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Description:

pytestpostgresql 6.0.1

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 >= 10. See tests for more details.

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')

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:

client fixture specific
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
from pathlib import Path
postgresql_my_with_schema = factories.postgresql(
'postgresql_my_proc',
load=[Path("schemafile.sql"), Path("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.
from pathlib import Path
postgresql_my_proc = factories.postgresql_proc(
load=[Path("schemafile.sql"), Path("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

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.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,
)

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:
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 initialisation:
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]