https://github.com/sktime/skbase
Base classes for creating scikit-learn-like parametric objects, and tools for working with them.
https://github.com/sktime/skbase
framework python scikit-learn-api skbase sktime
Last synced: about 2 months ago
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Base classes for creating scikit-learn-like parametric objects, and tools for working with them.
- Host: GitHub
- URL: https://github.com/sktime/skbase
- Owner: sktime
- License: bsd-3-clause
- Created: 2022-05-21T01:27:28.000Z (almost 4 years ago)
- Default Branch: main
- Last Pushed: 2026-01-19T21:42:58.000Z (2 months ago)
- Last Synced: 2026-01-20T04:15:48.718Z (2 months ago)
- Topics: framework, python, scikit-learn-api, skbase, sktime
- Language: Python
- Homepage:
- Size: 1.45 MB
- Stars: 31
- Watchers: 3
- Forks: 29
- Open Issues: 32
-
Metadata Files:
- Readme: README.md
- License: LICENSE
- Security: SECURITY.md
Awesome Lists containing this project
README
# 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 0.13.1 is now available. Check out our
[release notes](https://skbase.readthedocs.io/en/latest/changelog.html).
| Overview | |
|---|---|
| **CI/CD** | [](https://github.com/sktime/skbase/actions/workflows/test.yml) [](https://codecov.io/gh/sktime/skbase) [](https://skbase.readthedocs.io/en/latest/?badge=latest) [](https://results.pre-commit.ci/latest/github/sktime/skbase/main) |
| **Code** | [](https://pypi.org/project/scikit-base/) [](https://www.python.org/) [](https://github.com/psf/black) [](https://github.com/PyCQA/bandit) |
| **Downloads** |   [)](https://pepy.tech/project/scikit-base) |
| **Citation** | [](https://zenodo.org/doi/10.5281/zenodo.10980557) |
[](#contributors)
## Documentation and Tutorials
To learn more about the package check out:
* our [documentation](https://skbase.readthedocs.io/en/latest/)
* our [introductory tutorial](https://github.com/sktime/sktime-tutorial-pydata-seattle-2023) (jupyter notebooks and video presentation)
## :hourglass_flowing_sand: Install skbase
For trouble shooting or more information, see our
[detailed installation instructions](https://skbase.readthedocs.io/en/latest/user_documentation/installation.html).
- **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]: https://pip.pypa.io/en/stable/
### 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](https://pypi.org/simple/skbase/).
To install the core package use:
```bash
pip install scikit-base
```
or, if you want to install with the maximum set of dependencies, use:
```bash
pip install scikit-base[all_extras]
```
## Contributors ✨
This project follows the
[all-contributors](https://github.com/all-contributors/all-contributors) specification.
Contributions of any kind welcome!
Thanks go to these wonderful people:
[skbase contributors](https://github.com/sktime/skbase/graphs/contributors)
