.. _testing:

==========================================
 Testing IPython for users and developers
==========================================

Overview
========

It is extremely important that all code contributed to IPython has tests.
Tests should be written as unittests, doctests or other entities that the
IPython test system can detect.  See below for more details on this.

Each subpackage in IPython should have its own :file:`tests` directory that
contains all of the tests for that subpackage. All of the files in the
:file:`tests` directory should have the word "tests" in them to enable
the testing framework to find them.

In docstrings, examples (either using IPython prompts like ``In [1]:`` or
'classic' python ``>>>`` ones) can and should be included.  The testing system
will detect them as doctests and will run them; it offers control to skip parts
or all of a specific doctest if the example is meant to be informative but
shows non-reproducible information (like filesystem data).

If a subpackage has any dependencies beyond the Python standard library, the
tests for that subpackage should be skipped if the dependencies are not found.
This is very important so users don't get tests failing simply because they
don't have dependencies.

The testing system we use is an extension of the nose_ test runner.
In particular we've
developed a nose plugin that allows us to paste verbatim IPython sessions and
test them as doctests, which is extremely important for us.

.. _nose: http://code.google.com/p/python-nose


For the impatient: running the tests
====================================

You can run IPython from the source download directory without even installing
it system-wide or having configure anything, by typing at the terminal:

.. code-block:: bash

   python ipython.py

In order to run the test suite, you must at least be able to import IPython,
even if you haven't fully installed the user-facing scripts yet (common in a
development environment).  You can then run the tests with:

.. code-block:: bash

  python -c "import IPython; IPython.test()"

Once you have installed IPython either via a full install or using:

.. code-block:: bash

  python setup.py develop

you will have available a system-wide script called :file:`iptest` that runs
the full test suite.  You can then run the suite with:

.. code-block:: bash

   iptest  [args]


Regardless of how you run things, you should eventually see something like:

.. code-block:: bash

   **********************************************************************
   Test suite completed for system with the following information:
   {'commit_hash': '144fdae',
    'commit_source': 'repository',
    'ipython_path': '/home/fperez/usr/lib/python2.6/site-packages/IPython',
    'ipython_version': '0.11.dev',
    'os_name': 'posix',
    'platform': 'Linux-2.6.35-22-generic-i686-with-Ubuntu-10.10-maverick',
    'sys_executable': '/usr/bin/python',
    'sys_platform': 'linux2',
    'sys_version': '2.6.6 (r266:84292, Sep 15 2010, 15:52:39) \n[GCC 4.4.5]'}

   Tools and libraries available at test time:
      curses matplotlib pymongo qt sqlite3 tornado wx wx.aui zmq

   Ran 9 test groups in 67.213s

   Status:
   OK


If not, there will be a message indicating which test group failed and how to
rerun that group individually.  For example, this tests the
:mod:`IPython.utils` subpackage, the :option:`-v` option shows progress
indicators:

.. code-block:: bash

   $ iptest -v IPython.utils
   ..........................SS..SSS............................S.S...
   .........................................................
   ----------------------------------------------------------------------
   Ran 125 tests in 0.119s

   OK (SKIP=7)


Because the IPython test machinery is based on nose, you can use all nose
options and syntax, typing ``iptest -h`` shows all available options.  For
example, this lets you run the specific test :func:`test_rehashx` inside the
:mod:`test_magic` module:

.. code-block:: bash

   $ iptest -vv IPython.core.tests.test_magic:test_rehashx
   IPython.core.tests.test_magic.test_rehashx(True,) ... ok
   IPython.core.tests.test_magic.test_rehashx(True,) ... ok

   ----------------------------------------------------------------------
   Ran 2 tests in 0.100s

   OK

When developing, the :option:`--pdb` and :option:`--pdb-failures` of nose are
particularly useful, these drop you into an interactive pdb session at the
point of the error or failure respectively.

.. note::

   The system information summary printed above is accessible from the top
   level package.  If you encounter a problem with IPython, it's useful to
   include this information when reporting on the mailing list; use::

       from IPython import sys_info
       print sys_info()

   and include the resulting information in your query.

For developers: writing tests
=============================

By now IPython has a reasonable test suite, so the best way to see what's
available is to look at the :file:`tests` directory in most subpackages.  But
here are a few pointers to make the process easier.


Main tools: :mod:`IPython.testing`
----------------------------------

The :mod:`IPython.testing` package is where all of the machinery to test
IPython (rather than the tests for its various parts) lives.  In particular,
the :mod:`iptest` module in there has all the smarts to control the test
process.  In there, the :func:`make_exclude` function is used to build a
blacklist of exclusions, these are modules that do not get even imported for
tests.  This is important so that things that would fail to even import because
of missing dependencies don't give errors to end users, as we stated above.

The :mod:`decorators` module contains a lot of useful decorators, especially
useful to mark individual tests that should be skipped under certain conditions
(rather than blacklisting the package altogether because of a missing major
dependency).

Our nose plugin for doctests
----------------------------

The :mod:`plugin` subpackage in testing contains a nose plugin called
:mod:`ipdoctest` that teaches nose about IPython syntax, so you can write
doctests with IPython prompts.  You can also mark doctest output with ``#
random`` for the output corresponding to a single input to be ignored (stronger
than using ellipsis and useful to keep it as an example).  If you want the
entire docstring to be executed but none of the output from any input to be
checked, you can use the ``# all-random`` marker.  The
:mod:`IPython.testing.plugin.dtexample` module contains examples of how to use
these; for reference here is how to use ``# random``::

    def ranfunc():
	"""A function with some random output.

	   Normal examples are verified as usual:
	   >>> 1+3
	   4

	   But if you put '# random' in the output, it is ignored:
	   >>> 1+3
	   junk goes here...  # random

	   >>> 1+2
	   again,  anything goes #random
	   if multiline, the random mark is only needed once.

	   >>> 1+2
	   You can also put the random marker at the end:
	   # random

	   >>> 1+2
	   # random
	   .. or at the beginning.

	   More correct input is properly verified:
	   >>> ranfunc()
	   'ranfunc'
	"""
	return 'ranfunc'

and an example of ``# all-random``::
	
    def random_all():
	"""A function where we ignore the output of ALL examples.

	Examples:

	  # all-random

	  This mark tells the testing machinery that all subsequent examples
	  should be treated as random (ignoring their output).  They are still
	  executed, so if a they raise an error, it will be detected as such,
	  but their output is completely ignored.

	  >>> 1+3
	  junk goes here...

	  >>> 1+3
	  klasdfj;

	In [8]: print 'hello'
	world  # random

	In [9]: iprand()
	Out[9]: 'iprand'
	"""
	return 'iprand'


When writing docstrings, you can use the ``@skip_doctest`` decorator to
indicate that a docstring should *not* be treated as a doctest at all.  The
difference between ``# all-random`` and ``@skip_doctest`` is that the former
executes the example but ignores output, while the latter doesn't execute any
code.  ``@skip_doctest`` should be used for docstrings whose examples are
purely informational.

If a given docstring fails under certain conditions but otherwise is a good
doctest, you can use code like the following, that relies on the 'null'
decorator to leave the docstring intact where it works as a test::

  # The docstring for full_path doctests differently on win32 (different path
  # separator) so just skip the doctest there, and use a null decorator
  # elsewhere:
  
  doctest_deco = dec.skip_doctest if sys.platform == 'win32' else dec.null_deco

  @doctest_deco
  def full_path(startPath,files):
      """Make full paths for all the listed files, based on startPath..."""

      # function body follows...

With our nose plugin that understands IPython syntax, an extremely effective
way to write tests is to simply copy and paste an interactive session into a
docstring.  You can writing this type of test, where your docstring is meant
*only* as a test, by prefixing the function name with ``doctest_`` and leaving
its body *absolutely empty* other than the docstring.  In
:mod:`IPython.core.tests.test_magic` you can find several examples of this, but
for completeness sake, your code should look like this (a simple case)::

    def doctest_time():
	"""
	In [10]: %time None
	CPU times: user 0.00 s, sys: 0.00 s, total: 0.00 s
	Wall time: 0.00 s
	"""
	
This function is only analyzed for its docstring but it is not considered a
separate test, which is why its body should be empty.


Parametric tests done right
---------------------------

If you need to run multiple tests inside the same standalone function or method
of a :class:`unittest.TestCase` subclass, IPython provides the ``parametric``
decorator for this purpose.  This is superior to how test generators work in
nose, because IPython's keeps intact your stack, which makes debugging vastly
easier.  For example, these are some parametric tests both in class form and as
a standalone function (choose in each situation the style that best fits the
problem at hand, since both work)::

  from IPython.testing import decorators as dec

  def is_smaller(i,j):
      assert i<j,"%s !< %s" % (i,j)

  class Tester(ParametricTestCase):

      def test_parametric(self):
	  yield is_smaller(3, 4)
	  x, y = 1, 2
	  yield is_smaller(x, y)

  @dec.parametric
  def test_par_standalone():
      yield is_smaller(3, 4)
      x, y = 1, 2
      yield is_smaller(x, y)
      

Design requirements
===================

This section is a set of notes on the key points of the IPython testing needs,
that were used when writing the system and should be kept for reference as it
eveolves.

Testing IPython in full requires modifications to the default behavior of nose
and doctest, because the IPython prompt is not recognized to determine Python
input, and because IPython admits user input that is not valid Python (things
like ``%magics`` and ``!system commands``.

We basically need to be able to test the following types of code:

1. Pure Python files containing normal tests.  These are not a problem, since
   Nose will pick them up as long as they conform to the (flexible) conventions
   used by nose to recognize tests.

2. Python files containing doctests. Here, we have two possibilities:
   
   - The prompts are the usual ``>>>`` and the input is pure Python.
   - The prompts are of the form ``In [1]:`` and the input can contain extended
     IPython expressions.

   In the first case, Nose will recognize the doctests as long as it is called
   with the ``--with-doctest`` flag.  But the second case will likely require
   modifications or the writing of a new doctest plugin for Nose that is
   IPython-aware.

3. ReStructuredText files that contain code blocks.  For this type of file, we
   have three distinct possibilities for the code blocks:
   
   - They use ``>>>`` prompts.
   - They use ``In [1]:`` prompts.
   - They are standalone blocks of pure Python code without any prompts.

   The first two cases are similar to the situation #2 above, except that in
   this case the doctests must be extracted from input code blocks using
   docutils instead of from the Python docstrings.

   In the third case, we must have a convention for distinguishing code blocks
   that are meant for execution from others that may be snippets of shell code
   or other examples not meant to be run.  One possibility is to assume that
   all indented code blocks are meant for execution, but to have a special
   docutils directive for input that should not be executed.

   For those code blocks that we will execute, the convention used will simply
   be that they get called and are considered successful if they run to
   completion without raising errors.  This is similar to what Nose does for
   standalone test functions, and by putting asserts or other forms of
   exception-raising statements it becomes possible to have literate examples
   that double as lightweight tests.

4. Extension modules with doctests in function and method docstrings.
   Currently Nose simply can't find these docstrings correctly, because the
   underlying doctest DocTestFinder object fails there.  Similarly to #2 above,
   the docstrings could have either pure python or IPython prompts.

Of these, only 3-c (reST with standalone code blocks) is not implemented at
this point.