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I have an implementation of a network system based on Twisted. I noticed that when I run a function (which do some mathematical operations and prints the result) in a new thread, not in the main one, the print function causes Segmentation fault. Is it possible? Is there an option to avoid that?
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Python doesn't support multi-threading because Python on the Cpython interpreter does not support true multi-core execution via multithreading. However, Python does have a threading library. The GIL does not prevent threading.
The print() function is a built-in function for printing a string on stdout and is not thread-safe.
Python is NOT a single-threaded language. Python processes typically use a single thread because of the GIL. Despite the GIL, libraries that perform computationally heavy tasks like numpy, scipy and pytorch utilise C-based implementations under the hood, allowing the use of multiple cores.
Multithreading in Python By default, your Python programs have a single thread, called the main thread. You can create threads by passing a function to the Thread() constructor or by inheriting the Thread class and overriding the run() method.
My approach, based on Bram Cohen's suggestion:
Define a global Lock variable
from threading import Lock
s_print_lock = Lock()
Define a function to call print with the Lock
def s_print(*a, **b):
"""Thread safe print function"""
with s_print_lock:
print(*a, **b)
Use s_print instead of print in your threads.
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