If it's entirely CPU bound, you can use multiprocessing to negate most of the GIL issues, and transparently send inputs/outputs between the parent and child processes. If it's I/O bound, then AsyncIO is a great way to express asynchronous workflows. If it's a combination of both I/O and CPU bound workloads, there are ways to mix multiprocessing and AsyncIO to better saturate your cores without losing the simplicity or readability of Python: https://github.com/jreese/aiomultiprocess

Indeed and as a Perl developer I make use of XS/external libraries, cooperative multitasking (event loops/promises), and forking to cover these use cases. It doesn't preclude wanting the additional option to take advantage of threads in a useful way, since they do exist.

It's not just CPU bound problems, handling multiple overlapping i/o operations is more trouble than it ought to be.