """
+        return self._raw.sum_by_name(name)
+
+    def __repr__(self) -> str:
+        """Return a string representation of the metrics set."""
+        return repr(self._raw)
+
+
+class Metric:
+    """A single execution metric with name, value, partition, and labels."""
+
+    def __init__(self, raw: df_internal.Metric) -> None:
+        """This constructor should not be called by the end user."""
+        self._raw = raw
+
+    @property
+    def name(self) -> str:
+        """The name of this metric (e.g. ``output_rows``)."""
+        return self._raw.name
+
+    @property
+    def value(self) -> int | datetime.datetime | None:
+        """The value of this metric.
+
+        Returns an ``int`` for counters, gauges, and time-based metrics
+        (nanoseconds), a :py:class:`~datetime.datetime` (UTC) for
+        ``start_timestamp`` / ``end_timestamp`` metrics, or ``None``
+        when the value has not been set or is not representable.
+        """
+        return self._raw.value
+
+    @property
+    def value_as_datetime(self) -> datetime.datetime | None:
+        """The value as a UTC :py:class:`~datetime.datetime` for timestamp metrics.
+
+        Returns ``None`` for all non-timestamp metrics and for timestamp
+        metrics whose value has not been set (e.g. before execution).
+        """
+        return self._raw.value_as_datetime
+
+    @property
+    def partition(self) -> int | None:
+        """The 0-based partition index this metric applies to.
+
+        Returns ``None`` for metrics that are not partition-specific (i.e. they
+        apply globally across all partitions of the operator).
+        """
+        return self._raw.partition
+
+    def labels(self) -> dict[str, str]:
+        """Return the labels associated with this metric.
+
+        Labels provide additional context for a metric.  For example::
+
+            metric.labels()
+            # {'output_type': 'final'}
+        """
+        return self._raw.labels()
+
+    def __repr__(self) -> str:
+        """Return a string representation of the metric."""
+        return repr(self._raw)
diff --git a/python/datafusion/substrait.py b/python/datafusion/substrait.py
index 3115238fa..6353ef8cc 100644
--- a/python/datafusion/substrait.py
+++ b/python/datafusion/substrait.py
@@ -25,11 +25,6 @@
 
 from typing import TYPE_CHECKING
 
-try:
-    from warnings import deprecated  # Python 3.13+
-except ImportError:
-    from typing_extensions import deprecated  # Python 3.12
-
 from datafusion.plan import LogicalPlan
 
 from ._internal import substrait as substrait_internal
@@ -88,11 +83,6 @@ def from_json(json: str) -> Plan:
         return Plan(substrait_internal.Plan.from_json(json))
 
 
-@deprecated("Use `Plan` instead.")
-class plan(Plan):  # noqa: N801
-    """See `Plan`."""
-
-
 class Serde:
     """Provides the ``Substrait`` serialization and deserialization."""
 
@@ -158,11 +148,6 @@ def deserialize_bytes(proto_bytes: bytes) -> Plan:
         return Plan(substrait_internal.Serde.deserialize_bytes(proto_bytes))
 
 
-@deprecated("Use `Serde` instead.")
-class serde(Serde):  # noqa: N801
-    """See `Serde` instead."""
-
-
 class Producer:
     """Generates substrait plans from a logical plan."""
 
@@ -184,11 +169,6 @@ def to_substrait_plan(logical_plan: LogicalPlan, ctx: SessionContext) -> Plan:
         )
 
 
-@deprecated("Use `Producer` instead.")
-class producer(Producer):  # noqa: N801
-    """Use `Producer` instead."""
-
-
 class Consumer:
     """Generates a logical plan from a substrait plan."""
 
@@ -206,8 +186,3 @@ def from_substrait_plan(ctx: SessionContext, plan: Plan) -> LogicalPlan:
         return LogicalPlan(
             substrait_internal.Consumer.from_substrait_plan(ctx.ctx, plan.plan_internal)
         )
-
-
-@deprecated("Use `Consumer` instead.")
-class consumer(Consumer):  # noqa: N801
-    """Use `Consumer` instead."""
diff --git a/python/datafusion/user_defined.py b/python/datafusion/user_defined.py
index d4e5302b5..848ab4cee 100644
--- a/python/datafusion/user_defined.py
+++ b/python/datafusion/user_defined.py
@@ -184,7 +184,8 @@ def udf(*args: Any, **kwargs: Any):  # noqa: D417
         This class can be used both as either a function or a decorator.
 
         Usage:
-            - As a function: ``udf(func, input_fields, return_field, volatility, name)``.
+            - As a function: ``udf(func, input_fields, return_field,
+              volatility, name)``.
             - As a decorator: ``@udf(input_fields, return_field, volatility, name)``.
               When used a decorator, do **not** pass ``func`` explicitly.
 
@@ -209,19 +210,32 @@ def udf(*args: Any, **kwargs: Any):  # noqa: D417
             A user-defined function that can be used in SQL expressions,
             data aggregation, or window function calls.
 
-        Example: Using ``udf`` as a function::
+        Examples:
+            Using ``udf`` as a function:
 
-            def double_func(x):
-                return x * 2
-            double_udf = udf(double_func, [pa.int32()], pa.int32(),
-            "volatile", "double_it")
+            >>> import pyarrow.compute as pc
+            >>> from datafusion.user_defined import ScalarUDF
+            >>> def double_func(x):
+            ...     return pc.multiply(x, 2)
+            >>> double_udf = ScalarUDF.udf(
+            ...     double_func, [pa.int64()], pa.int64(),
+            ...     "volatile", "double_it")
 
-        Example: Using ``udf`` as a decorator::
+            Using ``udf`` as a decorator:
 
-            @udf([pa.int32()], pa.int32(), "volatile", "double_it")
-            def double_udf(x):
-                return x * 2
-        """  # noqa: W505 E501
+            >>> @ScalarUDF.udf([pa.int64()], pa.int64(), "volatile")
+            ... def decorator_double_udf(x):
+            ...     return pc.multiply(x, 3)
+
+            Apply to a dataframe:
+
+            >>> ctx = dfn.SessionContext()
+            >>> df = ctx.from_pydict({"x": [1, 2, 3]})
+            >>> df.select(double_udf(col("x")).alias("result")).to_pydict()
+            {'result': [2, 4, 6]}
+            >>> df.select(decorator_double_udf(col("x")).alias("result")).to_pydict()
+            {'result': [3, 6, 9]}
+        """
 
         def _function(
             func: Callable[..., _R],
@@ -458,48 +472,71 @@ def udaf(*args: Any, **kwargs: Any):  # noqa: D417, C901
             - As a decorator: ``@udaf(input_types, return_type, state_type, volatility, name)``.
               When using ``udaf`` as a decorator, do not pass ``accum`` explicitly.
 
-        Function example:
-
         If your :py:class:`Accumulator` can be instantiated with no arguments, you
-        can simply pass it's type as `accum`. If you need to pass additional
-        arguments to it's constructor, you can define a lambda or a factory method.
+        can simply pass its type as ``accum``. If you need to pass additional
+        arguments to its constructor, you can define a lambda or a factory method.
         During runtime the :py:class:`Accumulator` will be constructed for every
-        instance in which this UDAF is used. The following examples are all valid::
-
-            import pyarrow as pa
-            import pyarrow.compute as pc
-
-            class Summarize(Accumulator):
-                def __init__(self, bias: float = 0.0):
-                    self._sum = pa.scalar(bias)
-
-                def state(self) -> list[pa.Scalar]:
-                    return [self._sum]
-
-                def update(self, values: pa.Array) -> None:
-                    self._sum = pa.scalar(self._sum.as_py() + pc.sum(values).as_py())
-
-                def merge(self, states: list[pa.Array]) -> None:
-                    self._sum = pa.scalar(self._sum.as_py() + pc.sum(states[0]).as_py())
-
-                def evaluate(self) -> pa.Scalar:
-                    return self._sum
-
-            def sum_bias_10() -> Summarize:
-                return Summarize(10.0)
-
-            udaf1 = udaf(Summarize, pa.float64(), pa.float64(), [pa.float64()],
-                "immutable")
-            udaf2 = udaf(sum_bias_10, pa.float64(), pa.float64(), [pa.float64()],
-                "immutable")
-            udaf3 = udaf(lambda: Summarize(20.0), pa.float64(), pa.float64(),
-                [pa.float64()], "immutable")
-
-        Decorator example:::
-
-            @udaf(pa.float64(), pa.float64(), [pa.float64()], "immutable")
-            def udf4() -> Summarize:
-                return Summarize(10.0)
+        instance in which this UDAF is used.
+
+        Examples:
+            >>> import pyarrow.compute as pc
+            >>> from datafusion.user_defined import AggregateUDF, Accumulator, udaf
+            >>> class Summarize(Accumulator):
+            ...     def __init__(self, bias: float = 0.0):
+            ...         self._sum = pa.scalar(bias)
+            ...     def state(self):
+            ...         return [self._sum]
+            ...     def update(self, values):
+            ...         self._sum = pa.scalar(
+            ...             self._sum.as_py() + pc.sum(values).as_py())
+            ...     def merge(self, states):
+            ...         self._sum = pa.scalar(
+            ...             self._sum.as_py() + pc.sum(states[0]).as_py())
+            ...     def evaluate(self):
+            ...         return self._sum
+
+            Using ``udaf`` as a function:
+
+            >>> udaf1 = AggregateUDF.udaf(
+            ...     Summarize, pa.float64(), pa.float64(),
+            ...     [pa.float64()], "immutable")
+
+            Wrapping ``udaf`` with a function:
+
+            >>> def sum_bias_10() -> Summarize:
+            ...     return Summarize(10.0)
+            >>> udaf2 = udaf(sum_bias_10, pa.float64(), pa.float64(), [pa.float64()],
+            ...     "immutable")
+
+            Using ``udaf`` with lambda:
+
+            >>> udaf3 = udaf(lambda: Summarize(20.0), pa.float64(), pa.float64(),
+            ...     [pa.float64()], "immutable")
+
+            Using ``udaf`` as a decorator:
+
+            >>> @AggregateUDF.udaf(
+            ...     pa.float64(), pa.float64(),
+            ...     [pa.float64()], "immutable")
+            ... def udaf4():
+            ...     return Summarize(10.0)
+
+            Apply to a dataframe:
+
+            >>> ctx = dfn.SessionContext()
+            >>> df = ctx.from_pydict({"a": [1.0, 2.0, 3.0]})
+            >>> df.aggregate([], [udaf1(col("a")).alias("total")]).collect_column(
+            ...     "total")[0].as_py()
+            6.0
+            >>> df.aggregate([], [udaf2(col("a")).alias("total")]).collect_column(
+            ...     "total")[0].as_py()
+            16.0
+            >>> df.aggregate([], [udaf3(col("a")).alias("total")]).collect_column(
+            ...     "total")[0].as_py()
+            26.0
+            >>> df.aggregate([], [udaf4(col("a")).alias("total")]).collect_column(
+            ...     "total")[0].as_py()
+            16.0
 
         Args:
             accum: The accumulator python function. Only needed when calling as a
@@ -583,11 +620,11 @@ def from_pycapsule(func: AggregateUDFExportable | _PyCapsule) -> AggregateUDF:
         AggregateUDF that is exported via the FFI bindings.
         """
         if _is_pycapsule(func):
-            aggregate = cast(AggregateUDF, object.__new__(AggregateUDF))
+            aggregate = cast("AggregateUDF", object.__new__(AggregateUDF))
             aggregate._udaf = df_internal.AggregateUDF.from_pycapsule(func)
             return aggregate
 
-        capsule = cast(AggregateUDFExportable, func)
+        capsule = cast("AggregateUDFExportable", func)
         name = str(capsule.__class__)
         return AggregateUDF(
             name=name,
@@ -834,31 +871,44 @@ def udwf(*args: Any, **kwargs: Any):  # noqa: D417
             - As a decorator: ``@udwf(input_types, return_type, volatility, name)``.
               When using ``udwf`` as a decorator, do not pass ``func`` explicitly.
 
-        Function example::
-
-            import pyarrow as pa
-
-            class BiasedNumbers(WindowEvaluator):
-                def __init__(self, start: int = 0) -> None:
-                    self.start = start
-
-                def evaluate_all(self, values: list[pa.Array],
-                    num_rows: int) -> pa.Array:
-                    return pa.array([self.start + i for i in range(num_rows)])
-
-            def bias_10() -> BiasedNumbers:
-                return BiasedNumbers(10)
-
-            udwf1 = udwf(BiasedNumbers, pa.int64(), pa.int64(), "immutable")
-            udwf2 = udwf(bias_10, pa.int64(), pa.int64(), "immutable")
-            udwf3 = udwf(lambda: BiasedNumbers(20), pa.int64(), pa.int64(), "immutable")
-
-
-        Decorator example::
-
-            @udwf(pa.int64(), pa.int64(), "immutable")
-            def biased_numbers() -> BiasedNumbers:
-                return BiasedNumbers(10)
+        Examples:
+            >>> from datafusion.user_defined import WindowUDF, WindowEvaluator, udwf
+            >>> class BiasedNumbers(WindowEvaluator):
+            ...     def __init__(self, start: int = 0):
+            ...         self.start = start
+            ...     def evaluate_all(self, values, num_rows):
+            ...         return pa.array(
+            ...             [self.start + i for i in range(num_rows)])
+
+            Using ``udwf`` as a function:
+
+            >>> udwf1 = WindowUDF.udwf(
+            ...     BiasedNumbers, pa.int64(), pa.int64(), "immutable")
+            >>> def bias_10() -> BiasedNumbers:
+            ...    return BiasedNumbers(10)
+            >>> udwf2 = udwf(bias_10, pa.int64(), pa.int64(), "immutable")
+            >>> udwf3 = udwf(
+            ...     lambda: BiasedNumbers(20), pa.int64(), pa.int64(), "immutable"
+            ... )
+
+            Using ``udwf`` as a decorator:
+
+            >>> @WindowUDF.udwf(pa.int64(), pa.int64(), "immutable")
+            ... def biased_numbers():
+            ...     return BiasedNumbers(10)
+
+            Apply to a dataframe:
+
+            >>> ctx = dfn.SessionContext()
+            >>> df = ctx.from_pydict({"a": [10, 20, 30]})
+            >>> df.select(udwf1(col("a")).alias("result")).to_pydict()
+            {'result': [0, 1, 2]}
+            >>> df.select(udwf2(col("a")).alias("result")).to_pydict()
+            {'result': [10, 11, 12]}
+            >>> df.select(udwf3(col("a")).alias("result")).to_pydict()
+            {'result': [20, 21, 22]}
+            >>> df.select(biased_numbers(col("a")).alias("result")).to_pydict()
+            {'result': [10, 11, 12]}
 
         Args:
             func: Only needed when calling as a function. Skip this argument when
diff --git a/python/tests/test_aggregation.py b/python/tests/test_aggregation.py
index f595127fa..240332848 100644
--- a/python/tests/test_aggregation.py
+++ b/python/tests/test_aggregation.py
@@ -141,14 +141,14 @@ def test_aggregation_stats(df, agg_expr, calc_expected):
         ),
         (
             f.approx_percentile_cont_with_weight(column("b"), lit(0.6), 0.5),
-            pa.array([6], type=pa.float64()),
+            pa.array([4], type=pa.float64()),
             False,
         ),
         (
             f.approx_percentile_cont_with_weight(
                 column("b").sort(ascending=False, nulls_first=False), lit(0.6), 0.5
             ),
-            pa.array([6], type=pa.float64()),
+            pa.array([4], type=pa.float64()),
             False,
         ),
         (
diff --git a/python/tests/test_catalog.py b/python/tests/test_catalog.py
index 71c08da26..c89da36bf 100644
--- a/python/tests/test_catalog.py
+++ b/python/tests/test_catalog.py
@@ -120,6 +120,12 @@ def register_catalog(
         self.catalogs[name] = catalog
 
 
+class CustomTableProviderFactory(dfn.catalog.TableProviderFactory):
+    def create(self, cmd: dfn.expr.CreateExternalTable):
+        assert cmd.name() == "test_table_factory"
+        return create_dataset()
+
+
 def test_python_catalog_provider_list(ctx: SessionContext):
     ctx.register_catalog_provider_list(CustomCatalogProviderList())
 
@@ -248,7 +254,7 @@ def test_exception_not_mangled(ctx: SessionContext):
 
     schema.register_table("test_table", create_dataset())
 
-    with pytest.raises(ValueError, match="^test_table is not an acceptable name$"):
+    with pytest.raises(ValueError, match=r"^test_table is not an acceptable name$"):
         ctx.sql(f"select * from {catalog_name}.{schema_name}.test_table")
 
 
@@ -314,3 +320,24 @@ def my_table_function_udtf() -> Table:
     assert len(result[0]) == 1
     assert len(result[0][0]) == 1
     assert result[0][0][0].as_py() == 3
+
+
+def test_register_python_table_provider_factory(ctx: SessionContext):
+    ctx.register_table_factory("CUSTOM_FACTORY", CustomTableProviderFactory())
+
+    ctx.sql("""
+        CREATE EXTERNAL TABLE test_table_factory
+        STORED AS CUSTOM_FACTORY
+        LOCATION foo;
+    """).collect()
+
+    result = ctx.sql("SELECT * FROM test_table_factory;").collect()
+
+    expect = [
+        pa.RecordBatch.from_arrays(
+            [pa.array([1, 2, 3]), pa.array([4, 5, 6])],
+            names=["a", "b"],
+        )
+    ]
+
+    assert result == expect
diff --git a/python/tests/test_context.py b/python/tests/test_context.py
index 5853f9feb..13c05a9e6 100644
--- a/python/tests/test_context.py
+++ b/python/tests/test_context.py
@@ -31,6 +31,7 @@
     Table,
     column,
     literal,
+    udf,
 )
 
 
@@ -351,6 +352,125 @@ def test_deregister_table(ctx, database):
     assert public.names() == {"csv1", "csv2"}
 
 
+def test_deregister_udf():
+    ctx = SessionContext()
+
+    is_null = udf(
+        lambda x: x.is_null(),
+        [pa.float64()],
+        pa.bool_(),
+        volatility="immutable",
+        name="my_is_null",
+    )
+    ctx.register_udf(is_null)
+
+    # Verify it works
+    df = ctx.from_pydict({"a": [1.0, None]})
+    ctx.register_table("t", df.into_view())
+    result = ctx.sql("SELECT my_is_null(a) FROM t").collect()
+    assert result[0].column(0) == pa.array([False, True])
+
+    # Deregister and verify it's gone
+    ctx.deregister_udf("my_is_null")
+    with pytest.raises(ValueError):
+        ctx.sql("SELECT my_is_null(a) FROM t").collect()
+
+
+def test_deregister_udaf():
+    import pyarrow.compute as pc
+
+    ctx = SessionContext()
+    from datafusion import Accumulator, udaf
+
+    class MySum(Accumulator):
+        def __init__(self):
+            self._sum = 0.0
+
+        def update(self, values: pa.Array) -> None:
+            self._sum += pc.sum(values).as_py()
+
+        def merge(self, states: list[pa.Array]) -> None:
+            self._sum += pc.sum(states[0]).as_py()
+
+        def state(self) -> list:
+            return [self._sum]
+
+        def evaluate(self) -> pa.Scalar:
+            return self._sum
+
+    my_sum = udaf(
+        MySum,
+        [pa.float64()],
+        pa.float64(),
+        [pa.float64()],
+        volatility="immutable",
+        name="my_sum",
+    )
+    ctx.register_udaf(my_sum)
+    df = ctx.from_pydict({"a": [1.0, 2.0, 3.0]})
+    ctx.register_table("t", df.into_view())
+
+    result = ctx.sql("SELECT my_sum(a) FROM t").collect()
+    assert result[0].column(0) == pa.array([6.0])
+
+    ctx.deregister_udaf("my_sum")
+    with pytest.raises(ValueError):
+        ctx.sql("SELECT my_sum(a) FROM t").collect()
+
+
+def test_deregister_udwf():
+    ctx = SessionContext()
+    from datafusion import udwf
+    from datafusion.user_defined import WindowEvaluator
+
+    class MyRowNumber(WindowEvaluator):
+        def __init__(self):
+            self._row = 0
+
+        def evaluate_all(self, values, num_rows):
+            return pa.array(list(range(1, num_rows + 1)), type=pa.uint64())
+
+    my_row_number = udwf(
+        MyRowNumber,
+        [pa.float64()],
+        pa.uint64(),
+        volatility="immutable",
+        name="my_row_number",
+    )
+    ctx.register_udwf(my_row_number)
+    df = ctx.from_pydict({"a": [1.0, 2.0, 3.0]})
+    ctx.register_table("t", df.into_view())
+
+    result = ctx.sql("SELECT my_row_number(a) OVER () FROM t").collect()
+    assert result[0].column(0) == pa.array([1, 2, 3], type=pa.uint64())
+
+    ctx.deregister_udwf("my_row_number")
+    with pytest.raises(ValueError):
+        ctx.sql("SELECT my_row_number(a) OVER () FROM t").collect()
+
+
+def test_deregister_udtf():
+    import pyarrow.dataset as ds
+
+    ctx = SessionContext()
+    from datafusion import Table, udtf
+
+    class MyTable:
+        def __call__(self):
+            batch = pa.RecordBatch.from_pydict({"x": [1, 2, 3]})
+            return Table(ds.dataset([batch]))
+
+    my_table = udtf(MyTable(), "my_table")
+    ctx.register_udtf(my_table)
+
+    result = ctx.sql("SELECT * FROM my_table()").collect()
+    assert result[0].column(0) == pa.array([1, 2, 3])
+
+    ctx.deregister_udtf("my_table")
+    with pytest.raises(ValueError):
+        ctx.sql("SELECT * FROM my_table()").collect()
+
+
 def test_register_table_from_dataframe(ctx):
     df = ctx.from_pydict({"a": [1, 2]})
     ctx.register_table("df_tbl", df)
@@ -551,6 +671,61 @@ def test_table_not_found(ctx):
         ctx.table(f"not-found-{uuid4()}")
 
 
+def test_session_start_time(ctx):
+    import datetime
+    import re
+
+    st = ctx.session_start_time()
+    assert isinstance(st, str)
+    # Truncate nanoseconds to microseconds for Python 3.10 compat
+    st = re.sub(r"(\.\d{6})\d+", r"\1", st)
+    dt = datetime.datetime.fromisoformat(st)
+    assert dt.isoformat()
+
+
+def test_enable_ident_normalization(ctx):
+    assert ctx.enable_ident_normalization() is True
+    ctx.sql("SET datafusion.sql_parser.enable_ident_normalization = false")
+    assert ctx.enable_ident_normalization() is False
+
+
+def test_parse_sql_expr(ctx):
+    from datafusion.common import DFSchema
+
+    schema = DFSchema.empty()
+    expr = ctx.parse_sql_expr("1 + 2", schema)
+    assert str(expr) == "Expr(Int64(1) + Int64(2))"
+
+
+def test_execute_logical_plan(ctx):
+    df = ctx.from_pydict({"a": [1, 2, 3]})
+    plan = df.logical_plan()
+    df2 = ctx.execute_logical_plan(plan)
+    result = df2.collect()
+    assert result[0].column(0) == pa.array([1, 2, 3])
+
+
+def test_refresh_catalogs(ctx):
+    ctx.refresh_catalogs()
+
+
+def test_remove_optimizer_rule(ctx):
+    assert ctx.remove_optimizer_rule("push_down_filter") is True
+    assert ctx.remove_optimizer_rule("nonexistent_rule") is False
+
+
+def test_table_provider(ctx):
+    batch = pa.RecordBatch.from_pydict({"x": [10, 20, 30]})
+    ctx.register_record_batches("provider_test", [[batch]])
+    tbl = ctx.table_provider("provider_test")
+    assert tbl.schema == pa.schema([("x", pa.int64())])
+
+
+def test_table_provider_not_found(ctx):
+    with pytest.raises(KeyError):
+        ctx.table_provider("nonexistent_table")
+
+
 def test_read_json(ctx):
     path = pathlib.Path(__file__).parent.resolve()
 
@@ -668,6 +843,68 @@ def test_read_avro(ctx):
     assert avro_df is not None
 
 
+def test_read_arrow(ctx, tmp_path):
+    # Write an Arrow IPC file, then read it back
+    table = pa.table({"a": [1, 2, 3], "b": ["x", "y", "z"]})
+    arrow_path = tmp_path / "test.arrow"
+    with pa.ipc.new_file(str(arrow_path), table.schema) as writer:
+        writer.write_table(table)
+
+    df = ctx.read_arrow(str(arrow_path))
+    result = df.collect()
+    assert result[0].column(0) == pa.array([1, 2, 3])
+    assert result[0].column(1) == pa.array(["x", "y", "z"])
+
+    # Also verify pathlib.Path works
+    df = ctx.read_arrow(arrow_path)
+    result = df.collect()
+    assert result[0].column(0) == pa.array([1, 2, 3])
+
+
+def test_read_empty(ctx):
+    df = ctx.read_empty()
+    result = df.collect()
+    assert len(result) == 1
+    assert result[0].num_columns == 0
+
+    df = ctx.empty_table()
+    result = df.collect()
+    assert len(result) == 1
+    assert result[0].num_columns == 0
+
+
+def test_register_arrow(ctx, tmp_path):
+    # Write an Arrow IPC file, then register and query it
+    table = pa.table({"x": [10, 20, 30]})
+    arrow_path = tmp_path / "test.arrow"
+    with pa.ipc.new_file(str(arrow_path), table.schema) as writer:
+        writer.write_table(table)
+
+    ctx.register_arrow("arrow_tbl", str(arrow_path))
+    result = ctx.sql("SELECT * FROM arrow_tbl").collect()
+    assert result[0].column(0) == pa.array([10, 20, 30])
+
+    # Also verify pathlib.Path works
+    ctx.register_arrow("arrow_tbl_path", arrow_path)
+    result = ctx.sql("SELECT * FROM arrow_tbl_path").collect()
+    assert result[0].column(0) == pa.array([10, 20, 30])
+
+
+def test_register_batch(ctx):
+    batch = pa.RecordBatch.from_pydict({"a": [1, 2, 3], "b": [4, 5, 6]})
+    ctx.register_batch("batch_tbl", batch)
+    result = ctx.sql("SELECT * FROM batch_tbl").collect()
+    assert result[0].column(0) == pa.array([1, 2, 3])
+    assert result[0].column(1) == pa.array([4, 5, 6])
+
+
+def test_register_batch_empty(ctx):
+    batch = pa.RecordBatch.from_pydict({"a": pa.array([], type=pa.int64())})
+    ctx.register_batch("empty_batch_tbl", batch)
+    result = ctx.sql("SELECT * FROM empty_batch_tbl").collect()
+    assert result[0].num_rows == 0
+
+
 def test_create_sql_options():
     SQLOptions()
 
@@ -759,7 +996,7 @@ def read_csv_with_options_inner(
     group_dir.mkdir(exist_ok=True)
 
     csv_path = group_dir / "test.csv"
-    csv_path.write_text(csv_content)
+    csv_path.write_text(csv_content, newline="\n")
 
     ctx = SessionContext()
 
diff --git a/python/tests/test_dataframe.py b/python/tests/test_dataframe.py
index 71abe2925..091fa9b56 100644
--- a/python/tests/test_dataframe.py
+++ b/python/tests/test_dataframe.py
@@ -29,6 +29,7 @@
 import pytest
 from datafusion import (
     DataFrame,
+    ExplainFormat,
     InsertOp,
     ParquetColumnOptions,
     ParquetWriterOptions,
@@ -295,10 +296,17 @@ def test_drop_quoted_columns():
     ctx = SessionContext()
     batch = pa.RecordBatch.from_arrays([pa.array([1, 2, 3])], names=["ID_For_Students"])
     df = ctx.create_dataframe([[batch]])
-
-    # Both should work
+    # here we must quote to match the original column name
     assert df.drop('"ID_For_Students"').schema().names == []
-    assert df.drop("ID_For_Students").schema().names == []
+
+    batch = pa.RecordBatch.from_arrays(
+        [pa.array([1, 2, 3]), pa.array([4, 5, 6])], names=["a", "b"]
+    )
+    df = ctx.create_dataframe([[batch]])
+    # with a lower case column, both 'a' and '"a"' work
+    assert df.drop("a").schema().names == ["b"]
+    df = ctx.create_dataframe([[batch]])
+    assert df.drop('"a"').schema().names == ["b"]
 
 
 def test_select_mixed_expr_string(df):
@@ -404,6 +412,16 @@ def test_show_empty(df, capsys):
     assert "DataFrame has no rows" in captured.out
 
 
+def test_show_on_explain(ctx, capsys):
+    ctx.sql("explain select 1").show()
+    captured = capsys.readouterr()
+    assert "1 as Int64(1)" in captured.out
+
+    ctx.sql("explain analyze select 1").show()
+    captured = capsys.readouterr()
+    assert "1 as Int64(1)" in captured.out
+
+
 def test_sort(df):
     df = df.sort(column("b").sort(ascending=False))
 
@@ -2790,7 +2808,7 @@ def test_write_parquet_with_options_encoding(tmp_path, encoding, data_types, res
 def test_write_parquet_with_options_unsupported_encoding(df, tmp_path, encoding):
     """Test that unsupported Parquet encodings do not work."""
     # BaseException is used since this throws a Rust panic: https://github.com/PyO3/pyo3/issues/3519
-    with pytest.raises(BaseException, match="Encoding .*? is not supported"):
+    with pytest.raises(BaseException, match=r"Encoding .*? is not supported"):
         df.write_parquet_with_options(tmp_path, ParquetWriterOptions(encoding=encoding))
 
 
@@ -3562,3 +3580,263 @@ def test_read_parquet_file_sort_order(tmp_path, file_sort_order):
     pa.parquet.write_table(table, path)
     df = ctx.read_parquet(path, file_sort_order=file_sort_order)
     assert df.collect()[0].column(0).to_pylist() == [1, 2]
+
+
+@pytest.mark.parametrize(
+    ("df1_data", "df2_data", "method", "kwargs", "expected_a", "expected_b"),
+    [
+        pytest.param(
+            {"a": [1, 2, 3, 1], "b": [10, 20, 30, 10]},
+            {"a": [1, 2], "b": [10, 20]},
+            "except_all",
+            {"distinct": True},
+            [3],
+            [30],
+            id="except_all(distinct=True): removes matching rows and deduplicates",
+        ),
+        pytest.param(
+            {"a": [1, 2, 3, 1], "b": [10, 20, 30, 10]},
+            {"a": [1, 4], "b": [10, 40]},
+            "intersect",
+            {"distinct": True},
+            [1],
+            [10],
+            id="intersect(distinct=True): keeps common rows and deduplicates",
+        ),
+        pytest.param(
+            {"a": [1], "b": [10]},
+            {"b": [20], "a": [2]},  # reversed column order tests matching by name
+            "union_by_name",
+            {},
+            [1, 2],
+            [10, 20],
+            id="union_by_name: matches columns by name not position",
+        ),
+    ],
+)
+def test_set_operations_distinct(
+    df1_data, df2_data, method, kwargs, expected_a, expected_b
+):
+    ctx = SessionContext()
+    df1 = ctx.from_pydict(df1_data)
+    df2 = ctx.from_pydict(df2_data)
+    result = (
+        getattr(df1, method)(df2, **kwargs)
+        .sort(column("a").sort(ascending=True))
+        .collect()[0]
+    )
+    assert result.column(0).to_pylist() == expected_a
+    assert result.column(1).to_pylist() == expected_b
+
+
+def test_union_by_name_distinct():
+    ctx = SessionContext()
+    df1 = ctx.from_pydict({"a": [1, 1], "b": [10, 10]})
+    df2 = ctx.from_pydict({"b": [10], "a": [1]})
+    result = df1.union_by_name(df2, distinct=True).collect()[0]
+    assert result.column(0).to_pylist() == [1]
+    assert result.column(1).to_pylist() == [10]
+
+
+def test_column_qualified():
+    """DataFrame.column() returns a qualified column expression."""
+    ctx = SessionContext()
+    df = ctx.from_pydict({"a": [1, 2], "b": [3, 4]})
+    expr = df.column("a")
+    result = df.select(expr).collect()[0]
+    assert result.column(0).to_pylist() == [1, 2]
+
+
+def test_column_not_found():
+    ctx = SessionContext()
+    df = ctx.from_pydict({"a": [1]})
+    with pytest.raises(Exception, match="not found"):
+        df.column("z")
+
+
+def test_column_ambiguous():
+    """After a join, duplicate column names that cannot be resolved raise an error."""
+    ctx = SessionContext()
+    left = ctx.from_pydict({"id": [1, 2], "val": [10, 20]})
+    right = ctx.from_pydict({"id": [1, 2], "val": [30, 40]})
+    joined = left.join(right, on="id", how="inner")
+    with pytest.raises(Exception, match="not found"):
+        joined.column("val")
+
+
+def test_column_after_join():
+    """Qualified column works for non-ambiguous columns after a join."""
+    ctx = SessionContext()
+    left = ctx.from_pydict({"id": [1, 2], "x": [10, 20]})
+    right = ctx.from_pydict({"id": [1, 2], "y": [30, 40]})
+    joined = left.join(right, on="id", how="inner")
+    expr = joined.column("y")
+    result = joined.select("id", expr).sort("id").collect()[0]
+    assert result.column(0).to_pylist() == [1, 2]
+    assert result.column(1).to_pylist() == [30, 40]
+
+
+def test_col_join_disambiguate():
+    """Use col() to disambiguate and select columns after a join."""
+    ctx = SessionContext()
+    df1 = ctx.from_pydict({"foo": [1, 2, 3], "bar": [5, 6, 7]})
+    df2 = ctx.from_pydict({"foo": [1, 2, 3], "baz": [8, 9, 10]})
+    joined = df1.join_on(df2, df1.col("foo") == df2.col("foo"), how="inner")
+    result = (
+        joined.select(df1.col("foo"), df1.col("bar"), df2.col("baz"))
+        .sort(df1.col("foo"))
+        .to_pydict()
+    )
+    assert result["bar"] == [5, 6, 7]
+    assert result["baz"] == [8, 9, 10]
+
+
+def test_find_qualified_columns():
+    ctx = SessionContext()
+    df = ctx.from_pydict({"a": [1, 2], "b": [3, 4], "c": [5, 6]})
+    exprs = df.find_qualified_columns("a", "c")
+    assert len(exprs) == 2
+    result = df.select(*exprs).collect()[0]
+    assert result.column(0).to_pylist() == [1, 2]
+    assert result.column(1).to_pylist() == [5, 6]
+
+
+def test_find_qualified_columns_not_found():
+    ctx = SessionContext()
+    df = ctx.from_pydict({"a": [1]})
+    with pytest.raises(Exception, match="not found"):
+        df.find_qualified_columns("a", "z")
+
+
+def test_distinct_on():
+    ctx = SessionContext()
+    df = ctx.from_pydict({"a": [1, 1, 2, 2], "b": [10, 20, 30, 40]})
+    result = (
+        df.distinct_on(
+            [column("a")],
+            [column("a"), column("b")],
+            [column("a").sort(ascending=True), column("b").sort(ascending=True)],
+        )
+        .sort(column("a").sort(ascending=True))
+        .collect()[0]
+    )
+    # Keeps the first row per group (smallest b per a)
+    assert result.column(0).to_pylist() == [1, 2]
+    assert result.column(1).to_pylist() == [10, 30]
+
+
+@pytest.mark.parametrize(
+    ("input_values", "expected"),
+    [
+        ([3, 1, 2], [1, 2, 3]),
+        ([1, 2, 3], [1, 2, 3]),
+        ([3, None, 1, 2], [1, 2, 3, None]),
+    ],
+)
+def test_sort_by(input_values, expected):
+    """sort_by always sorts ascending with nulls last regardless of input order."""
+    ctx = SessionContext()
+    df = ctx.from_pydict({"a": input_values})
+    result = df.sort_by(column("a")).collect()[0]
+    assert result.column(0).to_pylist() == expected
+
+
+@pytest.mark.parametrize(
+    ("fmt", "verbose", "analyze", "expected_substring"),
+    [
+        pytest.param(None, False, False, None, id="default format"),
+        pytest.param(ExplainFormat.TREE, False, False, "---", id="tree format"),
+        pytest.param(
+            ExplainFormat.INDENT, True, True, None, id="indent verbose+analyze"
+        ),
+        pytest.param(ExplainFormat.PGJSON, False, False, '"Plan"', id="pgjson format"),
+        pytest.param(
+            ExplainFormat.GRAPHVIZ, False, False, "digraph", id="graphviz format"
+        ),
+    ],
+)
+def test_explain_with_format(capsys, fmt, verbose, analyze, expected_substring):
+    ctx = SessionContext()
+    df = ctx.from_pydict({"a": [1]})
+    df.explain(verbose=verbose, analyze=analyze, format=fmt)
+    captured = capsys.readouterr()
+    assert "plan_type" in captured.out
+    if expected_substring is not None:
+        assert expected_substring in captured.out
+
+
+@pytest.mark.parametrize(
+    ("window_exprs", "expected_columns"),
+    [
+        pytest.param(
+            lambda: [
+                f.row_number(partition_by=[column("b")], order_by=[column("a")]).alias(
+                    "rn"
+                ),
+            ],
+            {"rn": [1, 2, 1]},
+            id="single window expression",
+        ),
+        pytest.param(
+            lambda: [
+                f.row_number(partition_by=[column("b")], order_by=[column("a")]).alias(
+                    "rn"
+                ),
+                f.rank(partition_by=[column("b")], order_by=[column("a")]).alias("rnk"),
+            ],
+            {"rn": [1, 2, 1], "rnk": [1, 2, 1]},
+            id="multiple window expressions",
+        ),
+    ],
+)
+def test_window(window_exprs, expected_columns):
+    ctx = SessionContext()
+    df = ctx.from_pydict({"a": [1, 2, 3], "b": ["x", "x", "y"]})
+    result = (
+        df.window(*window_exprs()).sort(column("a").sort(ascending=True)).collect()[0]
+    )
+    for col_name, expected_values in expected_columns.items():
+        assert col_name in result.schema.names
+        assert (
+            result.column(result.schema.get_field_index(col_name)).to_pylist()
+            == expected_values
+        )
+
+
+@pytest.mark.parametrize(
+    ("input_data", "recursions", "expected_a"),
+    [
+        pytest.param(
+            {"a": [[1, 2], [3]], "b": ["x", "y"]},
+            None,
+            [1, 2, 3],
+            id="basic unnest without recursions",
+        ),
+        pytest.param(
+            {"a": [[1, 2], [3]], "b": ["x", "y"]},
+            [("a", "a", 1)],
+            [1, 2, 3],
+            id="explicit depth 1 matches basic unnest",
+        ),
+        pytest.param(
+            {"a": [[[1, 2], [3]], [[4]]], "b": ["x", "y"]},
+            [("a", "a", 1)],
+            [[1, 2], [3], [4]],
+            id="depth 1 on nested lists keeps inner lists",
+        ),
+        pytest.param(
+            {"a": [[[1, 2], [3]], [[4]]], "b": ["x", "y"]},
+            [("a", "a", 2)],
+            [1, 2, 3, 4],
+            id="depth 2 fully flattens nested lists",
+        ),
+    ],
+)
+def test_unnest_columns_with_recursions(input_data, recursions, expected_a):
+    ctx = SessionContext()
+    df = ctx.from_pydict(input_data)
+    kwargs = {}
+    if recursions is not None:
+        kwargs["recursions"] = recursions
+    result = df.unnest_columns("a", **kwargs).collect()[0]
+    assert result.column(0).to_pylist() == expected_a
diff --git a/python/tests/test_expr.py b/python/tests/test_expr.py
index 92251827b..d046eb48c 100644
--- a/python/tests/test_expr.py
+++ b/python/tests/test_expr.py
@@ -153,8 +153,8 @@ def test_relational_expr(test_ctx):
 
     batch = pa.RecordBatch.from_arrays(
         [
-            pa.array([1, 2, 3]),
-            pa.array(["alpha", "beta", "gamma"], type=pa.string_view()),
+            pa.array([1, 2, 3, None]),
+            pa.array(["alpha", "beta", "gamma", None], type=pa.string_view()),
         ],
         names=["a", "b"],
     )
@@ -171,6 +171,10 @@ def test_relational_expr(test_ctx):
     assert df.filter(col("b") != "beta").count() == 2
 
     assert df.filter(col("a") == "beta").count() == 0
+    assert df.filter(col("a") == None).count() == 1  # noqa: E711
+    assert df.filter(col("a") != None).count() == 3  # noqa: E711
+    assert df.filter(col("b") == None).count() == 1  # noqa: E711
+    assert df.filter(col("b") != None).count() == 3  # noqa: E711
 
 
 def test_expr_to_variant():
@@ -319,27 +323,6 @@ def test_expr_getitem() -> None:
     assert array_values == [2, 5, None, None]
 
 
-def test_display_name_deprecation():
-    import warnings
-
-    expr = col("foo")
-    with warnings.catch_warnings(record=True) as w:
-        # Cause all warnings to always be triggered
-        warnings.simplefilter("always")
-
-        # should trigger warning
-        name = expr.display_name()
-
-        # Verify some things
-        assert len(w) == 1
-        assert issubclass(w[-1].category, DeprecationWarning)
-        assert "deprecated" in str(w[-1].message)
-
-    # returns appropriate result
-    assert name == expr.schema_name()
-    assert name == "foo"
-
-
 @pytest.fixture
 def df():
     ctx = SessionContext()
@@ -857,20 +840,20 @@ def test_alias_with_metadata(df):
         pytest.param(
             col("d").list_distinct(),
             pa.array(
-                [[-1, 0, 1], [5, 10, 15, 20], [], None], type=pa.list_(pa.int64())
+                [[-1, 1, 0], [5, 10, 15, 20], [], None], type=pa.list_(pa.int64())
             ),
             id="list_distinct",
         ),
         pytest.param(
             col("d").array_distinct(),
             pa.array(
-                [[-1, 0, 1], [5, 10, 15, 20], [], None], type=pa.list_(pa.int64())
+                [[-1, 1, 0], [5, 10, 15, 20], [], None], type=pa.list_(pa.int64())
             ),
             id="array_distinct",
         ),
         pytest.param(
             col("d").cardinality(),
-            pa.array([3, 4, None, None], type=pa.uint64()),
+            pa.array([3, 4, 0, None], type=pa.uint64()),
             id="cardinality",
         ),
         pytest.param(
diff --git a/python/tests/test_functions.py b/python/tests/test_functions.py
index 7b3332ed7..11e94af1c 100644
--- a/python/tests/test_functions.py
+++ b/python/tests/test_functions.py
@@ -15,13 +15,14 @@
 # specific language governing permissions and limitations
 # under the License.
 import math
-from datetime import datetime, timezone
+from datetime import date, datetime, time, timezone
 
 import numpy as np
 import pyarrow as pa
 import pytest
-from datafusion import SessionContext, column, literal, string_literal
+from datafusion import SessionContext, column, literal
 from datafusion import functions as f
+from datafusion.expr import GroupingSet
 
 np.seterr(invalid="ignore")
 
@@ -303,19 +304,19 @@ def py_flatten(arr):
             lambda data: [np.concatenate([arr, arr]) for arr in data],
         ),
         (
-            lambda col: f.array_dims(col),
+            f.array_dims,
             lambda data: [[len(r)] for r in data],
         ),
         (
-            lambda col: f.array_distinct(col),
-            lambda data: [list(set(r)) for r in data],
+            lambda col: f.array_sort(f.array_distinct(col)),
+            lambda data: [sorted(set(r)) for r in data],
         ),
         (
-            lambda col: f.list_distinct(col),
-            lambda data: [list(set(r)) for r in data],
+            lambda col: f.list_sort(f.list_distinct(col)),
+            lambda data: [sorted(set(r)) for r in data],
         ),
         (
-            lambda col: f.list_dims(col),
+            f.list_dims,
             lambda data: [[len(r)] for r in data],
         ),
         (
@@ -323,11 +324,15 @@ def py_flatten(arr):
             lambda data: [r[0] for r in data],
         ),
         (
-            lambda col: f.array_empty(col),
+            f.array_empty,
             lambda data: [len(r) == 0 for r in data],
         ),
         (
-            lambda col: f.empty(col),
+            f.empty,
+            lambda data: [len(r) == 0 for r in data],
+        ),
+        (
+            f.list_empty,
             lambda data: [len(r) == 0 for r in data],
         ),
         (
@@ -343,29 +348,65 @@ def py_flatten(arr):
             lambda data: [r[0] for r in data],
         ),
         (
-            lambda col: f.array_length(col),
+            f.array_length,
             lambda data: [len(r) for r in data],
         ),
         (
-            lambda col: f.list_length(col),
+            f.list_length,
             lambda data: [len(r) for r in data],
         ),
         (
             lambda col: f.array_has(col, literal(1.0)),
             lambda data: [1.0 in r for r in data],
         ),
+        (
+            lambda col: f.list_has(col, literal(1.0)),
+            lambda data: [1.0 in r for r in data],
+        ),
+        (
+            lambda col: f.array_contains(col, literal(1.0)),
+            lambda data: [1.0 in r for r in data],
+        ),
+        (
+            lambda col: f.list_contains(col, literal(1.0)),
+            lambda data: [1.0 in r for r in data],
+        ),
         (
             lambda col: f.array_has_all(
                 col, f.make_array(*[literal(v) for v in [1.0, 3.0, 5.0]])
             ),
             lambda data: [np.all([v in r for v in [1.0, 3.0, 5.0]]) for r in data],
         ),
+        (
+            lambda col: f.list_has_all(
+                col, f.make_array(*[literal(v) for v in [1.0, 3.0, 5.0]])
+            ),
+            lambda data: [np.all([v in r for v in [1.0, 3.0, 5.0]]) for r in data],
+        ),
         (
             lambda col: f.array_has_any(
                 col, f.make_array(*[literal(v) for v in [1.0, 3.0, 5.0]])
             ),
             lambda data: [np.any([v in r for v in [1.0, 3.0, 5.0]]) for r in data],
         ),
+        (
+            lambda col: f.list_has_any(
+                col, f.make_array(*[literal(v) for v in [1.0, 3.0, 5.0]])
+            ),
+            lambda data: [np.any([v in r for v in [1.0, 3.0, 5.0]]) for r in data],
+        ),
+        (
+            lambda col: f.arrays_overlap(
+                col, f.make_array(*[literal(v) for v in [1.0, 3.0, 5.0]])
+            ),
+            lambda data: [np.any([v in r for v in [1.0, 3.0, 5.0]]) for r in data],
+        ),
+        (
+            lambda col: f.list_overlap(
+                col, f.make_array(*[literal(v) for v in [1.0, 3.0, 5.0]])
+            ),
+            lambda data: [np.any([v in r for v in [1.0, 3.0, 5.0]]) for r in data],
+        ),
         (
             lambda col: f.array_position(col, literal(1.0)),
             lambda data: [py_indexof(r, 1.0) for r in data],
@@ -391,11 +432,11 @@ def py_flatten(arr):
             lambda data: [[i + 1 for i, _v in enumerate(r) if _v == 1.0] for r in data],
         ),
         (
-            lambda col: f.array_ndims(col),
+            f.array_ndims,
             lambda data: [np.array(r).ndim for r in data],
         ),
         (
-            lambda col: f.list_ndims(col),
+            f.list_ndims,
             lambda data: [np.array(r).ndim for r in data],
         ),
         (
@@ -415,11 +456,19 @@ def py_flatten(arr):
             lambda data: [np.insert(arr, 0, 99.0) for arr in data],
         ),
         (
-            lambda col: f.array_pop_back(col),
+            f.array_pop_back,
             lambda data: [arr[:-1] for arr in data],
         ),
         (
-            lambda col: f.array_pop_front(col),
+            f.list_pop_back,
+            lambda data: [arr[:-1] for arr in data],
+        ),
+        (
+            f.array_pop_front,
+            lambda data: [arr[1:] for arr in data],
+        ),
+        (
+            f.list_pop_front,
             lambda data: [arr[1:] for arr in data],
         ),
         (
@@ -519,19 +568,19 @@ def py_flatten(arr):
             lambda data: [arr[1:4:2] for arr in data],
         ),
         (
-            lambda col: f.array_intersect(col, literal([3.0, 4.0])),
+            lambda col: f.array_sort(f.array_intersect(col, literal([3.0, 4.0]))),
             lambda data: [np.intersect1d(arr, [3.0, 4.0]) for arr in data],
         ),
         (
-            lambda col: f.list_intersect(col, literal([3.0, 4.0])),
+            lambda col: f.list_sort(f.list_intersect(col, literal([3.0, 4.0]))),
             lambda data: [np.intersect1d(arr, [3.0, 4.0]) for arr in data],
         ),
         (
-            lambda col: f.array_union(col, literal([12.0, 999.0])),
+            lambda col: f.array_sort(f.array_union(col, literal([12.0, 999.0]))),
             lambda data: [np.union1d(arr, [12.0, 999.0]) for arr in data],
         ),
         (
-            lambda col: f.list_union(col, literal([12.0, 999.0])),
+            lambda col: f.list_sort(f.list_union(col, literal([12.0, 999.0]))),
             lambda data: [np.union1d(arr, [12.0, 999.0]) for arr in data],
         ),
         (
@@ -668,6 +717,106 @@ def test_array_function_obj_tests(stmt, py_expr):
         assert a == b
 
 
+@pytest.mark.parametrize(
+    ("args", "expected"),
+    [
+        pytest.param(
+            ({"x": 1, "y": 2},),
+            [("x", 1), ("y", 2)],
+            id="dict",
+        ),
+        pytest.param(
+            ({"x": literal(1), "y": literal(2)},),
+            [("x", 1), ("y", 2)],
+            id="dict_with_exprs",
+        ),
+        pytest.param(
+            ("x", 1, "y", 2),
+            [("x", 1), ("y", 2)],
+            id="variadic_pairs",
+        ),
+        pytest.param(
+            (literal("x"), literal(1), literal("y"), literal(2)),
+            [("x", 1), ("y", 2)],
+            id="variadic_with_exprs",
+        ),
+    ],
+)
+def test_make_map(args, expected):
+    ctx = SessionContext()
+    batch = pa.RecordBatch.from_arrays([pa.array([1])], names=["a"])
+    df = ctx.create_dataframe([[batch]])
+
+    result = df.select(f.make_map(*args).alias("m")).collect()[0].column(0)
+    assert result[0].as_py() == expected
+
+
+def test_make_map_from_two_lists():
+    ctx = SessionContext()
+    batch = pa.RecordBatch.from_arrays(
+        [
+            pa.array(["k1", "k2", "k3"]),
+            pa.array([10, 20, 30]),
+        ],
+        names=["keys", "vals"],
+    )
+    df = ctx.create_dataframe([[batch]])
+
+    m = f.make_map([column("keys")], [column("vals")])
+    result = df.select(f.map_keys(m).alias("k")).collect()[0].column(0)
+    assert result.to_pylist() == [["k1"], ["k2"], ["k3"]]
+
+    result = df.select(f.map_values(m).alias("v")).collect()[0].column(0)
+    assert result.to_pylist() == [[10], [20], [30]]
+
+
+def test_make_map_odd_args_raises():
+    with pytest.raises(ValueError, match="make_map expects"):
+        f.make_map("x", 1, "y")
+
+
+def test_make_map_mismatched_lengths():
+    with pytest.raises(ValueError, match="same length"):
+        f.make_map(["a", "b"], [1])
+
+
+@pytest.mark.parametrize(
+    ("func", "expected"),
+    [
+        pytest.param(f.map_keys, ["x", "y"], id="map_keys"),
+        pytest.param(f.map_values, [1, 2], id="map_values"),
+        pytest.param(
+            lambda m: f.map_extract(m, literal("x")),
+            [1],
+            id="map_extract",
+        ),
+        pytest.param(
+            lambda m: f.map_extract(m, literal("z")),
+            [None],
+            id="map_extract_missing_key",
+        ),
+        pytest.param(
+            f.map_entries,
+            [{"key": "x", "value": 1}, {"key": "y", "value": 2}],
+            id="map_entries",
+        ),
+        pytest.param(
+            lambda m: f.element_at(m, literal("y")),
+            [2],
+            id="element_at",
+        ),
+    ],
+)
+def test_map_functions(func, expected):
+    ctx = SessionContext()
+    batch = pa.RecordBatch.from_arrays([pa.array([1])], names=["a"])
+    df = ctx.create_dataframe([[batch]])
+
+    m = f.make_map({"x": 1, "y": 2})
+    result = df.select(func(m).alias("out")).collect()[0].column(0)
+    assert result[0].as_py() == expected
+
+
 @pytest.mark.parametrize(
     ("function", "expected_result"),
     [
@@ -697,7 +846,10 @@ def test_array_function_obj_tests(stmt, py_expr):
             f.initcap(column("c")),
             pa.array(["Hello ", " World ", " !"], type=pa.string_view()),
         ),
-        (f.left(column("a"), literal(3)), pa.array(["Hel", "Wor", "!"])),
+        (
+            f.left(column("a"), literal(3)),
+            pa.array(["Hel", "Wor", "!"], type=pa.string_view()),
+        ),
         (f.length(column("c")), pa.array([6, 7, 2], type=pa.int32())),
         (f.lower(column("a")), pa.array(["hello", "world", "!"])),
         (f.lpad(column("a"), literal(7)), pa.array(["  Hello", "  World", "      !"])),
@@ -726,7 +878,10 @@ def test_array_function_obj_tests(stmt, py_expr):
             pa.array(["He??o", "Wor?d", "!"]),
         ),
         (f.reverse(column("a")), pa.array(["olleH", "dlroW", "!"])),
-        (f.right(column("a"), literal(4)), pa.array(["ello", "orld", "!"])),
+        (
+            f.right(column("a"), literal(4)),
+            pa.array(["ello", "orld", "!"], type=pa.string_view()),
+        ),
         (
             f.rpad(column("a"), literal(8)),
             pa.array(["Hello   ", "World   ", "!       "]),
@@ -739,6 +894,7 @@ def test_array_function_obj_tests(stmt, py_expr):
             f.split_part(column("a"), literal("l"), literal(1)),
             pa.array(["He", "Wor", "!"]),
         ),
+        (f.contains(column("a"), literal("ell")), pa.array([True, False, False])),
         (f.starts_with(column("a"), literal("Wor")), pa.array([False, True, False])),
         (f.strpos(column("a"), literal("o")), pa.array([5, 2, 0], type=pa.int32())),
         (
@@ -952,6 +1108,12 @@ def test_temporal_functions(df):
         f.to_timestamp_nanos(
             literal("2023-09-07 05:06:14.523952000"), literal("%Y-%m-%d %H:%M:%S.%f")
         ),
+        f.to_time(literal("12:30:45")),
+        f.to_time(literal("12-30-45"), literal("%H-%M-%S")),
+        f.to_date(literal("2017-05-31")),
+        f.to_date(literal("2017-05-31"), literal("%Y-%m-%d")),
+        f.to_local_time(column("d")),
+        f.to_char(column("d"), literal("%d-%m-%Y")),
     )
     result = df.collect()
     assert len(result) == 1
@@ -964,7 +1126,7 @@ def test_temporal_functions(df):
             datetime(2027, 6, 1, tzinfo=DEFAULT_TZ),
             datetime(2020, 7, 1, tzinfo=DEFAULT_TZ),
         ],
-        type=pa.timestamp("ns", tz=DEFAULT_TZ),
+        type=pa.timestamp("us", tz=DEFAULT_TZ),
     )
     assert result.column(3) == pa.array(
         [
@@ -972,7 +1134,7 @@ def test_temporal_functions(df):
             datetime(2027, 6, 26, tzinfo=DEFAULT_TZ),
             datetime(2020, 7, 2, tzinfo=DEFAULT_TZ),
         ],
-        type=pa.timestamp("ns", tz=DEFAULT_TZ),
+        type=pa.timestamp("us", tz=DEFAULT_TZ),
     )
     assert result.column(4) == pa.array(
         [
@@ -1026,15 +1188,112 @@ def test_temporal_functions(df):
         [datetime(2023, 9, 7, 5, 6, 14, 523952, tzinfo=DEFAULT_TZ)] * 3,
         type=pa.timestamp("ns"),
     )
+    assert result.column(17) == pa.array(
+        [time(12, 30, 45)] * 3,
+        type=pa.time64("ns"),
+    )
+    assert result.column(18) == pa.array(
+        [time(12, 30, 45)] * 3,
+        type=pa.time64("ns"),
+    )
+    assert result.column(19) == pa.array(
+        [date(2017, 5, 31)] * 3,
+        type=pa.date32(),
+    )
+    assert result.column(20) == pa.array(
+        [date(2017, 5, 31)] * 3,
+        type=pa.date32(),
+    )
+    assert result.column(21) == pa.array(
+        [
+            datetime(2022, 12, 31, tzinfo=DEFAULT_TZ),
+            datetime(2027, 6, 26, tzinfo=DEFAULT_TZ),
+            datetime(2020, 7, 2, tzinfo=DEFAULT_TZ),
+        ],
+        type=pa.timestamp("us"),
+    )
+
+    assert result.column(22) == pa.array(
+        [
+            "31-12-2022",
+            "26-06-2027",
+            "02-07-2020",
+        ],
+        type=pa.string(),
+    )
+
+
+def test_to_time_invalid_input(df):
+    with pytest.raises(Exception, match=r"Error parsing 'not-a-time' as time"):
+        df.select(f.to_time(literal("not-a-time"))).collect()
+
+
+def test_to_time_mismatched_formatter(df):
+    with pytest.raises(Exception, match=r"Error parsing '12:30:45' as time"):
+        df.select(f.to_time(literal("12:30:45"), literal("%Y-%m-%d"))).collect()
+
+
+def test_to_date_invalid_input(df):
+    with pytest.raises(Exception, match=r"Date32"):
+        df.select(f.to_date(literal("not-a-date"))).collect()
+
+
+def test_temporal_formatter_requires_expr():
+    with pytest.raises(AttributeError, match="'str' object has no attribute 'expr'"):
+        f.to_time(literal("12:30:45"), "not-an-expr")
+
+
+def test_today_returns_date32(df):
+    result = df.select(f.today().alias("today")).collect()[0]
+    assert result.column(0).type == pa.date32()
+
+
+def test_today_alias_matches_current_date(df):
+    result = df.select(
+        f.current_date().alias("current_date"),
+        f.today().alias("today"),
+    ).collect()[0]
+
+    assert result.column(0) == result.column(1)
+
+
+def test_current_timestamp_alias_matches_now(df):
+    result = df.select(
+        f.now().alias("now"),
+        f.current_timestamp().alias("current_timestamp"),
+    ).collect()[0]
+
+    assert result.column(0) == result.column(1)
+
+
+def test_date_format_alias_matches_to_char(df):
+    result = df.select(
+        f.to_char(
+            f.to_timestamp(literal("2021-01-01T00:00:00")), literal("%Y/%m/%d")
+        ).alias("to_char"),
+        f.date_format(
+            f.to_timestamp(literal("2021-01-01T00:00:00")), literal("%Y/%m/%d")
+        ).alias("date_format"),
+    ).collect()[0]
+
+    assert result.column(0) == result.column(1)
+    assert result.column(0)[0].as_py() == "2021/01/01"
+
+
+def test_make_time(df):
+    ctx = SessionContext()
+    df_time = ctx.from_pydict({"h": [12], "m": [30], "s": [0]})
+    result = df_time.select(
+        f.make_time(column("h"), column("m"), column("s")).alias("t")
+    ).collect()[0]
+
+    assert result.column(0)[0].as_py() == time(12, 30)
 
 
 def test_arrow_cast(df):
     df = df.select(
-        # we use `string_literal` to return utf8 instead of `literal` which returns
-        # utf8view because datafusion.arrow_cast expects a utf8 instead of utf8view
-        # https://github.com/apache/datafusion/blob/86740bfd3d9831d6b7c1d0e1bf4a21d91598a0ac/datafusion/functions/src/core/arrow_cast.rs#L179
-        f.arrow_cast(column("b"), string_literal("Float64")).alias("b_as_float"),
-        f.arrow_cast(column("b"), string_literal("Int32")).alias("b_as_int"),
+        f.arrow_cast(column("b"), "Float64").alias("b_as_float"),
+        f.arrow_cast(column("b"), "Int32").alias("b_as_int"),
     )
     result = df.collect()
     assert len(result) == 1
@@ -1044,6 +1303,19 @@ def test_arrow_cast(df):
     assert result.column(1) == pa.array([4, 5, 6], type=pa.int32())
 
 
+def test_arrow_cast_with_pyarrow_type(df):
+    df = df.select(
+        f.arrow_cast(column("b"), pa.float64()).alias("b_as_float"),
+        f.arrow_cast(column("b"), pa.int32()).alias("b_as_int"),
+        f.arrow_cast(column("b"), pa.string()).alias("b_as_str"),
+    )
+    result = df.collect()[0]
+
+    assert result.column(0) == pa.array([4.0, 5.0, 6.0], type=pa.float64())
+    assert result.column(1) == pa.array([4, 5, 6], type=pa.int32())
+    assert result.column(2) == pa.array(["4", "5", "6"], type=pa.string())
+
+
 def test_case(df):
     df = df.select(
         f.case(column("b")).when(literal(4), literal(10)).otherwise(literal(8)),
@@ -1297,62 +1569,533 @@ def test_alias_with_metadata(df):
     assert df.schema().field("b").metadata == {b"key": b"value"}
 
 
-def test_coalesce(df):
-    # Create a DataFrame with null values
+@pytest.fixture
+def df_with_nulls():
     ctx = SessionContext()
+    # Rows:
+    #   0: both values present
+    #   1: a/d/h/k null, b/e/i/l present
+    #   2: a/d/h/k present, b/e/i/l null
+    #   3: all null
     batch = pa.RecordBatch.from_arrays(
         [
-            pa.array(["Hello", None, "!"]),  # string column with null
-            pa.array([4, None, 6]),  # integer column with null
-            pa.array(["hello ", None, " !"]),  # string column with null
+            pa.array([1, None, 3, None], type=pa.int64()),
+            pa.array([5, 10, None, None], type=pa.int64()),
+            pa.array([20, 30, 40, None], type=pa.int64()),
+            pa.array(["apple", None, "cherry", None], type=pa.utf8()),
+            pa.array(["banana", "date", None, None], type=pa.utf8()),
+            pa.array(["x", "y", "z", None], type=pa.utf8()),
             pa.array(
                 [
-                    datetime(2022, 12, 31, tzinfo=DEFAULT_TZ),
+                    datetime(2020, 1, 1, tzinfo=DEFAULT_TZ),
                     None,
-                    datetime(2020, 7, 2, tzinfo=DEFAULT_TZ),
-                ]
-            ),  # datetime with null
-            pa.array([False, None, True]),  # boolean column with null
+                    datetime(2025, 6, 15, tzinfo=DEFAULT_TZ),
+                    None,
+                ],
+                type=pa.timestamp("us", tz="UTC"),
+            ),
+            pa.array(
+                [
+                    datetime(2022, 7, 4, tzinfo=DEFAULT_TZ),
+                    datetime(2023, 12, 25, tzinfo=DEFAULT_TZ),
+                    None,
+                    None,
+                ],
+                type=pa.timestamp("us", tz="UTC"),
+            ),
+            pa.array([True, None, False, None], type=pa.bool_()),
+            pa.array([False, True, None, None], type=pa.bool_()),
         ],
-        names=["a", "b", "c", "d", "e"],
+        names=["a", "b", "c", "d", "e", "g", "h", "i", "k", "l"],
     )
-    df_with_nulls = ctx.create_dataframe([[batch]])
+    return ctx.create_dataframe([[batch]])
 
-    # Test coalesce with different data types
-    result_df = df_with_nulls.select(
-        f.coalesce(column("a"), literal("default")).alias("a_coalesced"),
-        f.coalesce(column("b"), literal(0)).alias("b_coalesced"),
-        f.coalesce(column("c"), literal("default")).alias("c_coalesced"),
-        f.coalesce(column("d"), literal(datetime(2000, 1, 1, tzinfo=DEFAULT_TZ))).alias(
-            "d_coalesced"
+
+@pytest.mark.parametrize(
+    ("expr", "expected"),
+    [
+        pytest.param(
+            f.greatest(column("a"), column("b")),
+            pa.array([5, 10, 3, None], type=pa.int64()),
+            id="greatest_int",
         ),
-        f.coalesce(column("e"), literal(value=False)).alias("e_coalesced"),
-    )
+        pytest.param(
+            f.greatest(column("d"), column("e")),
+            pa.array(["banana", "date", "cherry", None], type=pa.utf8()),
+            id="greatest_str",
+        ),
+        pytest.param(
+            f.least(column("a"), column("b")),
+            pa.array([1, 10, 3, None], type=pa.int64()),
+            id="least_int",
+        ),
+        pytest.param(
+            f.least(column("d"), column("e")),
+            pa.array(["apple", "date", "cherry", None], type=pa.utf8()),
+            id="least_str",
+        ),
+        pytest.param(
+            f.coalesce(column("a"), column("b"), column("c")),
+            pa.array([1, 10, 3, None], type=pa.int64()),
+            id="coalesce_int",
+        ),
+        pytest.param(
+            f.coalesce(column("d"), column("e"), column("g")),
+            pa.array(["apple", "date", "cherry", None], type=pa.utf8()),
+            id="coalesce_str",
+        ),
+        pytest.param(
+            f.nvl(column("a"), column("c")),
+            pa.array([1, 30, 3, None], type=pa.int64()),
+            id="nvl_int",
+        ),
+        pytest.param(
+            f.nvl(column("d"), column("g")),
+            pa.array(["apple", "y", "cherry", None], type=pa.utf8()),
+            id="nvl_str",
+        ),
+        pytest.param(
+            f.ifnull(column("a"), column("c")),
+            pa.array([1, 30, 3, None], type=pa.int64()),
+            id="ifnull_int",
+        ),
+        pytest.param(
+            f.ifnull(column("d"), column("g")),
+            pa.array(["apple", "y", "cherry", None], type=pa.utf8()),
+            id="ifnull_str",
+        ),
+        pytest.param(
+            f.nvl2(column("a"), column("b"), column("c")),
+            pa.array([5, 30, None, None], type=pa.int64()),
+            id="nvl2_int",
+        ),
+        pytest.param(
+            f.nvl2(column("d"), column("e"), column("g")),
+            pa.array(["banana", "y", None, None], type=pa.utf8()),
+            id="nvl2_str",
+        ),
+        pytest.param(
+            f.nullif(column("a"), column("b")),
+            pa.array([1, None, 3, None], type=pa.int64()),
+            id="nullif_int",
+        ),
+        pytest.param(
+            f.nullif(column("d"), column("e")),
+            pa.array(["apple", None, "cherry", None], type=pa.utf8()),
+            id="nullif_str",
+        ),
+        pytest.param(
+            f.nullif(column("a"), literal(1)),
+            pa.array([None, None, 3, None], type=pa.int64()),
+            id="nullif_equal_values",
+        ),
+        pytest.param(
+            f.greatest(column("a"), column("b"), column("c")),
+            pa.array([20, 30, 40, None], type=pa.int64()),
+            id="greatest_variadic",
+        ),
+        pytest.param(
+            f.least(column("a"), column("b"), column("c")),
+            pa.array([1, 10, 3, None], type=pa.int64()),
+            id="least_variadic",
+        ),
+        pytest.param(
+            f.greatest(column("a"), literal(2)),
+            pa.array([2, 2, 3, 2], type=pa.int64()),
+            id="greatest_literal",
+        ),
+        pytest.param(
+            f.least(column("a"), literal(2)),
+            pa.array([1, 2, 2, 2], type=pa.int64()),
+            id="least_literal",
+        ),
+        pytest.param(
+            f.coalesce(column("a"), literal(0)),
+            pa.array([1, 0, 3, 0], type=pa.int64()),
+            id="coalesce_literal_int",
+        ),
+        pytest.param(
+            f.coalesce(column("d"), literal("default")),
+            pa.array(["apple", "default", "cherry", "default"], type=pa.string_view()),
+            id="coalesce_literal_str",
+        ),
+        pytest.param(
+            f.nvl(column("a"), literal(99)),
+            pa.array([1, 99, 3, 99], type=pa.int64()),
+            id="nvl_literal",
+        ),
+        pytest.param(
+            f.ifnull(column("d"), literal("unknown")),
+            pa.array(["apple", "unknown", "cherry", "unknown"], type=pa.string_view()),
+            id="ifnull_literal",
+        ),
+        pytest.param(
+            f.nvl2(column("a"), literal(1), literal(0)),
+            pa.array([1, 0, 1, 0], type=pa.int64()),
+            id="nvl2_literal",
+        ),
+        pytest.param(
+            f.greatest(column("h"), column("i")),
+            pa.array(
+                [
+                    datetime(2022, 7, 4, tzinfo=DEFAULT_TZ),
+                    datetime(2023, 12, 25, tzinfo=DEFAULT_TZ),
+                    datetime(2025, 6, 15, tzinfo=DEFAULT_TZ),
+                    None,
+                ],
+                type=pa.timestamp("us", tz="UTC"),
+            ),
+            id="greatest_datetime",
+        ),
+        pytest.param(
+            f.least(column("h"), column("i")),
+            pa.array(
+                [
+                    datetime(2020, 1, 1, tzinfo=DEFAULT_TZ),
+                    datetime(2023, 12, 25, tzinfo=DEFAULT_TZ),
+                    datetime(2025, 6, 15, tzinfo=DEFAULT_TZ),
+                    None,
+                ],
+                type=pa.timestamp("us", tz="UTC"),
+            ),
+            id="least_datetime",
+        ),
+        pytest.param(
+            f.coalesce(column("h"), column("i")),
+            pa.array(
+                [
+                    datetime(2020, 1, 1, tzinfo=DEFAULT_TZ),
+                    datetime(2023, 12, 25, tzinfo=DEFAULT_TZ),
+                    datetime(2025, 6, 15, tzinfo=DEFAULT_TZ),
+                    None,
+                ],
+                type=pa.timestamp("us", tz="UTC"),
+            ),
+            id="coalesce_datetime",
+        ),
+        pytest.param(
+            f.nvl(column("k"), column("l")),
+            pa.array([True, True, False, None], type=pa.bool_()),
+            id="nvl_bool",
+        ),
+        pytest.param(
+            f.coalesce(column("k"), column("l")),
+            pa.array([True, True, False, None], type=pa.bool_()),
+            id="coalesce_bool",
+        ),
+        pytest.param(
+            f.nvl2(column("k"), column("k"), column("l")),
+            pa.array([True, True, False, None], type=pa.bool_()),
+            id="nvl2_bool",
+        ),
+        pytest.param(
+            f.coalesce(
+                column("h"),
+                literal(datetime(2000, 1, 1, tzinfo=DEFAULT_TZ)),
+            ),
+            pa.array(
+                [
+                    datetime(2020, 1, 1, tzinfo=DEFAULT_TZ),
+                    datetime(2000, 1, 1, tzinfo=DEFAULT_TZ),
+                    datetime(2025, 6, 15, tzinfo=DEFAULT_TZ),
+                    datetime(2000, 1, 1, tzinfo=DEFAULT_TZ),
+                ],
+                type=pa.timestamp("us", tz="UTC"),
+            ),
+            id="coalesce_literal_datetime",
+        ),
+        pytest.param(
+            f.coalesce(column("k"), literal(value=False)),
+            pa.array([True, False, False, False], type=pa.bool_()),
+            id="coalesce_literal_bool",
+        ),
+        pytest.param(
+            f.coalesce(column("a"), literal(None), literal(99)),
+            pa.array([1, 99, 3, 99], type=pa.int64()),
+            id="coalesce_skip_null_literal",
+        ),
+    ],
+)
+def test_conditional_functions(df_with_nulls, expr, expected):
+    result = df_with_nulls.select(expr.alias("result")).collect()[0]
+    assert result.column(0) == expected
 
-    result = result_df.collect()[0]
 
-    # Verify results
-    assert result.column(0) == pa.array(
-        ["Hello", "default", "!"], type=pa.string_view()
-    )
-    assert result.column(1) == pa.array([4, 0, 6], type=pa.int64())
-    assert result.column(2) == pa.array(
-        ["hello ", "default", " !"], type=pa.string_view()
+@pytest.mark.parametrize(
+    ("func", "filter_expr", "expected"),
+    [
+        (f.percentile_cont, None, 3.0),
+        (f.percentile_cont, column("a") > literal(1.0), 3.5),
+        (f.quantile_cont, None, 3.0),
+    ],
+    ids=["no_filter", "with_filter", "quantile_cont_alias"],
+)
+def test_percentile_cont(func, filter_expr, expected):
+    ctx = SessionContext()
+    df = ctx.from_pydict({"a": [1.0, 2.0, 3.0, 4.0, 5.0]})
+    result = df.aggregate(
+        [], [func(column("a"), 0.5, filter=filter_expr).alias("v")]
+    ).collect()[0]
+    assert result.column(0)[0].as_py() == expected
+
+
+@pytest.mark.parametrize(
+    ("grouping_set_expr", "expected_grouping", "expected_sums"),
+    [
+        (GroupingSet.rollup(column("a")), [0, 0, 1], [30, 30, 60]),
+        (GroupingSet.cube(column("a")), [0, 0, 1], [30, 30, 60]),
+        (GroupingSet.rollup("a"), [0, 0, 1], [30, 30, 60]),
+        (GroupingSet.cube("a"), [0, 0, 1], [30, 30, 60]),
+    ],
+    ids=["rollup", "cube", "rollup_str", "cube_str"],
+)
+def test_grouping_set_single_column(
+    grouping_set_expr, expected_grouping, expected_sums
+):
+    ctx = SessionContext()
+    df = ctx.from_pydict({"a": [1, 1, 2], "b": [10, 20, 30]})
+    result = df.aggregate(
+        [grouping_set_expr],
+        [f.sum(column("b")).alias("s"), f.grouping(column("a"))],
+    ).sort(column("a").sort(ascending=True, nulls_first=False))
+    batches = result.collect()
+    g = pa.concat_arrays([b.column(2) for b in batches]).to_pylist()
+    s = pa.concat_arrays([b.column("s") for b in batches]).to_pylist()
+    assert g == expected_grouping
+    assert s == expected_sums
+
+
+@pytest.mark.parametrize(
+    ("grouping_set_expr", "expected_rows"),
+    [
+        # rollup(a, b) => (a,b), (a), () => 3 + 2 + 1 = 6
+        (GroupingSet.rollup(column("a"), column("b")), 6),
+        # cube(a, b) => (a,b), (a), (b), () => 3 + 2 + 2 + 1 = 8
+        (GroupingSet.cube(column("a"), column("b")), 8),
+        (GroupingSet.rollup("a", "b"), 6),
+        (GroupingSet.cube("a", "b"), 8),
+    ],
+    ids=["rollup", "cube", "rollup_str", "cube_str"],
+)
+def test_grouping_set_multi_column(grouping_set_expr, expected_rows):
+    ctx = SessionContext()
+    df = ctx.from_pydict({"a": [1, 1, 2], "b": ["x", "y", "x"], "c": [10, 20, 30]})
+    result = df.aggregate(
+        [grouping_set_expr],
+        [f.sum(column("c")).alias("s")],
     )
-    assert result.column(3).to_pylist() == [
-        datetime(2022, 12, 31, tzinfo=DEFAULT_TZ),
-        datetime(2000, 1, 1, tzinfo=DEFAULT_TZ),
-        datetime(2020, 7, 2, tzinfo=DEFAULT_TZ),
-    ]
-    assert result.column(4) == pa.array([False, False, True], type=pa.bool_())
+    total_rows = sum(b.num_rows for b in result.collect())
+    assert total_rows == expected_rows
 
-    # Test multiple arguments
-    result_df = df_with_nulls.select(
-        f.coalesce(column("a"), literal(None), literal("fallback")).alias(
-            "multi_coalesce"
-        )
+
+@pytest.mark.parametrize(
+    "grouping_set_expr",
+    [
+        GroupingSet.grouping_sets([column("a")], [column("b")]),
+        GroupingSet.grouping_sets(["a"], ["b"]),
+    ],
+    ids=["expr", "str"],
+)
+def test_grouping_sets_explicit(grouping_set_expr):
+    # Each row's grouping() value tells you which columns are aggregated across.
+    ctx = SessionContext()
+    df = ctx.from_pydict({"a": ["x", "x", "y"], "b": ["m", "n", "m"], "c": [1, 2, 3]})
+    result = df.aggregate(
+        [grouping_set_expr],
+        [
+            f.sum(column("c")).alias("s"),
+            f.grouping(column("a")),
+            f.grouping(column("b")),
+        ],
+    ).sort(
+        column("a").sort(ascending=True, nulls_first=False),
+        column("b").sort(ascending=True, nulls_first=False),
     )
-    result = result_df.collect()[0]
-    assert result.column(0) == pa.array(
-        ["Hello", "fallback", "!"], type=pa.string_view()
+    batches = result.collect()
+    ga = pa.concat_arrays([b.column(3) for b in batches]).to_pylist()
+    gb = pa.concat_arrays([b.column(4) for b in batches]).to_pylist()
+    # Rows grouped by (a): ga=0 (a is a key), gb=1 (b is aggregated across)
+    # Rows grouped by (b): ga=1 (a is aggregated across), gb=0 (b is a key)
+    assert ga == [0, 0, 1, 1]
+    assert gb == [1, 1, 0, 0]
+
+
+def test_var_population():
+    ctx = SessionContext()
+    df = ctx.from_pydict({"a": [-1.0, 0.0, 2.0]})
+    result = df.aggregate([], [f.var_population(column("a")).alias("v")]).collect()[0]
+    # var_population is an alias for var_pop
+    expected = df.aggregate([], [f.var_pop(column("a")).alias("v")]).collect()[0]
+    assert abs(result.column(0)[0].as_py() - expected.column(0)[0].as_py()) < 1e-10
+
+
+def test_get_field(df):
+    df = df.with_column(
+        "s",
+        f.named_struct(
+            [
+                ("x", column("a")),
+                ("y", column("b")),
+            ]
+        ),
     )
+    result = df.select(
+        f.get_field(column("s"), "x").alias("x_val"),
+        f.get_field(column("s"), "y").alias("y_val"),
+    ).collect()[0]
+
+    assert result.column(0) == pa.array(["Hello", "World", "!"], type=pa.string_view())
+    assert result.column(1) == pa.array([4, 5, 6])
+
+
+def test_arrow_metadata():
+    ctx = SessionContext()
+    field = pa.field("val", pa.int64(), metadata={"key1": "value1", "key2": "value2"})
+    schema = pa.schema([field])
+    batch = pa.RecordBatch.from_arrays([pa.array([1, 2, 3])], schema=schema)
+    df = ctx.create_dataframe([[batch]])
+
+    # One-argument form: returns a Map of all metadata key-value pairs
+    result = df.select(
+        f.arrow_metadata(column("val")).alias("meta"),
+    ).collect()[0]
+    assert result.column(0).type == pa.map_(pa.utf8(), pa.utf8())
+    meta = result.column(0)[0].as_py()
+    assert ("key1", "value1") in meta
+    assert ("key2", "value2") in meta
+
+    # Two-argument form: returns the value for a specific metadata key
+    result = df.select(
+        f.arrow_metadata(column("val"), "key1").alias("meta_val"),
+    ).collect()[0]
+    assert result.column(0)[0].as_py() == "value1"
+
+
+def test_version():
+    ctx = SessionContext()
+    df = ctx.from_pydict({"a": [1]})
+    result = df.select(f.version().alias("v")).collect()[0]
+    version_str = result.column(0)[0].as_py()
+    assert "Apache DataFusion" in version_str
+
+
+def test_row(df):
+    result = df.select(
+        f.row(column("a"), column("b")).alias("r"),
+        f.struct(column("a"), column("b")).alias("s"),
+    ).collect()[0]
+    # row is an alias for struct, so they should produce the same output
+    assert result.column(0) == result.column(1)
+
+
+def test_union_tag():
+    ctx = SessionContext()
+    types = pa.array([0, 1, 0], type=pa.int8())
+    offsets = pa.array([0, 0, 1], type=pa.int32())
+    children = [pa.array([1, 2]), pa.array(["hello"])]
+    arr = pa.UnionArray.from_dense(types, offsets, children, ["int", "str"], [0, 1])
+    df = ctx.create_dataframe([[pa.RecordBatch.from_arrays([arr], names=["u"])]])
+
+    result = df.select(f.union_tag(column("u")).alias("tag")).collect()[0]
+    assert result.column(0).to_pylist() == ["int", "str", "int"]
+
+
+def test_union_extract():
+    ctx = SessionContext()
+    types = pa.array([0, 1, 0], type=pa.int8())
+    offsets = pa.array([0, 0, 1], type=pa.int32())
+    children = [pa.array([1, 2]), pa.array(["hello"])]
+    arr = pa.UnionArray.from_dense(types, offsets, children, ["int", "str"], [0, 1])
+    df = ctx.create_dataframe([[pa.RecordBatch.from_arrays([arr], names=["u"])]])
+
+    result = df.select(f.union_extract(column("u"), "int").alias("val")).collect()[0]
+    assert result.column(0).to_pylist() == [1, None, 2]
+
+
+@pytest.mark.parametrize("func", [f.array_any_value, f.list_any_value])
+def test_any_value_aliases(func):
+    ctx = SessionContext()
+    df = ctx.from_pydict({"a": [[None, 2, 3], [None, None, None], [1, 2, 3]]})
+    result = df.select(func(column("a")).alias("v")).collect()
+    values = [row.as_py() for row in result[0].column(0)]
+    assert values[0] == 2
+    assert values[1] is None
+    assert values[2] == 1
+
+
+@pytest.mark.parametrize("func", [f.array_distance, f.list_distance])
+def test_array_distance_aliases(func):
+    ctx = SessionContext()
+    df = ctx.from_pydict({"a": [[1.0, 2.0]], "b": [[1.0, 4.0]]})
+    result = df.select(func(column("a"), column("b")).alias("v")).collect()
+    assert result[0].column(0)[0].as_py() == pytest.approx(2.0)
+
+
+@pytest.mark.parametrize(
+    ("func", "expected"),
+    [
+        (f.array_max, [5, 10]),
+        (f.list_max, [5, 10]),
+        (f.array_min, [1, 2]),
+        (f.list_min, [1, 2]),
+    ],
+)
+def test_array_min_max(func, expected):
+    ctx = SessionContext()
+    df = ctx.from_pydict({"a": [[1, 5, 3], [10, 2]]})
+    result = df.select(func(column("a")).alias("v")).collect()
+    values = [row.as_py() for row in result[0].column(0)]
+    assert values == expected
+
+
+@pytest.mark.parametrize("func", [f.array_reverse, f.list_reverse])
+def test_array_reverse_aliases(func):
+    ctx = SessionContext()
+    df = ctx.from_pydict({"a": [[1, 2, 3], [4, 5]]})
+    result = df.select(func(column("a")).alias("v")).collect()
+    values = [row.as_py() for row in result[0].column(0)]
+    assert values == [[3, 2, 1], [5, 4]]
+
+
+@pytest.mark.parametrize("func", [f.arrays_zip, f.list_zip])
+def test_arrays_zip_aliases(func):
+    ctx = SessionContext()
+    df = ctx.from_pydict({"a": [[1, 2]], "b": [[3, 4]]})
+    result = df.select(func(column("a"), column("b")).alias("v")).collect()
+    values = result[0].column(0)[0].as_py()
+    assert values == [{"c0": 1, "c1": 3}, {"c0": 2, "c1": 4}]
+
+
+@pytest.mark.parametrize("func", [f.string_to_array, f.string_to_list])
+def test_string_to_array_aliases(func):
+    ctx = SessionContext()
+    df = ctx.from_pydict({"a": ["hello,world,foo"]})
+    result = df.select(func(column("a"), literal(",")).alias("v")).collect()
+    assert result[0].column(0)[0].as_py() == ["hello", "world", "foo"]
+
+
+def test_string_to_array_with_null_string():
+    ctx = SessionContext()
+    df = ctx.from_pydict({"a": ["hello,NA,world"]})
+    result = df.select(
+        f.string_to_array(column("a"), literal(","), literal("NA")).alias("v")
+    ).collect()
+    values = result[0].column(0)[0].as_py()
+    assert values == ["hello", None, "world"]
+
+
+@pytest.mark.parametrize("func", [f.gen_series, f.generate_series])
+def test_gen_series_aliases(func):
+    ctx = SessionContext()
+    df = ctx.from_pydict({"a": [0]})
+    result = df.select(func(literal(1), literal(5)).alias("v")).collect()
+    assert result[0].column(0)[0].as_py() == [1, 2, 3, 4, 5]
+
+
+def test_gen_series_with_step():
+    ctx = SessionContext()
+    df = ctx.from_pydict({"a": [0]})
+    result = df.select(
+        f.gen_series(literal(1), literal(10), literal(3)).alias("v")
+    ).collect()
+    assert result[0].column(0)[0].as_py() == [1, 4, 7, 10]
diff --git a/python/tests/test_plans.py b/python/tests/test_plans.py
index 396acbe97..3705fc7ef 100644
--- a/python/tests/test_plans.py
+++ b/python/tests/test_plans.py
@@ -15,8 +15,16 @@
 # specific language governing permissions and limitations
 # under the License.
 
+import datetime
+
 import pytest
-from datafusion import ExecutionPlan, LogicalPlan, SessionContext
+from datafusion import (
+    ExecutionPlan,
+    LogicalPlan,
+    Metric,
+    MetricsSet,
+    SessionContext,
+)
 
 
 # Note: We must use CSV because memory tables are currently not supported for
@@ -40,3 +48,185 @@ def test_logical_plan_to_proto(ctx, df) -> None:
     execution_plan = ExecutionPlan.from_proto(ctx, execution_plan_bytes)
 
     assert str(original_execution_plan) == str(execution_plan)
+
+
+def test_metrics_tree_walk() -> None:
+    ctx = SessionContext()
+    ctx.sql("CREATE TABLE t AS VALUES (1, 'a'), (2, 'b'), (3, 'c')")
+    df = ctx.sql("SELECT * FROM t WHERE column1 > 1")
+    df.collect()
+    plan = df.execution_plan()
+
+    results = plan.collect_metrics()
+    assert len(results) >= 1
+    output_rows_by_op: dict[str, int] = {}
+    for name, ms in results:
+        assert isinstance(name, str)
+        assert isinstance(ms, MetricsSet)
+        if ms.output_rows is not None:
+            output_rows_by_op[name] = ms.output_rows
+
+    # The filter passes rows where column1 > 1, so exactly
+    # 2 rows from (1,'a'),(2,'b'),(3,'c').
+    # At least one operator must report exactly 2 output rows (the filter).
+    assert 2 in output_rows_by_op.values(), (
+        f"Expected an operator with output_rows=2, got {output_rows_by_op}"
+    )
+
+
+def test_metric_properties() -> None:
+    ctx = SessionContext()
+    ctx.sql("CREATE TABLE t AS VALUES (1, 'a'), (2, 'b'), (3, 'c')")
+    df = ctx.sql("SELECT * FROM t WHERE column1 > 1")
+    df.collect()
+    plan = df.execution_plan()
+
+    found_any_metric = False
+    for _, ms in plan.collect_metrics():
+        r = repr(ms)
+        assert isinstance(r, str)
+        for metric in ms.metrics():
+            found_any_metric = True
+            assert isinstance(metric, Metric)
+            assert isinstance(metric.name, str)
+            assert len(metric.name) > 0
+            assert metric.partition is None or isinstance(metric.partition, int)
+            assert metric.value is None or isinstance(
+                metric.value, int | datetime.datetime
+            )
+            assert isinstance(metric.labels(), dict)
+            mr = repr(metric)
+            assert isinstance(mr, str)
+            assert len(mr) > 0
+    assert found_any_metric, "Expected at least one metric after execution"
+
+
+def test_no_meaningful_metrics_before_execution() -> None:
+    ctx = SessionContext()
+    ctx.sql("CREATE TABLE t AS VALUES (1, 'a'), (2, 'b'), (3, 'c')")
+    df = ctx.sql("SELECT * FROM t WHERE column1 > 1")
+    plan_before = df.execution_plan()
+
+    # Some plan nodes (e.g. DataSourceExec) eagerly initialize a MetricsSet,
+    # so metrics() may return a set even before execution.  However, no rows
+    # should have been processed yet — output_rows must be absent or zero.
+    for _, ms in plan_before.collect_metrics():
+        rows = ms.output_rows
+        assert rows is None or rows == 0, (
+            f"Expected 0 output_rows before execution, got {rows}"
+        )
+
+    # After execution, at least one operator must report rows processed.
+    df.collect()
+    plan_after = df.execution_plan()
+    output_rows_after = [
+        ms.output_rows
+        for _, ms in plan_after.collect_metrics()
+        if ms.output_rows is not None and ms.output_rows > 0
+    ]
+    assert len(output_rows_after) > 0, "Expected output_rows > 0 after execution"
+
+
+def test_collect_partitioned_metrics() -> None:
+    ctx = SessionContext()
+    ctx.sql("CREATE TABLE t AS VALUES (1, 'a'), (2, 'b'), (3, 'c')")
+    df = ctx.sql("SELECT * FROM t WHERE column1 > 1")
+
+    df.collect_partitioned()
+    plan = df.execution_plan()
+
+    output_rows_values = [
+        ms.output_rows for _, ms in plan.collect_metrics() if ms.output_rows is not None
+    ]
+    assert 2 in output_rows_values, f"Expected 2 in {output_rows_values}"
+
+
+def test_execute_stream_metrics() -> None:
+    ctx = SessionContext()
+    ctx.sql("CREATE TABLE t AS VALUES (1, 'a'), (2, 'b'), (3, 'c')")
+    df = ctx.sql("SELECT * FROM t WHERE column1 > 1")
+
+    for _ in df.execute_stream():
+        pass
+
+    plan = df.execution_plan()
+    output_rows_values = [
+        ms.output_rows for _, ms in plan.collect_metrics() if ms.output_rows is not None
+    ]
+    assert 2 in output_rows_values, f"Expected 2 in {output_rows_values}"
+
+
+def test_execute_stream_partitioned_metrics() -> None:
+    ctx = SessionContext()
+    ctx.sql("CREATE TABLE t AS VALUES (1, 'a'), (2, 'b'), (3, 'c')")
+    df = ctx.sql("SELECT * FROM t WHERE column1 > 1")
+
+    for stream in df.execute_stream_partitioned():
+        for _ in stream:
+            pass
+
+    plan = df.execution_plan()
+    output_rows_values = [
+        ms.output_rows for _, ms in plan.collect_metrics() if ms.output_rows is not None
+    ]
+    assert 2 in output_rows_values, f"Expected 2 in {output_rows_values}"
+
+
+def test_value_as_datetime() -> None:
+    ctx = SessionContext()
+    ctx.sql("CREATE TABLE t AS VALUES (1, 'a'), (2, 'b'), (3, 'c')")
+    df = ctx.sql("SELECT * FROM t WHERE column1 > 1")
+    df.collect()
+    plan = df.execution_plan()
+
+    for _, ms in plan.collect_metrics():
+        for metric in ms.metrics():
+            if metric.name in ("start_timestamp", "end_timestamp"):
+                dt = metric.value_as_datetime
+                assert dt is None or isinstance(dt, datetime.datetime)
+                if dt is not None:
+                    assert dt.tzinfo is not None
+            else:
+                assert metric.value_as_datetime is None
+
+
+def test_metric_names_and_labels() -> None:
+    """Verify that known metric names appear and labels are well-formed."""
+    ctx = SessionContext()
+    ctx.sql("CREATE TABLE t AS VALUES (1, 'a'), (2, 'b'), (3, 'c')")
+    df = ctx.sql("SELECT * FROM t WHERE column1 > 1")
+    df.collect()
+    plan = df.execution_plan()
+
+    all_metric_names: set[str] = set()
+    for _, ms in plan.collect_metrics():
+        for metric in ms.metrics():
+            all_metric_names.add(metric.name)
+            # Labels must be a dict of str->str
+            labels = metric.labels()
+            for k, v in labels.items():
+                assert isinstance(k, str)
+                assert isinstance(v, str)
+
+    # After a filter query, we expect at minimum these standard metric names.
+    assert "output_rows" in all_metric_names, (
+        f"Expected 'output_rows' in {all_metric_names}"
+    )
+    assert "elapsed_compute" in all_metric_names, (
+        f"Expected 'elapsed_compute' in {all_metric_names}"
+    )
+
+
+def test_collect_twice_has_metrics() -> None:
+    ctx = SessionContext()
+    ctx.sql("CREATE TABLE t AS VALUES (1, 'a'), (2, 'b'), (3, 'c')")
+    df = ctx.sql("SELECT * FROM t WHERE column1 > 1")
+
+    df.collect()
+    df.collect()
+
+    plan = df.execution_plan()
+    output_rows_values = [
+        ms.output_rows for _, ms in plan.collect_metrics() if ms.output_rows is not None
+    ]
+    assert len(output_rows_values) > 0
diff --git a/python/tests/test_sql.py b/python/tests/test_sql.py
index 12710cf08..1ed1746e1 100644
--- a/python/tests/test_sql.py
+++ b/python/tests/test_sql.py
@@ -31,7 +31,7 @@
 def test_no_table(ctx):
     with pytest.raises(
         ValueError,
-        match="^Error during planning: table 'datafusion.public.b' not found$",
+        match=r"^Error during planning: table 'datafusion.public.b' not found$",
     ):
         ctx.sql("SELECT a FROM b").collect()
 
@@ -188,7 +188,7 @@ def test_register_parquet_partitioned(ctx, tmp_path, path_to_str, legacy_data_ty
     partition_data_type = "string" if legacy_data_type else pa.string()
 
     if legacy_data_type:
-        with pytest.warns(DeprecationWarning):
+        with pytest.warns(DeprecationWarning):  # noqa: PT030
             ctx.register_parquet(
                 "datapp",
                 dir_root,
diff --git a/python/tests/test_udf.py b/python/tests/test_udf.py
index c0ba1d831..b2540fb57 100644
--- a/python/tests/test_udf.py
+++ b/python/tests/test_udf.py
@@ -15,7 +15,10 @@
 # specific language governing permissions and limitations
 # under the License.
 
+from uuid import UUID
+
 import pyarrow as pa
+import pyarrow.compute as pc
 import pytest
 from datafusion import SessionContext, column, udf
 from datafusion import functions as f
@@ -128,8 +131,6 @@ def udf_with_param(values: pa.Array) -> pa.Array:
 
 
 def test_udf_with_metadata(ctx) -> None:
-    from uuid import UUID
-
     @udf([pa.string()], pa.uuid(), "stable")
     def uuid_from_string(uuid_string):
         return pa.array((UUID(s).bytes for s in uuid_string.to_pylist()), pa.uuid())
@@ -151,8 +152,6 @@ def uuid_version(uuid):
 
 
 def test_udf_with_nullability(ctx: SessionContext) -> None:
-    import pyarrow.compute as pc
-
     field_nullable_i64 = pa.field("with_nulls", type=pa.int64(), nullable=True)
     field_non_nullable_i64 = pa.field("no_nulls", type=pa.int64(), nullable=False)
 
diff --git a/python/tests/test_udwf.py b/python/tests/test_udwf.py
index 5aaf00664..38b935b7e 100644
--- a/python/tests/test_udwf.py
+++ b/python/tests/test_udwf.py
@@ -433,8 +433,8 @@ def test_udwf_functions(complex_window_df, name, expr, expected):
     [
         udwf(SimpleWindowCount, pa.int64(), pa.int64(), "immutable"),
         udwf(SimpleWindowCount, [pa.int64()], pa.int64(), "immutable"),
-        udwf([pa.int64()], pa.int64(), "immutable")(lambda: SimpleWindowCount()),
-        udwf(pa.int64(), pa.int64(), "immutable")(lambda: SimpleWindowCount()),
+        udwf([pa.int64()], pa.int64(), "immutable")(SimpleWindowCount),
+        udwf(pa.int64(), pa.int64(), "immutable")(SimpleWindowCount),
     ],
 )
 def test_udwf_overloads(udwf_func, count_window_df):
diff --git a/uv.lock b/uv.lock
index 743611005..3b7135e32 100644
--- a/uv.lock
+++ b/uv.lock
@@ -1,4 +1,5 @@
 version = 1
+revision = 2
 requires-python = ">=3.10"
 resolution-markers = [
     "python_full_version >= '3.14'",
@@ -11,9 +12,71 @@ resolution-markers = [
 name = "alabaster"
 version = "1.0.0"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/a6/f8/d9c74d0daf3f742840fd818d69cfae176fa332022fd44e3469487d5a9420/alabaster-1.0.0.tar.gz", hash = "sha256:c00dca57bca26fa62a6d7d0a9fcce65f3e026e9bfe33e9c538fd3fbb2144fd9e", size = 24210 }
+sdist = { url = "https://files.pythonhosted.org/packages/a6/f8/d9c74d0daf3f742840fd818d69cfae176fa332022fd44e3469487d5a9420/alabaster-1.0.0.tar.gz", hash = "sha256:c00dca57bca26fa62a6d7d0a9fcce65f3e026e9bfe33e9c538fd3fbb2144fd9e", size = 24210, upload-time = "2024-07-26T18:15:03.762Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/7e/b3/6b4067be973ae96ba0d615946e314c5ae35f9f993eca561b356540bb0c2b/alabaster-1.0.0-py3-none-any.whl", hash = "sha256:fc6786402dc3fcb2de3cabd5fe455a2db534b371124f1f21de8731783dec828b", size = 13929 },
+    { url = "https://files.pythonhosted.org/packages/7e/b3/6b4067be973ae96ba0d615946e314c5ae35f9f993eca561b356540bb0c2b/alabaster-1.0.0-py3-none-any.whl", hash = "sha256:fc6786402dc3fcb2de3cabd5fe455a2db534b371124f1f21de8731783dec828b", size = 13929, upload-time = "2024-07-26T18:15:02.05Z" },
+]
+
+[[package]]
+name = "arro3-core"
+version = "0.6.5"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "typing-extensions", marker = "python_full_version < '3.12'" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/2a/01/f06342d2eb822153f63d188153e41fbeabb29b48247f7a11ce76c538f7d1/arro3_core-0.6.5.tar.gz", hash = "sha256:768078887cd7ac82de4736f94bbd91f6d660f10779848bd5b019f511badd9d75", size = 107522, upload-time = "2025-10-13T23:12:38.872Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/7a/8a/24b35cf01a68621f5f07e3191ca96f70a145022ca367347266901eb504a7/arro3_core-0.6.5-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:da193dc2fb8c2005d0b3887b09d1a90d42cec1f59f17a8a1a5791f0de90946ae", size = 2678116, upload-time = "2025-10-13T23:09:04.198Z" },
+    { url = "https://files.pythonhosted.org/packages/5a/7a/4398bb0582fb22d575f256f2b9ac7be735c765222cc61fb214d606bdb77c/arro3_core-0.6.5-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:ed1a760ec39fe19c65e98f45515582408002d0212df5db227a5959ffeb07ad4a", size = 2383214, upload-time = "2025-10-13T23:09:06.841Z" },
+    { url = "https://files.pythonhosted.org/packages/82/3f/a321501c5da4bf3ff7438c3e5eb6e63bcecb5630c0f4a89a017cbfa8e4a0/arro3_core-0.6.5-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:6584a3d28007740afcef1e301332876e2b785bd8edd59a458a6bc9b051bce052", size = 2883536, upload-time = "2025-10-13T23:09:08.877Z" },
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