- 1 year ago
Multiprocessing python within frozen script
When using multiprocessing in Python within a frozen script (e.g., a script bundled using tools like PyInstaller or cx_Freeze), you need to take certain considerations into account to ensure proper execution. Here are a few tips:
Specify
freeze_support()
:
In the main entry point of your script, before creating any multiprocessing processes, add the following code:pythonfrom multiprocessing import freeze_support
if __name__ == '__main__':
freeze_support()
# Your code here
This is necessary to initialize the multiprocessing module correctly in frozen script environments.
Use
spawn
orforkserver
start methods:
By default, the multiprocessing module uses thefork
start method, which may not work in all frozen script environments. Instead, consider using thespawn
orforkserver
start methods, which are more compatible in these scenarios. You can specify the start method by setting themultiprocessing.set_start_method()
before creating any processes.pythonfrom multiprocessing import set_start_method
if __name__ == '__main__':
freeze_support()
set_start_method('spawn') # or 'forkserver'
# Your code here
Avoid importing the main script:
In some cases, frozen script environments may encounter issues if the main script is imported by child processes. To avoid potential conflicts, it is generally recommended to organize your code in a way that minimizes the need for importing the main script from child processes. Instead, encapsulate the functionality that you need within separate modules and import those modules directly.
By following these guidelines, you can ensure proper execution of multiprocessing code within a frozen script environment. However, keep in mind that frozen script environments can have their own limitations and considerations, so it's always a good idea to refer to the documentation of the specific freezing tool you are using and test your script thoroughly in the target environment.