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Postgresql fixtures and fixture factories for Pytest.

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pytest-postgresql

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What is this?

This is a pytest plugin, that enables you to test your code that relies on a running PostgreSQL Database. It allows you to specify fixtures for PostgreSQL process and client.

How to use

Install with:

pip install pytest-postgresql

You will also need to install psycopg. See its installation instructions. Note that this plugin requires psycopg version 3. It is possible to simultaneously install version 3 and version 2 for libraries that require the latter (see those instructions).

Plugin contains three fixtures:

  • postgresql - it’s a client fixture that has functional scope. After each test it ends all leftover connections, and drops test database from PostgreSQL ensuring repeatability. This fixture returns already connected psycopg connection.

  • postgresql_proc - session scoped fixture, that starts PostgreSQL instance at it’s first use and stops at the end of the tests.

  • postgresql_noproc - a noprocess fixture, that’s connecting to already running postgresql instance. For example on dockerized test environments, or CI providing postgresql services

Simply include one of these fixtures into your tests fixture list.

You can also create additional postgresql client and process fixtures if you’d need to:

from pytest_postgresql import factories

postgresql_my_proc = factories.postgresql_proc(
    port=None, unixsocketdir='/var/run')
postgresql_my = factories.postgresql('postgresql_my_proc')

Sample test

def test_example_postgres(postgresql):
    """Check main postgresql fixture."""
    cur = postgresql.cursor()
    cur.execute("CREATE TABLE test (id serial PRIMARY KEY, num integer, data varchar);")
    postgresql.commit()
    cur.close()

If you want the database fixture to be automatically populated with your schema there are two ways:

  1. client fixture specific

  2. process fixture specific

Both are accepting same set of possible loaders:

  • sql file path

  • loading function import path (string)

  • actual loading function

That function will receive host, port, user, dbname and password kwargs and will have to perform connection to the database inside. However, you’ll be able to run SQL files or even trigger programmatically database migrations you have.

Client specific loads the database each test

postgresql_my_with_schema = factories.postgresql(
    'postgresql_my_proc',
    load=["schemafile.sql", "otherschema.sql", "import.path.to.function", "import.path.to:otherfunction", load_this]
)

The process fixture performs the load once per test session, and loads the data into the template database. Client fixture then creates test database out of the template database each test, which significantly speeds up the tests.

postgresql_my_proc = factories.postgresql_proc(
    load=["schemafile.sql", "otherschema.sql", "import.path.to.function", "import.path.to:otherfunction", load_this]
)
pytest --postgresql-populate-template=path.to.loading_function --postgresql-populate-template=path.to.other:loading_function --postgresql-populate-template=path/to/file.sql

The loading_function from example will receive , and have to commit that.

Connecting to already existing postgresql database

Some projects are using already running postgresql servers (ie on docker instances). In order to connect to them, one would be using the postgresql_noproc fixture.

postgresql_external = factories.postgresql('postgresql_noproc')

By default the postgresql_noproc fixture would connect to postgresql instance using 5432 port. Standard configuration options apply to it.

These are the configuration options that are working on all levels with the postgresql_noproc fixture:

Configuration

You can define your settings in three ways, it’s fixture factory argument, command line option and pytest.ini configuration option. You can pick which you prefer, but remember that these settings are handled in the following order:

  • Fixture factory argument

  • Command line option

  • Configuration option in your pytest.ini file

Configuration options

PostgreSQL option

Fixture factory argument

Command line option

pytest.ini option

Noop process fixture

Default

Path to executable

executable

–postgresql-exec

postgresql_exec

/usr/lib/postgresql/13/bin/pg_ctl

host

host

–postgresql-host

postgresql_host

yes

127.0.0.1

port

port

–postgresql-port

postgresql_port

yes (5432)

random

postgresql user

user

–postgresql-user

postgresql_user

yes

postgres

password

password

–postgresql-password

postgresql_password

yes

Starting parameters (extra pg_ctl arguments)

startparams

–postgresql-startparams

postgresql_startparams

-w

Postgres exe extra arguments (passed via pg_ctl’s -o argument)

postgres_options

–postgresql-postgres-options

postgresql_postgres_options

Location for unixsockets

unixsocket

–postgresql-unixsocketdir

postgresql_unixsocketdir

$TMPDIR

Database name which will be created by the fixtures

dbname

–postgresql-dbname

postgresql_dbname

yes, however with xdist an index is being added to name, resulting in test0, test1 for each worker.

test

Default Schema either in sql files or import path to function that will load it (list of values for each)

load

–postgresql-load

postgresql_load

yes

PostgreSQL connection options

options

–postgresql-options

postgresql_options

yes

Example usage:

  • pass it as an argument in your own fixture

    postgresql_proc = factories.postgresql_proc(
        port=8888)
  • use --postgresql-port command line option when you run your tests

    py.test tests --postgresql-port=8888
  • specify your port as postgresql_port in your pytest.ini file.

    To do so, put a line like the following under the [pytest] section of your pytest.ini:

    [pytest]
    postgresql_port = 8888

Examples

Populating database for tests

With SQLAlchemy

This example shows how to populate database and create an SQLAlchemy’s ORM connection:

Sample below is simplified session fixture from pyramid_fullauth tests:

from sqlalchemy import create_engine
from sqlalchemy.orm import scoped_session, sessionmaker
from sqlalchemy.pool import NullPool
from zope.sqlalchemy import register


@pytest.fixture
def db_session(postgresql):
    """Session for SQLAlchemy."""
    from pyramid_fullauth.models import Base

    connection = f'postgresql+psycopg2://{postgresql.info.user}:@{postgresql.info.host}:{postgresql.info.port}/{postgresql.info.dbname}'

    engine = create_engine(connection, echo=False, poolclass=NullPool)
    pyramid_basemodel.Session = scoped_session(sessionmaker(extension=ZopeTransactionExtension()))
    pyramid_basemodel.bind_engine(
        engine, pyramid_basemodel.Session, should_create=True, should_drop=True)

    yield pyramid_basemodel.Session

    transaction.commit()
    Base.metadata.drop_all(engine)


@pytest.fixture
def user(db_session):
    """Test user fixture."""
    from pyramid_fullauth.models import User
    from tests.tools import DEFAULT_USER

    new_user = User(**DEFAULT_USER)
    db_session.add(new_user)
    transaction.commit()
    return new_user


def test_remove_last_admin(db_session, user):
    """
    Sample test checks internal login, but shows usage in tests with SQLAlchemy
    """
    user = db_session.merge(user)
    user.is_admin = True
    transaction.commit()
    user = db_session.merge(user)

    with pytest.raises(AttributeError):
        user.is_admin = False

Maintaining database state outside of the fixtures

It is possible and appears it’s used in other libraries for tests, to maintain database state with the use of the pytest-postgresql database managing functionality:

For this import DatabaseJanitor and use its init and drop methods:

import pytest
from pytest_postgresql.janitor import DatabaseJanitor

@pytest.fixture
def database(postgresql_proc):
    # variable definition

    janitor = DatabaseJanitor(
        postgresql_proc.user,
        postgresql_proc.host,
        postgresql_proc.port,
        "my_test_database",
        postgresql_proc.version,
        password="secret_password",
    )
    janitor.init()
    yield psycopg2.connect(
        dbname="my_test_database",
        user=postgresql_proc.user,
        password="secret_password",
        host=postgresql_proc.host,
        port=postgresql_proc.port,
    )
    janitor.drop()

or use it as a context manager:

import pytest
from pytest_postgresql.janitor import DatabaseJanitor

@pytest.fixture
def database(postgresql_proc):
    # variable definition

    with DatabaseJanitor(
        postgresql_proc.user,
        postgresql_proc.host,
        postgresql_proc.port,
        "my_test_database",
        postgresql_proc.version,
        password="secret_password",
    ):
        yield psycopg2.connect(
            dbname="my_test_database",
            user=postgresql_proc.user,
            password="secret_password",
            host=postgresql_proc.host,
            port=postgresql_proc.port,
        )

Connecting to Postgresql (in a docker)

To connect to a docker run postgresql and run test on it, use noproc fixtures.

docker run --name some-postgres -e POSTGRES_PASSWORD=mysecretpassword -d postgres

This will start postgresql in a docker container, however using a postgresql installed locally is not much different.

In tests, make sure that all your tests are using postgresql_noproc fixture like that:

from pytest_postgresql import factories


postgresql_in_docker = factories.postgresql_noproc()
postgresql = factories.postgresql("postgresql_in_docker", dbname="test")


def test_postgres_docker(postgresql):
    """Run test."""
    cur = postgresql.cursor()
    cur.execute("CREATE TABLE test (id serial PRIMARY KEY, num integer, data varchar);")
    postgresql.commit()
    cur.close()

And run tests:

pytest --postgresql-host=172.17.0.2 --postgresql-password=mysecretpassword

Basic database state for all tests

If you’ve got several tests that require common initialisation, you can to define a load and pass it to your custom postgresql process fixture:

import pytest_postgresql.factories
def load_database(**kwargs):
    db_connection: connection = psycopg2.connect(**kwargs)
    with db_connection.cursor() as cur:
        cur.execute("CREATE TABLE stories (id serial PRIMARY KEY, name varchar);")
        cur.execute(
            "INSERT INTO stories (name) VALUES"
            "('Silmarillion'), ('Star Wars'), ('The Expanse'), ('Battlestar Galactica')"
        )
        db_connection.commit()

postgresql_proc = factories.postgresql_proc(
    load=[load_database],
)

postgresql = factories.postgresql(
    "postgresql_proc",
)

The way this will work is that the process fixture will populate template database, which in turn will be used automatically by client fixture to create a test database from scratch. Fast, clean and no dangling transactions, that could be accidentally rolled back.

Same approach will work with noproces fixture, while connecting to already running postgresql instance whether it’ll be on a docker machine or running remotely or locally.

Using SQLAlchemy to initialise basic database state

How to use SQLAlchemy for common initalisation:

def load_database(**kwargs):
    connection = f"postgresql+psycopg2://{kwargs['user']}:@{kwargs['host']}:{kwargs['port']}/{kwargs['dbname']}"
    engine = create_engine(connection)
    Base.metadata.create_all(engine)
    session = scoped_session(sessionmaker(bind=engine))
    # add things to session
    session.commit()

postgresql_proc = factories.postgresql_proc(load=[load_database])

postgresql = factories.postgresql('postgresql_proc') # still need to check if this is actually needed or not

@pytest.fixture
def dbsession(postgresql):
    connection = f'postgresql+psycopg2://{postgresql.info.user}:@{postgresql.info.host}:{postgresql.info.port}/{postgresql.info.dbname}'
    engine = create_engine(connection)

    session = scoped_session(sessionmaker(bind=engine))

    yield session
    # 'Base.metadata.drop_all(engine)' here specifically does not work. It is also not needed. If you leave out the session.close()
    # all the tests still run, but you get a warning/error at the end of the tests.
    session.close()

Release

Install pipenv and –dev dependencies first, Then run:

pipenv run tbump [NEW_VERSION]

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