quickstarts/tutorials/workflow/python/monitor-pattern/README.md

Monitor Pattern

This tutorial demonstrates how to run a workflow in a loop. This can be used for recurring tasks that need to be executed on a certain frequency (e.g. a clean-up job that runs every hour). For more information on the monitor pattern see the Dapr docs.

Inspect the code

Open the monitor_workflow.py file in the tutorials/workflow/python/monitor-pattern/monitor folder. This file contains the definition for the workflow that calls the check_status activity to checks to see if a fictional resource is ready. The check_status activity uses a random number generator to simulate the status of the resource. If the status is not ready, the workflow will wait for one second and is continued as a new instance.

graph LR
   SW((Start
   Workflow))
   CHECK[check_status]
   IF{Is Ready}
   TIMER[Wait for a period of time]
   NEW[Continue as a new instance]
   EW((End
   Workflow))
   SW --> CHECK
   CHECK --> IF
   IF -->|Yes| EW
   IF -->|No| TIMER
   TIMER --> NEW
   NEW --> SW

Run the tutorial

1. Use a terminal to navigate to the tutorials/workflow/python/monitor-pattern/monitor folder.

2. Install the dependencies using pip:

   pip3 install -r requirements.txt
   

3. Navigate one level up to the monitor-pattern folder and use the Dapr CLI to run the Dapr Multi-App run file

   ```bash
   

   dapr run -f .

   <!-- END_STEP -->
   
   

4. Use the POST request in the monitor.http file to start the workflow, or use this cURL command:

   curl -i --request POST http://localhost:5257/start/0
   

   The input for the workflow is an integer with the value 0.

   The expected app logs are as follows:

   == APP - monitor == check_status: Received input: 0.
   == APP - monitor == check_status: Received input: 1.
   == APP - monitor == check_status: Received input: 2.
   == APP - monitor == check_status: Received input: 3.
   

   Note that the number of app log statements can vary due to the randomization in the check_status activity.

5. Use the GET request in the monitor.http file to get the status of the workflow, or use this cURL command:

   curl --request GET --url http://localhost:3557/v1.0/workflows/dapr/<INSTANCEID>
   

   Where <INSTANCEID> is the workflow instance ID you received in the Location header in the previous step.

   The expected serialized output of the workflow is:

   "\"Status is healthy after checking 3 times.\""
   

   The actual number of checks can vary since some randomization is used in the check_status activity.

6. Stop the Dapr Multi-App run process by pressing Ctrl+C.