This application consists of a frontend and a backend service, a PostgreSQL database, and a connector proxy, all orchestrated with Docker Compose.
spiffworkflow-frontend: The frontend user interface for the workflow application.spiffworkflow-backend: The backend service providing API endpoints for the frontend.spiffdb: A PostgreSQL database service used by the backend to store workflow data.spiffworkflow-connector: A connector proxy service for external integrations.
- Ensure Docker and Docker Compose are installed on your system.
- Clone the repository and navigate to the directory containing the
docker-compose.ymlfile. The default ports are set in this file, but you can change them if needed. - Run
make upto start all services. The services will be available on the following default ports: - Access the frontend at
http://localhost:8001, where8001is the default port for the frontend service. - Access the backend API at
http://localhost:8000/v1.0, where8000is the default port for the backend service. - Run
make downto stop all services.
To access the PostgreSQL database from within the spiffdb container, use the following command:
psql -U spiffuser -d spiffworkflowThe default username is spiffuser and the password is spiffpass, as configured in the docker-compose.yml file.
Health checks are configured for the spiffworkflow-backend and spiffdb services to ensure they are ready before dependent services start.
The api is available at localhost:8000/v1.0 if you run make up in this repo.
This example uses an approval process to show how to navigate tasks that need to wait for human interaction.
To get an idea of how the process works, you might want to view the diagram and run the process at http://localhost:8001/process-models/approvals:basic-approval before hammering the API.
Some of the followiong commands use jq, a useful tool for parsing JSON, in case you want to follow along with that by installing it.
# use a little script to get a token from the nonproduction openid server built in to spiffworkflow-backend and store it in a file.
# note that spiffworkflow supports any openid system, and this built in server should never be used in production.
./bin/get_token admin > /tmp/t
# create a process instance
curl -s -X POST localhost:8000/v1.0/process-instances/approvals:basic-approval -H "Authorization: Bearer $(cat /tmp/t)"
# let's assume that the previous request returned id 24. run that instance
curl -s -X POST localhost:8000/v1.0/process-instances/approvals:basic-approval/24/run -H "Authorization: Bearer $(cat /tmp/t)"
# it requires some human interaction. fetch the tasks that might need completing
curl -s "localhost:8000/v1.0/tasks?process_instance_id=24" -H "Authorization: Bearer $(cat /tmp/t)" | jq .
# the tasks API will return json like this:
# {
# "results": [
# {
# "id": "64c3738c-0dc1-48f6-98fc-7db41e03dab3",
# "form_file_name": "request-schema.json",
# "task_type": "UserTask",
# "ui_form_file_name": "request-uischema.json",
# "task_status": "READY",
# [SNIP]
# "assigned_user_group_identifier": null,
# "potential_owner_usernames": "[email protected]"
# }
# ],
# }
# it looks like this task uses the request-schema.json form. let's fetch it.
curl -s "localhost:8000/v1.0/process-models/approvals:basic-approval/files/request-schema.json" -H "Authorization: Bearer $(cat /tmp/t)" | jq -r .file_contents
# this response tells us that we need a request_item when submitting the task
# submit the task based on the information from the tasks response
curl -X PUT -H 'Content-type: application/json' -d '{"request_item": "apple"}' "localhost:8000/v1.0/tasks/24/64c3738c-0dc1-48f6-98fc-7db41e03dab3" -H "Authorization: Bearer $(cat /tmp/t)" | jq .
# next the process instance will proceed to the approval task.
# its form can be inspected and the task submitted in the same way as above.
# note that normally the same user who started the process instance would not be able to complete the approval,
# but in this case the user whose token we are using is also in the "admin" group,
# so they have access to complete the approval task in the admin lane.
curl -s "localhost:8000/v1.0/process-models/approvals:basic-approval/files/approval-schema.json" -H "Authorization: Bearer $(cat /tmp/t)" | jq -r .file_contents
curl -X PUT -H 'Content-type: application/json' -d '{"is_approved": false, "comments": "looks good to me"}' "localhost:8000/v1.0/tasks/24/f796b2d5-8d7c-423f-ac1a-2cfbc95f4c04" -H "Authorization: Bearer $(cat /tmp/t)" | jq .
# at this point, after the two PUT requests, you can check on the instance,
# and it will hopefully be completed if you said is_approved false
curl -s localhost:8000/v1.0/process-instances/approvals:basic-approval/24 -H "Authorization: Bearer $(cat /tmp/t)" | jq .If you approved it by setting is_approved to true, the instance will be waiting on a final manual task that is just giving you a message about how you approved the item.
Hopefully this has been helpful in describing how to access some of the important functionality via the API.
If you encounter any issues with the services, check the logs using docker-compose logs.
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