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python-pro

Optimize Python 3.12+ code with modern tooling and production practices.

Updated Mar 11, 2026

Search Tags:#web development #python #data science #performance optimization #async programming #modern python #production ready

Ready to run

npx skills add https://github.com/act70255/SkillsBundle --skill python-pro-act70255

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: python-pro
Source: https://github.com/act70255/SkillsBundle/tree/main/dev-python/skills/python-pro
Command: npx skills add https://github.com/act70255/SkillsBundle --skill python-pro-act70255

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires uv, ruff, pydantic, FastAPI, pytest, Hypothesis, cProfile, py-spy, memory_profiler, NumPy, Pandas, Matplotlib, Scikit-learn, PyTorch, Django, Flask, SQLAlchemy, Celery, Redis, Docker, Kubernetes, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill provides expert-level guidance and automation for modern Python development, addressing the complexities of Python 3.12+ with performance optimization and production-ready practices.

Core Features & Use Cases

Modern Python 3.12+ Expertise: Offers comprehensive knowledge of the latest Python features, async programming, and performance optimizations.
Modern Tooling & Development Environment: Integrates with the latest tools like uv, ruff, pydantic, and FastAPI for efficient development.
Testing & Quality Assurance: Provides robust testing strategies with pytest, Hypothesis, and performance testing tools.
Performance & Optimization: Offers profiling, optimization techniques, and memory management for high-performance applications.
Web Development & APIs: Specializes in FastAPI, Django, Flask, and SQLAlchemy for web development and API creation.
Data Science & Machine Learning: Supports NumPy, Pandas, Matplotlib, Scikit-learn, and PyTorch for data analysis and machine learning.
DevOps & Production Deployment: Covers Docker, Kubernetes, cloud deployment, monitoring, and security best practices.
Advanced Python Patterns: Implements design patterns, SOLID principles, and functional programming concepts.
Behavioral Traits: Adheres to PEP 8, emphasizes code readability, and focuses on security and best practices.

Quick Start

Implement modern Python practices with the python-pro skill to enhance your codebase and improve performance.

Frequently Asked Questions about python-pro

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I optimize Python performance and memory management for production applications?▼

Optimize Python performance and memory management by profiling code with cProfile, py-spy, and memory_profiler. This Skill automates bottleneck identification and implements optimization techniques to ensure high-performance, production-ready applications.

How do I set up a modern Python development environment with uv and ruff?▼

Set up a modern Python environment using uv for package management and ruff for linting. This Skill automates tool configuration alongside pydantic and FastAPI, streamlining development workflows and enforcing code quality standards.

Does this Skill support async programming and FastAPI for web API development?▼

Yes, this Skill supports async programming and FastAPI for web API development. It provides expert guidance on modern Python 3.12+ features, enabling you to build, optimize, and secure asynchronous web applications with production-ready practices.

What's the best way to test Python code using pytest and Hypothesis?▼

The best way to test Python code is combining pytest for structured testing with Hypothesis for property-based testing. This Skill provides robust testing strategies and integrates performance testing tools to ensure comprehensive quality assurance for production.

Can I use this Skill for data science workflows with Pandas, NumPy, and PyTorch?▼

Yes, you can use this Skill for data science workflows as it supports NumPy, Pandas, Matplotlib, Scikit-learn, and PyTorch. It helps optimize data analysis and machine learning pipelines using modern Python 3.12+ features and performance best practices.

How do I deploy Python applications using Docker and Kubernetes?▼

Deploy Python applications by containerizing them with Docker and orchestrating deployments with Kubernetes. This Skill covers DevOps best practices, including cloud deployment, monitoring, and security, ensuring your modern Python applications run reliably in production.