For a quick setup to run the application, copy the values in .env.example to .env and run the ./run_mock_local.sh script, this will setup the project using Docker Compose, and will also run a mock rexflow server that simulates communication to a rexflow cluster.
To run the project with rexflow, you must set the required endpoints to flowd and uibridge in REX_REXFLOW_HOST and REX_REXFLOW_FLOWD_HOST and then execute the run_local.sh script. You may also need to change the REX_REXUI_SERVER_CALLBACK_HOST to an appropiate value to allow callback communication from rexflow uibridge.
If you already have a local kubernetes cluster running rexflow, it might be better to deploy the project into the cluster for a better integration. In this case, you can execute the ./deploy.sh script that will add a pod for the project and redis to the local cluster, using the values in charts/prism-api.yaml and charts/redis.yaml.
You can run linter and tests inside docker using the ci configuration with ./run_ci_test.sh.
If you want to be able to run linter and tests directly you should setup the conda environment with conda env update -f environment.yml, activate with conda activate prism-api and then run the linter with flake8 and tests with pytest. If you want to check the project coverage run pytest --cov.
If you run the project using the run_local.sh or run_mock_local.sh scripts, a Python debugger will be available at port 5678. You can also include the docker-compose.debug.yml configuration or use the debug target on the docker image to activate the debugger.