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# Agent Instructions for Contributors
This file is for agents working **on** the datafusion-python project (developing,
testing, reviewing). If you need to **use** the DataFusion DataFrame API (write
queries, build expressions, understand available functions), see the user-facing
skill at [`SKILL.md`](skills/datafusion_python/SKILL.md).
## Skills
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.
To discover what skills are available, list `.ai/skills/` and read each
`SKILL.md`. The frontmatter `name` and `description` fields summarize the
skill's purpose.
## Pull Requests
Every pull request must follow the template in
`.github/pull_request_template.md`. The description must include these sections:
1. **Which issue does this PR close?** — Link the issue with `Closes #NNN`.
2. **Rationale for this change** — Why the change is needed (skip if the issue
already explains it clearly).
3. **What changes are included in this PR?** — Summarize the individual changes.
4. **Are there any user-facing changes?** — Note any changes visible to users
(new APIs, changed behavior, new files shipped in the package, etc.). If
there are breaking changes to public APIs, add the `api change` label.
## Pre-commit Checks
Always run pre-commit checks **before** committing. The hooks are defined in
`.pre-commit-config.yaml` and run automatically on `git commit` if pre-commit
is installed as a git hook. To run all hooks manually:
```bash
pre-commit run --all-files
```
Fix any failures before committing.
## 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.md` —
add new aggregate functions to the "Aggregate Functions" list and include usage
examples if appropriate.
- **Window functions**: `docs/source/user-guide/common-operations/windows.md` —
add new window functions to the "Available Functions" list and include usage
examples if appropriate.