Скачать или смотреть Resolving Import Errors in Visual Studio Code with Pylance and Hatch

Discover how to fix import resolution issues in Visual Studio Code when using Pylance with the Hatch build tool. Follow our comprehensive guide to ensure proper Python interpreter configuration.
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This video is based on the question https://stackoverflow.com/q/76487207/ asked by the user 'Matija Sirk' ( https://stackoverflow.com/u/6212530/ ) and on the answer https://stackoverflow.com/a/77272527/ provided by the user 'Taejun' ( https://stackoverflow.com/u/6197064/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

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Resolving Import Errors in Visual Studio Code with Pylance and Hatch: A Step-by-Step Guide

If you’re a Python developer using Visual Studio Code (VSCode) alongside the Pylance extension and the Hatch build tool, you may have encountered a frustrating issue: import errors appearing for modules that were previously resolved correctly. This problem typically manifests as a yellow squiggly line beneath your imports, with a tooltip indicating that the import cannot be resolved. Let’s dive into the details of why this happens and explore an effective solution.

The Problem

When you create a Python project using the command hatch new name, imports are usually resolved correctly. However, upon reopening the project, you might see messages like:

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

This issue often arises from VSCode using the incorrect Python interpreter. Specifically, it may default to the global Python interpreter rather than the virtual environment (venv) that Hatch manages.

Typically, when this occurs, developers can resolve it by configuring the .vscode/settings.json file to point to the correct Python interpreter. For example:

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

However, since you’re using Hatch—a tool designed to manage environments automatically—this traditional approach might not work effectively. So, how can we fix this?

Understanding Hatch Environment Management

Hatch manages virtual environments for your project, which means they might not be located in the expected project directory. To better understand the solution, we need to look into how Hatch defines environments in the pyproject.toml configuration file.

Initial Troubleshooting Steps

Check the Existing Configuration: You might have tried adding a [dirs.env] section to your pyproject.toml, as shown below:

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

Attempt to Prune and Recreate: By running the following commands, you hoped to delete the existing default environment and create it again:

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

Querying Environment Locations: Using hatch env find default should ideally point to your updated environment location. Instead, you find it still points to an old location in the AppData directory.

Discovering the Effective Solution

After investigating the issue, the solution lies in a different section of the pyproject.toml file. Instead of specifying the environment location in [dirs.env], you should define it within the [tool.hatch.envs.default] section. Here’s how to do it:

Update Create the Environment Path:

Replace your previous entry with:

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

Doing so ensures that Pylance resolves the imports correctly by explicitly telling Hatch to use the .hatch directory for your environment.

Verify the Configuration: After updating the configuration, you can recreate the environment again:

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

Confirm the Correct Environment: Use hatch env find default to verify that it now points to the correct path within the .hatch directory.

Conclusion

By understanding how to configure the Python interpreter settings correctly with hatch managing your environments, you can resolve these import issues efficiently. If you run into similar problems in the future, remember to adjust your pyproject.toml to prioritize the [tool.hatch.envs.default] section, ensuring that Pylance picks up the correct environment path. This simple change can save you time and prevent frustration while coding in VSCode.

Stay curious and happy coding!