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https://github.com/pytest-dev/pytest-randomly

:game_die: Pytest plugin to randomly order tests and control random.seed
https://github.com/pytest-dev/pytest-randomly

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:game_die: Pytest plugin to randomly order tests and control random.seed

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README 

        
===============

pytest-randomly

===============



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.. figure:: https://raw.githubusercontent.com/pytest-dev/pytest-randomly/main/logo.png

   :scale: 50%

   :alt: Randomness power.



Pytest plugin to randomly order tests and control ``random.seed``.



----



**Testing a Django project?**

Check out my book `Speed Up Your Django Tests `__ which covers loads of ways to write faster, more accurate tests.



----



Features

========



All of these features are on by default but can be disabled with flags.



* Randomly shuffles the order of test items. This is done first at the level of

  modules, then at the level of test classes (if you have them), then at the

  order of functions. This also works with things like doctests.



* Resets the global ``random.seed()`` at the start of every test case and test

  to a fixed number - this defaults to ``time.time()`` from the start of your

  test run, but you can pass in ``--randomly-seed`` to repeat a

  randomness-induced failure.



* If

  `factory boy `_

  is installed, its random state is reset at the start of every test. This

  allows for repeatable use of its random 'fuzzy' features.



* If `faker `_ is installed, its random

  state is reset at the start of every test. This is also for repeatable fuzzy

  data in tests - factory boy uses faker for lots of data. This is also done

  if you're using the ``faker`` pytest fixture, by defining the ``faker_seed``

  fixture

  (`docs `__).



* If

  `Model Bakery `_

  is installed, its random state is reset at the start of every test. This

  allows for repeatable use of its random fixture field values.



* If `numpy `_ is installed, its legacy global random state in |numpy.random|__ is reset at the start of every test.



  .. |numpy.random| replace:: ``numpy.random``

  __ https://numpy.org/doc/stable/reference/random/index.html



* If additional random generators are used, they can be registered under the

  ``pytest_randomly.random_seeder``

  `entry point `_ and

  will have their seed reset at the start of every test. Register a function

  that takes the current seed value.



* Works with `pytest-xdist `__.



About

=====



Randomness in testing can be quite powerful to discover hidden flaws in the

tests themselves, as well as giving a little more coverage to your system.



By randomly ordering the tests, the risk of surprising inter-test dependencies

is reduced - a technique used in many places, for example Google's C++ test

runner `googletest

`_.

Research suggests that "dependent tests do exist in practice" and a random

order of test executions can effectively detect such dependencies [1]_.

Alternatively, a reverse order of test executions, as provided by `pytest-reverse

`__, may find less dependent

tests but can achieve a better benefit/cost ratio.



By resetting the random seed to a repeatable number for each test, tests can

create data based on random numbers and yet remain repeatable, for example

factory boy's fuzzy values. This is good for ensuring that tests specify the

data they need and that the tested system is not affected by any data that is

filled in randomly due to not being specified.



I have written a `blog post covering the history of

pytest-randomly `__,

including how it started life as the nose plugin

`nose-randomly `__.



Additionally, I appeared on the Test and Code podcast to `talk about

pytest-randomly `__.



Installation

============



Install with:



.. code-block:: bash



    python -m pip install pytest-randomly



Python 3.8 to 3.12 supported.



Usage

=====



Pytest will automatically find the plugin and use it when you run ``pytest``.

The output will start with an extra line that tells you the random seed that is

being used:



.. code-block:: bash



    $ pytest

    ...

    platform darwin -- Python ...

    Using --randomly-seed=1553614239

    ...



If the tests fail due to ordering or randomly created data, you can restart

them with that seed using the flag as suggested:



.. code-block:: bash



    pytest --randomly-seed=1234



Or more conveniently, use the special value ``last``:



.. code-block:: bash



    pytest --randomly-seed=last



(This only works if pytest’s cacheprovider plugin has not been disabled.)



Since the ordering is by module, then by class, you can debug inter-test

pollution failures by narrowing down which tests are being run to find the bad

interaction by rerunning just the module/class:



.. code-block:: bash



    pytest --randomly-seed=1234 tests/module_that_failed/



You can disable behaviours you don't like with the following flags:



* ``--randomly-dont-reset-seed`` - turn off the reset of ``random.seed()`` at

  the start of every test

* ``--randomly-dont-reorganize`` - turn off the shuffling of the order of tests



The plugin appears to Pytest with the name 'randomly'. To disable it

altogether, you can use the ``-p`` argument, for example:



.. code-block:: sh



    pytest -p no:randomly



Avoid reordering some tests

---------------------------



To fix the order of some tests, use the ``pytest-order`` plugin.

See its `documentation section `__ on usage with pytest-randomly.



Entry Point

===========



If you're using a different randomness generator in your third party package,

you can register an entrypoint to be called every time ``pytest-randomly``

reseeds. Implement the entrypoint ``pytest_randomly.random_seeder``, referring

to a function/callable that takes one argument, the new seed (int).



For example in your ``setup.cfg``:



.. code-block:: ini



    [options.entry_points]

    pytest_randomly.random_seeder =

        mypackage = mypackage.reseed



Then implement ``reseed(new_seed)``.



References

==========



.. [1] Sai Zhang, Darioush Jalali, Jochen Wuttke, Kıvanç Muşlu, Wing Lam, Michael D. Ernst, and David Notkin. 2014. Empirically revisiting the test independence assumption. In Proceedings of the 2014 International Symposium on Software Testing and Analysis (ISSTA 2014). Association for Computing Machinery, New York, NY, USA, 385–396. doi:https://doi.org/10.1145/2610384.2610404