Testing infrastructure

Tests are run with pytest.

Pytest plugins

Pytest plugins are used for various purposes, some of which are optional and can be enabled with command line parameters or environment variables. Others are required by the test environment and are always enabled.

One very important always-enabled plugin applies patches before tests are run. The patches remain in effect for the duration of the test run unless utilities are provided to temporarily disable them. For example, sync_users_to_es is a decorator/context manager that enables syncing of users to ElasticSearch when a user is saved. Since this syncing involves custom test setup not done by most tests it is disabled by default, but it can be temporarily enabled using sync_users_to_es in tests that need it.

Testing best practices

Class-based vs function-based tests

Both styles are fine — pick whichever is more readable and maintainable for the situation. There is no project-wide preference. Class-based tests (TestCase, SimpleTestCase) work well when several tests share expensive setup or naturally group together. Function-based tests work well for standalone cases and pair nicely with pytest.mark.parametrize and explicit pytest-unmagic fixtures.

Test set up

The setUp method is run before each test, so doing a lot of work there can add a lot of run time to the tests. If possible, consider moving common setup of things that are not mutated by tests into setUpClass. Some things that can be easily moved to setUpClass are domain creation, user creation, or any other static models needed for the test.

Sometimes classes share the same base class and inherit the setUpClass function. Below is an example:

# BAD EXAMPLE

class MyBaseTestClass(TestCase):

    @classmethod
    def setUpClass(cls):
        ...


class MyTestClass(MyBaseTestClass):

    def test1(self):
        ...

class MyTestClassTwo(MyBaseTestClass):

    def test2(self):
        ...

In the above example the setUpClass is run twice, once for MyTestClass and once for MyTestClassTwo. If setUpClass has expensive operations, then it’s best for all the tests to be combined under one test class.

# GOOD EXAMPLE

class MyBigTestClass(TestCase):

    @classmethod
    def setUpClass(cls):
        ...

    def test1(self):
        ...

    def test2(self):
        ...

However this can lead to giant Test classes. If you find that all the tests in a package or module are sharing the same set up, you can use a ‘module’ or ‘package’ scoped fixture.

Test tear down

It is important to ensure that all objects you have created in databases are deleted when the test class finishes running. The best practice is to use pytest fixtures or addCleanup or addClassCleanup to call cleanup routines. Cleanup can also be done in the tearDown method or the tearDownClass method, although pytest fixtures and add[Class]Cleanup are preferred because, unlike tearDown[Class], they get run if setUp[Class] raises an exception.

SQL data in non-shard databases is automatically cleaned up on transaction rollback by test classes that override django.test.TestCase or function tests that use pytest-django’s db fixture, so it is not necessary to delete SQL data in most cases. One exception to this is the shard dbs, since most usages of shard databases do not support transactions.

Also beware that unneccessary cleanup “just to be safe” can add a large amount of time onto your tests and should be avoided.

Functional database tests

Function tests may access databases by using pytest-django’s db or transactional_db fixture. This is similar to extending django.test.TestCase or django.test.TransactionTestCase respectively.

from unmagic import use

@use("db")
def test_database():
    ...

Using `SimpleTestCase` and function tests

SimpleTestCase and function tests that do not use the db or transactional_db fixture run tests without a database and are often MUCH faster than database tests. Many times this can be achieved through the use of the mock library. A good rule of thumb is to have 80% of your tests be unit tests that do not touch the database, and 20% of your tests be integration tests that use the database.

CommCare HQ also has some custom in mocking tools.

Fake Couch - Fake implementation of CouchDBKit api for testing purposes.
ESQueryFake - For faking ES queries.

Squashing Migrations

There is overhead to running many migrations at once. Django allows you to squash migrations which will help speed up the migrations when running tests.