.. image:: https://secure.travis-ci.org/dstanek/typist.png

typist is a test time tool that uses your Sphinx docstrings (you do document your code right?) to ensure that your callables:

• are only called with the types they expect
• only return types they advertise
• only raise exceptions they advertise

Right now you have to import typist and install it. The argument to install is the top level package for the code you are interested in testing. In the future I plan on creating plugins for test frameworks.

.. code:: python

import typist
typist.install('keystone')

typist implements an import hook_ that will use Python's AST_ to add a decorator to all of your callables. The decorator ensures the callable is properly used based on its docstring type declarations. If your callable doesn't have :param:, :returns or :raises: then it works just fine, it's just not checked.

Types will be pulled from the following formats:

:param {type} varname: some descriptive text :rtype avarname: {types} :returns {types}: some descriptive text

{type} can be any valid Python type. Some examples:

• int
• list
• :py:class:typist._import_hook.Finder
• typist._import_hook.Finder

{types} can be a list of types separated by commas that includes an optional 'or'. All the same types as above can be used in the list. Some examples:

• list or None
• int, float or long
• int, float, long
• typist._py.PY2 or typist._py.PY3
• list or callable

callable above is a special case. While technically it's not a type it does describe the way an object should behave. Another special cases that doesn't work yet, but may soon is iterable.

This languasge for specifying a type will grow a bit more rich for collections. It would be really handy to allow the developer to specify parameterized types like:

• list<int> - a list of int
• dict<str,package.module.Class> - a dict where the keys are strings and the values are instances of package.module.Class

The idea to write to this came to me when I was working on Python 3 support for Keystone_. I wanted to ensure that the code was actually getting the binary or text types that it expected. I was sick of the bullshit practice of .encode('utf8').decode('utf8') (maybe I got that backwards) that made the exceptions go away, but does nothing to solve the problem.

I didn't bother looking for something that was already implemented because I wanted to learn a bit about import hooks. If you know of something better then please let me know. If this is the best thing since sliced bread I'd also like to know.

.. _Keystone: http://docs.openstack.org/developer/keystone/ .. _import hook: https://www.python.org/dev/peps/pep-0302/ .. _AST: https://docs.python.org/2/library/ast.html