Can I use this on existing legacy projects?

Yes, the skill provides strategies for gradual adoption, allowing you to implement linting first and increase MyPy strictness over time.

How does pre-commit help my workflow?

Pre-commit ensures that all quality checks are run automatically before every commit, preventing sub-standard code from entering your repository.

What primary tools does this skill configure?

It primarily configures Ruff for linting and formatting, MyPy for static type checking, and pre-commit for automated git hooks.

Why is this skill specific to scientific Python?

It includes specialized configurations and rules for the scientific ecosystem, such as NumPy-aware linting and type checking for multi-dimensional arrays.

Does Ruff replace my existing formatting tools?

Yes, Ruff is a modern, high-performance replacement for Black, Flake8, Isort, and several other legacy Python quality tools.

Scientific Python Code Quality Tools

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

byuw-ssec

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开发者工具

Implements automated linting, formatting, and static type checking to ensure maintainable and error-free scientific Python projects.

关于

This skill equips Claude with the expertise to configure and manage essential code quality tools specifically tailored for scientific Python development. It focuses on integrating Ruff for high-performance linting and formatting, MyPy for robust static type checking of numerical code, and pre-commit hooks to automate quality gates. By establishing these standards, it helps research software engineers catch bugs early, maintain consistent style across collaborative teams, and prevent dimension-related errors common in data science and numerical computing.

主要功能

Seamless migration from legacy tools like Black, Flake8, and Isort
Static type checking with MyPy tailored for NumPy and SciPy
Optimized pyproject.toml patterns for scientific-aware linting rules
5 GitHub stars
Automated Ruff configuration for ultra-fast linting and formatting
Pre-commit hook integration for automated git workflow checks

使用场景

Reducing runtime errors in complex numerical simulations through static type analysis
Automating the preparation of scientific packages for publication and distribution
Standardizing code style and quality across multi-contributor research projects

关于

主要功能

Seamless migration from legacy tools like Black, Flake8, and Isort
Static type checking with MyPy tailored for NumPy and SciPy
Optimized pyproject.toml patterns for scientific-aware linting rules
5 GitHub stars
Automated Ruff configuration for ultra-fast linting and formatting
Pre-commit hook integration for automated git workflow checks

使用场景

Reducing runtime errors in complex numerical simulations through static type analysis
Automating the preparation of scientific packages for publication and distribution
Standardizing code style and quality across multi-contributor research projects