test_ok1/doc/faq.txt

146 lines
6.0 KiB
Plaintext

Some Issues and Questions
==================================
.. note::
If you don't find an answer here, checkout the :ref:`contact channels`
to get help.
On naming, nosetests, licensing and magic
------------------------------------------------
Why a ``py.test`` instead of a ``pytest`` command?
++++++++++++++++++++++++++++++++++++++++++++++++++
Some historic, some practical reasons: ``py.test`` used to be part of
the ``py`` package which provided several developer utitilities,
all starting with ``py.<TAB>``, providing nice TAB-completion. If
you install ``pip install pycmd`` you get these tools from a separate
package. These days the command line tool could be called ``pytest``
but then again many people have gotten used to the old name and there
is another tool named "pytest" so we just decided to stick with
``py.test``.
What's the relation to nose and unittest?
+++++++++++++++++++++++++++++++++++++++++++++++++
py.test and nose_ share basic philosophy when it comes
to running Python tests. In fact, you can run many tests
written nose with py.test. nose_ was originally created
as a clone of ``py.test`` when py.test was in the ``0.8`` release
cycle. As of version 2.0 support for running unittest test
suites is majorly improved and you should be able to run
many Django and Twisted test suites.
.. _features: test/features.html
What's this "magic" with py.test?
++++++++++++++++++++++++++++++++++++++++++
Around 2007 (version ``0.8``) some people claimed that py.test
was using too much "magic". It has been refactored a lot. Thrown
out old code. Deprecated unused approaches and code. And it is today
probably one of the smallest, most universally runnable and most
customizable testing frameworks for Python. It's true that
``py.test`` uses metaprogramming techniques, i.e. it views
test code similar to how compilers view programs, using a
somewhat abstract internal model.
It's also true that the no-boilerplate testing is implemented by making
use of the Python assert statement through "re-interpretation":
When an ``assert`` statement fails, py.test re-interprets the expression
to show intermediate values if a test fails. If your expression
has side effects the intermediate values may not be the same, obfuscating
the initial error (this is also explained at the command line if it happens).
``py.test --no-assert`` turns off assert re-intepretation.
Sidenote: it is good practise to avoid asserts with side effects.
.. _`py namespaces`: index.html
.. _`py/__init__.py`: http://bitbucket.org/hpk42/py-trunk/src/trunk/py/__init__.py
function arguments, parametrized tests and setup
-------------------------------------------------------
.. _funcargs: test/funcargs.html
Is using funcarg- versus xUnit setup a style question?
+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
For simple applications and for people experienced with nose_ or
unittest-style test setup using `xUnit style setup`_ often
feels natural. For larger test suites, parametrized testing
or setup of complex test resources using funcargs_ may feel more natural.
Moreover, funcargs are ideal for writing advanced test support
code (like e.g. the monkeypatch_, the tmpdir_ or capture_ funcargs)
because the support code can register setup/teardown functions
in a managed class/module/function scope.
.. _monkeypatch: test/plugin/monkeypatch.html
.. _tmpdir: test/plugin/tmpdir.html
.. _capture: test/plugin/capture.html
.. _`why pytest_pyfuncarg__ methods?`:
Why the ``pytest_funcarg__*`` name for funcarg factories?
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
We alternatively implemented an explicit registration mechanism for
function argument factories. But lacking a good use case for this
indirection and flexibility we decided to go for `Convention over
Configuration`_ and rather have factories specified by convention.
Besides removing the need for an registration indirection it allows to
"grep" for ``pytest_funcarg__MYARG`` and will safely find all factory
functions for the ``MYARG`` function argument.
.. _`Convention over Configuration`: http://en.wikipedia.org/wiki/Convention_over_Configuration
Can I yield multiple values from a funcarg factory function?
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
There are two conceptual reasons why yielding from a factory function
is not possible:
* Calling factories for obtaining test function arguments
is part of setting up and running a test. At that
point it is not possible to add new test calls to
the test collection anymore.
* If multiple factories yielded values there would
be no natural place to determine the combination
policy - in real-world examples some combinations
often should not run.
Use the `pytest_generate_tests`_ hook to solve both issues
and implement the `parametrization scheme of your choice`_.
.. _`pytest_generate_tests`: test/funcargs.html#parametrizing-tests
.. _`parametrization scheme of your choice`: http://tetamap.wordpress.com/2009/05/13/parametrizing-python-tests-generalized/
py.test interaction with other packages
---------------------------------------------------
Issues with py.test, multiprocess and setuptools?
+++++++++++++++++++++++++++++++++++++++++++++++++++++++++
On windows the multiprocess package will instantiate sub processes
by pickling and thus implicitely re-import a lot of local modules.
Unfortuantely, setuptools-0.6.11 does not ``if __name__=='__main__'``
protect its generated command line script. This leads to infinite
recursion when running a test that instantiates Processes.
A good solution is to `install Distribute`_ as a drop-in replacement
for setuptools and then re-install ``pytest``. Otherwise you could
fix the script that is created by setuptools by inserting an
``if __name__ == '__main__'``. Or you can create a "pytest.py"
script with this content and invoke that with the python version::
import pytest
if __name__ == '__main__':
pytest.main()
.. _`install distribute`: http://pypi.python.org/pypi/distribute#installation-instructions
.. include:: links.inc