Is multi-threading supported in Python and can it speed up execution time as well

Question

So why is it that everyone keep saying that Python is locked by the GIL and that only one thread can run at a time? It clearly does work. Or is there some distinction I'm not getting here?

Many posters/respondents also keep mentioning that threading is limited because it does not make use of multiple cores. But I would say they are still useful because they do work simultaneously and thus get the combined workload done faster. I mean why would there even be a Python thread module otherwise?

Answer 1

The GIL does not prevent threading. All the GIL does is make sure only one thread is executing Python code at a time; control still switches between threads.

What the GIL prevents then, is making use of more than one CPU core or separate CPUs to run threads in parallel.

This only applies to Python code. C extensions can and do release the GIL to allow multiple threads of C code and one Python thread to run across multiple cores. This extends to I/O controlled by the kernel, such as select() calls for socket reads and writes, making Python handle network events reasonably efficiently in a multi-threaded multi-core setup.

Any task that tries to get a speed boost from parallel execution, using pure Python code, will not see a speed-up as threaded Python code is locked to one thread executing at a time. If you mix in C extensions and I/O, however (such as PIL or numpy operations) and any C code can run in parallel with one active Python thread.