.. highlight:: python .. _`goodpractices`: Good Integration Practices ================================================= Install package with pip ------------------------------------------------- For development, we recommend you use venv_ for virtual environments and pip_ for installing your application and any dependencies, as well as the ``pytest`` package itself. This ensures your code and dependencies are isolated from your system Python installation. Next, place a ``setup.py`` file in the root of your package with the following minimum content: .. code-block:: python from setuptools import setup, find_packages setup(name="PACKAGENAME", packages=find_packages()) Where ``PACKAGENAME`` is the name of your package. You can then install your package in "editable" mode by running from the same directory: .. code-block:: bash pip install -e . which lets you change your source code (both tests and application) and rerun tests at will. This is similar to running ``python setup.py develop`` or ``conda develop`` in that it installs your package using a symlink to your development code. .. _`test discovery`: .. _`Python test discovery`: Conventions for Python test discovery ------------------------------------------------- ``pytest`` implements the following standard test discovery: * If no arguments are specified then collection starts from :confval:`testpaths` (if configured) or the current directory. Alternatively, command line arguments can be used in any combination of directories, file names or node ids. * Recurse into directories, unless they match :confval:`norecursedirs`. * In those directories, search for ``test_*.py`` or ``*_test.py`` files, imported by their `test package name`_. * From those files, collect test items: * ``test`` prefixed test functions or methods outside of class * ``test`` prefixed test functions or methods inside ``Test`` prefixed test classes (without an ``__init__`` method) For examples of how to customize your test discovery :doc:`example/pythoncollection`. Within Python modules, ``pytest`` also discovers tests using the standard :ref:`unittest.TestCase ` subclassing technique. Choosing a test layout / import rules ------------------------------------- ``pytest`` supports two common test layouts: Tests outside application code ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Putting tests into an extra directory outside your actual application code might be useful if you have many functional tests or for other reasons want to keep tests separate from actual application code (often a good idea): .. code-block:: text setup.py mypkg/ __init__.py app.py view.py tests/ test_app.py test_view.py ... This has the following benefits: * Your tests can run against an installed version after executing ``pip install .``. * Your tests can run against the local copy with an editable install after executing ``pip install --editable .``. * If you don't have a ``setup.py`` file and are relying on the fact that Python by default puts the current directory in ``sys.path`` to import your package, you can execute ``python -m pytest`` to execute the tests against the local copy directly, without using ``pip``. .. note:: See :ref:`pytest vs python -m pytest` for more information about the difference between calling ``pytest`` and ``python -m pytest``. Note that this scheme has a drawback if you are using ``prepend`` :ref:`import mode ` (which is the default): your test files must have **unique names**, because ``pytest`` will import them as *top-level* modules since there are no packages to derive a full package name from. In other words, the test files in the example above will be imported as ``test_app`` and ``test_view`` top-level modules by adding ``tests/`` to ``sys.path``. If you need to have test modules with the same name, you might add ``__init__.py`` files to your ``tests`` folder and subfolders, changing them to packages: .. code-block:: text setup.py mypkg/ ... tests/ __init__.py foo/ __init__.py test_view.py bar/ __init__.py test_view.py Now pytest will load the modules as ``tests.foo.test_view`` and ``tests.bar.test_view``, allowing you to have modules with the same name. But now this introduces a subtle problem: in order to load the test modules from the ``tests`` directory, pytest prepends the root of the repository to ``sys.path``, which adds the side-effect that now ``mypkg`` is also importable. This is problematic if you are using a tool like `tox`_ to test your package in a virtual environment, because you want to test the *installed* version of your package, not the local code from the repository. .. _`src-layout`: In this situation, it is **strongly** suggested to use a ``src`` layout where application root package resides in a sub-directory of your root: .. code-block:: text setup.py src/ mypkg/ __init__.py app.py view.py tests/ __init__.py foo/ __init__.py test_view.py bar/ __init__.py test_view.py This layout prevents a lot of common pitfalls and has many benefits, which are better explained in this excellent `blog post by Ionel Cristian Mărieș `_. .. note:: The new ``--import-mode=importlib`` (see :ref:`import-modes`) doesn't have any of the drawbacks above because ``sys.path`` and ``sys.modules`` are not changed when importing test modules, so users that run into this issue are strongly encouraged to try it and report if the new option works well for them. The ``src`` directory layout is still strongly recommended however. Tests as part of application code ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Inlining test directories into your application package is useful if you have direct relation between tests and application modules and want to distribute them along with your application: .. code-block:: text setup.py mypkg/ __init__.py app.py view.py test/ __init__.py test_app.py test_view.py ... In this scheme, it is easy to run your tests using the ``--pyargs`` option: .. code-block:: bash pytest --pyargs mypkg ``pytest`` will discover where ``mypkg`` is installed and collect tests from there. Note that this layout also works in conjunction with the ``src`` layout mentioned in the previous section. .. note:: You can use Python3 namespace packages (PEP420) for your application but pytest will still perform `test package name`_ discovery based on the presence of ``__init__.py`` files. If you use one of the two recommended file system layouts above but leave away the ``__init__.py`` files from your directories it should just work on Python3.3 and above. From "inlined tests", however, you will need to use absolute imports for getting at your application code. .. _`test package name`: .. note:: In ``prepend`` and ``append`` import-modes, if pytest finds a ``"a/b/test_module.py"`` test file while recursing into the filesystem it determines the import name as follows: * determine ``basedir``: this is the first "upward" (towards the root) directory not containing an ``__init__.py``. If e.g. both ``a`` and ``b`` contain an ``__init__.py`` file then the parent directory of ``a`` will become the ``basedir``. * perform ``sys.path.insert(0, basedir)`` to make the test module importable under the fully qualified import name. * ``import a.b.test_module`` where the path is determined by converting path separators ``/`` into "." characters. This means you must follow the convention of having directory and file names map directly to the import names. The reason for this somewhat evolved importing technique is that in larger projects multiple test modules might import from each other and thus deriving a canonical import name helps to avoid surprises such as a test module getting imported twice. With ``--import-mode=importlib`` things are less convoluted because pytest doesn't need to change ``sys.path`` or ``sys.modules``, making things much less surprising. .. _`virtualenv`: https://pypi.org/project/virtualenv/ .. _`buildout`: http://www.buildout.org/ .. _pip: https://pypi.org/project/pip/ .. _`use tox`: tox ------ Once you are done with your work and want to make sure that your actual package passes all tests you may want to look into `tox`_, the virtualenv test automation tool and its `pytest support `_. tox helps you to setup virtualenv environments with pre-defined dependencies and then executing a pre-configured test command with options. It will run tests against the installed package and not against your source code checkout, helping to detect packaging glitches. .. _`venv`: https://docs.python.org/3/library/venv.html