Performant Python Skill

Goal

Building high-concurrency, low-latency Python services by leveraging asynchronous patterns, optimized runtimes, and efficient memory management.

Capabilities

1. Asynchronous Mastery (Asyncio & FastAPI)

• Non-blocking I/O: Use async/await for all network and disk I/O. Use run_in_executor for CPU-bound tasks to avoid blocking the event loop.
• Event Loop Tuning: Use uvloop as the drop-in replacement for the default asyncio loop for significant speedups.
• Concurrent Execution: Use asyncio.gather() or asyncio.TaskGroup (Python 3.11+) for parallel I/O operations.

2. Database & Data Handling

• Async Drivers: Use asyncpg for PostgreSQL or aiomysql. Use SQLAlchemy/Tortoise with async support.
• Serialization: Use ORJSONResponse or UJSONResponse in FastAPI for faster JSON encoding/decoding.
• Efficient Models: Use Pydantic v2 for its Rust-based speed. Use .model_dump(include={...}) to minimize data transfer.