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Update docs to reference main instead of develop (#1634)
#### Metadata * Reference Issue: Fixes #1549 * New Tests Added: NA * Documentation Updated: Yes * Change Log Entry: Updated `PULL_REQUEST_TEMPLATE.md`, `CONTRIBUTING.md`, and `README.md` to reference the `main` branch instead of `develop`. #### Details * **What does this PR implement/fix? Explain your changes.** This PR updates the contribution documentation and the PR template to correctly reference the `main` branch as the default/target branch. The previous documentation incorrectly instructed contributors to use the `develop` branch, which does not exist in this repository. * **Why is this change necessary? What is the problem it solves?** The instructions were outdated for new contributors, as they referred to a non-existent `develop` branch. This corrects the workflow to align with the repository's actual structure (using `main`). * **How can I reproduce the issue this PR is solving and its solution?** Navigate to the previous version of `CONTRIBUTING.md` or `PULL_REQUEST_TEMPLATE.md` and observe the references to `develop`. Check the repository branches to confirm `develop` does not exist. * **Any other comments?** I have also verified the changes by running `pre-commit` locally to ensure no formatting issues were introduced.
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.github/PULL_REQUEST_TEMPLATE.md

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@@ -5,7 +5,7 @@ the contribution guidelines: https://github.com/openml/openml-python/blob/main/C
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Please make sure that:
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* the title of the pull request is descriptive
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* this pull requests is against the `develop` branch
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* this pull requests is against the `main` branch
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* for any new functionality, consider adding a relevant example
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* add unit tests for new functionalities
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* collect files uploaded to test server using _mark_entity_for_removal()

CONTRIBUTING.md

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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).
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pytest tests/test_datasets/test_dataset.py::OpenMLDatasetTest::test_get_data
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```
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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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### 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:

README.md

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[![License](https://img.shields.io/badge/License-BSD%203--Clause-blue.svg)](https://opensource.org/licenses/BSD-3-Clause)
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<!-- Add green badges for CI and precommit -->
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[Installation](https://openml.github.io/openml-python/main/#how-to-get-openml-for-python) | [Documentation](https://openml.github.io/openml-python) | [Contribution guidelines](https://github.com/openml/openml-python/blob/develop/CONTRIBUTING.md)
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[Installation](https://openml.github.io/openml-python/main/#how-to-get-openml-for-python) | [Documentation](https://openml.github.io/openml-python) | [Contribution guidelines](https://github.com/openml/openml-python/blob/main/CONTRIBUTING.md)
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</div>
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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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[Contribution Guidelines](https://github.com/openml/openml-python/blob/develop/CONTRIBUTING.md).
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[Contribution Guidelines](https://github.com/openml/openml-python/blob/main/CONTRIBUTING.md).
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If you are new to open-source development, a great way to get started is by
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looking at issues labeled **"good first issue"** in our GitHub issue tracker.

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