quickstarts/tutorials/workflow/python/task-chaining/README.md

Task Chaining Pattern

This tutorial demonstrates how to chain multiple tasks together as a sequence in a workflow. For more information about the task chaining pattern see the Dapr docs.

Inspect the code

Open the chaining_workflow.py file in the tutorials/workflow/python/task-chaining/task_chaining folder. This file contains the definition for the workflow.

graph LR
   SW((Start
   Workflow))
   A1[activity1]
   A2[activity2]
   A3[activity3]
   EW((End
   Workflow))
   SW --> A1
   A1 --> A2
   A2 --> A3
   A3 --> EW

Run the tutorial

1. Use a terminal to navigate to the tutorials/workflow/python/task-chaining/task_chaining folder.

2. Install the dependencies using pip:

   pip3 install -r requirements.txt
   

3. Navigate back one level to the task-chaining 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 chaining.http file to start the workflow, or use this cURL command:

   curl -i --request POST http://localhost:5255/start
   

   The input for the workflow is a string with the value This. The expected app logs are as follows:

   == APP - chaining == activity1: Received input: This.
   == APP - chaining == activity2: Received input: This is.
   == APP - chaining == activity3: Received input: This is task.
   

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

   curl --request GET --url http://localhost:3555/v1.0/workflows/dapr/<INSTANCEID>
   

   Where <INSTANCEID> is the workflow instance ID you received in the instance_id property in the previous step.

   The expected serialized output of the workflow is:

   "\"This is task chaining\""
   

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