Python multithreading model

Question

I have been studying multithreading in python for a while, however I was confused on a few issues-

1. Firstly, are the threads created by the python threading library user level or kernel level threads?

Books say that user level threads must be mapped to kernel threads and the operating system only creates and maintains kernel level threads.

Which thread model will be used in the python threading library? Further, who makes the choice between kernel and user level threads? Is it the operating system or can the programmer have a say?

If the many-to-one model (illustrated in the picture) is used, I think it is not real multithreading, since all the threads map to a single kernel thread.

2. Is there a way to direct the operating system to adhere to a certain threading model in my python program?

3. Can all running threads for a process be shown with their state separately marked as either kernel or user level. Also can the mappings between the two levels (user and kernel) be shown?

Answer 1

Usually, you never create 'kernel level threads' directly - everything you do in user space executes in user space, otherwise even a random browser JavaScript would be executing at the kernel level guaranteeing that within seconds the whole internet would go dark.

Thus, in most languages, a threading interface (if supported) is far removed from the actual 'kernel threads' and depending on implementation it will either link to a lower-level threading interface (pthreads for example) or just simulate threading unbeknownst to the user. Going down that chain, pthreads may or may not link to actual 'kernel' threads (it happens to be true on Linux, but on Windows there is another level of separation) but even then, the code executes in the user space - the 'supporting' kernel thread is there to control the scheduling the code runs separately.

When it comes to CPython, its threading interface links to pthreads so, technically, there is a chain from a Python thread all the way down to the kernel threads. However, Python also has the dreaded GIL pretty much guaranteeing that, with some rare exceptions mostly related to I/O, no two threads ever execute at the same time, pretty much making its threads operate in a cooperative multitasking mode. However, since on most systems processes are also backed by kernel threads, you can still utilize them in all their glory by using the multiprocessing interface.

Also, until you have multiple cores/CPUs on your system even kernel threads execute in a cooperative multitasking mode so, technically, kernel threads don't guarantee actual multi-threading as you're describing it.

As for how to list threads and their dependencies, you can use top -H -p <pid> to show the thread tree of a process.