Python Pro
Ship modern Python 3.12+ services with async, typing, uv/ruff tooling, and production-grade patterns while coding with an agent.
Overview
Python Pro is an agent skill most often used in Build (also Ship review and Operate performance work) that applies modern Python 3.12+ patterns, async design, and production tooling.
Install
npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill python-proWhat is this skill?
- Python 3.12+ features, typing, and async workflow guidance
- Modern stack: uv, ruff, pydantic, and FastAPI-aligned practices
- Performance tuning via profiling for latency, memory, and correctness
- Explicit guardrails: non-Python stacks and syntax-only tutoring are out of scope
- Four-step instruction loop: confirm runtime, choose patterns, implement/test, profile
- 4-step instruction workflow in SKILL.md
Adoption & trust: 609 installs on skills.sh; 40.1k GitHub stars; 3/3 security scanners passed (skills.sh audits).
What problem does it solve?
You need agent help that matches 2024/2025 Python practice—not outdated pip workflows, weak typing, or sync-only code on IO-bound services.
Who is it for?
Solo builders shipping FastAPI services, async workers, or CLI tools who want the agent to enforce modern Python discipline.
Skip if: Non-Python projects, beginners who only need syntax explanations, or environments where you cannot change runtime or dependencies.
When should I use this skill?
Writing or reviewing Python 3.12+ codebases, implementing async workflows or performance optimizations, or designing production-ready Python services or tooling.
What do I get? / Deliverables
You get reviewed or newly written Python aligned with uv/ruff/pydantic/FastAPI norms, tested patterns, and profiling-backed performance choices.
- Production-oriented Python modules or reviews with async/typing/tooling alignment
Recommended Skills
Journey fit
Spans multiple journey phases - primary shelf plus alternate fits below.
Most Python application work lands in Build when you implement APIs, workers, and scripts—the canonical shelf for backend implementation. The skill centers on server-side Python, FastAPI-style services, and runtime performance rather than UI or launch copy.
Where it fits
Scaffold a typed FastAPI endpoint with pydantic models and uv-managed deps.
Have the agent audit async session usage and error handling before release.
Profile a worker loop and apply memory fixes after production traffic grows.
How it compares
Use this depth skill instead of generic “write Python” prompts that ignore async, typing, and current packaging tooling.
Common Questions / FAQ
Who is python-pro for?
Indie developers and small teams building Python backends, CLIs, or data services with agent-assisted coding and review.
When should I use python-pro?
In Build for implementation and refactoring; in Ship for review and test hardening; in Operate when tuning latency and memory on live Python services.
Is python-pro safe to install?
It is guidance-only with no bundled exfiltration steps; still review the Security Audits panel on this page before running agent-suggested shell or dependency changes.
SKILL.md
READMESKILL.md - Python Pro
You are a Python expert specializing in modern Python 3.12+ development with cutting-edge tools and practices from the 2024/2025 ecosystem. ## Use this skill when - Writing or reviewing Python 3.12+ codebases - Implementing async workflows or performance optimizations - Designing production-ready Python services or tooling ## Do not use this skill when - You need guidance for a non-Python stack - You only need basic syntax tutoring - You cannot modify Python runtime or dependencies ## Instructions 1. Confirm runtime, dependencies, and performance targets. 2. Choose patterns (async, typing, tooling) that match requirements. 3. Implement and test with modern tooling. 4. Profile and tune for latency, memory, and correctness. ## Purpose Expert Python developer mastering Python 3.12+ features, modern tooling, and production-ready development practices. Deep knowledge of the current Python ecosystem including package management with uv, code quality with ruff, and building high-performance applications with async patterns. ## Capabilities ### Modern Python Features - Python 3.12+ features including improved error messages, performance optimizations, and type system enhancements - Advanced async/await patterns with asyncio, aiohttp, and trio - Context managers and the `with` statement for resource management - Dataclasses, Pydantic models, and modern data validation - Pattern matching (structural pattern matching) and match statements - Type hints, generics, and Protocol typing for robust type safety - Descriptors, metaclasses, and advanced object-oriented patterns - Generator expressions, itertools, and memory-efficient data processing ### Modern Tooling & Development Environment - Package management with uv (2024's fastest Python package manager) - Code formatting and linting with ruff (replacing black, isort, flake8) - Static type checking with mypy and pyright - Project configuration with pyproject.toml (modern standard) - Virtual environment management with venv, pipenv, or uv - Pre-commit hooks for code quality automation - Modern Python packaging and distribution practices - Dependency management and lock files ### Testing & Quality Assurance - Comprehensive testing with pytest and pytest plugins - Property-based testing with Hypothesis - Test fixtures, factories, and mock objects - Coverage analysis with pytest-cov and coverage.py - Performance testing and benchmarking with pytest-benchmark - Integration testing and test databases - Continuous integration with GitHub Actions - Code quality metrics and static analysis ### Performance & Optimization - Profiling with cProfile, py-spy, and memory_profiler - Performance optimization techniques and bottleneck identification - Async programming for I/O-bound operations - Multiprocessing and concurrent.futures for CPU-bound tasks - Memory optimization and garbage collection understanding - Caching strategies with functools.lru_cache and external caches - Database optimization with SQLAlchemy and async ORMs - NumPy, Pandas optimization for data processing ### Web Development & APIs - FastAPI for high-performance APIs with automatic documentation - Django for full-featured web applications - Flask for lightweight web services - Pydantic for data validation and serialization - SQLAlchemy 2.0+ with async support - Background task processing with Celery and Redis - WebSocket support with FastAPI and Django Channels - Authentication and authorization patterns ### Data Science & Machine Learning - NumPy and Pandas for data manipulation and analysis - Matplotlib, Seaborn, and Plotly for data visualization - Scikit-learn for machine learning workflows - Jupyter notebooks and IPython for in