| Name | scikit-base JSON |
| Version |
0.7.6
JSON |
| download |
| home_page | None |
| Summary | Base classes for sklearn-like parametric objects |
| upload_time | 2024-04-16 16:39:28 |
| maintainer | Franz Király |
| docs_url | None |
| author | None |
| requires_python | <3.13,>=3.8 |
| license | BSD 3-Clause License Copyright (c) 2022, skbase Developers All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. 3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. |
| keywords |
data-science
machine-learning
scikit-learn
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
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No coveralls.
|
<a href="https://skbase.readthedocs.io/en/latest/"><img src="https://github.com/sktime/skbase/blob/main/docs/source/images/skbase-logo-with-name.png" width="175" align="right" /></a>
# 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 0.7.6 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) [)](https://pepy.tech/project/scikit-base) [)](https://pepy.tech/project/scikit-base) |
<!-- ALL-CONTRIBUTORS-BADGE:START - Do not remove or modify this section -->
[](#contributors)
<!-- ALL-CONTRIBUTORS-BADGE:END -->
## 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 X · Linux · Windows 8.1 or higher
- **Python version**: Python 3.8, 3.9, 3.10, 3.11 and 3.12
- **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]
```
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