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DOC: Add section on how to start contributing
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doc/devel/contributing.rst

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@@ -36,16 +36,15 @@ Contributor incubator
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---------------------
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The incubator is our non-public communication channel for new contributors. It
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is a private gitter room moderated by core Matplotlib developers where you can
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is a private gitter_ room moderated by core Matplotlib developers where you can
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get guidance and support for your first few PRs. It's a place you can ask
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questions about anything: how to use git, GitHub, how our PR review process
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works, technical questions about the code, what makes for good documentation
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or a blog post, how to get involved in community work, or get
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"pre-review" on your PR.
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To join, please go to our public `gitter
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<https://gitter.im/matplotlib/matplotlib>`_ community channel, and ask to be
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added to '#incubator'. One of our core developers will see your message and will
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To join, please go to our public gitter_ community channel, and ask to be added
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added to `#incubator`. One of our core developers will see your message and will
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add you.
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New Contributors meeting
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new_contributor_meeting>`_.
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We recommend joining the meeting to clarify any doubts, or lingering
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questions you might have, and to get to know a few of the people behind the
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GitHub handles 😉. You can reach out to @noatamir on `gitter
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<https://gitter.im/matplotlib/matplotlib>`_ for any clarifications or
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GitHub handles 😉. You can reach out to us on gitter_ for any clarifications or
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suggestions. We <3 feedback!
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.. _new_contributors:
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PR is an outline, unlikely to work, or stalled, and the original author is
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unresponsive, feel free to open a new PR referencing the old one.
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.. _start-contributing:
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Is there a recommended way to get started with contributions?
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-------------------------------------------------------------
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There is no pre-defined pathway for new contributors, but in practical terms -
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looking at subsets of the Matplotlib source code is reasonable, as is looking at
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existing issue and pull request discussions. You can learn a lot from the
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observations and corrections that come up in code review, for example.
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There are a few very typical new contributor profiles:
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* **You are a Matplotlib user, and you see a bug, a potential improvement, or
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something that annoys you, and you can fix it.**
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This is how a lot of people approach open-source development. You can search
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our issue tracker for an existing issue that describes your problem or open a
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new issue to inform us of the problem you observed and discuss the best
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approach to fix it. If your contributions would not be captured on GitHub
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(social media, communication, educational content), you can also reach out to
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us on gitter_, `Discourse <https://discourse.matplotlib.org/>`__ or attend any
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of our `community meetings <https://scientific-python.org/calendars>`__.
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* **You are not a regular Matplotlib user but a domain expert (you know about
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visualization, 3D plotting, design, technical writing, statistics, or some
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other field where Matplotlib could be improved).**
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In this case, even if you need help with programming skills or don't know
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where to start, you have a focus on a specific application and domain and can
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start there. In this case, maintainers can help you figure out the best
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implementation; you can open a (draft or not) pull request with a starting
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point, and we'll be happy to discuss technical approaches.
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* **You are new to Matplotlib, both as a user and contributor, and want to start
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contributing but have yet to develop a particular interest.**
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Having some previous experience or relationship with the library can be very
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helpful when making open-source contributions. It helps you understand why
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things are the way they are and how they *should* be. Having first-hand
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experience and context is valuable both for what you can bring to the
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conversation (and given the breadth of Matplotlib's usage, there is a good
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chance it is a unique context in any given conversation) and make it easier to
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understand where other people are coming from.
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Understanding the entire codebase is a long-term project, and nobody expects
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you to do this right away. If you are determined to get started with
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Matplotlib and want to learn, going through the basic functionality and
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choosing something to focus on (3d, testing, documentation, animations, etc.)
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and building your way up from issues and pull requests touching these subjects
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is a reasonable approach.
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.. _submitting-a-bug-report:
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Submitting a bug report
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import matplotlib.cbook as cbook
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fh = cbook.get_sample_data('mydata.dat')
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.. _gitter: https://gitter.im/matplotlib/matplotlib

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