===============
pytest-randomly
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Pytest plugin to randomly order tests and control random.seed
.
Testing a Django project?
Check out my book Speed Up Your Django Tests <https://adamchainz.gumroad.com/l/suydt>
__ 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 <https://factoryboy.readthedocs.io/en/latest/reference.html>
_
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 <https://pypi.org/project/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 <https://faker.readthedocs.io/en/master/pytest-fixtures.html#seeding-configuration>
__).
-
If
Model Bakery <https://model-bakery.readthedocs.io/en/latest/>
_
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 <http://www.numpy.org/>
_ 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 <https://packaging.python.org/specifications/entry-points/>
_ 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 <https://pypi.org/project/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 <https://code.google.com/p/googletest/wiki/V1_5_AdvancedGuide#Shuffling_the_Tests>
.
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 <https://github.com/adamchainz/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 <https://adamj.eu/tech/2018/01/08/pytest-randomly-history/>
,
including how it started life as the nose plugin
nose-randomly <https://github.com/adamchainz/nose-randomly>
.
Additionally, I appeared on the Test and Code podcast to talk about pytest-randomly <https://testandcode.com/128>
__.
Installation
Install with:
.. code-block:: bash
python -m pip install pytest-randomly
Python 3.9 to 3.13 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 <https://pytest-order.readthedocs.io/en/latest/other_plugins.html#pytest-randomly>
__ 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