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Testcontainers is a Python library that providing a friendly API to run Docker container. It is designed to create runtime environment to use during your automatic tests.

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Sebastian Hätälä
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testcontainers-python

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Python port for testcontainers-java that allows using docker containers for functional and integration testing. Testcontainers-python provides capabilities to spin up docker containers (such as a database, Selenium web browser, or any other container) for testing.

Currently available features:

  • Selenium Grid containers
  • Selenium Standalone containers
  • MySql Db container
  • MariaDb container
  • Neo4j container
  • OracleDb container
  • PostgreSQL Db container
  • Microsoft SQL Server container
  • Generic docker containers
  • LocalStack

Installation

The testcontainers package is available from PyPI, and it can be installed using pip. Depending on which containers are needed, you can specify additional dependencies as extras:

# Install without extras
pip install testcontainers
# Install with one or more extras
pip install testcontainers[mysql]
pip install testcontainers[mysql,oracle]

Basic usage

import sqlalchemy
from testcontainers.mysql import MySqlContainer

with MySqlContainer('mysql:5.7.17') as mysql:
    engine = sqlalchemy.create_engine(mysql.get_connection_url())
    version, = engine.execute("select version()").fetchone()
    print(version)  # 5.7.17

The snippet above will spin up a MySql database in a container. The get_connection_url() convenience method returns a sqlalchemy compatible url we use to connect to the database and retrieve the database version.

More extensive documentation can be found at Read The Docs.

Usage within Docker (i.e. in a CI)

When trying to launch a testcontainer from within a Docker container two things have to be provided:

  1. The container has to provide a docker client installation. Either use an image that has docker pre-installed (e.g. the [official docker images](https://hub.docker.com/_/docker)) or install the client from within the Dockerfile specification.
  2. The container has to have access to the docker daemon which can be achieved by mounting /var/run/docker.sock or setting the DOCKER_HOST environment variable as part of your docker run command.

Setting up a development environment

We recommend you use a virtual environment for development. Note that a python version >=3.6 is required. After setting up your virtual environment, you can install all dependencies and test the installation by running the following snippet.

pip install -r requirements/$(python -c 'import sys; print("%d.%d" % sys.version_info[:2])').txt
pytest -s

Adding requirements

We use pip-tools to resolve and manage dependencies. If you need to add a dependency to testcontainers or one of the extras, run pip install pip-tools followed by make requirements to update the requirements files.