Async Python is Secretly Deterministic

The challenge of adding async support to a Python durable execution library lies in ensuring deterministic workflows for replay-based recovery, despite the inherent concurrency of async operations. Async Python employs an event loop, which is a single-threaded scheduler that runs tasks sequentially, allowing concurrency through task scheduling and yielding control via the `await` keyword. While asyncio allows for concurrent execution using functions like `asyncio.gather`, it introduces complexities in step execution order due to overlapping tasks. To resolve this, tasks are deterministically ordered by assigning step IDs before any awaited operations, ensuring a consistent execution sequence that can be accurately replayed during recovery. This approach leverages the predictable nature of the single-threaded event loop, allowing developers to create concurrent and safe workflows without the unpredictability of parallel threads. Understanding these subtleties is crucial for developing reliable Python libraries and systems that effectively utilize async capabilities.

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