UNPICK added AGENTS.md

Author: kosiew

AGENTS.md

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+# AGENTS Instructions
+
+This repository contains Python bindings for Rust's DataFusion.
+
+## Development workflow
+- Ensure git submodules are initialized: `git submodule update --init`.
+- Build the Rust extension before running tests:
+  - `uv run --no-project maturin develop --uv`
+- Run tests with pytest:
+  - `uv --no-project pytest .`
+
+## Linting and formatting
+- Use pre-commit for linting/formatting.
+- Run hooks for changed files before committing:
+  - `pre-commit run --files <files>`
+  - or `pre-commit run --all-files`
+- Hooks enforce:
+  - Python linting/formatting via Ruff
+  - Rust formatting via `cargo fmt`
+  - Rust linting via `cargo clippy`
+
+## Notes
+- The repository mixes Python and Rust; ensure changes build for both languages.
+- If adding new dependencies, update `pyproject.toml` and run `uv sync --dev --no-install-package datafusion`.
+
+## Refactoring opportunities
+  - Avoid using private or low-level APIs when a stable, public helper exists. For example,
+    automated refactors should spot and replace uses: 
+
+    ```python
+    # Before (uses private/low-level API) 
+    # PyArrow example
+    reader = pa.RecordBatchReader._import_from_c_capsule(
+            df.__arrow_c_stream__()
+    )
+
+    # After (use public API)
+    reader = pa.RecordBatchReader.from_stream(df)
+    ```
+
+    Look for call chains that invoke `_import_from_c_capsule` with `__arrow_c_stream__()`
+    and prefer `from_stream(df)` instead. This improves readability and avoids
+    relying on private PyArrow internals that may change.
+
+## Helper Functions
+- `python/datafusion/io.py` offers global context readers:
+  - `read_parquet`
+  - `read_json`
+  - `read_csv`
+  - `read_avro`
+- `python/datafusion/user_defined.py` exports convenience creators for user-defined functions:
+  - `udf` (scalar)
+  - `udaf` (aggregate)
+  - `udwf` (window)
+  - `udtf` (table)
+- `python/datafusion/col.py` exposes the `Col` helper with `col` and `column` instances for building column expressions using attribute access.
+- `python/datafusion/catalog.py` provides Python-based catalog and schema providers.
+- `python/datafusion/object_store.py` exposes object store connectors: `AmazonS3`, `GoogleCloud`, `MicrosoftAzure`, `LocalFileSystem`, and `Http`.
+- `python/datafusion/unparser.py` converts logical plans back to SQL via the `Dialect` and `Unparser` classes.
+- `python/datafusion/dataframe_formatter.py` offers configurable HTML and string formatting for DataFrames (replaces the deprecated `html_formatter.py`).
+- `python/tests/generic.py` includes utilities for test data generation:
+  - `data`
+  - `data_with_nans`
+  - `data_datetime`
+  - `data_date32`
+  - `data_timedelta`
+  - `data_binary_other`
+  - `write_parquet`
+- `python/tests/conftest.py` defines reusable pytest fixtures:
+  - `ctx` creates a `SessionContext`.
+  - `database` registers a sample CSV dataset.
+- `src/dataframe.rs` provides the `collect_record_batches_to_display` helper to fetch the first non-empty record batch and flag if more are available.