Updates docs

Signed-off-by: Elena Kolevska <[email protected]>

Author: elena-kolevska

daprdocs/content/en/python-sdk-docs/python-client.md

@@ -518,85 +518,68 @@ def main():
 ### Workflow
 
 ```python
-from dapr.ext.workflow import WorkflowRuntime, DaprWorkflowContext, WorkflowActivityContext
-from dapr.clients import DaprClient
+from time import sleep
 
-instanceId = "exampleInstanceID"
-workflowComponent = "dapr"
-workflowName = "hello_world_wf"
-eventName = "event1"
-eventData = "eventData"
+import dapr.ext.workflow as wf
 
-def main():
-    with DaprClient() as d:
-        host = settings.DAPR_RUNTIME_HOST
-        port = settings.DAPR_GRPC_PORT
-        workflowRuntime = WorkflowRuntime(host, port)
-        workflowRuntime = WorkflowRuntime()
-        workflowRuntime.register_workflow(hello_world_wf)
-        workflowRuntime.register_activity(hello_act)
-        workflowRuntime.start()
-
-        # Start the workflow
-        start_resp = d.start_workflow(instance_id=instanceId, workflow_component=workflowComponent,
-                        workflow_name=workflowName, input=inputData, workflow_options=workflowOptions)
-        print(f"start_resp {start_resp.instance_id}")
-
-        # ...
-
-        # Pause Test
-        d.pause_workflow(instance_id=instanceId, workflow_component=workflowComponent)
-        getResponse = d.get_workflow(instance_id=instanceId, workflow_component=workflowComponent)
-        print(f"Get response from {workflowName} after pause call: {getResponse.runtime_status}")
-
-        # Resume Test
-        d.resume_workflow(instance_id=instanceId, workflow_component=workflowComponent)
-        getResponse = d.get_workflow(instance_id=instanceId, workflow_component=workflowComponent)
-        print(f"Get response from {workflowName} after resume call: {getResponse.runtime_status}")
-        
-        sleep(1)
-        # Raise event
-        d.raise_workflow_event(instance_id=instanceId, workflow_component=workflowComponent,
-                    event_name=eventName, event_data=eventData)
 
-        sleep(5)
-        # Purge Test
-        d.purge_workflow(instance_id=instanceId, workflow_component=workflowComponent)
-        try:
-            getResponse = d.get_workflow(instance_id=instanceId, workflow_component=workflowComponent)
-        except DaprInternalError as err:
-            if nonExistentIDError in err._message:
-                print("Instance Successfully Purged")
-
-        
-        # Kick off another workflow for termination purposes 
-        # This will also test using the same instance ID on a new workflow after
-        # the old instance was purged
-        start_resp = d.start_workflow(instance_id=instanceId, workflow_component=workflowComponent,
-                        workflow_name=workflowName, input=inputData, workflow_options=workflowOptions)
-        print(f"start_resp {start_resp.instance_id}")
-
-        # Terminate Test
-        d.terminate_workflow(instance_id=instanceId, workflow_component=workflowComponent)
-        sleep(1)
-        getResponse = d.get_workflow(instance_id=instanceId, workflow_component=workflowComponent)
-        print(f"Get response from {workflowName} after terminate call: {getResponse.runtime_status}")
-
-        # Purge Test
-        d.purge_workflow(instance_id=instanceId, workflow_component=workflowComponent)
-        try:
-            getResponse = d.get_workflow(instance_id=instanceId, workflow_component=workflowComponent)
-        except DaprInternalError as err:
-            if nonExistentIDError in err._message:
-                print("Instance Successfully Purged")
+wfr = wf.WorkflowRuntime()
+
+
+@wfr.workflow(name='random_workflow')
+def task_chain_workflow(ctx: wf.DaprWorkflowContext, wf_input: int):
+    try:
+        result1 = yield ctx.call_activity(step1, input=wf_input)
+        result2 = yield ctx.call_activity(step2, input=result1)
+    except Exception as e:
+        yield ctx.call_activity(error_handler, input=str(e))
+        raise
+    # TODO update to set custom status
+    return [result1, result2]
+
 
-        workflowRuntime.shutdown()
+@wfr.activity(name='step1')
+def step1(ctx, activity_input):
+    print(f'Step 1: Received input: {activity_input}.')
+    # Do some work
+    return activity_input + 1
+
+
+@wfr.activity
+def step2(ctx, activity_input):
+    print(f'Step 2: Received input: {activity_input}.')
+    # Do some work
+    return activity_input * 2
+
+@wfr.activity
+def error_handler(ctx, error):
+    print(f'Executing error handler: {error}.')
+    # Do some compensating work
+
+
+if __name__ == '__main__':
+    wfr.start()
+    sleep(10)  # wait for workflow runtime to start
+
+    wf_client = wf.DaprWorkflowClient()
+    instance_id = wf_client.schedule_new_workflow(workflow=task_chain_workflow, input=42)
+    print(f'Workflow started. Instance ID: {instance_id}')
+    state = wf_client.wait_for_workflow_completion(instance_id)
+    print(f'Workflow completed! Status: {state.runtime_status}')
+
+    wfr.shutdown()
 ```
 
 - Learn more about authoring and managing workflows: 
   - [How-To: Author a workflow]({{< ref howto-author-workflow.md >}}).
   - [How-To: Manage a workflow]({{< ref howto-manage-workflow.md >}}).
-- Visit [Python SDK examples](https://github.com/dapr/python-sdk/blob/master/examples/demo_workflow/app.py) for code samples and instructions to try out Dapr Workflow.
+- Visit [Python SDK examples](https://github.com/dapr/python-sdk/tree/main/examples/workflow) for code samples and instructions to try out Dapr Workflow:
+  - [Task chaining example](https://github.com/dapr/python-sdk/blob/main/examples/workflow/task_chaining.py)
+  - [Fan-out/Fan-in example](https://github.com/dapr/python-sdk/blob/main/examples/workflow/fan_out_fan_in.py)
+  - [Child workflow example](https://github.com/dapr/python-sdk/blob/main/examples/workflow/child_workflow.py)
+  - [Human approval example](https://github.com/dapr/python-sdk/blob/main/examples/workflow/human_approval.py)
+  - [Monitor example](https://github.com/dapr/python-sdk/blob/main/examples/workflow/monitor.py)
+
 
 
 ## Related links

daprdocs/content/en/python-sdk-docs/python-sdk-extensions/python-workflow-ext/_index.md

@@ -7,11 +7,7 @@ description: How to get up and running with the Dapr Workflow extension
 no_list: true
 ---
 
-{{% alert title="Note" color="primary" %}}
-Dapr Workflow is currently in alpha.
-{{% /alert %}}
-
-The Dapr Python SDK provides a built in Dapr Workflow extension, `dapr.ext.workflow`, for creating Dapr services.
+The Dapr Python SDK provides a built-in Dapr Workflow extension, `dapr.ext.workflow`, for creating Dapr services. The extension is currently in alpha.
 
 ## Installation