Asynchronous Programming & Concurrency

• Coroutine - Wikipedia

multiprocessing — Process-based parallelism

Source code: Lib/multiprocessing/

multiprocessing is a package that supports spawning processes using an API similar to the threading module. The multiprocessing package offers both local and remote concurrency, effectively side-stepping the Global Interpreter Lock by using subprocesses instead of threads. Due to this, the multiprocessing module allows the programmer to fully leverage multiple processors on a given machine. It runs on both Unix and Windows.

The multiprocessing module also introduces APIs which do not have analogs in the threading module. A prime example of this is the Pool object which offers a convenient means of parallelizing the execution of a function across multiple input values, distributing the input data across processes (data parallelism). The following example demonstrates the common practice of defining such functions in a module so that child processes can successfully import that module.

This basic example of data parallelism using Pool:

from multiprocessing import Pool
 
def f(x):
    return x*x
 
if __name__ == '__main__':
    with Pool(5) as p:
        print(p.map(f, [1, 2, 3]))

Asyncio in Python

• Coroutines and Tasks - Python official docs with asyncio
• Async IO in Python A Complete Walkthrough – Real Python
• How does asyncio actually work? $\leftarrow$ excellent, elucidating post