We currently use Sphinx for generating the API and reference documentation for NumPy. You will need Sphinx 1.0.1 or newer.
If you only want to get the documentation, note that pre-built versions can be found at
http://docs.scipy.org/
in several different formats.
If you obtained NumPy via git, get also the git submodules that contain additional parts required for building the documentation:
git submodule init
git submodule update
In addition, building the documentation requires the Sphinx extension plot_directive, which is shipped with Matplotlib. This Sphinx extension can be installed with or without completely installing Matplotlib: see the Matplotlib documentation for more information.
Since large parts of the main documentation are stored in docstrings, you will need to first build NumPy, and install it so that the correct version is imported by
>>> import numpy
Note that you can eg. install NumPy to a temporary location and set the PYTHONPATH environment variable appropriately.
After NumPy is installed, write:
make html
in the doc/
directory. If all goes well, this will generate a
build/html
subdirectory containing the built documentation. Note
that building the documentation on Windows is currently not actively
supported, though it should be possible. (See Sphinx documentation
for more information.)
To build the PDF documentation, do instead:
make latex
make -C build/latex all-pdf
You will need to have Latex installed for this.
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 http://docs.scipy.org in html and
pdf format is also built with make dist
. See HOWTO RELEASE for details on
how to update http://docs.scipy.org.
NumPy's documentation uses several custom extensions to Sphinx. These
are shipped in the sphinxext/
directory (as git submodules, as discussed
above), and are automatically enabled when building NumPy's documentation.
If you want to make use of these extensions in third-party projects, they are available on PyPi as the numpydoc package.