pyo3-performance-patterns

Optimize async Rust functions called from Python by releasing the GIL before awaiting operations and leveraging `pyo3_async_runtimes` for faster callbacks. This approach ensures performant, deadlock-free execution paths based on operation duration.

Use `spawn_blocking` for long-running operations and `block_in_place` for quick operations when integrating Rust with Python. Choosing the correct method prevents GIL deadlocks in critical sections like PostProcessor and Validator components.

PyO3 async runtimes deadlock when the GIL is held during await operations. Prevent this by releasing the GIL before awaiting async tasks and using `Python::attach()` appropriately to manage critical sections safely.

The best way to handle Python callbacks in an async Rust runtime is using `pyo3_async_runtimes`, which provides significantly faster execution compared to `spawn_blocking` while properly managing GIL release and attachment.

Yes, PyO3 supports releasing the GIL during asynchronous operations. You can release the GIL before awaiting async tasks and use `Python::attach()` to re-enter the interpreter context only when necessary, maximizing concurrency.