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Discover how to fix the `ModuleNotFoundError` when importing custom modules in Python, ensuring a seamless development experience for your Flask applications. --- This video is based on the question https://stackoverflow.com/q/73169785/ asked by the user 'gwaugh' ( https://stackoverflow.com/u/19385921/ ) and on the answer https://stackoverflow.com/a/73172325/ provided by the user 'gwaugh' ( https://stackoverflow.com/u/19385921/ ) 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: Import of my custom module could not be resolved 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. --- Resolving the ModuleNotFoundError in Python Imports: A Quick Guide When developing applications in Python, especially with frameworks like Flask, importing custom modules is a common task. However, a frustrating issue can arise: the dreaded ModuleNotFoundError. In this post, we’ll delve into a specific case where one module fails to import while others work fine, and we’ll explore a solution that solved the issue. Understanding the Problem Consider the following file structure for a Python project: [[See Video to Reveal this Text or Code Snippet]] In this setup, you might attempt to run your Flask application by executing python app.py. However, you encounter an error like this: [[See Video to Reveal this Text or Code Snippet]] This indicates that Python cannot find the specified data_analysis module, despite your other imports (like begin and model_creation) working perfectly. Investigating the Cause At first glance, it might seem that the issue is related to the way relative or absolute imports are handled in Python. Three key points to consider: File Structure: Ensure your project structure is correctly set to allow imports. The hierarchy plays a significant role in how modules are accessed. Import Statements: Verify that your import statements are correct. Sometimes, typos or incorrect paths cause modules to go unrecognized. File Anomalies: Occasionally, issues might arise from the specific file itself, rather than the code structure or import statements. Implementing the Solution In this particular case, the solution was surprisingly simple but effective. Here’s how it was tackled: Copy the Module: Take the data_analysis.py file and create a duplicate of it within the same directory. Delete the Original: Remove the original data_analysis.py file from the directory. Rename the New File: Rename the copied file from something like data_analysis_copy.py back to data_analysis.py. After following these steps, the ModuleNotFoundError ceased, allowing the import statement to work seamlessly. Why This Worked: This solution likely worked due to one of several reasons: There might have been hidden issues or corruption in the original file, causing Python to misinterpret it. Renaming the file could have forced the interpreter to refresh its cached state about the module, allowing it to recognize and import properly. Conclusion Module import errors can be daunting, especially when they seem confined to specific files. In our example, restructuring or manipulating the module—through copying and renaming—resolved the issue effectively. When faced with similar situations, don’t hesitate to explore unconventional solutions. It may save you time and frustration, allowing you to focus on building your application. Keep Coding! If you are building applications with Python and Flask, and you find yourself getting stuck, remember that each error is an opportunity to learn more about the language and troubleshoot effectively.