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<section id="contributing">
<span id="id1"></span><h1>Contributing<a class="headerlink" href="#contributing" title="Link to this heading">#</a></h1>
<p>This project is a community effort, and everyone is welcome to
contribute. It is hosted on <a class="github reference external" href="https://github.com/scikit-learn/scikit-learn">scikit-learn/scikit-learn</a>.
The decision making process and governance structure of scikit-learn is laid
out in <a class="reference internal" href="../governance.html#governance"><span class="std std-ref">Scikit-learn governance and decision-making</span></a>.</p>
<p>Scikit-learn is somewhat <a class="reference internal" href="../faq.html#selectiveness"><span class="std std-ref">selective</span></a> when it comes to
adding new algorithms, and the best way to contribute and to help the project
is to start working on known issues.
See <a class="reference internal" href="#new-contributors"><span class="std std-ref">Issues for New Contributors</span></a> to get started.</p>
<aside class="topic">
<p class="topic-title"><strong>Our community, our values</strong></p>
<p>We are a community based on openness and friendly, didactic,
discussions.</p>
<p>We aspire to treat everybody equally, and value their contributions. We
are particularly seeking people from underrepresented backgrounds in Open
Source Software and scikit-learn in particular to participate and
contribute their expertise and experience.</p>
<p>Decisions are made based on technical merit and consensus.</p>
<p>Code is not the only way to help the project. Reviewing pull
requests, answering questions to help others on mailing lists or
issues, organizing and teaching tutorials, working on the website,
improving the documentation, are all priceless contributions.</p>
<p>We abide by the principles of openness, respect, and consideration of
others of the Python Software Foundation:
<a class="reference external" href="https://www.python.org/psf/codeofconduct/">https://www.python.org/psf/codeofconduct/</a></p>
</aside>
<p>In case you experience issues using this package, do not hesitate to submit a
ticket to the
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/issues">GitHub issue tracker</a>. You are also
welcome to post feature requests or pull requests.</p>
<section id="ways-to-contribute">
<h2>Ways to contribute<a class="headerlink" href="#ways-to-contribute" title="Link to this heading">#</a></h2>
<p>There are many ways to contribute to scikit-learn, with the most common ones
being contribution of code or documentation to the project. Improving the
documentation is no less important than improving the library itself. If you
find a typo in the documentation, or have made improvements, do not hesitate to
create a GitHub issue or preferably submit a GitHub pull request.
Full documentation can be found under the doc/ directory.</p>
<p>But there are many other ways to help. In particular helping to
<a class="reference internal" href="bug_triaging.html#bug-triaging"><span class="std std-ref">improve, triage, and investigate issues</span></a> and
<a class="reference internal" href="#code-review"><span class="std std-ref">reviewing other developers’ pull requests</span></a> are very
valuable contributions that decrease the burden on the project
maintainers.</p>
<p>Another way to contribute is to report issues you’re facing, and give a “thumbs
up” on issues that others reported and that are relevant to you. It also helps
us if you spread the word: reference the project from your blog and articles,
link to it from your website, or simply star to say “I use it”:</p>
<p>
<object
data="https://img.shields.io/github/stars/scikit-learn/scikit-learn?style=for-the-badge&logo=github"
type="image/svg+xml">
</object>
</p><p>In case a contribution/issue involves changes to the API principles
or changes to dependencies or supported versions, it must be backed by a
<a class="reference internal" href="../governance.html#slep"><span class="std std-ref">Enhancement proposals (SLEPs)</span></a>, where a SLEP must be submitted as a pull-request to
<a class="reference external" href="https://scikit-learn-enhancement-proposals.readthedocs.io">enhancement proposals</a>
using the <a class="reference external" href="https://scikit-learn-enhancement-proposals.readthedocs.io/en/latest/slep_template.html">SLEP template</a>
and follows the decision-making process outlined in <a class="reference internal" href="../governance.html#governance"><span class="std std-ref">Scikit-learn governance and decision-making</span></a>.</p>
<details class="sd-sphinx-override sd-dropdown sd-card sd-mb-3" id="contributing-to-related-projects">
<summary class="sd-summary-title sd-card-header">
<span class="sd-summary-text">Contributing to related projects<a class="headerlink" href="#contributing-to-related-projects" title="Link to this dropdown">#</a></span><span class="sd-summary-state-marker sd-summary-chevron-right"><svg version="1.1" width="1.5em" height="1.5em" class="sd-octicon sd-octicon-chevron-right" viewBox="0 0 24 24" aria-hidden="true"><path d="M8.72 18.78a.75.75 0 0 1 0-1.06L14.44 12 8.72 6.28a.751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018l6.25 6.25a.75.75 0 0 1 0 1.06l-6.25 6.25a.75.75 0 0 1-1.06 0Z"></path></svg></span></summary><div class="sd-summary-content sd-card-body docutils">
<p class="sd-card-text">Scikit-learn thrives in an ecosystem of several related projects, which also
may have relevant issues to work on, including smaller projects such as:</p>
<ul class="simple">
<li><p class="sd-card-text"><a class="reference external" href="https://github.com/search?q=org%3Ascikit-learn-contrib+is%3Aissue+is%3Aopen+sort%3Aupdated-desc&type=Issues">scikit-learn-contrib</a></p></li>
<li><p class="sd-card-text"><a class="reference external" href="https://github.com/joblib/joblib/issues">joblib</a></p></li>
<li><p class="sd-card-text"><a class="reference external" href="https://github.com/sphinx-gallery/sphinx-gallery/issues">sphinx-gallery</a></p></li>
<li><p class="sd-card-text"><a class="reference external" href="https://github.com/numpy/numpydoc/issues">numpydoc</a></p></li>
<li><p class="sd-card-text"><a class="reference external" href="https://github.com/renatopp/liac-arff/issues">liac-arff</a></p></li>
</ul>
<p class="sd-card-text">and larger projects:</p>
<ul class="simple">
<li><p class="sd-card-text"><a class="reference external" href="https://github.com/numpy/numpy/issues">numpy</a></p></li>
<li><p class="sd-card-text"><a class="reference external" href="https://github.com/scipy/scipy/issues">scipy</a></p></li>
<li><p class="sd-card-text"><a class="reference external" href="https://github.com/matplotlib/matplotlib/issues">matplotlib</a></p></li>
<li><p class="sd-card-text">and so on.</p></li>
</ul>
<p class="sd-card-text">Look for issues marked “help wanted” or similar. Helping these projects may help
scikit-learn too. See also <a class="reference internal" href="../related_projects.html#related-projects"><span class="std std-ref">Related Projects</span></a>.</p>
</div>
</details></section>
<section id="automated-contributions-policy">
<h2>Automated Contributions Policy<a class="headerlink" href="#automated-contributions-policy" title="Link to this heading">#</a></h2>
<p>Please refrain from submitting issues or pull requests generated by
fully-automated tools. Maintainers reserve the right, at their sole discretion,
to close such submissions and to block any account responsible for them.</p>
<p>Ideally, contributions should follow from a human-to-human discussion in the
form of an issue.</p>
</section>
<section id="submitting-a-bug-report-or-a-feature-request">
<h2>Submitting a bug report or a feature request<a class="headerlink" href="#submitting-a-bug-report-or-a-feature-request" title="Link to this heading">#</a></h2>
<p>We use GitHub issues to track all bugs and feature requests; feel free to open
an issue if you have found a bug or wish to see a feature implemented.</p>
<p>In case you experience issues using this package, do not hesitate to submit a
ticket to the
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/issues">Bug Tracker</a>. You are
also welcome to post feature requests or pull requests.</p>
<p>It is recommended to check that your issue complies with the
following rules before submitting:</p>
<ul class="simple">
<li><p>Verify that your issue is not being currently addressed by other
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/issues?q=">issues</a>
or <a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pulls?q=">pull requests</a>.</p></li>
<li><p>If you are submitting an algorithm or feature request, please verify that
the algorithm fulfills our
<a class="reference external" href="https://scikit-learn.org/stable/faq.html#what-are-the-inclusion-criteria-for-new-algorithms">new algorithm requirements</a>.</p></li>
<li><p>If you are submitting a bug report, we strongly encourage you to follow the guidelines in
<a class="reference internal" href="#filing-bugs"><span class="std std-ref">How to make a good bug report</span></a>.</p></li>
</ul>
<section id="how-to-make-a-good-bug-report">
<span id="filing-bugs"></span><h3>How to make a good bug report<a class="headerlink" href="#how-to-make-a-good-bug-report" title="Link to this heading">#</a></h3>
<p>When you submit an issue to <a class="reference external" href="https://github.com/scikit-learn/scikit-learn/issues">GitHub</a>, please do your best to
follow these guidelines! This will make it a lot easier to provide you with good
feedback:</p>
<ul>
<li><p>The ideal bug report contains a <a class="reference internal" href="minimal_reproducer.html#minimal-reproducer"><span class="std std-ref">short reproducible code snippet</span></a>, this way anyone can try to reproduce the bug easily. If your
snippet is longer than around 50 lines, please link to a <a class="reference external" href="https://gist.github.com">Gist</a> or a GitHub repo.</p></li>
<li><p>If not feasible to include a reproducible snippet, please be specific about
what <strong>estimators and/or functions are involved and the shape of the data</strong>.</p></li>
<li><p>If an exception is raised, please <strong>provide the full traceback</strong>.</p></li>
<li><p>Please include your <strong>operating system type and version number</strong>, as well as
your <strong>Python, scikit-learn, numpy, and scipy versions</strong>. This information
can be found by running:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><style type="text/css">
span.prompt1:before {
content: "$ ";
}
</style><span class="prompt1">python<span class="w"> </span>-c<span class="w"> </span><span class="s2">"import sklearn; sklearn.show_versions()"</span></span>
</pre></div></div></li>
<li><p>Please ensure all <strong>code snippets and error messages are formatted in
appropriate code blocks</strong>. See <a class="reference external" href="https://help.github.com/articles/creating-and-highlighting-code-blocks">Creating and highlighting code blocks</a>
for more details.</p></li>
</ul>
<p>If you want to help curate issues, read about <a class="reference internal" href="bug_triaging.html#bug-triaging"><span class="std std-ref">Bug triaging and issue curation</span></a>.</p>
</section>
</section>
<section id="contributing-code">
<h2>Contributing code<a class="headerlink" href="#contributing-code" title="Link to this heading">#</a></h2>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>To avoid duplicating work, it is highly advised that you search through the
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/issues">issue tracker</a> and
the <a class="reference external" href="https://github.com/scikit-learn/scikit-learn/pulls">PR list</a>.
If in doubt about duplicated work, or if you want to work on a non-trivial
feature, it’s recommended to first open an issue in
the <a class="reference external" href="https://github.com/scikit-learn/scikit-learn/issues">issue tracker</a>
to get some feedback from core developers.</p>
<p>One easy way to find an issue to work on is by applying the “help wanted”
label in your search. This lists all the issues that have been unclaimed
so far. In order to claim an issue for yourself, please comment exactly
<code class="docutils literal notranslate"><span class="pre">/take</span></code> on it for the CI to automatically assign the issue to you.</p>
</div>
<p>To maintain the quality of the codebase and ease the review process, any
contribution must conform to the project’s <a class="reference internal" href="develop.html#coding-guidelines"><span class="std std-ref">coding guidelines</span></a>, in particular:</p>
<ul class="simple">
<li><p>Don’t modify unrelated lines to keep the PR focused on the scope stated in its
description or issue.</p></li>
<li><p>Only write inline comments that add value and avoid stating the obvious: explain
the “why” rather than the “what”.</p></li>
<li><p><strong>Most importantly</strong>: Do not contribute code that you don’t understand.</p></li>
</ul>
<section id="video-resources">
<h3>Video resources<a class="headerlink" href="#video-resources" title="Link to this heading">#</a></h3>
<p>These videos are step-by-step introductions on how to contribute to
scikit-learn, and are a great companion to the following text guidelines.
Please make sure to still check our guidelines below, since they describe our
latest up-to-date workflow.</p>
<ul class="simple">
<li><p>Crash Course in Contributing to Scikit-Learn & Open Source Projects:
<a class="reference external" href="https://youtu.be/5OL8XoMMOfA">Video</a>,
<a class="reference external" href="https://github.com/data-umbrella/event-transcripts/blob/main/2020/05-andreas-mueller-contributing.md">Transcript</a></p></li>
<li><p>Example of Submitting a Pull Request to scikit-learn:
<a class="reference external" href="https://youtu.be/PU1WyDPGePI">Video</a>,
<a class="reference external" href="https://github.com/data-umbrella/event-transcripts/blob/main/2020/06-reshama-shaikh-sklearn-pr.md">Transcript</a></p></li>
<li><p>Sprint-specific instructions and practical tips:
<a class="reference external" href="https://youtu.be/p_2Uw2BxdhA">Video</a>,
<a class="reference external" href="https://github.com/data-umbrella/data-umbrella-scikit-learn-sprint/blob/master/3_transcript_ACM_video_vol2.md">Transcript</a></p></li>
<li><p>3 Components of Reviewing a Pull Request:
<a class="reference external" href="https://youtu.be/dyxS9KKCNzA">Video</a>,
<a class="reference external" href="https://github.com/data-umbrella/event-transcripts/blob/main/2021/27-thomas-pr.md">Transcript</a></p></li>
</ul>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>In January 2021, the default branch name changed from <code class="docutils literal notranslate"><span class="pre">master</span></code> to <code class="docutils literal notranslate"><span class="pre">main</span></code>
for the scikit-learn GitHub repository to use more inclusive terms.
These videos were created prior to the renaming of the branch.
For contributors who are viewing these videos to set up their
working environment and submitting a PR, <code class="docutils literal notranslate"><span class="pre">master</span></code> should be replaced to <code class="docutils literal notranslate"><span class="pre">main</span></code>.</p>
</div>
</section>
<section id="how-to-contribute">
<h3>How to contribute<a class="headerlink" href="#how-to-contribute" title="Link to this heading">#</a></h3>
<p>The preferred way to contribute to scikit-learn is to fork the <a class="reference external" href="https://github.com/scikit-learn/scikit-learn/">main
repository</a> on GitHub,
then submit a “pull request” (PR).</p>
<p>In the first few steps, we explain how to locally install scikit-learn, and
how to set up your git repository:</p>
<ol class="arabic">
<li><p><a class="reference external" href="https://github.com/join">Create an account</a> on
GitHub if you do not already have one.</p></li>
<li><p>Fork the <a class="reference external" href="https://github.com/scikit-learn/scikit-learn">project repository</a>: click on the ‘Fork’
button near the top of the page. This creates a copy of the code under your
account on the GitHub user account. For more details on how to fork a
repository see <a class="reference external" href="https://help.github.com/articles/fork-a-repo/">this guide</a>.</p></li>
<li><p>Clone your fork of the scikit-learn repo from your GitHub account to your
local disk:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt1">git<span class="w"> </span>clone<span class="w"> </span>[email protected]:YourLogin/scikit-learn.git<span class="w"> </span><span class="c1"># add --depth 1 if your connection is slow</span></span>
<span class="prompt1"><span class="nb">cd</span><span class="w"> </span>scikit-learn</span>
</pre></div></div></li>
<li><p>Follow steps 2-6 in <a class="reference internal" href="advanced_installation.html#install-bleeding-edge"><span class="std std-ref">Building from source</span></a> to build scikit-learn in
development mode and return to this document.</p></li>
<li><p>Install the development dependencies:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt1">pip<span class="w"> </span>install<span class="w"> </span>pytest<span class="w"> </span>pytest-cov<span class="w"> </span><span class="nv">ruff</span><span class="o">==</span><span class="m">0</span>.11.2<span class="w"> </span>mypy<span class="w"> </span>numpydoc</span>
</pre></div></div></li>
</ol>
<ol class="arabic" id="upstream" start="6">
<li><p>Add the <code class="docutils literal notranslate"><span class="pre">upstream</span></code> remote. This saves a reference to the main
scikit-learn repository, which you can use to keep your repository
synchronized with the latest changes:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt1">git<span class="w"> </span>remote<span class="w"> </span>add<span class="w"> </span>upstream<span class="w"> </span>[email protected]:scikit-learn/scikit-learn.git</span>
</pre></div></div></li>
<li><p>Check that the <code class="docutils literal notranslate"><span class="pre">upstream</span></code> and <code class="docutils literal notranslate"><span class="pre">origin</span></code> remote aliases are configured correctly
by running:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt1">git<span class="w"> </span>remote<span class="w"> </span>-v</span>
</pre></div></div><p>This should display:</p>
<div class="highlight-text notranslate"><div class="highlight"><pre><span></span>origin [email protected]:YourLogin/scikit-learn.git (fetch)
origin [email protected]:YourLogin/scikit-learn.git (push)
upstream [email protected]:scikit-learn/scikit-learn.git (fetch)
upstream [email protected]:scikit-learn/scikit-learn.git (push)
</pre></div>
</div>
</li>
</ol>
<p>You should now have a working installation of scikit-learn, and your git repository
properly configured. It could be useful to run some test to verify your installation.
Please refer to <a class="reference internal" href="tips.html#pytest-tips"><span class="std std-ref">Useful pytest aliases and flags</span></a> for examples.</p>
<p>The next steps now describe the process of modifying code and submitting a PR:</p>
<ol class="arabic" start="8">
<li><p>Synchronize your <code class="docutils literal notranslate"><span class="pre">main</span></code> branch with the <code class="docutils literal notranslate"><span class="pre">upstream/main</span></code> branch,
more details on <a class="reference external" href="https://docs.github.com/en/github/collaborating-with-issues-and-pull-requests/syncing-a-fork">GitHub Docs</a>:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt1">git<span class="w"> </span>checkout<span class="w"> </span>main</span>
<span class="prompt1">git<span class="w"> </span>fetch<span class="w"> </span>upstream</span>
<span class="prompt1">git<span class="w"> </span>merge<span class="w"> </span>upstream/main</span>
</pre></div></div></li>
<li><p>Create a feature branch to hold your development changes:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt1">git<span class="w"> </span>checkout<span class="w"> </span>-b<span class="w"> </span>my_feature</span>
</pre></div></div><p>and start making changes. Always use a feature branch. It’s good
practice to never work on the <code class="docutils literal notranslate"><span class="pre">main</span></code> branch!</p>
</li>
<li><p>(<strong>Optional</strong>) Install <a class="reference external" href="https://pre-commit.com/#install">pre-commit</a> to
run code style checks before each commit:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt1">pip<span class="w"> </span>install<span class="w"> </span>pre-commit</span>
<span class="prompt1">pre-commit<span class="w"> </span>install</span>
</pre></div></div><p>pre-commit checks can be disabled for a particular commit with
<code class="docutils literal notranslate"><span class="pre">git</span> <span class="pre">commit</span> <span class="pre">-n</span></code>.</p>
</li>
<li><p>Develop the feature on your feature branch on your computer, using Git to
do the version control. When you’re done editing, add changed files using
<code class="docutils literal notranslate"><span class="pre">git</span> <span class="pre">add</span></code> and then <code class="docutils literal notranslate"><span class="pre">git</span> <span class="pre">commit</span></code>:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt1">git<span class="w"> </span>add<span class="w"> </span>modified_files</span>
<span class="prompt1">git<span class="w"> </span>commit</span>
</pre></div></div><p>to record your changes in Git, then push the changes to your GitHub
account with:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt1">git<span class="w"> </span>push<span class="w"> </span>-u<span class="w"> </span>origin<span class="w"> </span>my_feature</span>
</pre></div></div></li>
<li><p>Follow <a class="reference external" href="https://help.github.com/articles/creating-a-pull-request-from-a-fork">these</a>
instructions to create a pull request from your fork. This will send a
notification to potential reviewers. You may want to consider sending a message to
the <a class="reference external" href="https://discord.com/invite/h9qyrK8Jc8">discord</a> in the development
channel for more visibility if your pull request does not receive attention after
a couple of days (instant replies are not guaranteed though).</p></li>
</ol>
<p>It is often helpful to keep your local feature branch synchronized with the
latest changes of the main scikit-learn repository:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt1">git<span class="w"> </span>fetch<span class="w"> </span>upstream</span>
<span class="prompt1">git<span class="w"> </span>merge<span class="w"> </span>upstream/main</span>
</pre></div></div><p>Subsequently, you might need to solve the conflicts. You can refer to the
<a class="reference external" href="https://help.github.com/articles/resolving-a-merge-conflict-using-the-command-line/">Git documentation related to resolving merge conflict using the command
line</a>.</p>
<aside class="topic">
<p class="topic-title">Learning Git</p>
<p>The <a class="reference external" href="https://git-scm.com/doc">Git documentation</a> and
<a class="reference external" href="http://try.github.io">http://try.github.io</a> are excellent resources to get started with git,
and understanding all of the commands shown here.</p>
</aside>
</section>
<section id="pull-request-checklist">
<span id="pr-checklist"></span><h3>Pull request checklist<a class="headerlink" href="#pull-request-checklist" title="Link to this heading">#</a></h3>
<p>Before a PR can be merged, it needs to be approved by two core developers.
An incomplete contribution – where you expect to do more work before receiving
a full review – should be marked as a <a class="reference external" href="https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/proposing-changes-to-your-work-with-pull-requests/changing-the-stage-of-a-pull-request">draft pull request</a>
and changed to “ready for review” when it matures. Draft PRs may be useful to:
indicate you are working on something to avoid duplicated work, request
broad review of functionality or API, or seek collaborators. Draft PRs often
benefit from the inclusion of a <a class="reference external" href="https://github.com/blog/1375-task-lists-in-gfm-issues-pulls-comments">task list</a> in
the PR description.</p>
<p>In order to ease the reviewing process, we recommend that your contribution
complies with the following rules before marking a PR as “ready for review”. The
<strong>bolded</strong> ones are especially important:</p>
<ol class="arabic">
<li><p><strong>Give your pull request a helpful title</strong> that summarizes what your
contribution does. This title will often become the commit message once
merged so it should summarize your contribution for posterity. In some
cases “Fix <ISSUE TITLE>” is enough. “Fix #<ISSUE NUMBER>” is never a
good title.</p></li>
<li><p><strong>Make sure your code passes the tests</strong>. The whole test suite can be run
with <code class="docutils literal notranslate"><span class="pre">pytest</span></code>, but it is usually not recommended since it takes a long
time. It is often enough to only run the test related to your changes:
for example, if you changed something in
<code class="docutils literal notranslate"><span class="pre">sklearn/linear_model/_logistic.py</span></code>, running the following commands will
usually be enough:</p>
<ul class="simple">
<li><p><code class="docutils literal notranslate"><span class="pre">pytest</span> <span class="pre">sklearn/linear_model/_logistic.py</span></code> to make sure the doctest
examples are correct</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">pytest</span> <span class="pre">sklearn/linear_model/tests/test_logistic.py</span></code> to run the tests
specific to the file</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">pytest</span> <span class="pre">sklearn/linear_model</span></code> to test the whole
<a class="reference internal" href="../api/sklearn.linear_model.html#module-sklearn.linear_model" title="sklearn.linear_model"><code class="xref py py-mod docutils literal notranslate"><span class="pre">linear_model</span></code></a> module</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">pytest</span> <span class="pre">doc/modules/linear_model.rst</span></code> to make sure the user guide
examples are correct.</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">pytest</span> <span class="pre">sklearn/tests/test_common.py</span> <span class="pre">-k</span> <span class="pre">LogisticRegression</span></code> to run all our
estimator checks (specifically for <code class="docutils literal notranslate"><span class="pre">LogisticRegression</span></code>, if that’s the
estimator you changed).</p></li>
</ul>
<p>There may be other failing tests, but they will be caught by the CI so
you don’t need to run the whole test suite locally. For guidelines on how
to use <code class="docutils literal notranslate"><span class="pre">pytest</span></code> efficiently, see the <a class="reference internal" href="tips.html#pytest-tips"><span class="std std-ref">Useful pytest aliases and flags</span></a>.</p>
</li>
<li><p><strong>Make sure your code is properly commented and documented</strong>, and <strong>make
sure the documentation renders properly</strong>. To build the documentation, please
refer to our <a class="reference internal" href="#contribute-documentation"><span class="std std-ref">Documentation</span></a> guidelines. The CI will also
build the docs: please refer to <a class="reference internal" href="#generated-doc-ci"><span class="std std-ref">Generated documentation on GitHub Actions</span></a>.</p></li>
<li><p><strong>Tests are necessary for enhancements to be
accepted</strong>. Bug-fixes or new features should be provided with
<a class="reference external" href="https://en.wikipedia.org/wiki/Non-regression_testing">non-regression tests</a>. These tests
verify the correct behavior of the fix or feature. In this manner, further
modifications on the code base are granted to be consistent with the
desired behavior. In the case of bug fixes, at the time of the PR, the
non-regression tests should fail for the code base in the <code class="docutils literal notranslate"><span class="pre">main</span></code> branch
and pass for the PR code.</p></li>
<li><p>If your PR is likely to affect users, you need to add a changelog entry describing
your PR changes. See the
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn/blob/main/doc/whats_new/upcoming_changes/README.md">README</a>
for more details.</p></li>
<li><p>Follow the <a class="reference internal" href="develop.html#coding-guidelines"><span class="std std-ref">Coding guidelines</span></a>.</p></li>
<li><p>When applicable, use the validation tools and scripts in the <a class="reference internal" href="../api/sklearn.utils.html#module-sklearn.utils" title="sklearn.utils"><code class="xref py py-mod docutils literal notranslate"><span class="pre">sklearn.utils</span></code></a>
module. A list of utility routines available for developers can be found in the
<a class="reference internal" href="utilities.html#developers-utils"><span class="std std-ref">Utilities for Developers</span></a> page.</p></li>
<li><p>Often pull requests resolve one or more other issues (or pull requests).
If merging your pull request means that some other issues/PRs should
be closed, you should <a class="reference external" href="https://github.com/blog/1506-closing-issues-via-pull-requests/">use keywords to create link to them</a>
(e.g., <code class="docutils literal notranslate"><span class="pre">Fixes</span> <span class="pre">#1234</span></code>; multiple issues/PRs are allowed as long as each
one is preceded by a keyword). Upon merging, those issues/PRs will
automatically be closed by GitHub. If your pull request is simply
related to some other issues/PRs, or it only partially resolves the target
issue, create a link to them without using the keywords (e.g., <code class="docutils literal notranslate"><span class="pre">Towards</span> <span class="pre">#1234</span></code>).</p></li>
<li><p>PRs should often substantiate the change, through benchmarks of
performance and efficiency (see <a class="reference internal" href="#monitoring-performances"><span class="std std-ref">Monitoring performance</span></a>) or through
examples of usage. Examples also illustrate the features and intricacies of
the library to users. Have a look at other examples in the <a class="reference external" href="https://github.com/scikit-learn/scikit-learn/tree/main/examples">examples/</a>
directory for reference. Examples should demonstrate why the new
functionality is useful in practice and, if possible, compare it to other
methods available in scikit-learn.</p></li>
<li><p>New features have some maintenance overhead. We expect PR authors
to take part in the maintenance for the code they submit, at least
initially. New features need to be illustrated with narrative
documentation in the user guide, with small code snippets.
If relevant, please also add references in the literature, with PDF links
when possible.</p></li>
<li><p>The user guide should also include expected time and space complexity
of the algorithm and scalability, e.g. “this algorithm can scale to a
large number of samples > 100000, but does not scale in dimensionality:
<code class="docutils literal notranslate"><span class="pre">n_features</span></code> is expected to be lower than 100”.</p></li>
</ol>
<p>You can also check our <a class="reference internal" href="#code-review"><span class="std std-ref">Code Review Guidelines</span></a> to get an idea of what reviewers
will expect.</p>
<p>You can check for common programming errors with the following tools:</p>
<ul>
<li><p>Code with a good unit test coverage (at least 80%, better 100%), check with:</p>