What is a python thread


I have several questions regarding Python threads.

  1. Is a Python thread a Python or OS implementation?
  2. When I use htop a multi-threaded script has multiple entries – the same memory consumption, the same command but a different PID. Does this mean that a [Python] thread is actually a special kind of process? (I know there is a setting in htop to show these threads as one process – Hide userland threads)
  3. Documentation says:

A thread can be flagged as a “daemon thread”. The significance of this
flag is that the entire Python program exits when only daemon threads
are left.

My interpretation/understanding was: main thread terminates when all non-daemon threads are terminated.

So python daemon threads are not part of Python program if “the entire Python program exits when only daemon threads are left”?

Asked By: warvariuc



  1. Python threads are implemented using OS threads in all implementations I know (C Python, PyPy and Jython). For each Python thread, there is an underlying OS thread.

  2. Some operating systems (Linux being one of them) show all different threads launched by the same executable in the list of all running processes. This is an implementation detail of the OS, not of Python. On some other operating systems, you may not see those threads when listing all the processes.

  3. The process will terminate when the last non-daemon thread finishes. At that point, all the daemon threads will be terminated. So, those threads are part of your process, but are not preventing it from terminating (while a regular thread will prevent it). That is implemented in pure Python. A process terminates when the system _exit function is called (it will kill all threads), and when the main thread terminates (or sys.exit is called), the Python interpreter checks if there is another non-daemon thread running. If there is none, then it calls _exit, otherwise it waits for the non-daemon threads to finish.

The daemon thread flag is implemented in pure Python by the threading module. When the module is loaded, a Thread object is created to represent the main thread, and it’s _exitfunc method is registered as an atexit hook.

The code of this function is:

class _MainThread(Thread):

    def _exitfunc(self):
        t = _pickSomeNonDaemonThread()
        if t:
            if __debug__:
                self._note("%s: waiting for other threads", self)
        while t:
            t = _pickSomeNonDaemonThread()
        if __debug__:
            self._note("%s: exiting", self)

This function will be called by the Python interpreter when sys.exit is called, or when the main thread terminates. When the function returns, the interpreter will call the system _exit function. And the function will terminate, when there are only daemon threads running (if any).

When the _exit function is called, the OS will terminate all of the process threads, and then terminate the process. The Python runtime will not call the _exit function until all the non-daemon thread are done.

All threads are part of the process.

My interpretation/understanding was: main thread terminates when all
non-daemon threads are terminated.

So python daemon threads are not part of python program if “the entire
Python program exits when only daemon threads are left”?

Your understanding is incorrect. For the OS, a process is composed of many threads, all of which are equal (there is nothing special about the main thread for the OS, except that the C runtime add a call to _exit at the end of the main function). And the OS doesn’t know about daemon threads. This is purely a Python concept.

The Python interpreter uses native thread to implement Python thread, but has to remember the list of threads created. And using its atexit hook, it ensures that the _exit function returns to the OS only when the last non-daemon thread terminates. When using “the entire Python program”, the documentation refers to the whole process.

The following program can help understand the difference between daemon thread and regular thread:

import sys
import time
import threading

class WorkerThread(threading.Thread):

    def run(self):
        while True:
            print 'Working hard'

def main(args):
    use_daemon = False
    for arg in args:
        if arg == '--use_daemon':
            use_daemon = True
    worker = WorkerThread()

if __name__ == '__main__':

If you execute this program with the ‘–use_daemon’, you will see that the program will only print a small number of Working hard lines. Without this flag, the program will not terminate even when the main thread finishes, and the program will print Working hard lines until it is killed.

Answered By: Sylvain Defresne
  1. Python threads are practically an interpreter implementation, because the so called global interpreter lock (GIL), even if it’s technically using the os-level threading mechanisms. On *nix it’s utilizing the pthreads, but the GIL effectivly makes it a hybrid stucked to the application-level threading paradigm. So you will see it on *nix systems multiple times in a ps/top output, but it still behaves (performance-wise) like a software-implemented thread.

  2. No, you are just seeing the kind of underlying thread implementation of your os. This kind of behaviur is exposed by *nix pthread-like threading or im told even windows does implement threads this way.

  3. When your program closes, it waits for all threads to finish also. If you have threads, which could postpone the exit indefinitly, it may be wise to flag those threads as “daemons” and allow your program to finish even if those threads are still running.

Some reference material you might be interested:

Answered By: Don Question

I’m not familiar with the implementation, so let’s make an experiment:

import threading
import time

def target():
    while True:
        print 'Thread working...'


for i in range(NUM_THREADS):
    thread = threading.Thread(target=target)
  1. The number of threads reported using ps -o cmd,nlwp <pid> is NUM_THREADS+1 (one more for the main thread), so as long as the OS tools detect the number of threads, they should be OS threads. I tried both with cpython and jython and, despite in jython there are some other threads running, for each extra thread that I add, ps increments the thread count by one.

  2. I’m not sure about htop behaviour, but ps seems to be consistent.

  3. I added the following line before starting the threads:

    thread.daemon = True

    When I executed the using cpython, the program terminated almost immediately and no process was found using ps, so my guess is that the program terminated together with the threads. In jython the program worked the same way (it didn’t terminate), so maybe there are some other threads from the jvm that prevent the program from terminating or daemon threads aren’t supported.

Note: I used Ubuntu 11.10 with python 2.7.2+ and jython 2.2.1 on java1.6.0_23

Answered By: jcollado

There are great answers to the question, but I feel the daemon threads question is still not explained in a simple fashion. So this answer refers just to the third question

"main thread terminates when all non-daemon threads are terminated."

So python daemon threads are not part of Python program if "the entire Python program exits when only daemon threads are left"?

If you think about what a daemon is, it is usually a service. Some code that runs in an infinite loop, that serves request, fill queues, accepts connections, etc. Other threads use it. It has no purpose when running by itself (in a single process terms).

So the program can’t wait for the daemon thread to terminate, because it might never happen. Python will end the program when all non daemon threads are done. It also stops the daemon threads.

To wait until a daemon thread has completed its work, use the join() method.
daemon_thread.join() will make Python to wait for the daemon thread as well before exiting. The join() also accepts a timeout argument.

Answered By: Chen A.
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