
Code which depends on external resources such a databases (postgres, redshift, etc) can be difficult
to write automated tests for. Conventional wisdom might be to mock or stub out the actual database
calls and assert that the code works correctly before/after the calls.
However take the following, simple example:
def serialize(users):
return [
{
'user': user.serialize(),
'address': user.address.serialize(),
'purchases': [p.serialize() for p in user.purchases],
}
for user in users
]
def view_function(session):
users = session.query(User).join(Address).options(selectinload(User.purchases)).all()
return serialize(users)
Sure, you can test serialize, but whether the actual query did the correct thing truly
requires that you execute the query.
Having tests depend upon a real postgres instance running somewhere is a pain, very fragile, and
prone to issues across machines and test failures.
Therefore pytest-mock-resources (primarily) works by managing the lifecycle of docker containers
and providing access to them inside your tests.
As such, this package makes 2 primary assumptions:
- You're using
pytest (hopefully that's appropriate, given the package name)
- For many resources,
docker is required to be available and running (or accessible through remote
docker).
If you aren't familiar with Pytest Fixtures, you can read up on them in the Pytest
documentation.
In the above example, your test file could look something like
from pytest_mock_resources import create_postgres_fixture
from models import ModelBase
pg = create_postgres_fixture(ModelBase, session=True)
def test_view_function_empty_db(pg):
response = view_function(pg)
assert response == ...
def test_view_function_user_without_purchases(pg):
pg.add(User(...))
pg.flush()
response = view_function(pg)
assert response == ...
def test_view_function_user_with_purchases(pg):
pg.add(User(..., purchases=[Purchase(...)]))
pg.flush()
response = view_function(pg)
assert response == ...
Existing Resources (many more possible)
General features include:
- Support for "actions" which pre-populate the resource you're mocking before the test
- Async fixtures
- Custom configuration for container/resource startup
# Basic fixture support i.e. SQLite
pip install "pytest-mock-resources"
# General, docker-based fixture support
pip install "pytest-mock-resources[docker]"
# Mongo fixture support, installs `pymongo`
pip install "pytest-mock-resources[mongo]"
# Moto fixture support, installs non-driver extras specific to moto support
pip install "pytest-mock-resources[moto]"
# Redis fixture support, Installs `redis` client
pip install "pytest-mock-resources[redis]"
# Redshift fixture support, installs non-driver extras specific to redshift support
pip install "pytest-mock-resources[redshift]"
Additionally there are number of convenience extras currently provided
for installing drivers/clients of specific features. However in most cases,
you should already be installing the driver/client used for that fixture
as as first-party dependency of your project.
As such, we recommend against using these extras, and instead explcitly depending
on the package in question in your own project's 1st party dependencies.
# Installs psycopg2/psycopg2-binary driver
pip install "pytest-mock-resources[postgres-binary]"
pip install "pytest-mock-resources[postgres]"
# Installs asyncpg driver
pip install "pytest-mock-resources[postgres-async]"
# Installs pymysql driver
pip install "pytest-mock-resources[mysql]"
Possible Future Resources
Feel free to file an issue if you find
any bugs or want to start a conversation around a mock resource you want implemented!
Releases in the 1.x series were supportive of python 2. However starting from 2.0.0, support for
python 2 was dropped. We may accept bugfix PRs for the 1.x series, however new development and
features will not be backported.