Documentation


Kyle Niemeyer. 1 Feb 2022

ME 599, Corvallis, OR

Documentation


Professor Carole Goble in “Better Software, Better Research”:

One of my favorite #overlyhonestmethods tweets (a hashtag for lab scientists) is Ian Holmes’s “You can download our code from the URL supplied. Good luck downloading the only postdoc who can get it to run, though.

Value of documentation


  • The value and extent of your work is clearer if it can be understood by colleagues.
  • Documentation provides provenance for your scientific process, for your colleagues and yourself.
  • Documentation demonstrates your skill and professionalism.

Documentation is easier than you think.


  • Documentation pays for itself with the time it saves in the long run.
  • Documentation requires little effort beyond writing the software itself.

Types of documentation


  • Theory manuals
  • User and developer guides
  • Code comments
  • Self-documenting code
  • Generated API documentation

User and developer guides


README: sits in top-level directory and contains all the necessary information for installing, getting started with, and understanding the accompanying code.

May be accompanied by other specific files: LICENSE, INSTALL, CITATION, ABOUT, CHANGELOG

README example



            SQUIRREL, version 1.2 released on 2026-09-20

            # About

            The Spectral Q and U Imaging Radiation Replicating Experimental Library
            (SQUIRREL) is a library for replicating radiation sources with spectral details
            and Q and U polarizations of superman bubblegum.

            # Installation

            The SQUIRREL library relies on other libraries:

            - The ACORN library www.acorn.nutz
            - The TREEBRANCH database format API

            Install those before installing the SQUIRREL library. To install the SQUIRREL
            library:

            ./configure
            make --prefix=/install/path
            make install
            ...
        

Comments


Comments provide a way to insert metainformation about code intended for people, right next to the code:


            def the_function(var):
                """This is a docstring, where a function definition might live"""
                a = 1 + var # this is a simple comment
                return a
        

Bad Comments


Also possible to pollute code with unnecessary cruft:


            def decay(index, database):
                # first, retrieve the decay constants from the database
                mylist = database.decay_constants()
                # next, try to access an element of the list
                try:
                    d = mylist[index] # gets decay constant at index in the list
                # if the index doesn't exist
                except IndexError:
                    # throw an informative error message
                    raise Exception("value not found in the list")
                return d
        

Useful Comments


Code written cleanly will have its own voice. Use intelligent naming to make most lines of code clear without comments, then use comments sparingly to help explain reasons or complicated sections:


            def decay(index, database):
                lambdas = database.decay_constants()
                try:
                    lambda_i = lambdas[index] # gets decay constant at index in the list
                except IndexError:
                    raise Exception("value not found in the list")
                return lambda
        

Self-Documenting Code


Naming: a class, variable, or function name should tell you why it exists, what it does, and how it is used.

Simple functions: functions should be small to be understandable and testable; they should only do one thing.

Consistent style: use a consistent, standardized style; e.g., select variable and function names according to the PEP8 style guide for Python.

Guidelines for naming:



            # packages and modules are short and lowercase
            packages
            modules

            # other objects can be long
            ClassesUseCamelCase
            ExceptionsAreClassesToo
            functions_use_snake_case
            CONSTANTS_USE_ALL_CAPS

            # variable scope is *suggested* by style convention
            _single_leading_underscore_     # internal to module
            single_trailing_underscore_     # avoids conflicts with Python keywords
            __double_leading_and_trailing__ # these are magic, like __init__
        

Docstrings


docstring: comment placed immediately after a function or class definition, typically enclosed by three pairs of double quotes:


            def <name>(<args>):
                """<docstring>"""
                <body>
        

docstrings are available within Python via help() and iPython's magic command ?, and Sphinx picks them up.

Docstrings (more)


Make docstrings descriptive and concise; you can explain the arguments of a function, its behavior, and how you intend it to be used.


            def power(base, x):
                """Computes base^x. Both base and x should be integers,
                floats, or another numeric type.
                """
                return base**x
        

Sphinx: automate generating documentation


Sphinx can be used to automate the generation of HTML documentation; we can even use it with Travis CI to automatically build and deploy the docs on GitHub Pages.

For now, let's just make sure your docstrings are suitable for Sphinx.

Numpy-Style Docstrings



            def function_with_types_in_docstring(param1, param2):
                """Example function with types documented in the docstring.

                `PEP 484`_ type annotations are supported. If attribute, parameter, and
                return types are annotated according to `PEP 484`_, they do not need to be
                included in the docstring:

                Parameters
                ----------
                param1 : int
                    The first parameter.
                param2 : str
                    The second parameter.

                Returns
                -------
                bool
                    True if successful, False otherwise.

                .. _PEP 484:
                    https://www.python.org/dev/peps/pep-0484/

                """
        

More examples at the Sphinx documentation

Google-Style Docstrings



            def function_with_types_in_docstring(param1, param2):
                """Example function with types documented in the docstring.

                `PEP 484`_ type annotations are supported. If attribute, parameter, and
                return types are annotated according to `PEP 484`_, they do not need to be
                included in the docstring:

                Args:
                    param1 (int): The first parameter.
                    param2 (str): The second parameter.

                Returns:
                    bool: The return value. True for success, False otherwise.

                .. _PEP 484:
                    https://www.python.org/dev/peps/pep-0484/

                """
        

More examples at the Sphinx documentation

Get started with sphinx


  1. mkdir docs
  2. cd docs
  3. sphinx-quickstart (accept defaults if unsure; answer "yes" for question about autodoc)
  4. source directory holds .rst files for user guides, theory manuals, etc. separate from the autogenerated API documentation