pytest-postgresql

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

Warning

Tested on PostgreSQL versions >= 9.6. See tests for more details.

Install with:

pip install pytest-postgresql

You will also need to install psycopg2, or one of its alternative packagings such as psycopg2-binary (pre-compiled wheels) or psycopg2cffi (CFFI based, useful on PyPy).

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 psycopg2 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')

Note

Each PostgreSQL process fixture can be configured in a different way than the others through the fixture factory arguments.

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]
)

Warning

This way, the database will still be dropped each time.

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/9.6/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
Log filename's prefix	logsprefix	--postgresql-logsprefix	postgresql_logsprefix
Location for unixsockets	unixsocket	--postgresql-unixsocketdir	postgresql_unixsocketdir		$TMPDIR
Database name	db_name	--postgresql-dbname	postgresql_dbname		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  # pylint:disable=import-outside-toplevel

    # NOTE: this fstring assumes that psycopg2 >= 2.8 is used. Not sure about it's support in psycopg2cffi (PyPy)
    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

Note

See the original code at pyramid_fullauth's conftest file. Depending on your needs, that in between code can fire alembic migrations in case of sqlalchemy stack or any other code

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.factories import DatabaseJanitor

@pytest.fixture
func 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.factories import DatabaseJanitor

@pytest.fixture
func 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,
        )

Note

DatabaseJanitor manages the state of the database, but you'll have to create connection to use in test code yourself.

You can optionally pass in a recognized postgresql ISOLATION_LEVEL for additional control.

Note

See DatabaseJanitor usage in python's warehouse test code https://github.com/pypa/warehouse/blob/5d15bfe/tests/conftest.py#L127

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:

postgresql_in_docker = factories.postgresql_noproc()
postresql = factories.postgresql("postgresql_in_docker", db_name="test")


def test_postgres_docker(postresql):
    """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

Using a common database initialisation between tests

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

from pytest_postgresql.factories import postgresql, postgresql_proc
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 = postgresql_proc(
    load=[load_database],
)

postgresql = postgresql(
    "postgresql_proc",
)

You can also define your own database name by passing same dbname value to both factories.

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.