python-notebooks-async

What problem does it solve?

Notebook environments often face challenges running asynchronous code due to host-owned event loops, leading to RuntimeError or unpredictable behavior. This skill provides practical patterns to orchestrate async tasks in notebooks without fighting the loop, improving reliability and developer productivity.

Core Features & Use Cases

• Treat notebook kernels as loop-owned environments and prefer top-level await over creating new loops.
• Use asyncio.gather for concurrent tasks and TaskGroup for structured concurrency within IPython, Jupyter, and VS Code notebooks.
• Keep reusable async logic in regular Python modules and minimize global event loop patches.

Quick Start

Use top-level await in notebook cells and avoid asyncio.run to prevent conflicting event loops while keeping async tasks organized with asyncio.gather.