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Fixing the No module named 'numpy.core._multiarray_umath' Error in Python

Автор: vlogize

Загружено: 2025-04-09

Просмотров: 6

Описание: Encountering the `No module named 'numpy.core._multiarray_umath'` error when using matplotlib_cpp with Numpy? This guide provides a comprehensive guide to troubleshoot and resolve the issue effectively.
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This video is based on the question https://stackoverflow.com/q/75396739/ asked by the user '0xBADF00' ( https://stackoverflow.com/u/5082245/ ) and on the answer https://stackoverflow.com/a/75432328/ provided by the user '0xBADF00' ( https://stackoverflow.com/u/5082245/ ) 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: No module named 'numpy.core._multiarray_umath'

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.
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Resolving the No module named 'numpy.core._multiarray_umath' Error

If you've recently encountered the frustrating error message, "No module named 'numpy.core._multiarray_umath'", while trying to use matplotlib_cpp with Python and Numpy, you're not alone. Many users, especially those operating on Windows 11 with Python 3.11 and Numpy 1.24.2, report running into this issue frequently.

Understanding the Error

This error typically suggests that the Python interpreter is unable to locate a specific required module (_multiarray_umath) that Numpy is expected to provide. Below are key reasons why this may occur:

Incomplete installation of Numpy.

Conflicting installations of Python or Numpy.

Usage of incorrect binaries (debug vs. release binaries).

Issues with your virtual environment setup.

If you've already tried reinstalling Numpy following numerous online guides and found no success, you're likely looking for a more effective solution.

Solution: Using Release Binaries

Luckily, there's a straightforward way to resolve this issue, which is to use the release binaries instead of the debug binaries. Here’s a step-by-step guide to implement this solution effectively:

Step 1: Verify Your Current Installation

First, ensure that your current installation of Numpy is indeed conflicting. You can do this by navigating to your site-packages directory:

Open Command Prompt.

Run the following command:

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

Note the path for your packages, usually something like C:\Users\YourName\AppData\Local\Programs\Python\Python311\Lib\site-packages.

Step 2: Locate the Numpy Folder

Go to the identified path and browse to the numpy folder.

Confirm the presence of the following file:

_multiarray_umath.cp311-win_amd64.pyd

If you do not see a plain _multiarray_umath file, this indicates that the installation could be problematic.

Step 3: Remove Debug Binaries

To proceed, make sure you're not using any debug binaries:

If you have any debug binaries (check with a file extension like .pyd that does not have the release in its name), delete them.

Step 4: Reinstall Numpy with Release Binaries

You may need to uninstall the current version of Numpy:

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

After ensuring all remnants are removed, reinstall Numpy using the following command to ensure release binaries are fetched:

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

Step 5: Verification

To finalize, verify your installation by trying to import Numpy:

Open a Python shell or a script.

Enter:

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

If the version prints without any error, congratulations! You've successfully resolved the issue.

Troubleshooting Virtual Environments with Anaconda

If you were experimenting with a virtual environment like Anaconda but faced issues with building matplotlib_cpp, here's what you can do:

Ensure you have activated your environment using:

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

Then follow the same installation steps mentioned above within the activated environment.

Conclusion

Resolving the No module named 'numpy.core._multiarray_umath' error may seem daunting, but by following the above steps, you can eliminate the issue effectively. Always remember to double-check the type of binaries you are using and ensure your environment is configured correctly.

If you encounter further issues, don’t hesitate to seek additional support from community forums or consider reinstalling your Python environment entirely.

Happy coding!

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Fixing the No module named 'numpy.core._multiarray_umath' Error in Python

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