mirror of https://github.com/dapr/docs.git
remove python examples until ready
Signed-off-by: Hannah Hunter <hannahhunter@microsoft.com>
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@ -28,7 +28,7 @@ The Dapr sidecar doesn’t load any workflow definitions. Rather, the sidecar si
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## Write the workflow activities
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Define the workflow activities you'd like your workflow to perform. Activities are a class definition and can take inputs and outputs. Activities also participate in dependency injection, like binding to a Dapr client.
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Define the workflow activities you’d like your workflow to perform. Activities are a class definition and can take inputs and outputs. Activities also participate in dependency injection, like binding to a Dapr client.
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{{< tabs ".NET" Python >}}
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@ -87,55 +87,7 @@ It also includes a `RunAsync` method that does the heavy lifting of the workflow
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- HTTP API calls to start, pause, resume, terminate, and purge the workflow.
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```python
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from dapr.clients import DaprClient
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from dapr.clients.grpc._helpers import to_bytes
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# ...
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# Dapr Workflows are registered as part of the service configuration
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with DaprClient() as d:
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instanceId = "RRLINSTANCEID35"
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workflowComponent = "dapr"
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workflowName = "PlaceOrder"
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workflowOptions = dict()
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workflowOptions["task_queue"] = "testQueue"
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inventoryItem = ("Computers", 5, 10)
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item2 = "paperclips"
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encoded_data = b''.join(bytes(str(element), 'UTF-8') for element in item2)
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encoded_data2 = json.dumps(item2).encode("UTF-8")
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# ...
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# Start the workflow
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start_resp = d.start_workflow(instance_id=instanceId, workflow_component=workflowComponent,
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workflow_name=workflowName, input=encoded_data2, workflow_options=workflowOptions)
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print(f"Attempting to start {workflowName}")
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print(f"start_resp {start_resp.instance_id}")
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# Get workflow status
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getResponse = d.get_workflow(instance_id=instanceId, workflow_component=workflowComponent)
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print(f"Get response from {workflowName} after start call: {getResponse.runtime_status}")
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# Pause Test
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d.pause_workflow(instance_id=instanceId, workflow_component=workflowComponent)
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getResponse = d.get_workflow(instance_id=instanceId, workflow_component=workflowComponent)
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print(f"Get response from {workflowName} after pause call: {getResponse.runtime_status}")
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# Resume Test
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d.resume_workflow(instance_id=instanceId, workflow_component=workflowComponent)
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getResponse = d.get_workflow(instance_id=instanceId, workflow_component=workflowComponent)
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print(f"Get response from {workflowName} after resume call: {getResponse.runtime_status}")
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# Terminate Test
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d.terminate_workflow(instance_id=instanceId, workflow_component=workflowComponent)
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getResponse = d.get_workflow(instance_id=instanceId, workflow_component=workflowComponent)
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print(f"Get response from {workflowName} after terminate call: {getResponse.runtime_status}")
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# Purge Test
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d.purge_workflow(instance_id=instanceId, workflow_component=workflowComponent)
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getResponse = d.get_workflow(instance_id=instanceId, workflow_component=workflowComponent)
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print(f"Get response from {workflowName} after purge call: {getResponse}")
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todo
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```
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@ -232,34 +184,7 @@ app.Run();
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- HTTP API calls to start, pause, resume, terminate, and purge the workflow.
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```python
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from dapr.clients import DaprClient
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from dapr.clients.grpc._helpers import to_bytes
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# ...
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# Dapr Workflows are registered as part of the service configuration
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with DaprClient() as d:
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instanceId = "RRLINSTANCEID35"
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workflowComponent = "dapr"
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workflowName = "PlaceOrder"
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workflowOptions = dict()
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workflowOptions["task_queue"] = "testQueue"
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inventoryItem = ("Computers", 5, 10)
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item2 = "paperclips"
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encoded_data = b''.join(bytes(str(element), 'UTF-8') for element in item2)
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encoded_data2 = json.dumps(item2).encode("UTF-8")
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# ...
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# Start the workflow
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start_resp = d.start_workflow(instance_id=instanceId, workflow_component=workflowComponent,
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workflow_name=workflowName, input=encoded_data2, workflow_options=workflowOptions)
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print(f"Attempting to start {workflowName}")
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print(f"start_resp {start_resp.instance_id}")
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# Get workflow status
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getResponse = d.get_workflow(instance_id=instanceId, workflow_component=workflowComponent)
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print(f"Get response from {workflowName} after start call: {getResponse.runtime_status}")
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todo
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```
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