From 552a88e7f8898fd0f930f853648e8eb171e35142 Mon Sep 17 00:00:00 2001 From: Reshama Shaikh Date: Wed, 19 Dec 2018 05:14:01 -0500 Subject: [PATCH] DOC Shorten and improve CONTRIBUTING.md (#12801) * Reuse intro from contributing.rst * Removed content already on rst Simplified CONTRIBUTING.md by removing content that already exists in contributing.rst. Added Code of Conduct reference as seen in a few other CONTRIBUTING.md of popular libraries. * Update contributing.rst In shortening `CONTRIBUTING.md`, material deleted from `how to contribute` section are added onto `contributing.rst` if it doens't exist on the latter. * added full link to .rst file + removed 'Full' in 'Full Docum...' --- CONTRIBUTING.md | 282 +++++--------------------------- doc/developers/contributing.rst | 80 +++++---- 2 files changed, 85 insertions(+), 277 deletions(-) diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index 54938a511f905..32ca91f49f6aa 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -2,247 +2,41 @@ Contributing to scikit-learn ============================ -**Note: This document is a 'getting started' summary for contributing code, -documentation, testing, and filing issues.** Visit the [**Contributing -page**](http://scikit-learn.org/dev/developers/contributing.html) -for the full contributor's guide. Please read it carefully to help make -the code review process go as smoothly as possible and maximize the -likelihood of your contribution being merged. - -How to contribute ------------------ - -The preferred workflow for contributing to scikit-learn is to fork the -[main repository](https://github.com/scikit-learn/scikit-learn) on -GitHub, clone, and develop on a branch. Steps: - -1. Fork the [project repository](https://github.com/scikit-learn/scikit-learn) - by clicking on the 'Fork' button near the top right of the page. This creates - a copy of the code under your GitHub user account. For more details on - how to fork a repository see [this guide](https://help.github.com/articles/fork-a-repo/). - -2. Clone your fork of the scikit-learn repo from your GitHub account to your local disk: - - ```bash - $ git clone git@github.com:YourLogin/scikit-learn.git - $ cd scikit-learn - ``` - -3. Create a ``feature`` branch to hold your development changes: - - ```bash - $ git checkout -b my-feature - ``` - - Always use a ``feature`` branch. It's good practice to never work on the ``master`` branch! - -4. Develop the feature on your feature branch. Add changed files using ``git add`` and then ``git commit`` files: - - ```bash - $ git add modified_files - $ git commit - ``` - - to record your changes in Git, then push the changes to your GitHub account with: - - ```bash - $ git push -u origin my-feature - ``` - -5. Follow [these instructions](https://help.github.com/articles/creating-a-pull-request-from-a-fork) -to create a pull request from your fork. This will send an email to the committers. - -(If any of the above seems like magic to you, please look up the -[Git documentation](https://git-scm.com/documentation) on the web, or ask a friend or another contributor for help.) - -Pull Request Checklist ----------------------- - -We recommended that your contribution complies with the -following rules before you submit a pull request: - -- Follow the - [coding-guidelines](http://scikit-learn.org/dev/developers/contributing.html#coding-guidelines). - -- Use, when applicable, the validation tools and scripts in the - `sklearn.utils` submodule. A list of utility routines available - for developers can be found in the - [Utilities for Developers](http://scikit-learn.org/dev/developers/utilities.html#developers-utils) - page. - -- Give your pull request a helpful title that summarises what your - contribution does. In some cases `Fix ` is enough. - `Fix #` is not enough. - -- 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 - [use keywords to create link to them](https://github.com/blog/1506-closing-issues-via-pull-requests/) - (e.g., `Fixes #1234`; 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, create a link to them without using the keywords - (e.g., `See also #1234`). - -- All public methods should have informative docstrings with sample - usage presented as doctests when appropriate. - -- Please prefix the title of your pull request with `[MRG]` (Ready for - Merge), if the contribution is complete and ready for a detailed review. - Two core developers will review your code and change the prefix of the pull - request to `[MRG + 1]` and `[MRG + 2]` on approval, making it eligible - for merging. An incomplete contribution -- where you expect to do more work before - receiving a full review -- should be prefixed `[WIP]` (to indicate a work - in progress) and changed to `[MRG]` when it matures. WIPs may be useful - to: indicate you are working on something to avoid duplicated work, - request broad review of functionality or API, or seek collaborators. - WIPs often benefit from the inclusion of a - [task list](https://github.com/blog/1375-task-lists-in-gfm-issues-pulls-comments) - in the PR description. - -- All other tests pass when everything is rebuilt from scratch. On - Unix-like systems, check with (from the toplevel source folder): - - ```bash - $ make - ``` - -- When adding additional functionality, provide at least one - example script in the ``examples/`` folder. Have a look at other - examples 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. - -- Documentation and high-coverage tests are necessary for enhancements to be - accepted. Bug-fixes or new features should be provided with - [non-regression tests](https://en.wikipedia.org/wiki/Non-regression_testing). - 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. - For the Bug-fixes case, at the time of the PR, this tests should fail for - the code base in master and pass for the PR code. - - -- At least one paragraph of narrative documentation with links to - references in the literature (with PDF links when possible) and - the example. - -- The documentation 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: n_features is expected to be lower than - 100". - -You can also check for common programming errors with the following -tools: - -- Code with good unittest **coverage** (at least 80%), check with: - - ```bash - $ pip install pytest pytest-cov - $ pytest --cov sklearn path/to/tests_for_package - ``` - -- No flake8 warnings, check with: - - ```bash - $ pip install flake8 - $ flake8 path/to/module.py - ``` - -Bonus points for contributions that include a performance analysis with -a benchmark script and profiling output (please report on the mailing -list or on the GitHub issue). - -Filing bugs ------------ -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. - -It is recommended to check that your issue complies with the -following rules before submitting: - -- Verify that your issue is not being currently addressed by other - [issues](https://github.com/scikit-learn/scikit-learn/issues?q=) - or [pull requests](https://github.com/scikit-learn/scikit-learn/pulls?q=). - -- If you are submitting an algorithm or feature request, please verify that - the algorithm fulfills our - [new algorithm requirements](http://scikit-learn.org/dev/faq.html#what-are-the-inclusion-criteria-for-new-algorithms). - -- Please ensure all code snippets and error messages are formatted in - appropriate code blocks. - See [Creating and highlighting code blocks](https://help.github.com/articles/creating-and-highlighting-code-blocks). - -- Please include your operating system type and version number, as well - as your Python, scikit-learn, numpy, and scipy versions. This information - can be found by running the following code snippet: - - For scikit-learn >= 0.20: - - ```python - import sklearn; sklearn.show_versions() - ``` - - For scikit-learn < 0.20: - - ```python - import platform; print(platform.platform()) - import sys; print("Python", sys.version) - import numpy; print("NumPy", numpy.__version__) - import scipy; print("SciPy", scipy.__version__) - import sklearn; print("Scikit-Learn", sklearn.__version__) - ``` - -- Please be specific about what estimators and/or functions are involved - and the shape of the data, as appropriate; please include a - [reproducible](https://stackoverflow.com/help/mcve) code snippet - or link to a [gist](https://gist.github.com). If an exception is raised, - please provide the traceback. - -New contributor tips --------------------- - -A great way to start contributing to scikit-learn is to pick an item from the -list of -[good first issues](https://github.com/scikit-learn/scikit-learn/labels/good%20first%20issue). If -you have already contributed to scikit-learn look at -[Easy issues](https://github.com/scikit-learn/scikit-learn/labels/Easy) -instead. Resolving these issues allow you to start contributing to the project -without much prior knowledge. Your assistance in this area will be greatly -appreciated by the more experienced developers as it helps free up their time to -concentrate on other issues. - -Documentation -------------- - -We are glad to accept any sort of documentation: function docstrings, -reStructuredText documents (like this one), tutorials, etc. -reStructuredText documents live in the source code repository under the -doc/ directory. - -You can edit the documentation using any text editor and then generate -the HTML output by typing ``make html`` from the doc/ directory. -Alternatively, ``make`` can be used to quickly generate the -documentation without the example gallery. The resulting HTML files will -be placed in ``_build/html/stable`` and are viewable in a web browser. See the -``README`` file in the ``doc/`` directory for more information. - -For building the documentation, you will need -[sphinx](http://sphinx.pocoo.org/), -[matplotlib](https://matplotlib.org/), and -[pillow](https://pillow.readthedocs.io/en/latest/). - -When you are writing documentation, it is important to keep a good -compromise between mathematical and algorithmic details, and give -intuition to the reader on what the algorithm does. It is best to always -start with a small paragraph with a hand-waving explanation of what the -method does to the data and a figure (coming from an example) -illustrating it. - -Further Information -------------------- - -Visit the [Contributing Code](http://scikit-learn.org/stable/developers/contributing.html#coding-guidelines) -section of the website for more information including conforming to the -API spec and profiling contributed code. +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 +send an email to the mailing list or preferably submit a GitHub pull request. +Documentation can be found under the +[doc/](https://github.com/scikit-learn/scikit-learn/tree/master/doc) directory. + +But there are many other ways to help. In particular answering queries on the +[issue tracker](https://github.com/scikit-learn/scikit-learn/issues), +investigating bugs, and [reviewing other developers' pull +requests](http://scikit-learn.org/dev/developers/contributing.html#code-review-guidelines) +are very valuable contributions that decrease the burden on the project +maintainers. + +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 it in GitHub to say "I use it". + +Guideline +--------- + +Full contribution guidelines are available in the repository at +`doc/developers/contributing.rst`, or online at: + +http://scikit-learn.org/dev/developers/contributing.html + +Quick links to: +* [Submitting a bug report or feature request](http://scikit-learn.org/dev/developers/contributing.html#submitting-a-bug-report-or-a-feature-request) +* [Contributing code](http://scikit-learn.org/dev/developers/contributing.html#contributing-code) +* [Coding guidelines](http://scikit-learn.org/dev/developers/contributing.html#coding-guidelines) + +Code of Conduct +--------------- + +We abide by the principles of openness, respect, and consideration of others +of the Python Software Foundation: https://www.python.org/psf/codeofconduct/. diff --git a/doc/developers/contributing.rst b/doc/developers/contributing.rst index 158b562c0de40..a1a6068d53623 100644 --- a/doc/developers/contributing.rst +++ b/doc/developers/contributing.rst @@ -96,6 +96,9 @@ link to it from your website, or simply star to say "I use it": Submitting a bug report or a feature request ============================================ +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. + In case you experience issues using this package, do not hesitate to submit a ticket to the `Bug Tracker `_. You are @@ -185,34 +188,38 @@ then submit a "pull request" (PR): 2. Fork the `project repository `__: click on the 'Fork' button near the top of the page. This creates a copy of the code under your - account on the GitHub server. For more details on how to fork a + account on the GitHub user account. For more details on how to fork a repository see `this guide `_. - 3. Clone this copy to your local disk:: + 3. Clone your fork of the scikit-learn repo from your GitHub account to your + local disk:: $ git clone git@github.com:YourLogin/scikit-learn.git + $ cd scikit-learn - 4. Create a branch to hold your changes:: + 4. Create a branch to hold your development changes:: $ git checkout -b my-feature - and start making changes. Never work in the ``master`` branch! + and start making changes. Always use a ``feature`` branch. It's good practice to + never work on the ``master`` branch! - 5. Work on this copy, on your computer, using Git to do the version - control. When you're done editing, do:: + 5. 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 ``git add`` + and then ``git commit`` files:: $ git add modified_files $ git commit - to record your changes in Git, then push them to GitHub with:: + to record your changes in Git, then push the changes to your GitHub account with:: $ git push -u origin my-feature -Finally, follow `these -`_ -instructions to create a pull request from your fork. This will send an -email to the committers. You may want to consider sending an email to the -mailing list for more visibility. + 6. Follow `these + `_ + instructions to create a pull request from your fork. This will send an + email to the committers. You may want to consider sending an email to the + mailing list for more visibility. .. note:: @@ -226,8 +233,8 @@ mailing list for more visibility. If any of the above seems like magic to you, then look up the `Git documentation `_ and the `Git development workflow -`_ on the -web. +`_ on the +web, or ask a friend or another contributor for help. If some conflicts arise between your branch and the ``master`` branch, you need to merge ``master``. The command will be:: @@ -250,7 +257,7 @@ documentation related to resolving merge conflict using the command line Contributing pull requests -------------------------- -It is recommended to check that your contribution complies with the following +We recommend that that your contribution complies with the following rules before submitting a pull request: * Follow the `coding-guidelines`_ (see below). To make sure that @@ -258,7 +265,7 @@ rules before submitting a pull request: `./build_tools/travis/flake8_diff.sh` or `make flake8-diff` on a Unix-like system. -* When applicable, use the validation tools and other code in the +* When applicable, use the validation tools and scripts in the ``sklearn.utils`` submodule. A list of utility routines available for developers can be found in the :ref:`developers-utils` page. @@ -308,7 +315,8 @@ rules before submitting a pull request: accepted. Bug-fixes or new features should be provided with `non-regression tests `_. These tests - verify the correct behavior of the fix or feature. In this manner, further + verify the correct behavior of the fix or feature. 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. For the case of bug fixes, at the time of the PR, the non-regression tests should fail for the code base in the master branch @@ -319,9 +327,14 @@ rules before submitting a pull request: the example. For more details on writing and building the documentation, see the :ref:`contribute_documentation` section. +* The documentation 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: + n_features is expected to be lower than 100". + You can also check for common programming errors with the following tools: -* Code with a good unittest coverage (at least 90%, better 100%), check +* Code with a good unittest coverage (at least 80%, better 100%), check with:: $ pip install pytest pytest-cov @@ -336,7 +349,7 @@ You can also check for common programming errors with the following tools: Bonus points for contributions that include a performance analysis with a benchmark script and profiling output (please report on the mailing -list or on the GitHub wiki). +list or on the GitHub issue). Also check out the :ref:`performance-howto` guide for more details on profiling and Cython optimizations. @@ -399,10 +412,10 @@ underestimate how easy an issue is to solve! .. topic:: Easy tag - Another great way to contribute to scikit-learn is to pick an item from the - list of `Easy issues + If you have already contributed to scikit-learn, another great way to contribute + to scikit-learn is to pick an item from the list of `Easy issues `_ in the issue - tracker. Your assistance in this area will be greatly appreciated by the + tracker. Your assistance in this area will be greatly appreciated by the more experienced developers as it helps free up their time to concentrate on other issues. @@ -424,8 +437,13 @@ Documentation We are glad to accept any sort of documentation: function docstrings, reStructuredText documents (like this one), tutorials, etc. reStructuredText documents live in the source code repository under the ``doc/`` directory. + You can edit the documentation using any text editor, and then generate the -HTML output by building the documentation website. +HTML output by typing ``make html`` from the ``doc/`` directory. Alternatively, +``make`` can be used to quickly generate the documentation without the example +gallery. The resulting HTML files will be placed in ``_build/html/stable`` and are viewable +in a web browser. See the ``README``file in the ``doc/`` directory for more information. + Building the documentation ^^^^^^^^^^^^^^^^^^^^^^^^^^ @@ -481,18 +499,14 @@ details, and give intuition to the reader on what the algorithm does. Basically, to elaborate on the above, it is best to always start with a small paragraph with a hand-waving explanation of what the -method does to the data. Then, it is very helpful -to point out why the feature is useful and when it should be used - -the latter also including "big O" -(:math:`O\left(g\left(n\right)\right)`) -complexities of the algorithm, as opposed to just *rules of thumb*, -as the latter can be very machine-dependent. -If those complexities are not available, then rules of thumb -may be provided instead. +method does to the data. Then, it is very helpful to point out why the feature is +useful and when it should be used - the latter also including "big O" +(:math:`O\left(g\left(n\right)\right)`) complexities of the algorithm, as opposed +to just *rules of thumb*, as the latter can be very machine-dependent. If those +complexities are not available, then rules of thumb may be provided instead. Secondly, a generated figure from an example (as mentioned in the previous -paragraph) should then be included to further provide some -intuition. +paragraph) should then be included to further provide some intuition. Next, one or two small code examples to show its use can be added.