Table Of Contents

Previous topic

Good Integration Practises

Next topic

py.test reference documentation

This Page

Some Issues and Questions

Note

If you don’t find an answer here, checkout the Contact channels to get help.

On naming, nosetests, licensing and magic XXX

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 pytest but then many people have gotten used to the old name and there also is another tool with this same which would lead to some clashes.

What’s py.test’s relation to nosetests?

py.test and nose share basic philosophy when it comes to running Python tests. In fact, you can run many tests written for unittest or nose with py.test. nose was originally created as a clone of py.test when py.test was in the 0.8 release cycle.

What’s this “magic” with py.test?

Around 2007 (version 0.8) some several people claimed that py.test was using too much “magic”. It has been refactored a lot. It is today probably one of the smallest, most universally runnable and most customizable testing frameworks for Python. It remains 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.

function arguments, parametrized tests and setup

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.

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.

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.

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()