How does pre-commit help my development workflow?

Pre-commit runs automated checks before every git commit, blocking the commit if errors are found, which prevents sub-standard code from entering your repository.

Why use Ruff instead of Black or Flake8?

Ruff is written in Rust and is 10-100x faster than traditional tools, replacing Black, Flake8, isort, and more with a single, highly-compatible binary.

Can I use this skill with NumPy and Pandas?

Yes, this skill includes specific configurations and type-checking patterns optimized for scientific libraries, including NumPy-aware docstring checking.

Is this skill compatible with existing project configurations?

Yes, it provides patterns for Ruff and MyPy that can be easily integrated into your existing pyproject.toml or .pre-commit-config.yaml files.

Does it support environment managers like Pixi?

Yes, the skill provides specific integration patterns for Pixi to ensure your quality tools are part of a reproducible development environment.

Code Quality Tools for Python

Name: Code Quality Tools for Python
Author: uw-ssec

byuw-ssec

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Data Science & ML

Automates linting, formatting, and static type checking for scientific Python projects using Ruff, MyPy, and pre-commit hooks.

About

This skill streamlines the establishment and enforcement of high-quality coding standards in scientific Python environments. By integrating modern, high-performance tools like Ruff for lightning-fast linting and formatting, MyPy for catching type-related bugs, and pre-commit for automated quality gates, it ensures research code remains maintainable and error-free. It is specifically designed to handle the complexities of the scientific ecosystem, including support for NumPy-aware checking and integration with the Pixi package manager to create reproducible development workflows.

Key Features

Automated git hook integration via pre-commit
6 GitHub stars
Lightning-fast linting and formatting with Ruff
Static type checking setup with MyPy for numerical code
Scientific Python ecosystem support for NumPy and Pandas
Reproducible environment patterns using Pixi

Use Cases

Preventing runtime errors in numerical simulations via static type checking
Migrating legacy scientific codebases from Black/Flake8 to Ruff
Establishing coding standards for new research software projects

About

Key Features

Automated git hook integration via pre-commit
6 GitHub stars
Lightning-fast linting and formatting with Ruff
Static type checking setup with MyPy for numerical code
Scientific Python ecosystem support for NumPy and Pandas
Reproducible environment patterns using Pixi

Use Cases

Preventing runtime errors in numerical simulations via static type checking
Migrating legacy scientific codebases from Black/Flake8 to Ruff
Establishing coding standards for new research software projects