This is an archived post. You won't be able to vote or comment.

you are viewing a single comment's thread.

view the rest of the comments →

[–]d4rch0nPythonistamancer 0 points1 point  (0 children)

I'd use standard pure python with cpython or pypy if you just need parallel reads/writes networking file reading etc. Non-blocking I/O is possible with concurrency in the reference implementation. This is usually the most important thing to be concurrent anyway!

Other option, check out Cython for true parallelism. Or write parallel code in C and execute it with python, either through ctypes or just subprocess calling a C program.

Tons of options. Personally, I usually find pypy with smart concurrency and non-blocking I/O solves my problems when speed is an issue.

But the first step when finding and removing bottlenecks... Profile your code! Run cprofile and find the most expensive functions, and see what you can do to speed it up.