/pytest-mock-resources

Pytest Fixtures that let you actually test against external resource (Postgres, Mongo, Redshift...) dependent code.

Primary LanguagePythonMIT LicenseMIT

CircleCI codecov Documentation Status

Introduction

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.

The Pitch

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)

  • 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

Features

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

Installing

# Basic fixture support
pip install "pytest-mock-resources"

# For postgres install EITHER of the following:
pip install "pytest-mock-resources[postgres-binary]"
pip install "pytest-mock-resources[postgres]"

# For postgres async
pip install "pytest-mock-resources[postgres-async]"

# For redshift install EITHER of the following:
# (redshift fixtures require postgres dependencies...)
pip install "pytest-mock-resources[postgres, redshift]"
pip install "pytest-mock-resources[postgres-binary, redshift]"

# For mongo install the following:
pip install "pytest-mock-resources[mongo]"

# For redis
pip install "pytest-mock-resources[redis]"

# For mysql
pip install "pytest-mock-resources[mysql]"

Possible Future Resources

  • Rabbit Broker
  • AWS Presto

Feel free to file an issue if you find any bugs or want to start a conversation around a mock resource you want implemented!

Python 2

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.