Python Performance

This is a comprehensive learning resource for making Python code faster. It covers the full optimization toolkit: profiling to find slow spots, algorithm improvements, memory management, and leveraging compiled extensions like Cython and NumPy. You also get strategies for caching and parallelization. It's structured as a skill for Claude Code, meaning you can invoke it during development sessions to get guidance on performance work. If you're wrestling with sluggish Python applications or need to optimize compute-heavy operations, this gives you a systematic approach rather than random Stack Overflow fixes. The security audits are clean across the board, which matters since performance code often gets messy.