Understanding Why Your Whole Code Executes Multiple Times in Multiprocessing in Python

Learn why your Python code with multiprocessing might execute multiple times and how to resolve it effectively.
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Why Your Whole Code is Executing Three Times Instead of Just p1 and p2

If you've ever tried to run a Python script utilizing the multiprocessing module and noticed that the entire script seems to execute multiple times, you're not alone. A common point of confusion arises when developers see output that indicates their main code block is being executed more than expected. In this guide, we'll explore why that happens and how to fix the issue.

The Problem: Unexpected Multiple Executions

Let's take a look at an example scenario. You have written a Python script that utilizes multiprocessing to run two processes simultaneously. You might expect that only the two target functions (p1 and p2) would execute, but instead, the entire script seems to run several times, leading to unexpected output.

Here's a snippet of code that encapsulates the issue:

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

Your output can resemble the following:

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

Why This is Happening

The spawn Method and Global Scope Execution

The behavior exhibited in the output can often be attributed to the platform you are working on, particularly if it uses the spawn method for creating new processes (such as on Windows).

Global Scope Execution: In Python, any code defined in the global scope will execute in each new child process. This includes:

Variable assignments

Function definitions

Import statements

Because of this, when you run your script, both child processes execute everything at the global level, not just your target function.

Understanding the Output Layout

In your output, you see instances of Finished in 0.0 seconds(s) appearing multiple times. This result occurs because the section of code responsible for importing modules and initializing variables is executed each time a process is spawned.

The Solution: Properly Using if __name__ == '__main__'

To resolve the issue, you’ll need to ensure that code which should run only once does not appear in the global scope or is properly encapsulated within the if __name__ == '__main__': guard. Here’s how you can adjust your script:

Modified Code Example

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

Expected Output

With the fixed code, your output will reflect properly as expected:

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

Key Takeaways

Global Scope Execution: Any code in global scope executes in every newly spawned process.

Encapsulate Code: Use if __name__ == '__main__': to ensure code runs only in the main process.

Module Imports: Consider where you place imports when working with multiprocessing to avoid repeated execution.

Implementing these adjustments will help you avoid similar issues in the future and run your multiprocessing code effectively. Don't forget to test your code on the appropriate platform to ensure consistent behavior. Happy coding!