⚠️⚠️⚠️ 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

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"?

Historical brownout schedule

Starting 2023 December 1st, trying to install the sklearn PyPI package will
raise an error.

The following table shows the historical brownout schedule that was used
between 2022 December 1st and 2023 December 1st, in order to get more people
aware of the deprecation.

Dates	Window(s)
2022 December 1st - 2023 January 31st	:00-:05 every hour
2023 February 1st - March 31st	:00-:10 every hour
2023 April 1st - May 31st	:00-:15 every hour
2023 June 1st - July 31st	:00-:10 and :30-:40 every hour
2023 August 1st - September 30th	:00-:15 and :30-:45 every hour
2023 October 1st - November 30th	:00-:20 and :30-:50 every hour
2023 December 1st onwards	always raise an exception

Package profile

sklearn

Dependencies

Details

Package description