pytest-mastery
Python testing with pytest using uv package manager. Use when: (1) Running Python tests, (2) Writing test files or test functions, (3) Setting up fixtures, (4) Parametrizing tests, (5) Generating coverage repor...
Skills correspondant au nom, à la description ou à l’auteur GitHub.
Python testing with pytest using uv package manager. Use when: (1) Running Python tests, (2) Writing test files or test functions, (3) Setting up fixtures, (4) Parametrizing tests, (5) Generating coverage repor...
Python testing framework for writing simple, scalable, and powerful tests
Set up Python projects using nix/direnv with uv for environment management. Use when creating new Python projects, initializing Python environments, or when the user wants automatic Python virtual environment s...
Guide for creating MCP (Model Context Protocol) servers that enable LLMs to interact with external services. Use when building MCP servers, integrating external APIs, implementing tool servers, or creating agen...
Perform comprehensive dead code and clean-up analysis in Python projects using static analysis, coverage, dependency checks, and security scanning. Use when asked to clean up code, find unused code, analyze dep...
Modern Python coaching covering language foundations through advanced production patterns. Use when asked to "write Python code", "explain Python concepts", "set up a Python project", "configure Poetry or PDM",...
Web application testing toolkit using Playwright with Python. Use for verifying frontend functionality, debugging UI behavior, capturing browser screenshots, viewing browser logs, and automating web interaction...
Comprehensive Word document toolkit for reading, creating, and editing .docx files. Supports text extraction, document creation with python-docx, and tracked changes via redlining workflow. Use for legal, acade...
Generate standardized Python project structure with pyproject.toml, UV environment, pytest configuration, and workspace-hub compliance. Creates production-ready project scaffolding.
A math skill that can perform magic number calculations using python scripts.
Build AI agents with Google ADK Python (Agent Development Kit). Use for multi-agent systems, workflow agents (sequential/parallel/loop), Vertex AI deployment, tool integration, human-in-the-loop.
Build MCP servers for LLM-external service integration. Use for FastMCP (Python), MCP SDK (Node/TypeScript), tool design, API integration, resource providers.
Build backends with Node.js, Python, Go (NestJS, FastAPI, Django). Use for REST/GraphQL/gRPC APIs, auth (OAuth, JWT), databases, microservices, security (OWASP), Docker/K8s.
Use when building FastAPI apps with async database operations, complex dependency injection, partial update endpoints, async testing, or converting Python utilities to API endpoints
Guide for refactoring Python code to follow SOLID principles and improve maintainability
Deploy Python Flask applications to Railway.app with environment configuration and webhook setup
Manage Python projects and dependencies using UV, the ultra-fast Rust-based package manager. Use when creating Python projects, managing dependencies, or running Python scripts.
Set up GitHub Actions workflows for CI/CD with automated testing, linting, and deployment for Python/UV projects. Use when creating CI pipelines, automating tests, or setting up deployment workflows.
Create Dockerfiles, docker-compose configurations, and container workflows for Python projects with UV. Use when containerizing applications, setting up development environments, or deploying with Docker.
Maintain Python code quality using Black formatting, Ruff linting, and mypy type checking. Use when formatting code, running linters, fixing style issues, or adding type hints.
Create beautiful terminal output with Rich library including tables, progress bars, panels, and syntax highlighting. Use when building CLI applications or enhancing terminal output in Python.
Write and run Python tests using pytest with fixtures, mocking, coverage, and the AAA pattern. Use when writing Python tests, creating test files, or setting up pytest configuration.
Expert data science guidance for analytics, data processing, visualization, statistical analysis, machine learning, and AI integration. Use when analyzing data, building ML models, creating visualizations, proc...
Python programming patterns and best practices
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.