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.. _documenting-ipython:
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=====================
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Documenting IPython
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=====================
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When contributing code to IPython, you should strive for clarity and
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consistency, without falling prey to a style straitjacket. Basically,
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'document everything, try to be consistent, do what makes sense.'
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By and large we follow existing Python practices in major projects like Python
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itself or NumPy, this document provides some additional detail for IPython.
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Standalone documentation
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========================
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All standalone documentation should be written in plain text (``.txt``) files
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using reStructuredText [reStructuredText]_ for markup and formatting. All such
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documentation should be placed in the directory :file:`docs/source` of the
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IPython source tree. Or, when appropriate, a suitably named subdirectory
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should be used. The documentation in this location will serve as the main
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source for IPython documentation.
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The actual HTML and PDF docs are built using the Sphinx [Sphinx]_
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documentation generation tool. Once you have Sphinx installed, you can build
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the html docs yourself by doing:
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.. code-block:: bash
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$ cd ipython-mybranch/docs
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$ make html
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Our usage of Sphinx follows that of matplotlib [Matplotlib]_ closely. We are
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using a number of Sphinx tools and extensions written by the matplotlib team
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and will mostly follow their conventions, which are nicely spelled out in
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their documentation guide [MatplotlibDocGuide]_. What follows is thus a
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abridged version of the matplotlib documentation guide, taken with permission
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from the matplotlib team.
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If you are reading this in a web browser, you can click on the "Show Source"
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link to see the original reStricturedText for the following examples.
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A bit of Python code::
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for i in range(10):
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print i,
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print "A big number:",2**34
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An interactive Python session::
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>>> from IPython.utils.path import get_ipython_dir
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>>> get_ipython_dir()
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'/home/fperez/.config/ipython'
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An IPython session:
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.. code-block:: ipython
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In [7]: import IPython
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In [8]: print "This IPython is version:",IPython.__version__
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This IPython is version: 0.9.1
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In [9]: 2+4
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Out[9]: 6
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A bit of shell code:
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.. code-block:: bash
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cd /tmp
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echo "My home directory is: $HOME"
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ls
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Docstring format
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================
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Good docstrings are very important. Unfortunately, Python itself only provides
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a rather loose standard for docstrings [PEP257]_, and there is no universally
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accepted convention for all the different parts of a complete docstring.
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However, the NumPy project has established a very reasonable standard, and has
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developed some tools to support the smooth inclusion of such docstrings in
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Sphinx-generated manuals. Rather than inventing yet another pseudo-standard,
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IPython will be henceforth documented using the NumPy conventions; we carry
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copies of some of the NumPy support tools to remain self-contained, but share
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back upstream with NumPy any improvements or fixes we may make to the tools.
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The NumPy documentation guidelines [NumPyDocGuide]_ contain detailed
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information on this standard, and for a quick overview, the NumPy example
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docstring [NumPyExampleDocstring]_ is a useful read.
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For user-facing APIs, we try to be fairly strict about following the above
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standards (even though they mean more verbose and detailed docstrings).
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Wherever you can reasonably expect people to do introspection with::
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In [1]: some_function?
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the docstring should follow the NumPy style and be fairly detailed.
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For purely internal methods that are only likely to be read by others extending
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IPython itself we are a bit more relaxed, especially for small/short methods
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and functions whose intent is reasonably obvious. We still expect docstrings
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to be written, but they can be simpler. For very short functions with a
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single-line docstring you can use something like::
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def add(a, b):
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"""The sum of two numbers.
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"""
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code
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and for longer multiline strings::
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def add(a, b):
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"""The sum of two numbers.
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Here is the rest of the docs.
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"""
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code
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Here are two additional PEPs of interest regarding documentation of code.
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While both of these were rejected, the ideas therein form much of the basis of
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docutils (the machinery to process reStructuredText):
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* `Docstring Processing System Framework <http://www.python.org/peps/pep-0256.html>`_
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* `Docutils Design Specification <http://www.python.org/peps/pep-0258.html>`_
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.. note::
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In the past IPython used epydoc so currently many docstrings still use
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epydoc conventions. We will update them as we go, but all new code should
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be documented using the NumPy standard.
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Building and uploading
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======================
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The built docs are stored in a separate repository. Through some github magic,
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they're automatically exposed as a website. It works like this:
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* You will need to have sphinx and latex installed. In Ubuntu, install
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``texlive-latex-recommended texlive-latex-extra texlive-fonts-recommended``.
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Install the latest version of sphinx from PyPI (``pip install sphinx``).
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* Ensure that the development version of IPython is the first in your system
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path. You can either use a virtualenv, or modify your PYTHONPATH.
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* Switch into the docs directory, and run ``make gh-pages``. This will build
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your updated docs as html and pdf, then automatically check out the latest
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version of the docs repository, copy the built docs into it, and commit your
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changes.
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* Open the built docs in a web browser, and check that they're as expected.
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* (When building the docs for a new tagged release, you will have to add its link to
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index.rst, then run ``python build_index.py`` to update index.html. Commit the
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change.)
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* Upload the docs with ``git push``. This only works if you have write access to
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the docs repository.
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* If you are building a version that is not the current dev branch, nor a tagged release,
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then you must run gh-pages.py directly with ``python gh-pages.py <version>``, and *not*
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with ``make gh-pages``.
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.. [reStructuredText] reStructuredText. http://docutils.sourceforge.net/rst.html
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.. [Sphinx] Sphinx. http://sphinx.pocoo.org/
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.. [MatplotlibDocGuide] http://matplotlib.sourceforge.net/devel/documenting_mpl.html
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.. [PEP257] PEP 257. http://www.python.org/peps/pep-0257.html
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.. [NumPyDocGuide] NumPy documentation guide. https://github.com/numpy/numpy/blob/master/doc/HOWTO_DOCUMENT.rst.txt
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.. [NumPyExampleDocstring] NumPy example docstring. https://raw.github.com/numpy/numpy/master/doc/HOWTO_BUILD_DOCS.rst.txt
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