skops 0.13.0


pip install skops

  Latest version

Released: Aug 06, 2025


Meta
Maintainer: Adrin Jalali, Benjamin Bossan
Requires Python: >=3.9

Classifiers

Development Status
  • 1 - Planning

Intended Audience
  • Developers
  • Science/Research

License
  • OSI Approved

Operating System
  • MacOS
  • Microsoft :: Windows
  • POSIX
  • Unix

Programming Language
  • Python
  • Python :: 3
  • Python :: 3.9
  • Python :: 3.10
  • Python :: 3.11
  • Python :: 3.12
  • Python :: 3.13
  • Python :: Implementation :: CPython

Topic
  • Scientific/Engineering
  • Software Development

Documentation Linux, macOS, Windows tests Codecov PyPi Black

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SKOPS

skops is a Python library helping you share your scikit-learn based models and put them in production. At the moment, it includes skops.io to securely persist sklearn estimators and more, without using pickle. It also includes skops.card to create a model card explaining what the model does and how it should be used.

  • skops.io: Secure persistence of sklearn estimators and more, without using pickle. Visit the docs for more information.

  • skops.card: tools to create a model card explaining what the model does and how it should be used. The model card can then be stored as the README.md file on the Hugging Face Hub, with pre-populated metadata to help Hub understand the model. More information can be found here.

Please refer to our documentation on using the library as user, which includes user guides on the above topics as well as complete examples explaining how the features can be used.

If you want to contribute to the library, please refer to our contributing guidelines.

Installation

You can install this library using:

python -m pip install skops

Bug Reports and Questions

Please send all your questions and report issues on this repository’s issue tracker as an issue. Try to look for existing ones before you create a new one.

Wheel compatibility matrix

Platform Python 3
any

Files in release

Extras:
Dependencies:
numpy (>=1.25.0)
packaging (>=17.0)
prettytable (>=3.9)
scikit-learn (>=1.2)
scipy (>=1.10.0)