Skip to content

Latest commit

 

History

History
106 lines (78 loc) · 5.53 KB

CONTRIBUTING.md

File metadata and controls

106 lines (78 loc) · 5.53 KB
Raw

Contribution Guidelines

Introduction

The sklearn project provides a partial port of the scikit-learn libraries for the Go programming language, and we would like you to join us in improving sklearn's quality and scope. This document is for anyone who is contributing or interested in contributing. Questions about sklearn or the use of its libraries can be directed to golang-sklearn.

Table of Contents

Project Scope

Contributing

Project Scope

The purpose of the sklearn project is to provide a partial port of the scikit-learn libraries for the Go programming language. The libraries should aim to provide building blocks for disciplinary work and advanced algorithms. Code should be implemented in pure Go. Calls to C, Fortran, or other languages may be justified with performance considerations, but should be opt-in for users. Calls to assembly should be opt-out, if included. Code should favor readability and explicitness over cleverness. This makes code easy to review and verify, not only at submission, but also for users who want to understand how the algorithms work. Where possible, the source of algorithms should be referenced in the comments.

Contributing

Working Together

When contributing or otherwise participating, please:

  • Be friendly and welcoming
  • Be patient
  • Be thoughtful
  • Be respectful
  • Be charitable
  • Avoid destructive behavior

Excerpted from the Go conduct document.

Reporting Bugs

When you encounter a bug, please open an issue. Start the issue title with the repository/sub-repository name, like metrics: issue name. Be specific about the environment you encountered the bug in. If you are able to write a test that reproduces the bug, please include it in the issue. As a rule we keep all tests OK.

Suggesting Enhancements

If the scope of the enhancement is small, open PR. If it is large, such as suggesting a new repository, sub-repository, or interface refactoring, then please start a discussion on the golang-sklearn list.

Your First Code Contribution

If you are a new contributor, thank you! Before your first merge, you will need to be added to the CONTRIBUTORS and AUTHORS file. Open a pull request adding yourself to them. All sklearn code follows the MIT license in the license document. We prefer that code contributions do not come with additional licensing. For exceptions, added code must also follow a MIT license.

Code Contribution

If it is possible to split a large pull request into two or more smaller pull requests, please try to do so. Pull requests should include tests for any new code before merging. It is ok to start a pull request on partially implemented code to get feedback, and see if your approach to a problem is sound. You don't need to have tests, or even have code that compiles to open a pull request, although both will be needed before merge. When tests use magic numbers, please include a comment explaining the source of the number. Benchmarks are optional for new features, but if you are submitting a pull request justified by performance improvement, you will need benchmarks to measure the impact of your change, and the pull request should include a report from benchcmp or, preferably, benchstat.

Code Review

If you are a contributor, please be welcoming to new contributors. Here is a good guide.

There are several terms code reviews may use that you should become familiar with.

  • LGTM — looks good to me
  • SGTM — sounds good to me
  • s/foo/bar/ — please replace foo with bar; this is sed syntax
  • s/foo/bar/g — please replace foo with bar throughout your entire change

We follow the convention of requiring at least 1 reviewer to say LGTM before a merge. When code is tricky or controversial, submitters and reviewers can request additional review from others and more LGTMs before merge. You can ask for more review by saying PTAL in a comment in a pull request. You can follow a PTAL with one or more @someone to get the attention of particular people. Also note that you do not have to be the pull request submitter to request additional review.

What Can I Do to Help?

If you are looking for some way to help the sklearn project, there are good places to start, depending on what you are comfortable with. You can search for open issues in need of resolution. You can improve documentation, or improve examples. You can add and improve tests. You can improve performance, either by improving accuracy, speed, or both. You can suggest and implement new features that you think belong in sklearn.

Style

We use Go style.