Backend guide
In order start developing on Infrahub backend, it is recommended to have a decent knowledge about topics such as Docker, Python and generally UNIX systems. Tools such as Docker and Python virtual environment help us in isolating the development work without interfering with the system itself. In this guide, we will use:
- Python to be able to run the code
- Invoke to run some commands bundled with Infrahub
- Poetry to manage our Python virtual environment
- Docker and its Compose extension to run dependencies such as the database, cache and queueing system
To fetch Infrahub's code, we will use Git and we will use the develop
branch (default).
git clone --recursive [email protected]:opsmill/infrahub.git
cd infrahub
Basic settings
Most of Infrahub and tools around it rely on some settings. These settings are in general set as environment variables, dealing with many of these can be hard to maintain and manage. We can use a tool such as direnv to help. It allows to define environment variables (or pretty much anything bash can make sense of) in a file that will be interpreted when entering a given directory. Here is an example of a .envrc
file providing development friendly setting values:
export INFRAHUB_PRODUCTION=false
export INFRAHUB_SECURITY_SECRET_KEY=super-secret
export INFRAHUB_USERNAME=admin
export INFRAHUB_PASSWORD=infrahub
export INFRAHUB_TIMEOUT=20
export INFRAHUB_METRICS_PORT=8001
export INFRAHUB_DB_TYPE=neo4j # Accepts neo4j or memgraph
export INFRAHUB_INITIAL_ADMIN_TOKEN="${ADMIN_TOKEN}" # Random string which can be generated using: openssl rand -hex 16
export INFRAHUB_STORAGE_LOCAL_PATH="${HOME}/Development/infrahub-storage"
export INFRAHUB_API_CORS_ALLOW_ORIGINS='["http://localhost:8080"]' # Allow frontend/backend communications without CORS issues
The exported environment variables are very important and must be set before moving to another step. Without these, you will likely face some errors or issues later.
Required services
Infrahub uses several external services to work:
- A neo4j database
- A Redis in-memory store
- A RabbitMQ message broker
To run all these services, we will use Docker, but for local development some ports will need to be bound to local ones. To do so, a very basic Docker Compose override file is provided in the development
directory, but it has a tmp
extension which makes Compose ignore it by default. We will copy this file to a new one without the tmp
extension. In a development environment, having only the services in Docker and Infrahub running on local Python is convenient to take advantage of the server auto-reload feature when making changes.
cp development/docker-compose.dev-override.yml.tmp development/docker-compose.dev-override.yml
Now we need to make sure we have a compatible version of Python that Infrahub can run on top of, Poetry to create virtual environment and Invoke to run commands. Invoke can be installed in many ways, but we recommend to use the pipx
way to get it available user wide while without messing with the system Python. Assuming we have these utilities ready, we can run the following commands to build a proper Python environment:
cd infrahub # or the directory of your choice
poetry install
Some tests require some services to work. By default, they are automatically started by pytest before tests run. It is also possible to disable the automatic startup of services and to rely on existing services using an environment variable:
export INFRAHUB_USE_TEST_CONTAINERS=false
The required services now need to be started using dedicated commands:
invoke dev.destroy dev.deps
This will actually pass two commands, one to destroy any remains of a previous run and one to start services. So this will effectively bring up clean services without leftovers. We can see which services are running by using:
poetry run invoke dev.status
This should yield a Docker output like the following: docs
NAME IMAGE COMMAND SERVICE CREATED STATUS PORTS
infrahub-cache-1 redis:7.2 "docker-entrypoint.s…" cache 2 hours ago Up 2 hours (healthy) 0.0.0.0:6379->6379/tcp
infrahub-database-1 memgraph/memgraph:2.13.0 "/usr/lib/memgraph/m…" database 2 hours ago Up 2 hours (healthy) 0.0.0.0:7444->7444/tcp, 0.0.0.0:7474->7474/tcp, 0.0.0.0:7687->7687/tcp
infrahub-message-queue-1 rabbitmq:3.12-management "docker-entrypoint.s…" message-queue 2 hours ago Up 2 hours (healthy) 4369/tcp, 5671/tcp, 0.0.0.0:5672->5672/tcp, 15671/tcp, 15691-15692/tcp, 25672/tcp, 0.0.0.0:15672->15672/tcp
When following a guide, like the installation guide, the command demo.start
is mentioned. It is slightly different from the dev.deps
that is mentioned here. The demo.start
will bring up a demo environment as a whole including services and Infrahub while the dev.deps
will only start the services as seen in the code block above.
Running Infrahub test suite
With the required services working and properly setup Python virtual environment we can now run the Infrahub test suite to make sure the code works as intended.
INFRAHUB_LOG_LEVEL=CRITICAL pytest -v backend/tests/unit
The environment variable at the beginning of the command is useful to have a much more cleaner output when running tests.
Running Infrahub server
We can run the Infrahub server with the built-in command:
infrahub server start --debug
The debug
flag allows the server to be reloaded when a change is detected in the source code.
Note that this will only make the backend service usable, the frontend will not be available. Only Swagger documentation should be available at http://localhost:8000/api/docs. GraphQL sandbox is available through the frontend.
For running the frontend, please refer to its dedicated documentation section.
Loading a new schema via CLI
For testing code changes, you may want to load a new schema from a YAML file. This can be performed in the development environment using:
poetry run infrahubctl schema load ${PATH_TO_SCHEMA_FILE}
Code format
Formatting code in the backend relies on Ruff and yamllint. To ensure all files are as close as possible to the expected format, it is recommended to run the format
command:
poetry run invoke format