Pydantic Import Error: Base Settings Have Been Moved

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In this article, we will explore the issue of a PydanticImportError that is raised when trying to import BaseSettings from the pydantic package. We’ll delve into the cause of this error and provide solutions for resolving it.

Understanding Pydantic and Base Settings

Pydantic is a popular Python library used for building robust, fast, scalable, and type-safe data models. It provides a powerful way to define data structures and perform validation on them.

BaseSettings is a class in the pydantic package that serves as a base class for defining settings or configuration objects. It provides a convenient way to validate and enforce data types and structure for your settings.

The Problem: Base Settings Have Been Moved

The error message indicates that BaseSettings has been moved to the pydantic-settings package. This change was made in Pydantic version 2, which aims to improve performance and scalability.

However, some libraries, including ydata_profiling, still import BaseSettings from the original location. When you try to run your code, Pydantic raises a PydanticImportError because it cannot find the imported class in the new location.

Resolving the Issue

To resolve this issue, you have two options:

Option 1: Downgrade Your Pydantic Version

If you’re using an outdated version of Pydantic (version 2.3 or earlier), downgrading to a compatible version will fix the issue. However, be aware that downgrading may introduce security vulnerabilities and bugs fixed in later versions.

You can use pip to downgrade your Pydantic version:

pip install pydantic==2.2

Option 2: Upgrade Your ydata_profiling Library

Another solution is to upgrade your ydata-profiling library to a version that supports the new location of BaseSettings. You can use pip to upgrade the library:

pip install --upgrade ydata-profiling

If upgrading does not fix the issue, you’ll need to downgrade your Pydantic version.

Using the `pydantic-settings` Package

To avoid downgrading or upgrading libraries, you can modify your code to import BaseSettings from the new location in the pydantic-settings package:

from pydantic_settings import BaseSettings

However, this approach may not work if other libraries in your project still expect to find BaseSettings at its original location.

Best Practices and Recommendations

To avoid similar issues in the future:

Use venv or another package manager to manage your Python packages and dependencies.
Regularly check for updates and compatibility issues with libraries you’re using.
Consider creating a virtual environment for each project to isolate dependencies.

Conclusion

In this article, we explored the issue of a PydanticImportError caused by BaseSettings being moved to the pydantic-settings package. We provided solutions for resolving the issue and offered best practices for managing Python packages and dependencies.

By following these tips, you can ensure that your projects are up-to-date with the latest library releases and avoid compatibility issues like the one described in this article.

Last modified on 2024-12-15