⚠️⚠️⚠️ Summary ⚠️⚠️⚠️

⚠️⚠️⚠️ The sklearn PyPI package is deprecated use scikit-learn instead ⚠️⚠️⚠️

How to fix the error for the main use cases

• use pip install scikit-learn rather than pip install sklearn
• replace sklearn by scikit-learn in your pip requirements files (requirements.txt, setup.py, setup.cfg, Pipfile, etc ...)
• if the sklearn package is used by one of your dependencies it would be great if you take some time to track which package uses sklearn instead of scikit-learn and report it to their issue tracker
• as a last resort, set the environment variable SKLEARN_ALLOW_DEPRECATED_SKLEARN_PACKAGE_INSTALL=True to avoid this error

Brownout schedule

The following table shows the dates and time windows, where an exception will be raised if you attempt to install the sklearn package from PyPI.

How to test whether a package will be affected by the sklearn deprecation

If you want to test whether a package has sklearn in its dependencies independently of the brownout schedule, you can do:

SKLEARN_ALLOW_DEPRECATED_SKLEARN_PACKAGE_INSTALL=False \
    pip install package-to-test-goes-here

If you get an error that means that the package has sklearn in one of its dependencies. It would be greatly appreciated if you track which package it is, and if you report it to the appropriate project issue tracker to make them aware of the sklearn deprecation.

Reason for the deprecation

sklearn package on PyPI exists to prevent malicious actors from using the sklearn package, since sklearn (the import name) and scikit-learn (the project name) are sometimes used interchangeably. scikit-learn is the actual package name and should be used with pip, e.g. for:

• pip commands: pip install scikit-learn
• pip requirement files (requirements.txt, setup.py, setup.cfg, Pipfile, etc ...)

At the time of writing (October 2022) sklearn downloads is about 1/5 of the scikit-learn downloads on PyPI so a lot of people are using it.

There are some edge cases with the way the PyPI sklearn package is implemented:

• pip install sklearn==1.1.3 will say that the 1.1.3 version does not exist, which is confusing. The only available version at the time of writing of sklearn is 0.0.
• pip uninstall sklearn will actually not uninstall scikit-learn, you can still do import sklearn afterwards
• it can be confusing to have both sklearn and scikit-learn in the pip list output, prompting questions like "why do I have scikit-learn 1.1.3 and sklearn 0.0, and what does it even mean"?