Pytest fixures for running tests with Docker containers
Project description
PyDocks
PyDocks is a group of pytest fixures for running tests with Docker containers
Demonstration:
import pytest
import asyncpg
@pytest.mark.asyncio
async def test_postgresql_execute_command(postgresql_container):
# Connect to the PostgreSQL database
conn = await asyncpg.connect(
host="127.0.0.1",
port=5433,
user="postgres",
password="postgres",
database="postgres",
)
try:
# Execute a simple command
result = await conn.fetchval("SELECT 1")
assert result == 1, "Failed to execute command on PostgreSQL"
finally:
# Close the connection
await conn.close()
Table of Contents
Description
PyDocks is a Python library that provides a set of pytest fixtures for running tests with Docker containers. It simplifies the process of setting up, managing, and tearing down Docker containers during test execution.
Key features include:
- Easy integration with pytest
- Support for PostgreSQL, Hashicorp Vault, Redis, Valkey, and more
- Automatic container cleanup
- Configurable container settings
- Reusable session-scoped containers for improved test performance
PyDocks is designed to make testing with Docker containers more efficient and less error-prone, allowing developers to focus on writing tests rather than managing infrastructure.
Installation
# Install the dependency
pip install pydocks
uv add pydocks
poetry add pydocks
Documentation
- Published docs — MkDocs site (GitHub Pages)
- Product specification — feature status and roadmap
- Architecture — feature-based layout and extension guide
- CI coverage policy — threshold and reporting
Preview the site locally with just docs-serve or build it with just docs-build.
Development
just install # install dependencies
just test # run tests (no coverage gate)
just test-cov # run tests with 100% coverage enforcement
just coverage # show coverage report from the last test-cov run
just lint # run linter and formatter
just check # run pyright
just docs-build # build MkDocs site
just docs-serve # preview docs locally
just --list # list all recipes
Tests collect coverage via just test-cov, which fails if line coverage drops below 100%. CI runs the same recipe, publishes a coverage summary in the job output, posts a comment on pull requests, and uploads coverage.xml / HTML reports as workflow artifacts.
Usage
Remove all old containers
import logging
import pytest
import pytest_asyncio
logger = logging.getLogger(__name__)
@pytest_asyncio.fixture(scope="session", loop_scope="session", autouse=True)
async def begin_clean_all_containers(postgresql_clean_all_containers):
logger.info(
"Beginning container cleanup session",
extra={"feature": "postgresql"},
)
Use a function container
import pytest
@pytest.mark.asyncio
async def test_postgresql_execute_command(postgresql_container):
...
Use a session container, to keep the container to use it in multiple tests
import pytest
@pytest.mark.asyncio(loop_scope="session")
async def test_reuse_postgresql_container_1_2(postgresql_container_session):
...
# postgresql_container_session creates a new container
@pytest.mark.asyncio(loop_scope="session")
async def test_reuse_postgresql_container_2_2(postgresql_container_session):
...
# postgresql_container_session uses the same instance of container created in test_reuse_postgresql_container_1_2
Available Containers
PyDocks provides fixtures for the following Docker containers:
- PostgreSQL:
postgresql_container,postgresql_container_session,postgresql_clean_all_containers - Redis:
redis_container,redis_container_session,redis_clean_all_containers - Valkey:
valkey_container,valkey_container_session,valkey_clean_all_containers - Hashicorp Vault:
vault_container,vault_container_session,vault_clean_all_containers - Ubuntu:
ubuntu_container,ubuntu_container_session,ubuntu_clean_all_containers - Alpine:
alpine_container,alpine_container_session,alpine_clean_all_containers - OpenTofu:
opentofu_container,opentofu_container_session,opentofu_clean_all_containers
License
PyDocks is released under the MIT License. See the LICENSE file for more details.
Contact
For questions, suggestions, or issues related to PyDocks, please open an issue on the GitHub repository.
Project details
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