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Скачать или смотреть How to Use multiprocessing.Value on Mac with Spawn

  • vlogize
  • 2025-03-28
  • 1
How to Use multiprocessing.Value on Mac with Spawn
How do I use multprocessing.Value (or other shared resources) on Mac with Spawn?pythonmultithreadingmultiprocessingshared memory
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Описание к видео How to Use multiprocessing.Value on Mac with Spawn

Discover how to effectively use `multiprocessing.Value` and shared resources on Mac with Spawn. Follow this detailed guide for clear instructions and troubleshooting tips.
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This video is based on the question https://stackoverflow.com/q/74047092/ asked by the user 'thc' ( https://stackoverflow.com/u/2723734/ ) and on the answer https://stackoverflow.com/a/74047200/ provided by the user 'Ahmed AEK' ( https://stackoverflow.com/u/15649230/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: How do I use multprocessing.Value (or other shared resources) on Mac with Spawn?

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The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license.

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How to Use multiprocessing.Value on Mac with Spawn: A Step-by-Step Guide

If you've ever tried to use Python's multiprocessing module on a Mac, you may have encountered some unexpected behavior. One common issue arises when using multiprocessing.Value. Particularly, you may find that the shared value does not behave as intended when using the Spawn start method. In this guide, we'll explore how to properly set up your code to ensure that multiprocessing.Value works smoothly on Mac systems.

The Problem

You have a simple application where you want to share a counter variable across multiple processes. Your initial attempt looks something like this:

[[See Video to Reveal this Text or Code Snippet]]

When you run this on a Mac, you expect to see the output 4, since you're incrementing the shared variable across four processes. However, it outputs 0. This behavior is due to the way the Spawn start method initializes processes on Mac, which differs from the Fork method used in most Linux distributions.

The Solution

To solve this problem, you need to adjust where and how you initialize the counter. The key steps are outlined below.

Step 1: Move the Counter Declaration to the Main Function

Instead of declaring counter at the global level, declare it within the main function. This ensures that when you create the pool of processes, the counter is correctly initialized for each process.

Step 2: Use an Initializer Function

To access the shared value in your worker processes, you need to define an initializer function. This function will set counter as a global variable within child processes.

Here is the updated code to implement these changes:

[[See Video to Reveal this Text or Code Snippet]]

Explanation of the New Code

Initialization: The counter is created freshly in the main function, which is necessary when using the Spawn method.

Initializer Function (setup_fn): This function takes the counter as an argument and sets it as a global variable. It ensures that all worker processes have access to the same instance of counter.

Calling the Worker Function: The test_fun function modifies the shared value by acquiring a lock on counter, ensuring that increments do not clash and every process updates the shared state correctly.

Conclusion

Using multiprocessing.Value with the Spawn method on a Mac requires a few extra steps compared to using Fork on Linux. By properly setting up your shared resources—declaring your counter within the main process and utilizing an initializer function—you can effectively share data across multiple processes.

Now that you're equipped with this knowledge, go ahead and apply these changes in your applications. You should see the expected behavior, with the output being 4 this time. Happy coding!

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