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Скачать или смотреть Resolving Error Code 137 When Running Django Tests in GitHub Actions: A Simple Fix

  • vlogize
  • 2025-04-04
  • 5
Resolving Error Code 137 When Running Django Tests in GitHub Actions: A Simple Fix
Running django tests in github actions causes Error code 137djangodockerunit testingdocker composegithub actions
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Описание к видео Resolving Error Code 137 When Running Django Tests in GitHub Actions: A Simple Fix

Discover how to resolve `Error Code 137` from GitHub Actions while running Django tests with Docker. Learn how to fix environmental variable issues using GitHub secrets.
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This video is based on the question https://stackoverflow.com/q/72797522/ asked by the user 'WholesomeGhost' ( https://stackoverflow.com/u/6367928/ ) and on the answer https://stackoverflow.com/a/72814753/ provided by the user 'WholesomeGhost' ( https://stackoverflow.com/u/6367928/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

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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.

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Resolving Error Code 137 When Running Django Tests in GitHub Actions

When pushing changes to your repository, it's essential for your CI/CD pipeline to run smoothly. However, encountering errors like Error Code 137 during Django tests in GitHub Actions can be frustrating. This error is typically associated with memory issues, and if you are running your tests in a Docker container, it can lead to a halt in your workflow. In this post, we'll delve into the problem and offer a straightforward fix.

Understanding the Problem

You have an application developed with Django and deployed using Docker Compose. You configured GitHub Actions to automatically run unit tests upon every push to the main branch. However, during this process, you received the following error message:

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

Upon investigation, you might conclude that this error indicates a memory issue, potentially due to insufficient resources assigned to your Docker containers during testing. But what if the real culprit is misconfigured environmental variables?

The Solution: Fixing GitHub Secrets

In this situation, the root cause of Error Code 137 was not a memory-related issue, as initially suspected. The issue stemmed from not correctly setting GitHub Secrets for your environment variables. Here's how to resolve it effectively:

Step-by-Step Guide to Resolving the Issue

Create a Single GitHub Secret:

Instead of separately defining each environment variable as an individual secret, you can create one main secret.

This secret will encapsulate all your necessary environment variables in a single string, enabling you to streamline the setup process.

Update the .yml Configuration:

Modify the section of your GitHub Actions workflow file (.github/workflows/<your-file>.yml) where you create the environment file.

Here’s how to adjust your step for creating the env file in the workflow:

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

Key Points to Remember

Check for Proper Configuration: Ensure that your secret value in GitHub contains all necessary environment variables correctly formatted.

Avoid Overcomplicating Secrets: Keeping all variables in one secret simplifies the process and helps avoid errors related to multiple individual secrets.

Test Again: After modifying the workflow, push your changes to the repository and check if the tests run successfully without the Error Code 137.

Conclusion

While facing Error Code 137 in GitHub Actions during Django testing might initially lead you to believe it's a memory issue, sometimes the answer lies in your configuration—specifically, how you've set up your environment variables. By consolidating your secrets and adjusting your workflow, you can create a more efficient testing pipeline, allowing your CI/CD processes to run seamlessly.

Next time you run into an exit code or unexpected error in your GitHub workflows, remember that a simple configuration fix might just do the trick!

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