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@@ -44,7 +44,7 @@ To contribute to the openml-python package, follow these steps:
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0. Determine how you want to contribute (see above).
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1. Set up your local development environment.
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1. Fork and clone the `openml-python` repository. Then, create a new branch from the ``develop`` branch. If you are new to `git`, see our [detailed documentation](#basic-git-workflow), or rely on your favorite IDE.
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1. Fork and clone the `openml-python` repository. Then, create a new branch from the ``main`` branch. If you are new to `git`, see our [detailed documentation](#basic-git-workflow), or rely on your favorite IDE.
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2.[Install the local dependencies](#install-local-dependencies) to run the tests for your contribution.
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3.[Test your installation](#testing-your-installation) to ensure everything is set up correctly.
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4. Implement your contribution. If contributing to the documentation, see [here](#contributing-to-the-documentation).
To test your new contribution, add [unit tests](https://github.com/openml/openml-python/tree/develop/tests), and, if needed, [examples](https://github.com/openml/openml-python/tree/develop/examples) for any new functionality being introduced. Some notes on unit tests and examples:
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To test your new contribution, add [unit tests](https://github.com/openml/openml-python/tree/main/tests), and, if needed, [examples](https://github.com/openml/openml-python/tree/main/examples) for any new functionality being introduced. Some notes on unit tests and examples:
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* If a unit test contains an upload to the test server, please ensure that it is followed by a file collection for deletion, to prevent the test server from bulking up. For example, `TestBase._mark_entity_for_removal('data', dataset.dataset_id)`, `TestBase._mark_entity_for_removal('flow', (flow.flow_id, flow.name))`.
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* Please ensure that the example is run on the test server by beginning with the call to `openml.config.start_using_configuration_for_example()`, which is done by default for tests derived from `TestBase`.
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* Add the `@pytest.mark.sklearn` marker to your unit tests if they have a dependency on scikit-learn.
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#### Running Tests That Require Admin Privileges
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Some tests require admin privileges on the test server and will be automatically skipped unless you provide an admin API key. For regular contributors, the tests will skip gracefully. For core contributors who need to run these tests locally, you can set up the key by exporting the variable as below before running the tests:
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```bash
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# For windows
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$env:OPENML_TEST_SERVER_ADMIN_KEY = "admin-key"
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# For linux/mac
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export OPENML_TEST_SERVER_ADMIN_KEY="admin-key"
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```
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### Pull Request Checklist
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You can go to the `openml-python` GitHub repository to create the pull request by [comparing the branch](https://github.com/openml/openml-python/compare) from your fork with the `develop` branch of the `openml-python` repository. When creating a pull request, make sure to follow the comments and structured provided by the template on GitHub.
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You can go to the `openml-python` GitHub repository to create the pull request by [comparing the branch](https://github.com/openml/openml-python/compare) from your fork with the `main` branch of the `openml-python` repository. When creating a pull request, make sure to follow the comments and structured provided by the template on GitHub.
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**An incomplete contribution** -- where you expect to do more work before
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receiving a full review -- should be submitted as a `draft`. These may be useful
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The preferred workflow for contributing to openml-python is to
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fork the [main repository](https://github.com/openml/openml-python) on
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GitHub, clone, check out the branch `develop`, and develop on a new branch
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GitHub, clone, check out the branch `main`, and develop on a new branch
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branch. Steps:
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0. Make sure you have git installed, and a GitHub account.
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3. Switch to the ``develop`` branch:
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```bash
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git checkout develop
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git checkout main
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```
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3. Create a ``feature`` branch to hold your development changes:
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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 ``main`` or ``develop`` branch!
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Always use a ``feature`` branch. It's good practice to never work on the ``main`` 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:
OpenML-Python provides an easy-to-use and straightforward Python interface for [OpenML](http://openml.org), an online platform for open science collaboration in machine learning.
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We welcome contributions from both new and experienced developers!
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If you would like to contribute to OpenML-Python, please read our
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