Python Concurrency and Parallelism

threading

multiprocessing

asyncio

concurrent.futures

Dask

Flask

Django

Pyramid

A global interpreter lock that ensures only one thread can execute Python bytecode at a time.

A threading mechanism that allows Python to execute multiple threads in parallel.

A module for managing concurrent I/O in Python.

A library for creating and managing parallel processes in Python.

To provide a way to communicate between threads.

To prevent race conditions in multithreaded code.

To ensure only one thread can access a shared resource at a time.

To provide a way to limit the number of threads that can access a resource at a time.

result()

get()

retrieve()

fetch()

threading

multiprocessing

concurrent.futures

asyncio

It can be more difficult to share state between processes.

It can be less efficient than using threads.

It can be more difficult to synchronize tasks between processes.

It can be more difficult to detect and debug issues in multiprocessing code.

cancel()

stop()

terminate()

kill()

It is the execution of multiple threads simultaneously.

It is the execution of multiple processes simultaneously.

It is the execution of a single thread in multiple ways.

None of the above.

Using the multiprocessing module

Using the threading module

Using the concurrent.futures module

Using the asyncio module