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KB","deleteTooltip":"You must be signed in to make or propose changes","editTooltip":"You must be signed in to make or propose changes","ghDesktopPath":"https://desktop.github.com","isGitLfs":false,"onBranch":true,"shortPath":"29a9800","siteNavLoginPath":"/login?return_to=https%3A%2F%2Fgithub.com%2Fjortizcs%2Fscikit-learn%2Fblob%2Fmaster%2FCONTRIBUTING.md","isCSV":false,"isRichtext":true,"toc":[{"level":1,"text":"Contributing code","anchor":"contributing-code","htmlText":"Contributing code"},{"level":2,"text":"How to contribute","anchor":"how-to-contribute","htmlText":"How to 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dir=\"auto\"\u003e\u003ch1 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eContributing code\u003c/h1\u003e\u003ca id=\"user-content-contributing-code\" class=\"anchor\" aria-label=\"Permalink: Contributing code\" href=\"#contributing-code\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003e\u003cstrong\u003eNote: This document is just to get started, visit \u003ca href=\"http://scikit-learn.org/stable/developers/index.html\" rel=\"nofollow\"\u003e\u003cstrong\u003eContributing\npage\u003c/strong\u003e\u003c/a\u003e\nfor the full contributor's guide. Please be sure to read it carefully to make\nthe code review process go as smoothly as possible and maximize the\nlikelihood of your contribution being merged.\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eHow to contribute\u003c/h2\u003e\u003ca id=\"user-content-how-to-contribute\" class=\"anchor\" aria-label=\"Permalink: How to contribute\" href=\"#how-to-contribute\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eThe preferred way to contribute to scikit-learn is to fork the\n\u003ca href=\"http://github.com/scikit-learn/scikit-learn/\"\u003emain repository\u003c/a\u003e on\nGitHub:\u003c/p\u003e\n\u003col dir=\"auto\"\u003e\n\u003cli\u003e\n\u003cp dir=\"auto\"\u003eFork the \u003ca href=\"http://github.com/scikit-learn/scikit-learn\"\u003eproject repository\u003c/a\u003e:\nclick on the 'Fork' button near the top of the page. This creates\na copy of the code under your account on the GitHub server.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp dir=\"auto\"\u003eClone this copy to your local disk:\u003c/p\u003e\n\u003cdiv class=\"snippet-clipboard-content notranslate position-relative overflow-auto\" data-snippet-clipboard-copy-content=\" $ git clone git@github.com:YourLogin/scikit-learn.git\"\u003e\u003cpre class=\"notranslate\"\u003e\u003ccode\u003e $ git clone git@github.com:YourLogin/scikit-learn.git\n\u003c/code\u003e\u003c/pre\u003e\u003c/div\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp dir=\"auto\"\u003eCreate a branch to hold your changes:\u003c/p\u003e\n\u003cdiv class=\"snippet-clipboard-content notranslate position-relative overflow-auto\" data-snippet-clipboard-copy-content=\" $ git checkout -b my-feature\"\u003e\u003cpre class=\"notranslate\"\u003e\u003ccode\u003e $ git checkout -b my-feature\n\u003c/code\u003e\u003c/pre\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eand start making changes. Never work in the \u003ccode\u003emaster\u003c/code\u003e branch!\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp dir=\"auto\"\u003eWork on this copy on your computer using Git to do the version\ncontrol. When you're done editing, do:\u003c/p\u003e\n\u003cdiv class=\"snippet-clipboard-content notranslate position-relative overflow-auto\" data-snippet-clipboard-copy-content=\" $ git add modified_files\n $ git commit\"\u003e\u003cpre class=\"notranslate\"\u003e\u003ccode\u003e $ git add modified_files\n $ git commit\n\u003c/code\u003e\u003c/pre\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eto record your changes in Git, then push them to GitHub with:\u003c/p\u003e\n\u003cdiv class=\"snippet-clipboard-content notranslate position-relative overflow-auto\" data-snippet-clipboard-copy-content=\" $ git push -u origin my-feature\"\u003e\u003cpre class=\"notranslate\"\u003e\u003ccode\u003e $ git push -u origin my-feature\n\u003c/code\u003e\u003c/pre\u003e\u003c/div\u003e\n\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp dir=\"auto\"\u003eFinally, go to the web page of the your fork of the scikit-learn repo,\nand click 'Pull request' to send your changes to the maintainers for\nreview. request. This will send an email to the committers.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e(If any of the above seems like magic to you, then look up the\n\u003ca href=\"http://git-scm.com/documentation\" rel=\"nofollow\"\u003eGit documentation\u003c/a\u003e on the web.)\u003c/p\u003e\n\u003cp dir=\"auto\"\u003eIt is recommended to check that your contribution complies with the\nfollowing rules before submitting a pull request:\u003c/p\u003e\n\u003cul dir=\"auto\"\u003e\n\u003cli\u003e\n\u003cp dir=\"auto\"\u003eAll public methods should have informative docstrings with sample\nusage presented as doctests when appropriate.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp dir=\"auto\"\u003eAll other tests pass when everything is rebuilt from scratch. On\nUnix-like systems, check with (from the toplevel source folder):\u003c/p\u003e\n\u003cdiv class=\"snippet-clipboard-content notranslate position-relative overflow-auto\" data-snippet-clipboard-copy-content=\" $ make\"\u003e\u003cpre class=\"notranslate\"\u003e\u003ccode\u003e $ make\n\u003c/code\u003e\u003c/pre\u003e\u003c/div\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp dir=\"auto\"\u003eWhen adding additional functionality, provide at least one\nexample script in the \u003ccode\u003eexamples/\u003c/code\u003e folder. Have a look at other\nexamples for reference. Examples should demonstrate why the new\nfunctionality is useful in practice and, if possible, compare it\nto other methods available in scikit-learn.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp dir=\"auto\"\u003eAt least one paragraph of narrative documentation with links to\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003cdiv class=\"snippet-clipboard-content notranslate position-relative overflow-auto\" data-snippet-clipboard-copy-content=\" the example.\n\nThe documentation should also include expected time and space\ncomplexity of the algorithm and scalability, e.g. \u0026quot;this algorithm\ncan scale to a large number of samples \u0026gt; 100000, but does not\nscale in dimensionality: n_features is expected to be lower than\n100\u0026quot;.\n\nYou can also check for common programming errors with the following\ntools:\n\n- Code with good unittest coverage (at least 80%), check with:\n\n $ pip install nose coverage\n $ nosetests --with-coverage path/to/tests_for_package\n\n- No pyflakes warnings, check with:\n\n $ pip install pyflakes\n $ pyflakes path/to/module.py\n\n- No PEP8 warnings, check with:\n\n $ pip install pep8\n $ pep8 path/to/module.py\n\n- AutoPEP8 can help you fix some of the easy redundant errors:\n\n $ pip install autopep8\n $ autopep8 path/to/pep8.py\n\nBonus points for contributions that include a performance analysis with\na benchmark script and profiling output (please report on the mailing\nlist or on the GitHub issue).\n\nEasy Issues\n-----------\n\nA great way to start contributing to scikit-learn is to pick an item\nfrom the list of [Easy issues](https://github.com/scikit-learn/scikit-learn/issues?labels=Easy)\nin the issue tracker. Resolving these issues allow you to start\ncontributing to the project without much prior knowledge. Your\nassistance in this area will be greatly appreciated by the more\nexperienced developers as it helps free up their time to concentrate on\nother issues.\n\nDocumentation\n-------------\n\nWe are glad to accept any sort of documentation: function docstrings,\nreStructuredText documents (like this one), tutorials, etc.\nreStructuredText documents live in the source code repository under the\ndoc/ directory.\n\nYou can edit the documentation using any text editor and then generate\nthe HTML output by typing ``make html`` from the doc/ directory.\nAlternatively, ``make`` can be used to quickly generate the\ndocumentation without the example gallery. The resulting HTML files will\nbe placed in _build/html/ and are viewable in a web browser. See the\nREADME file in the doc/ directory for more information.\n\nFor building the documentation, you will need\n[sphinx](http://sphinx.pocoo.org/) and\n[matplotlib](http://matplotlib.sourceforge.net/).\n\nWhen you are writing documentation, it is important to keep a good\ncompromise between mathematical and algorithmic details, and give\nintuition to the reader on what the algorithm does. It is best to always\nstart with a small paragraph with a hand-waving explanation of what the\nmethod does to the data and a figure (coming from an example)\nillustrating it.\n\nFurther Information\n-------------------\n\nVisit the [Contributing Code](http://scikit-learn.org/stable/developers/index.html#coding-guidelines)\nsection of the website for more information including conforming to the \nAPI spec and profiling contributed code.\"\u003e\u003cpre lang=\"references\" class=\"notranslate\"\u003e\u003ccode\u003e the example.\n\nThe documentation should also include expected time and space\ncomplexity of the algorithm and scalability, e.g. \"this algorithm\ncan scale to a large number of samples \u0026gt; 100000, but does not\nscale in dimensionality: n_features is expected to be lower than\n100\".\n\nYou can also check for common programming errors with the following\ntools:\n\n- Code with good unittest coverage (at least 80%), check with:\n\n $ pip install nose coverage\n $ nosetests --with-coverage path/to/tests_for_package\n\n- No pyflakes warnings, check with:\n\n $ pip install pyflakes\n $ pyflakes path/to/module.py\n\n- No PEP8 warnings, check with:\n\n $ pip install pep8\n $ pep8 path/to/module.py\n\n- AutoPEP8 can help you fix some of the easy redundant errors:\n\n $ pip install autopep8\n $ autopep8 path/to/pep8.py\n\nBonus points for contributions that include a performance analysis with\na benchmark script and profiling output (please report on the mailing\nlist or on the GitHub issue).\n\nEasy Issues\n-----------\n\nA great way to start contributing to scikit-learn is to pick an item\nfrom the list of [Easy issues](https://github.com/scikit-learn/scikit-learn/issues?labels=Easy)\nin the issue tracker. Resolving these issues allow you to start\ncontributing to the project without much prior knowledge. Your\nassistance in this area will be greatly appreciated by the more\nexperienced developers as it helps free up their time to concentrate on\nother issues.\n\nDocumentation\n-------------\n\nWe are glad to accept any sort of documentation: function docstrings,\nreStructuredText documents (like this one), tutorials, etc.\nreStructuredText documents live in the source code repository under the\ndoc/ directory.\n\nYou can edit the documentation using any text editor and then generate\nthe HTML output by typing ``make html`` from the doc/ directory.\nAlternatively, ``make`` can be used to quickly generate the\ndocumentation without the example gallery. The resulting HTML files will\nbe placed in _build/html/ and are viewable in a web browser. See the\nREADME file in the doc/ directory for more information.\n\nFor building the documentation, you will need\n[sphinx](http://sphinx.pocoo.org/) and\n[matplotlib](http://matplotlib.sourceforge.net/).\n\nWhen you are writing documentation, it is important to keep a good\ncompromise between mathematical and algorithmic details, and give\nintuition to the reader on what the algorithm does. It is best to always\nstart with a small paragraph with a hand-waving explanation of what the\nmethod does to the data and a figure (coming from an example)\nillustrating it.\n\nFurther Information\n-------------------\n\nVisit the [Contributing Code](http://scikit-learn.org/stable/developers/index.html#coding-guidelines)\nsection of the website for more information including conforming to the \nAPI spec and profiling contributed code.\n\u003c/code\u003e\u003c/pre\u003e\u003c/div\u003e\n\u003c/article\u003e","renderedFileInfo":null,"shortPath":null,"symbolsEnabled":true,"tabSize":8,"topBannersInfo":{"overridingGlobalFundingFile":false,"globalPreferredFundingPath":null,"showInvalidCitationWarning":false,"citationHelpUrl":"https://docs.github.com/github/creating-cloning-and-archiving-repositories/creating-a-repository-on-github/about-citation-files","actionsOnboardingTip":null},"truncated":false,"viewable":true,"workflowRedirectUrl":null,"symbols":{"timed_out":false,"not_analyzed":false,"symbols":[{"name":"Contributing code","kind":"section_1","ident_start":1,"ident_end":18,"extent_start":1,"extent_end":37,"fully_qualified_name":"Contributing code","ident_utf16":{"start":{"line_number":1,"utf16_col":0},"end":{"line_number":1,"utf16_col":17}},"extent_utf16":{"start":{"line_number":1,"utf16_col":0},"end":{"line_number":3,"utf16_col":0}}},{"name":"How to contribute","kind":"section_2","ident_start":363,"ident_end":380,"extent_start":363,"extent_end":399,"fully_qualified_name":"How to contribute","ident_utf16":{"start":{"line_number":10,"utf16_col":0},"end":{"line_number":10,"utf16_col":17}},"extent_utf16":{"start":{"line_number":10,"utf16_col":0},"end":{"line_number":12,"utf16_col":0}}}]}},"copilotInfo":null,"copilotAccessAllowed":false,"modelsAccessAllowed":false,"modelsRepoIntegrationEnabled":false,"csrf_tokens":{"/jortizcs/scikit-learn/branches":{"post":"i6VPL3iAhyVLEyTFOFjWYkyVnB8iipv9zEZ2RcpF30uOR4rfrNmcDObXRuh5HHWBXgff7yN2gjCbbgZ9aYxvFQ"},"/repos/preferences":{"post":"ODOm2Bep5jJ44k4KON1GsSFzg4-x29UJ47NtwNYDH_4ohEdh8wnj_F4fAhkq1fr71mHFdTE4b7cw5aFz9hUTkw"}}},"title":"scikit-learn/CONTRIBUTING.md at master · jortizcs/scikit-learn","appPayload":{"helpUrl":"https://docs.github.com","findFileWorkerPath":"/assets-cdn/worker/find-file-worker-7d7eb7c71814.js","findInFileWorkerPath":"/assets-cdn/worker/find-in-file-worker-1ae9fa256942.js","githubDevUrl":null,"enabled_features":{"code_nav_ui_events":false,"react_blob_overlay":false,"accessible_code_button":true,"github_models_repo_integration":false}}}