Test containers with Docker in PyTest

Introduction

Test containers help you run real services like databases in Docker during tests. This makes tests more reliable and close to real use.

When you want to test your code with a real database instead of a fake one.

When your application depends on external services like Redis or Kafka during tests.

When you want to isolate tests so they don't affect your local environment.

When you want consistent test environments on different machines or CI servers.

Syntax

PyTest

from testcontainers.postgres import PostgresContainer
import pytest
from sqlalchemy import create_engine

@pytest.fixture(scope='module')
def postgres_container():
    with PostgresContainer('postgres:15') as postgres:
        yield postgres


def test_database_connection(postgres_container):
    engine = create_engine(postgres_container.get_connection_url())
    # Your test code here

Use with PostgresContainer('image') to start and stop the container automatically.

Use pytest fixtures to manage container lifecycle during tests.

Examples

This example shows how to start a Redis container for testing.

PyTest

from testcontainers.redis import RedisContainer

with RedisContainer('redis:7') as redis:
    redis_url = redis.get_connection_url()
    # Connect your app to redis_url

Fixture to start a MySQL container for each test function.

PyTest

import pytest
from testcontainers.mysql import MySqlContainer

@pytest.fixture(scope='function')
def mysql_container():
    with MySqlContainer('mysql:8') as mysql:
        yield mysql

Sample Program

This test starts a Postgres container, creates a table, inserts data, and queries it to check correctness.

PyTest

from testcontainers.postgres import PostgresContainer
from sqlalchemy import create_engine, text
import pytest

@pytest.fixture(scope='module')
def postgres_container():
    with PostgresContainer('postgres:15') as postgres:
        yield postgres


def test_insert_and_query(postgres_container):
    engine = create_engine(postgres_container.get_connection_url())
    with engine.connect() as conn:
        conn.execute(text('CREATE TABLE test (id INT PRIMARY KEY, name VARCHAR(50));'))
        conn.execute(text("INSERT INTO test (id, name) VALUES (1, 'Alice');"))
        conn.commit()
        result = conn.execute(text('SELECT name FROM test WHERE id=1;'))
        name = result.scalar()
        assert name == 'Alice'
        print(f'Queried name: {name}')

Important Notes

Make sure Docker is running before you run tests using test containers.

Test containers automatically clean up after tests, so no leftover services remain.

Use lightweight official images to keep tests fast.

Summary

Test containers let you run real services in Docker during tests.

Use pytest fixtures to manage container lifecycle easily.

This approach makes tests more reliable and closer to real-world use.

Practice

1. What is the main benefit of using test containers with Docker in pytest?

easy

A. They make tests run faster by skipping setup steps.

B. They replace the need for writing any test code.

C. They automatically fix bugs in the application code.

D. They provide real service environments during tests for better reliability.

Solution

1. Step 1: Understand test containers purpose

   Test containers run real services like databases inside Docker during tests.

2. Step 2: Identify benefit in pytest context

   This makes tests more reliable and realistic by using actual service environments.

3. Final Answer:

   They provide real service environments during tests for better reliability. -> Option D

4. Quick Check:

   Real service environment = Better test reliability [OK]

Hint: Remember: test containers run real services inside Docker [OK]

Common Mistakes:

• Thinking test containers replace writing tests
• Believing they fix code bugs automatically
• Assuming tests run faster by skipping setup

2. Which pytest fixture code correctly starts a Docker container for testing?

easy

A. def container():
container = docker.run('redis')
yield container
container.stop()

B. def container():
client = docker.from_env()
container = client.run('redis')
yield container
container.stop()

C. def container():
client = docker.from_env()
container = client.containers.run('redis', detach=True)
yield container
container.stop()

D. def container():
client = docker.from_env()
container = client.containers.run('redis')
container.start()
yield container
container.stop()

Solution

1. Step 1: Check correct Docker client usage

   Use docker.from_env() to get client, then client.containers.run() with detach=True to start container.

2. Step 2: Verify fixture lifecycle management

   Yield container for test, then stop container after test finishes.

3. Final Answer:

   def container(): client = docker.from_env() container = client.containers.run('redis', detach=True) yield container container.stop() -> Option C

4. Quick Check:

   Use client.containers.run with detach=True [OK]

Hint: Use client.containers.run with detach=True to start container [OK]

Common Mistakes:

• Calling client.run instead of client.containers.run
• Missing detach=True causing blocking call
• Not stopping container after test

3. Given this pytest fixture, what will be printed when running the test?

import pytest
import docker

@pytest.fixture
 def redis_container():
    client = docker.from_env()
    container = client.containers.run('redis:alpine', detach=True)
    yield container
    container.stop()

def test_redis_running(redis_container):
    print(redis_container.status)

medium

A. running

B. created

C. exited

D. paused

Solution

1. Step 1: Understand container lifecycle in fixture

   Container is started with detach=True, so status should be 'running' during test.

2. Step 2: Check printed status in test

   redis_container.status returns current container status, expected 'running' while test runs.

3. Final Answer:

   running -> Option A

4. Quick Check:

   Container started = status 'running' [OK]

Hint: Container status is 'running' while test uses it [OK]

Common Mistakes:

• Expecting 'created' before container starts
• Assuming container is 'exited' during test
• Confusing status with container image tag

4. Identify the error in this pytest fixture that manages a Docker container:

@pytest.fixture
def redis_container():
    client = docker.from_env()
    container = client.containers.run('redis', detach=True)
    yield container
    container.remove()

medium

A. Missing container.stop() before container.remove() to stop container properly.

B. Using container.remove() instead of container.delete() which is invalid.

C. Not specifying environment variables for Redis container causes failure.

D. Yielding container before starting it causes runtime error.

Solution

1. Step 1: Check container cleanup steps

   Container must be stopped before removal to avoid errors.

2. Step 2: Identify missing stop call

   Fixture calls container.remove() but misses container.stop() before it.

3. Final Answer:

   Missing container.stop() before container.remove() to stop container properly. -> Option A

4. Quick Check:

   Stop container before remove to clean up [OK]

Hint: Always stop container before removing it [OK]

Common Mistakes:

• Calling remove without stopping container
• Confusing remove() with non-existent delete()
• Assuming environment vars are mandatory for container start

5. You want to write a pytest fixture that starts a PostgreSQL container with Docker, waits until it is ready to accept connections, and then yields it for tests. Which approach correctly combines container management and readiness check?

hard

A. Start container without detach, yield immediately, and rely on test to wait for readiness.

B. Start container with detach=True, then poll container logs until 'database system is ready' appears before yielding.

C. Start container with detach=True and yield immediately without any readiness check.

D. Start container with detach=True, sleep fixed 1 second, then yield container.

Solution

1. Step 1: Manage container lifecycle properly

   Start PostgreSQL container detached to run in background during tests.

2. Step 2: Implement readiness check before yielding

   Poll container logs for 'database system is ready' message to ensure service is ready.

3. Step 3: Yield container after readiness confirmed

   This ensures tests run only after PostgreSQL is ready to accept connections.

4. Final Answer:

   Start container with detach=True, then poll container logs until 'database system is ready' appears before yielding. -> Option B

5. Quick Check:

   Wait for readiness log before yielding container [OK]

Hint: Wait for readiness log, don't guess with sleep [OK]

Common Mistakes:

• Yielding container before it is ready
• Using fixed sleep instead of log polling
• Starting container without detach causing blocking