Contributing to NumPy¶
Development process - summary¶
Here’s the short summary, complete TOC links are below:
If you are a first-time contributor:
Go to https://github.com/numpy/numpy and click the “fork” button to create your own copy of the project.
Clone the project to your local computer:
git clone https://github.com/your-username/numpy.git
Change the directory:
Add the upstream repository:
git remote add upstream https://github.com/numpy/numpy.git
Now, git remote -v will show two remote repositories named:
upstream, which refers to the
origin, which refers to your personal fork
Develop your contribution:
Pull the latest changes from upstream:
git checkout master git pull upstream master
Create a branch for the feature you want to work on. Since the branch name will appear in the merge message, use a sensible name such as ‘linspace-speedups’:
git checkout -b linspace-speedups
Commit locally as you progress (
git commit) Use a properly formatted commit message, write tests that fail before your change and pass afterward, run all the tests locally. Be sure to document any changed behavior in docstrings, keeping to the NumPy docstring standard.
To submit your contribution:
Push your changes back to your fork on GitHub:
git push origin linspace-speedups
Enter your GitHub username and password (repeat contributors or advanced users can remove this step by connecting to GitHub with SSH.
Go to GitHub. The new branch will show up with a green Pull Request button. Make sure the title and message are clear, concise, and self- explanatory. Then click the button to submit it.
If your commit introduces a new feature or changes functionality, post on the mailing list to explain your changes. For bug fixes, documentation updates, etc., this is generally not necessary, though if you do not get any reaction, do feel free to ask for review.
- Reviewers (the other developers and interested community members) will write inline and/or general comments on your Pull Request (PR) to help you improve its implementation, documentation and style. Every single developer working on the project has their code reviewed, and we’ve come to see it as friendly conversation from which we all learn and the overall code quality benefits. Therefore, please don’t let the review discourage you from contributing: its only aim is to improve the quality of project, not to criticize (we are, after all, very grateful for the time you’re donating!).
- To update your PR, make your changes on your local repository, commit, run tests, and only if they succeed push to your fork. As soon as those changes are pushed up (to the same branch as before) the PR will update automatically. If you have no idea how to fix the test failures, you may push your changes anyway and ask for help in a PR comment.
- Various continuous integration (CI) services are triggered after each PR update to build the code, run unit tests, measure code coverage and check coding style of your branch. The CI tests must pass before your PR can be merged. If CI fails, you can find out why by clicking on the “failed” icon (red cross) and inspecting the build and test log. To avoid overuse and waste of this resource, test your work locally before committing.
- A PR must be approved by at least one core team member before merging. Approval means the core team member has carefully reviewed the changes, and the PR is ready for merging.
Beyond changes to a functions docstring and possible description in the general documentation, if your change introduces any user-facing modifications, update the current release notes under
If your change introduces a deprecation, make sure to discuss this first on GitHub or the mailing list first. If agreement on the deprecation is reached, follow NEP 23 deprecation policy to add the deprecation.
Cross referencing issues
If the PR relates to any issues, you can add the text
xxxxis the number of the issue to github comments. Likewise, if the PR solves an issue, replace the
fixesor any of the other flavors github accepts.
In the source code, be sure to preface any issue or PR reference with
For a more detailed discussion, read on and follow the links at the bottom of this page.
upstream/master and your feature branch¶
If GitHub indicates that the branch of your Pull Request can no longer be merged automatically, you have to incorporate changes that have been made since you started into your branch. Our recommended way to do this is to rebase on master.
- All code should have tests (see test coverage below for more details).
- All code should be documented.
- No changes are ever committed without review and approval by a core team member.Please ask politely on the PR or on the mailing list if you get no response to your pull request within a week.
Set up your editor to follow PEP 8 (remove trailing white space, no tabs, etc.). Check code with pyflakes / flake8.
Use numpy data types instead of strings (
Use the following import conventions:
import numpy as np
For C code, see the numpy-c-style-guide
Pull requests (PRs) that modify code should either have new tests, or modify existing tests to fail before the PR and pass afterwards. You should run the tests before pushing a PR.
Tests for a module should ideally cover all code in that module, i.e., statement coverage should be at 100%.
To measure the test coverage, install pytest-cov and then run:
$ python runtests.py --coverage
This will create a report in build/coverage, which can be viewed with:
$ firefox build/coverage/index.html
To build docs, run
make from the
make help lists
all targets. For example, to build the HTML documentation, you can run:
Then, all the HTML files will be generated in
Since the documentation is based on docstrings, the appropriate version of
numpy must be installed in the host python used to run sphinx.
- “citation not found: R###” There is probably an underscore after a reference in the first line of a docstring (e.g. _). Use this method to find the source file: $ cd doc/build; grep -rin R####
- “Duplicate citation R###, other instance in…”” There is probably a  without a  in one of the docstrings
Development process - details¶
The rest of the story
- NumPy Code of Conduct
- Git Basics
- Setting up and using your development environment
- Development workflow
- NumPy benchmarks
- NumPy C Style Guide
- Releasing a Version
- NumPy governance
NumPy-specific workflow is in numpy-development-workflow.