Does this skill support modern Python tools?

Yes, it is pre-configured to work with uv for package management, ruff for linting, mypy for type checking, and pytest for testing.

How does it handle testing differently?

It mandates testing against real data using existing project infrastructure and fixtures, strictly prohibiting the mocking of internal code or the creation of redundant test databases.

What is the fail-fast philosophy in this skill?

The fail-fast philosophy ensures that the code crashes immediately upon encountering missing configurations or invalid data rather than using silent defaults, which prevents the corruption of research results.

Is this skill suitable for data science and academic research?

Absolutely. It is specifically designed for environments where data integrity, replicability, and strict adherence to research configurations are paramount.

Can it automatically fix linting and type errors?

Yes, it uses ruff for automated linting fixes and provides subagent patterns to implement type-safe code that passes mypy validation.

Python Production Development

Name: Python Production Development
Author: nicsuzor

bynicsuzor

0•

开发者工具

Writes production-grade Python code utilizing fail-fast principles, rigorous type safety, and modern testing patterns for academic and research environments.

The Python-Dev skill enforces high-integrity coding standards specifically designed for academic and research contexts where correctness and reproducibility are critical. It implements a fail-fast philosophy that eliminates silent failures, mandates strict type hinting, and promotes a Test-Driven Development (TDD) workflow using industry-standard tools like uv, pytest, and ruff. By prioritizing real-data testing over internal mocking and enforcing Pydantic-based validation, this skill ensures that Python applications are robust, maintainable, and scientifically verifiable.

主要功能

01TDD workflow optimized for real-data integration testing

02Fail-fast philosophy to prevent silent data corruption in research

03Strict adherence to academic integrity and research code standards

04Mandatory type safety with mypy and Pydantic validation

050 GitHub stars

06Seamless integration with modern tools like uv, ruff, and pytest

使用场景

01Developing reproducible research pipelines and data processing scripts

02Building robust backend services with strict configuration validation

03Automating code quality checks and type-safe refactoring in complex projects

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add nicsuzor/academicops python-dev

For use in Claude.ai and ChatGPT

Download Skill