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This document describes the workflow on how to contribute to the openml-python package.
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If you are interested in connecting a machine learning package with OpenML (i.e.
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write an openml-python extension) or want to find other ways to contribute, see [this page](https://openml.github.io/openml-python/master/contributing.html#contributing).
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write an openml-python extension) or want to find other ways to contribute, see [this page](https://openml.github.io/openml-python/main/contributing.html#contributing).
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Scope of the package
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--------------------
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Therefore, the connection to other machine learning libraries such as
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*pytorch*, *keras* or *tensorflow* should not be done directly inside this
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package, but in a separate package using the OpenML Python connector.
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More information on OpenML Python connectors can be found [here](https://openml.github.io/openml-python/master/contributing.html#contributing).
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More information on OpenML Python connectors can be found [here](https://openml.github.io/openml-python/main/contributing.html#contributing).
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Reporting bugs
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--------------
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$ git checkout -b feature/my-feature
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```
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Always use a ``feature`` branch. It's good practice to never work on the ``master`` or ``develop`` branch!
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Always use a ``feature`` branch. It's good practice to never work on the ``main`` or ``develop`` branch!
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To make the nature of your pull request easily visible, please prepend the name of the branch with the type of changes you want to merge, such as ``feature`` if it contains a new feature, ``fix`` for a bugfix, ``doc`` for documentation and ``maint`` for other maintenance on the package.
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4. Develop the feature on your feature branch. Add changed files using ``git add`` and then ``git commit`` files:
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- If any source file is being added to the repository, please add the BSD 3-Clause license to it.
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*Note*: We recommend to follow the instructions below to install all requirements locally.
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However it is also possible to use the [openml-python docker image](https://github.com/openml/openml-python/blob/main/docker/readme.md) for testing and building documentation.
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This can be useful for one-off contributions or when you are experiencing installation issues.
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First install openml with its test dependencies by running
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