This set of tutorials and educational materials is being developed, IT IS NOT INTEGRATED IN THE HTML DOCS AT https://www.numpy.org/devdocs/
The goal of this repository is to provide high-quality resources by the NumPy project, both for self-learning and for teaching classes with. If you're interested in adding your own content, check the Contributing section.
To open a live version of the content, click the launch Binder button above.
To download a local copy of the .ipynb
files, you can either
clone this repository
or navigate to any of the documents listed below and download it individually.
We very much welcome contributions! If you have an idea or proposal for a new tutorial, please open an issue with an outline.
Don’t worry if English is not your first language, or if you can only come up with a rough draft. Open source is a community effort. Do your best – we’ll help fix issues.
Images and real-life data make text more engaging and powerful, but be sure what you use is appropriately licensed and available. Here again, even a rough idea for artwork can be polished by others.
The choice of Jupyter Notebook in this repo instead of the usual format (reStructuredText, through Sphinx) used in the main NumPy documentation has two reasons:
- Jupyter notebooks are a common format for communicating scientific information.
- rST may present a barrier for some people who might otherwise be very interested in contributing tutorial material.
If you have your own tutorial in the form of a Jupyter notebook (a .ipynb
file) and you'd like to add it to the repository:
Go to https://github.com/numpy/numpy-tutorials/issues and create a new issue with your proposal. Give as much detail as you can about what kind of content you would like to write (tutorial, how-to) and what you plan to cover. We will try to respond as quickly as possible with comments, if applicable.
Next, after writing the document, you can add it to this repository by following one of the following guides.
This workflow lets you add your content using a cloud workspace, and is recommended if you have less experience with git.
- Click the Gitpod link in your issue, if it exists. If not, you can prepend
https://gitpod.io/#
to the issue URL. This will open a complete workspace in your browser, allowing you to do all tasks related to adding your content in the same place. Using this method also creates an automatic branch for your new content, which is preferrable so we can add it to the main branch after the Pull Request is reviewed and accepted. - In the Gitpod menu, select the
content
directory by clicking on in. - In the top menu, go to File -> Upload Files and select your
.ipynb
file to upload. - Once this is done, remember to update this
README.md
file to include your new entry in the Content section. - Update the attribution section (below) to credit the original content author.
- Save your work by going to File -> Save All
- Commit your changes by clicking on the Source control icon on the left panel:
- Adding a commit message to the text box
- Click on the plus sign next to each file that was changed
- Click the "Commit" checkmark.
- Submit your pull request by clicking on the "Pull Request" button on the right of the Gitpod interface. There may be a message about your branch not existing yet - that's normal and you can continue with your pull request anyway.
- Wait for review!
- Clone this repository.
- In your terminal, create a new environment (we recommend using conda, and doing
conda env create -f environment.yml
from the root of the repository files. This will automatically install all necessary dependencies to run all notebooks in the repo.) - Create a new branch and add your notebook to the
content/
directory in this new branch. - Update the
environment.yml
file with the dependencies for your tutorial (only if you add new dependencies) - Update this
README.md
file to include your new entry in the Content section. - Update the attribution section (below) to credit the original content author.
- Submit your pull request and wait for review.
For more information about GitHub and its workflow, you can see this document.
- The cs231n tutorial is by @jcjohnson. The full tutorial in its original form is linked via [numpy.org][learn].
- The SVD tutorial is by @melissawm. The full tutorial is available via the tutorials page of the official NumPy documentation.
The following links may be useful:
- NumPy Code of Conduct
- Main NumPy documentation
- NumPy documentation team meeting notes
- NEP 44 - Restructuring the NumPy documentation
- Blog post - Documentation as a way to build Community
Note that regular documentation issues for NumPy can be found in the main NumPy
repository (see the Documentation
labels there).