Скачать или смотреть How to Initialize Multiprocessing Pool with a Sequential Argument in Python

Discover how to properly initialize a `multiprocessing pool` with sequential arguments in Python, overcoming common challenges.
---
This video is based on the question https://stackoverflow.com/q/63564028/ asked by the user 'Karlson' ( https://stackoverflow.com/u/975797/ ) and on the answer https://stackoverflow.com/a/63565472/ provided by the user 'Darkonaut' ( https://stackoverflow.com/u/9059420/ ) 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: Multiprocess pool initialization with sequential initializer argument

Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l...
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.

If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
---
Understanding the Problem: Multiprocess Pool Initialization

When working with Python's multiprocessing module, one may encounter issues while trying to pass sequential parameters to initialize each process within a pool. This scenario often leads to the dreaded error message:

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

This occurs because generators, like the one created in the original code using yield, cannot be serialized (or "pickled") by the multiprocessing library—essential for transferring data between processes. In this guide, we will explore how to resolve this issue by ensuring that each process in the pool is initialized with a unique, sequential identifier.

Solution Overview

The main takeaway for resolving the initialization issue in multiprocessing is to move away from using a generator for creating sequential numbers. Instead, there are two primary strategies you can employ:

Extracting the Sequential Number from Process.name.

Utilizing multiprocessing.Value as a counter.

Method 1: Using Process.name

The simplest solution is to extract the sequential number directly from the process name. The multiprocessing library names each child process in the format SpawnPoolWorker-X, where X is the process ID.

To achieve this, you can add the following line within your initializer function:

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

This extracts the unique process number, allowing you to use it as a sequential identifier.

Method 2: Using multiprocessing.Value

If you require more control or need to start your sequence from a specific number, you can utilize multiprocessing.Value. This allows you to create a shared counter that each worker can access to get a unique identifier.

Implementation Steps

Define the initializer function. This function will acquire a lock, retrieve the current value from the counter, and increment the counter for the next worker.

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

Set up the main function to create the process pool. Here, you'll create a Value to hold the counter:

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

Example Output

When you run the given implementation, you will see an output similar to:

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

This confirms that each worker was correctly assigned a sequential ID.

Conclusion

By using either the process name extraction or the Value counter, you can effectively initialize your multiprocessing pool with unique, sequential arguments. These methods not only resolve the original error but also provide an organized and efficient way to handle process identifiers in Python’s multiprocessing environment.

Employ these techniques in your future multiprocess projects, and streamline your process handling with confidence!