Python performance myths and fairy tales
9 months ago
- #Python
- #Performance
- #Programming
- Antonio Cuni discusses common myths about Python performance, emphasizing that Python's dynamic nature inherently limits its speed.
- Python's performance issues stem from its dynamic features, which, while useful for flexibility, complicate optimization efforts.
- Memory management and cache-unfriendliness are identified as fundamental bottlenecks for Python's performance, beyond what JIT compilers can solve.
- Cuni introduces SPy (Static Python), a project aiming to improve Python's performance by tweaking language semantics without breaking compatibility.
- The talk highlights the trade-offs between Python's dynamism, speed, and implementation simplicity, suggesting localized optimizations as a potential path forward.