triage.rst

.. _bug_triaging:

Bug triaging and issue curation

The `issue tracker <https://github.com/matplotlib/matplotlib/issues>`_

is important to communication in the project because it serves as the

centralized location for making feature requests, reporting bugs,

identifying major projects to work on, and discussing priorities. For

this reason, it is important to curate the issue list, adding labels

to issues and closing issues that are not necessary.

Triaging issues does not require any particular expertise in the

internals of Matplotlib, is extremely valuable to the project, and we

welcome anyone to participate in issue triage! However, people who

are not part of the Matplotlib organization do not have `permissions

<https://docs.github.com/en/github/setting-up-and-managing-organizations-and-teams/repository-permission-levels-for-an-organization>`_.

If you do not have enough GitHub permissions do something (e.g. add a

label, close an issue), please leave a comment tagging

``@matplotlib/triageteam`` with your recommendations!

Working on issues to improve them

Improving issues increases their chances of being successfully resolved.

Guidelines on submitting good issues can be found :ref:`here

<submitting-a-bug-report>`.

A third party can give useful feedback or even add

comments on the issue.

The following actions are typically useful:

- documenting issues that are missing elements to reproduce the problem

such as code samples

- suggesting better use of code formatting (e.g. triple back ticks in the

markdown).

- suggesting to reformulate the title and description to make them more

explicit about the problem to be solved

- linking to related issues or discussions while briefly describing

how they are related, for instance "See also #xyz for a similar

attempt at this" or "See also #xyz where the same thing was

reported" provides context and helps the discussion

- verifying that the issue is reproducible

- classify the issue as a feature request, a long standing bug or a

regression

.. topic:: Fruitful discussions

Online discussions may be harder than it seems at first glance, in

particular given that a person new to open-source may have a very

different understanding of the process than a seasoned maintainer.

Overall, it is useful to stay positive and assume good will. `The

following article

<http://gael-varoquaux.info/programming/technical-discussions-are-hard-a-few-tips.html>`_

explores how to lead online discussions in the context of open source.

Triage Team

If you would like to join the triage team:

1. Correctly triage 2-3 issues.

2. Ask someone with on the `triage team

<https://github.com/orgs/matplotlib/teams/triageteam>`_ (publicly

or privately) to recommend you to the triage team . If you worked

with someone on the issue triaged, they would be a good person to

ask.

3. Responsibly exercise you new power!

Anyone with commit or triage rights may also nominate a user to be

invited to join the triage team.

Triaging operations for members of the core and triage teams

In addition to the above, members of the core team and the triage team

can do the following important tasks:

- Update labels for issues and PRs: see the list of

the `available github labels

<https://github.com/matplotlib/matplotlib/labels>`_.

- Triage issues:

- **reproduce the issue**, if the posted code is a bug label the issue

with "status: confirmed bug".

- **identify regressions**, determine if the reported bug used to

work as expected in a recent version of Matplotlib and if so

determine the last working version. Regression should be

milestone for the next bug-fix release and may be labeled as

"Release critical".

- **close usage questions** and politely point the reporter to use

`discourse <https://discourse.matplotlib.org>`_ or Stack Overflow

instead and label as "community support".

- **close duplicate issues**, after checking that they are

indeed duplicate. Ideally, the original submitter moves the

discussion to the older, duplicate issue

- **close issues that cannot be replicated**, after leaving time (at

least a week) to add extra information

.. topic:: Closing issues: a tough call

When uncertain on whether an issue should be closed or not, it is

best to strive for consensus with the original poster, and possibly

to seek relevant expertise. However, when the issue is a usage

question, or when it has been considered as unclear for many years it

should be closed.

A typical workflow for triaging issues

The following workflow [1]_ is a good way to approach issue triaging:

#. Thank the reporter for opening an issue

The issue tracker is many people’s first interaction with the

Matplotlib project itself, beyond just using the library. As such,

we want it to be a welcoming, pleasant experience.

#. Is this a usage question? If so close it with a polite message.

#. Is the necessary information provided?

Check that the poster has filled in the issue template. If crucial

information (the version of Python, the version of Matplotlib used,

the OS, and the backend), is missing politely ask the original

poster to provide the information.

#. Is the issue minimal and reproducible?

For bug reports, we ask that the reporter provide a minimal

reproducible example. See `this useful post

<https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports>`_

by Matthew Rocklin for a good explanation. If the example is not

reproducible, or if it's clearly not minimal, feel free to ask the reporter

if they can provide an example or simplify the provided one.

Do acknowledge that writing minimal reproducible examples is hard work.

If the reporter is struggling, you can try to write one yourself.

If a reproducible example is provided, but you see a simplification,

add your simpler reproducible example.

If you can not reproduce the issue, please report that along with your

OS, Python, and Matplotlib versions.

If we need more information from either this or the previous step

please label the issue with "status: needs clarification".

#. Is this a regression?

While we strive for a bug-free library, regressions are the highest

priority. If we have broken user-code that *used to* work, we should

fix that in the next patch release!

Try to determine when the regression happened by running the

reproduction code against older versions of Matplotlib. This can

be done by released versions of Matplotlib (to get the version it

last worked in) or by using `git bisect

<https://git-scm.com/docs/git-bisect>`_ . to find first commit

where it was broken.

#. Is this a duplicate issue?

We have many open issues. If a new issue seems to be a duplicate,

point to the original issue. If it is a clear duplicate, or consensus

is that it is redundant, close it. Make sure to still thank the

reporter, and encourage them to chime in on the original issue, and

perhaps try to fix it.

If the new issue provides relevant information, such as a better or

slightly different example, add it to the original issue as a comment

or an edit to the original post.

Label the closed issue with "status: duplicate"

#. Make sure that the title accurately reflects the issue. If you have the

necessary permissions edit it yourself if it's not clear.

#. Add the relevant labels, such as "Documentation" when the issue is

about documentation, "Bug" if it is clearly a bug, "New feature" if it

is a new feature request, ...

If the issue is clearly defined and the fix seems relatively

straightforward, label the issue as “Good first issue” (and

possibly a description of the fix or a hint as to where in the

code base to look to get started).

An additional useful step can be to tag the corresponding module e.g.

the "GUI/Qt" label when relevant.

.. [1] Adapted from the pandas project `maintainers guide

Working on PRs to help review

Reviewing code is also encouraged. Contributors and users are welcome to

participate to the review process following our :ref:`review guidelines

<pr-guidelines>`.

Acknowledgments

This page is lightly adapted from `the sckit-learn project

<https://scikit-learn.org/dev/developers/bug_triaging.html>`_ .