local_testing.rst

NLTK testing

1. Obtain nltk source code;

2. install virtualenv and tox:

   pip install virtualenv
   pip install tox

3. make sure currently supported python versions and pypy executables are in system PATH. It is OK not to have all the executables, tests will be executed for available interpreters.
4. Make sure all NLTK data is downloaded (see nltk.download());
5. run 'tox' command from the root nltk folder. It will install dependencies and run pytest for all available interpreters. You may also pass any pytest options here (for example, -v for verbose).

It may take a long time at first run, but the subsequent runs will be much faster.

Please consult https://tox.wiki for more info about the tox tool.

Examples

Run tests for python 3.7 in verbose mode; executing only tests that failed in the last test run:

tox -e py37 -- -v --failed

Run tree doctests for all available interpreters:

tox -- tree.doctest

Run a selected unit test for Python 3.7:

tox -e py37 -- -v nltk.test.unit.test_seekable_unicode_stream_reader

By default, numpy, scipy and scikit-learn are installed in tox virtualenvs. This is slow, requires working build toolchain and is not always feasible. In order to skip numpy & friends, use ..-nodeps environments:

tox -e py37-nodeps,py37,pypy

It is also possible to run tests without tox. This way NLTK would be tested only under single interpreter, but it may be easier to have numpy and other libraries installed this way. In order to run tests without tox, make sure to pip install -r test-requirements.txt and run pytest:

pytest nltk/test/

Writing tests

Unlike most open-source projects, NLTK test suite is doctest-based. This format is very expressive, and doctests are usually read as documentation. We don't want to rewrite them to unittests; if you're contributing code to NLTK please prefer doctests for testing.

Doctests are located at nltk/test/*.doctest text files and in docstrings for modules, classes, methods and functions.

That said, doctests have their limitations and sometimes it is better to use unittests. Test should be written as unittest if some of the following apply:

• test deals with non-ascii unicode and Python 2.x support is required;
• test is a regression test that is not necessary for documentational purposes.

Unittests currently reside in nltk/test/unit/test_*.py files; pytest is used for test running.

If a test should be written as unittest but also has a documentational value then it should be duplicated as doctest, but with a "# doctest: +SKIP" option.

There are some gotchas with NLTK doctests (and with doctests in general):

• Use print("foo"), not print "foo": NLTK doctests act like from __future__ import print_functions is in use.
• Don't write +ELLIPSIS, +NORMALIZE_WHITESPACE, +IGNORE_EXCEPTION_DETAIL flags (they are already ON by default in NLTK).

• Do not write doctests that have non-ascii output (they are not supported in Python 2.x). Incorrect:

  >>> greeting
  u'Привет'

  The proper way is to rewrite such a doctest as a unittest.

• In order to conditionally skip a doctest in a separate nltk/test/foo.doctest file, create nltk.test/foo_fixt.py file from the following template:

  # <a comment describing why should the test be skipped>
  
  def setup_module(module):
      import pytest
  
      if some_condition:
          pytest.skip("foo.doctest is skipped because <...>")

• In order to conditionally skip all doctests from the module/class/function docstrings, put the following function in a top-level module namespace:

  # <a comment describing why should the tests from this module be skipped>
  
  def setup_module(module):
      import pytest
  
      if some_condition:
          pytest.skip("doctests from nltk.<foo>.<bar> are skipped because <...>")

  A good idea is to define __all__ in such module and omit setup_module from __all__.

  It is not possible to conditionally skip only some doctests from a module.

• Do not expect the exact float output; this may fail on some machines:

  >>> some_float_constant
  0.867

  Use ellipsis in this case to make the test robust (or compare the values):

  >>> some_float_constant
  0.867...
  
  >>> abs(some_float_constant - 0.867) < 1e-6
  True

• Do not rely on dictionary or set item order. Incorrect:

  >>> some_dict
  {"x": 10, "y": 20}

  The proper way is to sort the items and print them:

  >>> for key, value in sorted(some_dict.items()):
  ...     print(key, value)
  x 10
  y 20

If the code requires some external dependencies, then

• tests for this code should be skipped if the dependencies are not available: use setup_module for doctests (as described above) and @pytest.mark.skipif / @pytest.mark.skip decorators or pytest.skip exception for unittests;
• if the dependency is a Python package, it should be added to tox.ini (but not to ..-nodeps environments).