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remove python examples until ready 

Signed-off-by: Hannah Hunter <hannahhunter@microsoft.com>
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Hannah Hunter 2023-05-09 10:05:04 -04:00
parent 7b1d40641a
commit d85b49abb7
1 changed files with 3 additions and 78 deletions
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daprdocs/content/en/developing-applications/building-blocks/workflow/howto-author-workflow.md
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@ -28,7 +28,7 @@ The Dapr sidecar doesn’t load any workflow definitions. Rather, the sidecar si
## Write the workflow activities ## Write the workflow activities
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. 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.
{{< tabs ".NET" Python >}} {{< tabs ".NET" Python >}}
@ -87,55 +87,7 @@ It also includes a `RunAsync` method that does the heavy lifting of the workflow
- HTTP API calls to start, pause, resume, terminate, and purge the workflow. - HTTP API calls to start, pause, resume, terminate, and purge the workflow.
```python ```python
from dapr.clients import DaprClient todo
from dapr.clients.grpc._helpers import to_bytes
# ...
# Dapr Workflows are registered as part of the service configuration
with DaprClient() as d:
instanceId = "RRLINSTANCEID35"
workflowComponent = "dapr"
workflowName = "PlaceOrder"
workflowOptions = dict()
workflowOptions["task_queue"] = "testQueue"
inventoryItem = ("Computers", 5, 10)
item2 = "paperclips"
encoded_data = b''.join(bytes(str(element), 'UTF-8') for element in item2)
encoded_data2 = json.dumps(item2).encode("UTF-8")
# ...
# Start the workflow
start_resp = d.start_workflow(instance_id=instanceId, workflow_component=workflowComponent,
workflow_name=workflowName, input=encoded_data2, workflow_options=workflowOptions)
print(f"Attempting to start {workflowName}")
print(f"start_resp {start_resp.instance_id}")
# Get workflow status
getResponse = d.get_workflow(instance_id=instanceId, workflow_component=workflowComponent)
print(f"Get response from {workflowName} after start call: {getResponse.runtime_status}")
# 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}")
# Terminate Test
d.terminate_workflow(instance_id=instanceId, workflow_component=workflowComponent)
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)
getResponse = d.get_workflow(instance_id=instanceId, workflow_component=workflowComponent)
print(f"Get response from {workflowName} after purge call: {getResponse}")
``` ```
@ -232,34 +184,7 @@ app.Run();
- HTTP API calls to start, pause, resume, terminate, and purge the workflow. - HTTP API calls to start, pause, resume, terminate, and purge the workflow.
```python ```python
from dapr.clients import DaprClient todo
from dapr.clients.grpc._helpers import to_bytes
# ...
# Dapr Workflows are registered as part of the service configuration
with DaprClient() as d:
instanceId = "RRLINSTANCEID35"
workflowComponent = "dapr"
workflowName = "PlaceOrder"
workflowOptions = dict()
workflowOptions["task_queue"] = "testQueue"
inventoryItem = ("Computers", 5, 10)
item2 = "paperclips"
encoded_data = b''.join(bytes(str(element), 'UTF-8') for element in item2)
encoded_data2 = json.dumps(item2).encode("UTF-8")
# ...
# Start the workflow
start_resp = d.start_workflow(instance_id=instanceId, workflow_component=workflowComponent,
workflow_name=workflowName, input=encoded_data2, workflow_options=workflowOptions)
print(f"Attempting to start {workflowName}")
print(f"start_resp {start_resp.instance_id}")
# Get workflow status
getResponse = d.get_workflow(instance_id=instanceId, workflow_component=workflowComponent)
print(f"Get response from {workflowName} after start call: {getResponse.runtime_status}")
``` ```