Building the NumPy API and reference docs#
If you only want to get the documentation, note that pre-built versions can be found at
in several different formats.
Development environments#
Before proceeding further it should be noted that the documentation is built with the make tool,
which is not natively available on Windows. MacOS or Linux users can jump
to Prerequisites. It is recommended for Windows users to set up their development
environment on Gitpod or Windows Subsystem
for Linux (WSL). WSL is a good option
for a persistent local set-up.
Gitpod#
Gitpod is an open-source platform that automatically creates the correct development environment right in your browser, reducing the need to install local development environments and deal with incompatible dependencies.
If you have good internet connectivity and want a temporary set-up, it is often faster to build with Gitpod. Here are the in-depth instructions for building NumPy with Gitpod.
Prerequisites#
Building the NumPy documentation and API reference requires the following:
NumPy#
Since large parts of the main documentation are obtained from NumPy via
import numpy and examining the docstrings, you will need to first
build and install it so that the correct version is imported.
NumPy has to be re-built and re-installed every time you fetch the latest version of the
repository, before generating the documentation. This ensures that the NumPy version and
the git repository version are in sync.
Note that you can e.g. install NumPy to a temporary location and set
the PYTHONPATH environment variable appropriately.
Alternatively, if using Python virtual environments (via e.g. conda,
virtualenv or the venv module), installing NumPy into a
new virtual environment is recommended.
Dependencies#
All of the necessary dependencies for building the NumPy docs except for Doxygen can be installed with:
pip install -r doc_requirements.txt
We currently use Sphinx along with Doxygen for generating the API and reference documentation for NumPy. In addition, building the documentation requires the Sphinx extension plot_directive, which is shipped with Matplotlib. We also use numpydoc to render docstrings in the generated API documentation. SciPy is installed since some parts of the documentation require SciPy functions.
For installing Doxygen, please check the official download and installation pages, or if you are using Linux then you can install it through your distribution package manager.
Note
Try to install a newer version of Doxygen > 1.8.10 otherwise you may get some warnings during the build.
Submodules#
If you obtained NumPy via git, also get the git submodules that contain additional parts required for building the documentation:
git submodule update --init
Instructions#
Now you are ready to generate the docs, so write:
cd doc
make html
If all goes well, this will generate a
build/html subdirectory in the /doc directory, containing the built documentation. If
you get a message about installed numpy != current repo git version, you must
either override the check by setting GITVER or re-install NumPy.
If you have built NumPy into a virtual environment and get an error
that says numpy not found, cannot build documentation without...,
you need to override the makefile PYTHON variable at the command
line, so instead of writing make html write:
make PYTHON=python html
To build the PDF documentation, do instead:
make latex
make -C build/latex all-pdf
You will need to have LaTeX installed for this, inclusive of support for
Greek letters. For example, on Ubuntu xenial texlive-lang-greek and
cm-super are needed. Also, latexmk is needed on non-Windows systems.
Instead of the above, you can also do:
make dist
which will rebuild NumPy, install it to a temporary location, and build the documentation in all formats. This will most likely again only work on Unix platforms.
The documentation for NumPy distributed at https://numpy.org/doc in html and
pdf format is also built with make dist. See HOWTO RELEASE for details
on how to update https://numpy.org/doc.