scikit-base0.13.0
Published
Base classes for sklearn-like parametric objects
pip install scikit-base
Package Downloads
Authors
Project URLs
Requires Python
<3.15,>=3.10
Dependencies
- numpy
; extra == "all-extras" - pandas
; extra == "all-extras" - scikit-learn
>=0.24.0; extra == "dev" - pre-commit
; extra == "dev" - pytest
; extra == "dev" - pytest-cov
; extra == "dev" - mypy
; extra == "linters" - isort
; extra == "linters" - flake8
; extra == "linters" - black
; extra == "linters" - pydocstyle
; extra == "linters" - nbqa
; extra == "linters" - flake8-bugbear
; extra == "linters" - flake8-builtins
; extra == "linters" - flake8-quotes
; extra == "linters" - flake8-comprehensions
; extra == "linters" - pandas-vet
; extra == "linters" - flake8-print
; extra == "linters" - pep8-naming
; extra == "linters" - doc8
; extra == "linters" - jupyter
; extra == "binder" - jupyter
; extra == "docs" - myst-parser
; extra == "docs" - nbsphinx
>=0.8.6; extra == "docs" - numpydoc
; extra == "docs" - pydata-sphinx-theme
; extra == "docs" - sphinx-issues
<6.0.0; extra == "docs" - sphinx-gallery
<0.20.0; extra == "docs" - sphinx-panels
; extra == "docs" - sphinx-design
<0.7.0; extra == "docs" - Sphinx
!=7.2.0,<9.0.0; extra == "docs" - tabulate
; extra == "docs" - pytest
; extra == "test" - coverage
; extra == "test" - pytest-cov
; extra == "test" - safety
; extra == "test" - numpy
; extra == "test" - scipy
; extra == "test" - pandas
; extra == "test" - scikit-learn
>=0.24.0; extra == "test"
Welcome to skbase
A framework factory for scikit-learn-like and sktime-like parametric objects
skbase provides base classes for creating scikit-learn-like parametric objects,
along with tools to make it easier to build your own packages that follow these design patterns.
:rocket: Version 0.13.0 is now available. Check out our release notes.
| Overview | |
|---|---|
| CI/CD |    |
| Code |     |
| Downloads |   ){kind=icon} |
| Citation |  |
Documentation and Tutorials
To learn more about the package check out:
- our documentation
- our introductory tutorial (jupyter notebooks and video presentation)
:hourglass_flowing_sand: Install skbase
For trouble shooting or more information, see our detailed installation instructions.
- Operating system: macOS · Linux · Windows 8.1 or higher
- Python version: Python 3.10, 3.11, 3.12, 3.13, and 3.14
- Package managers: pip
pip
skbase releases are available as source packages and binary wheels via PyPI and can be installed using pip. Checkout the full list of pre-compiled wheels on PyPi.
To install the core package use:
pip install scikit-base
or, if you want to install with the maximum set of dependencies, use:
pip install scikit-base[all_extras]
Contributors ✨
This project follows the all-contributors specification. Contributions of any kind welcome!
Thanks go to these wonderful people: