A pytest plugin, that enables you to test your code that relies on a running PostgreSQL Database

Overview

https://raw.githubusercontent.com/ClearcodeHQ/pytest-postgresql/master/logo.png

pytest-postgresql

Latest PyPI version Wheel Status Supported Python Versions License

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.

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:

  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/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
 
Log filename's prefix logsprefix --postgresql-logsprefix postgresql_logsprefix
 
Location for unixsockets unixsocket --postgresql-unixsocketdir postgresql_unixsocketdir
$TMPDIR
Database name 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:

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:

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",
)

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.

Owner
Clearcode
Software house with a passion for technology. We specialize in building enterprise-grade adtech, martech and analytics platforms.
Clearcode
A automated browsing experience.

browser-automation This app is an automated browsing technique where one has to enter the required information, it's just like searching for Animals o

Ojas Barawal 3 Aug 04, 2021
frwk_51pwn is an open-sourced remote vulnerability testing and proof-of-concept development framework

frwk_51pwn Legal Disclaimer Usage of frwk_51pwn for attacking targets without prior mutual consent is illegal. frwk_51pwn is for security testing purp

51pwn 4 Apr 24, 2022
An AWS Pentesting tool that lets you use one-liner commands to backdoor an AWS account's resources with a rogue AWS account - or share the resources with the entire internet 😈

An AWS Pentesting tool that lets you use one-liner commands to backdoor an AWS account's resources with a rogue AWS account - or share the resources with the entire internet 😈

Brandon Galbraith 276 Mar 03, 2021
Free cleverbot without headless browser

Cleverbot Scraper Simple free cleverbot library that doesn't require running a heavy ram wasting headless web browser to actually chat with the bot, a

Matheus Fillipe 3 Sep 25, 2022
An Instagram bot that can mass text users, receive and read a text, and store it somewhere with user details.

Instagram Bot 🤖 July 14, 2021 Overview 👍 A multifunctionality automated instagram bot that can mass text users, receive and read a message and store

Abhilash Datta 14 Dec 06, 2022
Doing dirty (but extremely useful) things with equals.

Doing dirty (but extremely useful) things with equals. Documentation: dirty-equals.helpmanual.io Source Code: github.com/samuelcolvin/dirty-equals dir

Samuel Colvin 602 Jan 05, 2023
User-oriented Web UI browser tests in Python

Selene - User-oriented Web UI browser tests in Python (Selenide port) Main features: User-oriented API for Selenium Webdriver (code like speak common

Iakiv Kramarenko 575 Jan 02, 2023
Automatic SQL injection and database takeover tool

sqlmap sqlmap is an open source penetration testing tool that automates the process of detecting and exploiting SQL injection flaws and taking over of

sqlmapproject 25.7k Jan 04, 2023
Airspeed Velocity: A simple Python benchmarking tool with web-based reporting

airspeed velocity airspeed velocity (asv) is a tool for benchmarking Python packages over their lifetime. It is primarily designed to benchmark a sing

745 Dec 28, 2022
Active Directory Penetration Testing methods with simulations

AD penetration Testing Project By Ruben Enkaoua - GL4Di4T0R Based on the TCM PEH course (Heath Adams) Index 1 - Setting Up the Lab Intallation of a Wi

GL4DI4T0R 3 Aug 12, 2021
Selenium-python but lighter: Helium is the best Python library for web automation.

Selenium-python but lighter: Helium Selenium-python is great for web automation. Helium makes it easier to use. For example: Under the hood, Helium fo

Michael Herrmann 3.2k Dec 31, 2022
automate the procedure of 403 response code bypass

403bypasser automate the procedure of 403 response code bypass Description i notice a lot of #bugbountytips describe how to bypass 403 response code s

smackerdodi2 40 Dec 16, 2022
Lightweight, scriptable browser as a service with an HTTP API

Splash - A javascript rendering service Splash is a javascript rendering service with an HTTP API. It's a lightweight browser with an HTTP API, implem

Scrapinghub 3.8k Jan 03, 2023
Turn any OpenAPI2/3 and Postman Collection file into an API server with mocking, transformations and validations.

Prism is a set of packages for API mocking and contract testing with OpenAPI v2 (formerly known as Swagger) and OpenAPI v3.x. Mock Servers: Life-like

Stoplight 3.3k Jan 05, 2023
The source code and slide for my talk about the subject: unittesing in python

PyTest Talk This talk give you some ideals about the purpose of unittest? how to write good unittest? how to use pytest framework? and show you the ba

nguyenlm 3 Jan 18, 2022
CNE-OVS-SIT - OVS System Integration Test Suite

CNE-OVS-SIT - OVS System Integration Test Suite Introduction User guide Discussion Introduction CNE-OVS-SIT is a test suite for OVS end-to-end functio

4 Jan 09, 2022
A modern API testing tool for web applications built with Open API and GraphQL specifications.

Schemathesis Schemathesis is a modern API testing tool for web applications built with Open API and GraphQL specifications. It reads the application s

Schemathesis.io 1.6k Jan 06, 2023
pytest plugin for a better developer experience when working with the PyTorch test suite

pytest-pytorch What is it? pytest-pytorch is a lightweight pytest-plugin that enhances the developer experience when working with the PyTorch test sui

Quansight 39 Nov 18, 2022
A rewrite of Python's builtin doctest module (with pytest plugin integration) but without all the weirdness

The xdoctest package is a re-write of Python's builtin doctest module. It replaces the old regex-based parser with a new abstract-syntax-tree based pa

Jon Crall 174 Dec 16, 2022
pytest splinter and selenium integration for anyone interested in browser interaction in tests

Splinter plugin for the pytest runner Install pytest-splinter pip install pytest-splinter Features The plugin provides a set of fixtures to use splin

pytest-dev 238 Nov 14, 2022