Choosing the Right Concurrency Model

Understanding when the GIL forces you to choose multiprocessing over threading or async for data workloads.

You have a data pipeline with two distinct stages: (1) fetching thousands of records from remote HTTP APIs, and (2) performing heavy CPU-bound numeric transformations in pure Python on those records. On a standard CPython 3.11 interpreter, which strategy maximizes throughput for each stage respectively?