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pytest-sqlalchemy-mock

PyPI version codecov CI Supported Python Version Code style: black

This plugin provides pytest fixtures to create an in-memory DB instance on tests and dump your raw test data.

Supported Python versions

Python 3.12 or later highly recommended but also might work on Python 3.11.

Installation

Download from PyPI

pip install pytest-sqlalchemy-mock

Building from source

At the top direcotry,

python3 -m build
python3 -m pip install dist/pytest_sqlalchemy_mock-*.whl

or

python3 -m pip install .

Uninstall

python3 -m pip uninstall pytest_sqlalchemy_mock

Usage

Let's assume you have a SQLAlchemy declarative base and some models with it.

models.py

from sqlalchemy import Column, Integer, String
from sqlalchemy.orm import declarative_base

Base = declarative_base()


class User(Base):
    __tablename__ = "user"

    id = Column(Integer, primary_key=True)
    name = Column(String)

Firstly SQLAlchemy base class which is used for declare models should be passed with sqlalchemy_declarative_base fixture in conftest.py

conftest.py

@pytest.fixture(scope="function")
def sqlalchemy_declarative_base():
    return Base

Then in test functions you can use mocked_session fixture to make query in mocked DB.

test_user_table.py

def test_mocked_session_user_table(mocked_session):
    user_data = mocked_session.execute("SELECT * from user;").all()
    assert user_data == []

Also, you can dump your mock data to DB before start testing via sqlalchemy_mock_config fixture like following.

conftest.py

@pytest.fixture(scope="function")
def sqlalchemy_mock_config():
    return [("user", [
        {
            "id": 1,
            "name": "Kevin"
        },
        {
            "id": 2,
            "name": "Dwight"
        }
    ])]

test_user_table.py

def test_mocked_session_user_class(mocked_session):
    user = mocked_session.query(User).filter_by(id=2).first()
    assert user.name == "Dwight"

Upcoming Features

  • Mock with decorator for specific DB states for specific cases.
  • Support to load data from .json and .csv
  • Async SQLAlchemy support