Scientific Python Development

Write and organize tests for scientific Python packages using pytest. Covers fixtures, parametrization, numerical testing with NumPy utilities, property-based testing with Hypothesis, and CI integration.

Create and publish distributable scientific Python packages following Scientific Python community best practices. Covers pyproject.toml, src layout, Hatchling, metadata, CLI entry points, and PyPI publishing.

Configure and use automated code quality tools (ruff, mypy, pre-commit) for scientific Python projects. Covers linting rules, type checking configuration, formatting, and CI integration.

Manage scientific Python dependencies and environments with the pixi package manager: create environments, add conda-forge and PyPI packages, define and run tasks, and generate reproducible multi-platform lockfiles. Use when the user mentions pixi, pixi.toml, pixi.lock, pixi init/add/run, conda-forge, or needs reproducible scientific Python environments combining conda and PyPI packages.

Set up and maintain documentation for scientific Python packages. Covers Sphinx, MkDocs, NumPy-style docstrings, Diataxis framework, accessibility standards, and documentation hosting with Read the Docs.