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
• ClickHouse container
• Microsoft SQL Server container
• Generic docker containers
• ArangoDB container
• LocalStack
• RabbitMQ
• Keycloak

Installation

The testcontainers package is available from PyPI <https://pypi.org/project/testcontainers/>, and it can be installed using :code:pip. Depending on which containers are needed, you can specify additional dependencies as extras <https://setuptools.readthedocs.io/en/latest/setuptools.html#declaring-extras-optional-features-with-their-own-dependencies>:

.. code-block:: bash

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

Basic usage

.. code-block:: python

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 :code:get_connection_url() convenience method returns a :code: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 <http://testcontainers-python.readthedocs.io/>_.

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 <https://virtualenv.pypa.io/en/stable/>_ for development. Note that a python version :code:>=3.6 is required. After setting up your virtual environment, you can install all dependencies and test the installation by running the following snippet.

.. code-block:: bash

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

Adding requirements ^^^^^^^^^^^^^^^^^^^

We use :code:pip-tools to resolve and manage dependencies. If you need to add a dependency to testcontainers or one of the extras, modify the :code:setup.py as well as the :code:requirements.in accordingly and then run :code:pip install pip-tools followed by :code:make requirements to update the requirements files.

Contributing a new container ^^^^^^^^^^^^^^^^^^^^^^^^^^^^

You can contribute a new container in three steps:

1. Create a new module at :code:testcontainers/[my fancy container].py that implements the new functionality.
2. Create a new test module at :code:tests/test_[my fancy container].py that tests the new functionality.
3. Add :code:[my fancy container] to the list of test components in the GitHub Action configuration at :code:.github/workflows/main.yml.