This repo implements brownout for the deprecated sklearn package on PyPI.
The following table shows the dates and time window, where an exception will be
raised if you attempt to install the sklearn package from PyPI.
| Dates | Window(s) |
|---|---|
| 2022 November 1st - December 30th | :00-:05 every hour |
| 2023 January 1st - February 28th | :00-:10 every hour |
| 2023 March 1st - April 30th | :00-:15 every hour |
| 2023 May 1st - June 30th | :00-:10 and :30-:40 every hour |
| 2023 July 1st - August 31st | :00-:15 and :30-45 every hour |
| 2023 September 1st - October 30th | :00-:20 and :00-50 every hour |
| 2023 November 1st onwards | always raise an exception |
- use
pip install scikit-learnrather thanpip install sklearn - replace
sklearnbyscikit-learnin your pip requirements files (requirements.txt,setup.py,setup.cfg,Pipfile, etc ...) - if the
sklearnpackage is used by one of your dependencies it would be great if you take some time to track which package usessklearninstead ofscikit-learnand report it to their issue tracker - as last resort, set the environment variable ,
SKLEARN_ALLOW_DEPRECATED_SKLEARN_PACKAGE_INSTALL=Trueto avoid this error
sklearn package on PyPI exists to prevent malicious actors to use 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==1.1.1will say that the 1.1.1 version does not exist, which is confusing. The only available version at the time of writing ofsklearnis 0.0.pip uninstall sklearnwill actually not uninstallscikit-learn, you can still doimport sklearnafterwards- it can be confusing to have both
sklearnandscikit-learnin thepip listoutput prompting questions like "why do I have scikit-learn 1.1.1 and sklearn 0.0, and what does it even mean"?
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.