Making python's dream of multithreading come true
Intro
So you are writing some CPU-intensive code in Python and really trying to find ways out of its single-threaded prison. You might be looking towards Numba's "nopython parallel" mode, you might be using forked processes with multiprocessing, you might be writing microservices with database-like coordinators, or even writing your own multithreaded programs in C/C++ just like creators of TensorFlow did.
In this article I'm describing a rationale for my pet project where I try to implement facilities for general purpose multitasking to be used in a form of simple python code, employing a database-like approach for interpreters communication, while keeping the GIL (Global Interpreter Lock) and trying to be as pythonic as possible.
It could also become handy in the light of upcoming multiple interpreters support in CPython.
As far as I know, nobody came that far in trying to provide Python program with native shareable storage. The last closest attempt was Python Object Sharing which is pretty much dead by now. I hope my project won't meet the same fate.