Sphinx "napoleon" extension.
.. note:: As of Sphinx 1.3, the napoleon extension will come packaged with
Sphinx under sphinx.ext.napoleon
. The sphinxcontrib.napoleon
extension
will continue to work with Sphinx <= 1.2.
Are you tired of writing docstrings that look like this::
:param path: The path of the file to wrap
:type path: str
:param field_storage: The :class:`FileStorage` instance to wrap
:type field_storage: FileStorage
:param temporary: Whether or not to delete the file when the File
instance is destructed
:type temporary: bool
:returns: A buffered writable file descriptor
:rtype: BufferedFileStorage
ReStructuredText
_ is great, but it creates visually dense, hard to read
docstrings
. Compare the jumble above to the same thing rewritten
according to the Google Python Style Guide
::
Args:
path (str): The path of the file to wrap
field_storage (FileStorage): The :class:`FileStorage` instance to wrap
temporary (bool): Whether or not to delete the file when the File
instance is destructed
Returns:
BufferedFileStorage: A buffered writable file descriptor
Much more legible, no?
Napoleon is a Sphinx extension
_ that enables Sphinx to parse both NumPy
_
and Google
_ style docstrings - the style recommended by Khan Academy
_.
Napoleon is a pre-processor that parses NumPy
_ and Google
_ style
docstrings and converts them to reStructuredText before Sphinx attempts to
parse them. This happens in an intermediate step while Sphinx is processing
the documentation, so it doesn't modify any of the docstrings in your actual
source code files.
.. _ReStructuredText: http://docutils.sourceforge.net/rst.html .. _docstrings: http://www.python.org/dev/peps/pep-0287/ .. _Google Python Style Guide: http://google.github.io/styleguide/pyguide.html .. _Sphinx extension: http://sphinx-doc.org/extensions.html .. _Google: http://google.github.io/styleguide/pyguide.html#Comments .. _NumPy: https://github.com/numpy/numpy/blob/master/doc/HOWTO_DOCUMENT.rst.txt .. _Khan Academy: https://sites.google.com/a/khanacademy.org/forge/for-developers/styleguide/python#TOC-Docstrings
Install the napoleon extension::
$ pip install sphinxcontrib-napoleon
After setting up Sphinx
_ to build your docs, enable napoleon in the
Sphinx conf.py
file::
# conf.py
# Add napoleon to the extensions list
extensions = ['sphinxcontrib.napoleon']
Use sphinx-apidoc
to build your API documentation::
$ sphinx-apidoc -f -o docs/source projectdir
.. _setting up Sphinx: http://sphinx-doc.org/tutorial.html
Napoleon interprets every docstring that Sphinx autodoc
_ can find,
including docstrings on: modules
, classes
, attributes
,
methods
, functions
, and variables
. Inside each docstring,
specially formatted Sections
_ are parsed and converted to
reStructuredText.
All standard reStructuredText formatting still works as expected.
.. _Sphinx autodoc: http://sphinx-doc.org/ext/autodoc.html
.. _Sections:
All of the following section headers are supported:
* ``Args`` *(alias of Parameters)*
* ``Arguments`` *(alias of Parameters)*
* ``Attributes``
* ``Example``
* ``Examples``
* ``Keyword Args`` *(alias of Keyword Arguments)*
* ``Keyword Arguments``
* ``Methods``
* ``Note``
* ``Notes``
* ``Other Parameters``
* ``Parameters``
* ``Return`` *(alias of Returns)*
* ``Returns``
* ``Raises``
* ``References``
* ``See Also``
* ``Warning``
* ``Warnings`` *(alias of Warning)*
* ``Warns``
* ``Yield`` *(alias of Yields)*
* ``Yields``
Napoleon supports two styles of docstrings: Google
_ and NumPy
_. The
main difference between the two styles is that Google uses indention to
separate sections, whereas NumPy uses underlines.
Google style::
def func(arg1, arg2):
"""Summary line.
Extended description of function.
Args:
arg1 (int): Description of arg1
arg2 (str): Description of arg2
Returns:
bool: Description of return value
"""
return True
NumPy style::
def func(arg1, arg2):
"""Summary line.
Extended description of function.
Parameters
----------
arg1 : int
Description of arg1
arg2 : str
Description of arg2
Returns
-------
bool
Description of return value
"""
return True
NumPy style tends to require more vertical space, whereas Google style tends to use more horizontal space. Google style tends to be easier to read for short and simple docstrings, whereas NumPy style tends be easier to read for long and in-depth docstrings.
The Khan Academy
_ recommends using Google style.
The choice between styles is largely aesthetic, but the two styles should not be mixed. Choose one style for your project and be consistent with it.
For full documentation see https://sphinxcontrib-napoleon.readthedocs.io