A pytest plugin for easily instantiating reproducible mock resources.
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:
pytest
(hopefully that's appropriate, given the package name)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 == ...
SQLite
from pytest_mock_resources import create_sqlite_fixture
Postgres
from pytest_mock_resources import create_postgres_fixture
Redshift
note Uses postgres under the hood, but the fixture tries to support as much redshift
functionality as possible (including redshift's COPY
/UNLOAD
commands).
from pytest_mock_resources import create_redshift_fixture
Mongo
from pytest_mock_resources import create_mongo_fixture
Redis
from pytest_mock_resources import create_redis_fixture
MySQL
from pytest_mock_resources import create_mysql_fixture
Moto
from pytest_mock_resources import create_moto_fixture
General features include:
# 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]"
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.