Resolving the pickle data error when loading NumPy arrays in Python

A guide on fixing the common `ValueError: Cannot load file containing pickled data` error in Python while working with NumPy arrays.
---
This video is based on the question https://stackoverflow.com/q/65518790/ asked by the user 'Farhan Kabir' ( https://stackoverflow.com/u/13118262/ ) and on the answer https://stackoverflow.com/a/65539610/ provided by the user 'Farhan Kabir' ( https://stackoverflow.com/u/13118262/ ) 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: Trouble loading numpy array where they show pickle data error in python

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.
---
Troubleshooting NumPy Array Loading Issues in Python

When working with NumPy arrays in Python, the convenience of saving and loading data using .npy files can sometimes result in frustrating errors. One such issue arises from the message: "Cannot load file containing pickled data when allow_pickle=False." If you're encountering problems loading an array that you have saved with NumPy's np.save() function, you're in the right place.

Let’s break down the process and find a solution!

Understanding the Problem

You attempted to save a simple array:

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

But when you tried to load it later with:

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

You encountered the following error:

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

Why Does This Error Occur?

This error typically occurs when the array is stored using a format not compatible with the current loading method. By default, NumPy does not allow pickled files to ensure security and to avoid unintentional execution of arbitrary code.

A Deeper Dive into the Alternative Fix

You then tried a workaround:

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

Only to face a new error:

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

This indicates that the file can't be read properly, likely because it wasn't saved in a way that allows pickling.

The Solution: Implementing a Delay

Based on valuable community support, including suggestions from users like @ hpaulj, a useful solution is to simply introduce a delay before attempting to load the saved array. This ensures that the writing process completes before any reading occurs.

Here’s How to Implement It

Add a Delay: Insert a sleep time for the program to wait before trying to load the saved array:

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

Review Your Code: Ensure that your entire function is structured to account for this delay, as illustrated in your EPS_process() function.

Example of Updated EPS_process

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

Conclusion

In many cases, the error you're encountering when loading a NumPy array with allow_pickle=False is simply a race condition between the save and load operations. By implementing a short delay, you can effectively avoid this issue and ensure that your data integrity remains intact.

This small change can save you from the frustrating pickle errors and make your coding experience smoother. Happy coding!