Some Issues and Questions¶
On naming, nosetests, licensing and magic¶
How does pytest relate to nose and unittest?¶
pytest and nose share basic philosophy when it comes
to running and writing Python tests. In fact, you can run many tests
written for nose with
pytest. nose was originally created
as a clone of
pytest was in the
cycle. Note that starting with pytest-2.0 support for running unittest
test suites is majorly improved.
how does pytest relate to twisted’s trial?¶
Since some time
pytest has builtin support for supporting tests
written using trial. It does not itself start a reactor, however,
and does not handle Deferreds returned from a test in pytest style.
If you are using trial’s unittest.TestCase chances are that you can
just run your tests even if you return Deferreds. In addition,
there also is a dedicated pytest-twisted plugin which allows you to
return deferreds from pytest-style tests, allowing the use of
pytest fixtures: explicit, modular, scalable and other features.
how does pytest work with Django?¶
In 2012, some work is going into the pytest-django plugin. It substitutes the usage of Django’s
manage.py test and allows the use of all pytest features most of which
are not available from Django directly.
What’s this “magic” with pytest? (historic notes)¶
Around 2007 (version
0.8) some people thought that
was using too much “magic”. It had been part of the pylib which
contains a lot of unrelated python library code. Around 2010 there
was a major cleanup refactoring, which removed unused or deprecated code
and resulted in the new
pytest PyPI package which strictly contains
only test-related code. This release also brought a complete pluginification
such that the core is around 300 lines of code and everything else is
implemented in plugins. Thus
pytest today is a small, universally runnable
and customizable testing framework for Python. Note, however, that
pytest uses metaprogramming techniques and reading its source is
thus likely not something for Python beginners.
A second “magic” issue was the assert statement debugging feature.
pytest explicitely rewrites assert statements in test modules
in order to provide more useful assert feedback.
This completely avoids previous issues of confusing assertion-reporting.
It also means, that you can use Python’s
-O optimization without losing
assertions in test modules.
pytest contains a second, mostly obsolete, assert debugging technique,
--assert=reinterpret, activated by default on
Python-2.5: When an
assert statement fails,
the expression part to show intermediate values. This technique suffers
from a caveat that the rewriting does not: If your expression has side
effects (better to avoid them anyway!) the intermediate values may not
be the same, confusing the reinterpreter and obfuscating the initial
error (this is also explained at the command line if it happens).
You can also turn off all assertion interaction using the
py.test instead of a
Some of the reasons are historic, others are practical.
used to be part of the
py package which provided several developer
utilities, all starting with
py.<TAB>, thus providing nice
pip install pycmd you get these tools from a separate
package. These days the command line tool could be called
but since many people have gotten used to the old name and there
is another tool named “pytest” we just decided to stick with
py.test for now.
pytest fixtures, parametrized tests¶
Is using pytest fixtures versus xUnit setup a style question?¶
For simple applications and for people experienced with nose or unittest-style test setup using xUnit style setup probably feels natural. For larger test suites, parametrized testing or setup of complex test resources using fixtures may feel more natural. Moreover, fixtures are ideal for writing advanced test support code (like e.g. the monkeypatch, the tmpdir or capture fixtures) because the support code can register setup/teardown functions in a managed class/module/function scope.
Can I yield multiple values from a fixture function function?¶
There are two conceptual reasons why yielding from a factory function is not possible:
- 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.
- 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.
However, with pytest-2.3 you can use the Fixtures as Function arguments decorator
params so that all tests depending on the factory-created
resource will run multiple times with different parameters.
pytest interaction with other packages¶
Issues with pytest, multiprocess and setuptools?¶
On Windows the multiprocess package will instantiate sub processes
by pickling and thus implicitly re-import a lot of local modules.
Unfortunately, setuptools-0.6.11 does not
protect its generated command line script. This leads to infinite
recursion when running a test that instantiates Processes.
As of mid-2013, there shouldn’t be a problem anymore when you use the standard setuptools (note that distribute has been merged back into setuptools which is now shipped directly with virtualenv).