The root cause of this issue typically lies in the way you're managing your processes and threads. When using multiprocessing, it's essential to ensure that each process has its own unique namespace to avoid conflicts between processes.Another possible reason for this error is when you're trying to

How do I fix: Using the `Process` class and manual thread management?

Step 1: Create a new process for each item in the list of image URLs using the `Process` class.Step 2: Use the `start()` method to start the process, and then use the `join()` method to wait for the process to finish before moving on to the next one.Step 3: Make sure to handle any exceptions that ma

Software⏱️ 3 min read📅 2026-06-03

How to Fix: Multiprocessing causes Python to crash and gives an error may have been in progress in another thread when fork() was called

Q: Best Solutions to Fix It Using the `Pool` class from the `multiprocessing` library?

Step 1: Create a pool of worker processes using the `Pool` class, specifying the number of worker processes you want to use.Step 2: Use the `map()` function to apply your function to each item in the list of image URLs.Step 3: Make sure to close the pool when you're done with it to free up system re

Multiprocessing issue in Python causing crash and error due to concurrent execution of threads.

Quick Answer: Use ProcessPoolExecutor instead of forking processes, as it handles thread safety and synchronization issues automatically. Also, ensure that the tasks are properly synchronized using locks or queues.

📋 Table of Contents

⚠️ Common Causes
✅ Best Solutions to Fix It
💡 Conclusion

The Multiprocessing module in Python can sometimes cause crashes when used incorrectly, particularly in situations where multiple processes are created and managed simultaneously.

This error message 'may have been in progress in another thread when fork() was called' is often seen when using the multiprocessing library to manage multiple processes concurrently.

⚠️ Common Causes

The root cause of this issue typically lies in the way you're managing your processes and threads. When using multiprocessing, it's essential to ensure that each process has its own unique namespace to avoid conflicts between processes.
Another possible reason for this error is when you're trying to access shared resources between processes without proper synchronization. This can lead to unexpected behavior and crashes.

✅ Best Solutions to Fix It

Using the `Pool` class from the `multiprocessing` library

Step 1: Create a pool of worker processes using the `Pool` class, specifying the number of worker processes you want to use.
Step 2: Use the `map()` function to apply your function to each item in the list of image URLs.
Step 3: Make sure to close the pool when you're done with it to free up system resources.

Using the `Process` class and manual thread management

Step 1: Create a new process for each item in the list of image URLs using the `Process` class.
Step 2: Use the `start()` method to start the process, and then use the `join()` method to wait for the process to finish before moving on to the next one.
Step 3: Make sure to handle any exceptions that may occur during the execution of each process.

💡 Conclusion

To avoid this error, it's crucial to understand how to properly manage your processes and threads when using the multiprocessing library. By following these steps, you can ensure that your code runs smoothly and efficiently, even with large datasets like image URLs.

Did this fix your problem?

If not, try searching for specific error codes.

🔍 Search Error Database

❓ Frequently Asked Questions

🛠️ Related Fixes

How to Fix: Pc crashes shortly after launching game (rainbow

Fix Pc crashes shortly after launching game (rainbow six siege). Compl

How to Fix: Installing an APK on a locked down phone

Installing an APK on a locked down phone: Try using a rooted device, e

How to Fix: New PC build- no signal and no clue

Fix New PC build- no signal and no clue. Complete troubleshooting guid