The service is a light wrapper service around pyciemss. Both a FastAPI and RQ tasks are provided so jobs can be run asynchronously for long periods of time. The service must also conform to this spec.
Experimental: sciml engine can be chosen for simulate.
To start the PyCIEMSS Simulation API, first run:
make init
in order to pull the PyCIEMSS repository in as a submodule and set up the environment file from the sample file. Next run:
make up
to start the containers and the API. The API url will be http://localhost:8010 by default
poetry run pytest executes tests. Run make tidy to execute the code formatter, tests, etc.
Every operation saves 3 files to S3
result.csveval.csv(if pyciemss engine is used)visualization.json(if pyciemss engine is used)
Only the calibrate operation reports progress to RabbitMQ. This is to
the simulation-status queue with a payload that looks like {"job_id": "some string", "progress": "float between 0 and 1"}.
The Docker Compose starts rabbitmq AND a mock consumer for the messages. The mock consumer is only helpful for testing without the full stack.