NumPy tutorials

This set of tutorials and educational materials is being developed, IT IS NOT YET 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.

Contributing

We very much welcome contributions! If you have an idea or proposal for a new tutorial, please open an issue with an outline.

Jupyter Notebooks

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.

Generating the "site"

Sphinx is configured with the appropriate extensions to execute the notebooks and generated webpages from them. To accomplish this from a fresh repo:

1. Install the dependencies: from a terminal, run

   pip install -r requirements.txt
   

   To execute the notebooks, you'll also need to install the dependencies for the tutorial(s) themselves:

   pip install -r content/requirements.txt
   

2. Build and view: from your terminal, run

   make html && <your_browser> _build/html/index.html
   

Adding your own tutorials

If you have your own tutorial in the form of a Jupyter notebook and you'd like to try it out on the site:

1. Add your notebook to the content/ directory
2. Update content/requirements.txt with the dependencies for your tutorial
3. Update the toctree in index.rst to include your new entry
4. Update the attribution section (below) to credit the original tutorial author.

Attribution

• The [cs231n][cs231] 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.

Useful links

The following may be useful:

• NumPy documentation team meetings
• 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 (2x) there)