TLS support for workflows

examples/demo_workflow/app.py

@@ -32,11 +32,11 @@
 
 def hello_world_wf(ctx: DaprWorkflowContext, wf_input):
     print(f'{wf_input}')
-    yield ctx.call_activity(hello_act, wf_input=1)
-    yield ctx.call_activity(hello_act, wf_input=10)
+    yield ctx.call_activity(hello_act, input=1)
+    yield ctx.call_activity(hello_act, input=10)
     yield ctx.wait_for_external_event("event1")
-    yield ctx.call_activity(hello_act, wf_input=100)
-    yield ctx.call_activity(hello_act, wf_input=1000)
+    yield ctx.call_activity(hello_act, input=100)
+    yield ctx.call_activity(hello_act, input=1000)
 
 
 def hello_act(ctx: WorkflowActivityContext, wf_input):
@@ -47,9 +47,7 @@ def hello_act(ctx: WorkflowActivityContext, wf_input):
 
 def main():
     with DaprClient() as d:
-        host = settings.DAPR_RUNTIME_HOST
-        port = settings.DAPR_GRPC_PORT
-        workflow_runtime = WorkflowRuntime(host, port)
+        workflow_runtime = WorkflowRuntime()
         workflow_runtime.register_workflow(hello_world_wf)
         workflow_runtime.register_activity(hello_act)
         workflow_runtime.start()
@@ -107,8 +105,8 @@ def main():
         sleep(1)
         get_response = d.get_workflow(instance_id=instance_id,
                                       workflow_component=workflow_component)
-        print(
-            f"Get response from {workflow_name} after terminate call: {get_response.runtime_status}")
+        print(f"Get response from {workflow_name} "
+              f"after terminate call: {get_response.runtime_status}")
 
         # Purge Test
         d.purge_workflow(instance_id=instance_id, workflow_component=workflow_component)

examples/workflow/monitor.py

@@ -52,7 +52,7 @@ def send_alert(ctx, message: str):
 
 
 if __name__ == '__main__':
-    workflowRuntime = wf.WorkflowRuntime("localhost", "50001")
+    workflowRuntime = wf.WorkflowRuntime()
     workflowRuntime.register_workflow(status_monitor_workflow)
     workflowRuntime.register_activity(check_status)
     workflowRuntime.register_activity(send_alert)

ext/dapr-ext-workflow/dapr/ext/workflow/dapr_workflow_client.py

@@ -22,9 +22,11 @@
 from dapr.ext.workflow.workflow_state import WorkflowState
 from dapr.ext.workflow.workflow_context import Workflow
 from dapr.ext.workflow.util import getAddress
+
+from dapr.clients import DaprInternalError
 from dapr.clients.http.client import DAPR_API_TOKEN_HEADER
 from dapr.conf import settings
-
+from dapr.conf.helpers import GrpcEndpoint
 
 T = TypeVar('T')
 TInput = TypeVar('TInput')
@@ -40,16 +42,22 @@ class DaprWorkflowClient:
        This client is intended to be used by workflow application, not by general purpose
        application.
     """
+
     def __init__(self, host: Optional[str] = None, port: Optional[str] = None):
         address = getAddress(host, port)
+
+        try:
+            uri = GrpcEndpoint(address)
+        except ValueError as error:
+            raise DaprInternalError(f'{error}') from error
+
         metadata = tuple()
         if settings.DAPR_API_TOKEN:
             metadata = ((DAPR_API_TOKEN_HEADER, settings.DAPR_API_TOKEN),)
-        self.__obj = client.TaskHubGrpcClient(host_address=address, metadata=metadata)
+        self.__obj = client.TaskHubGrpcClient(host_address=uri.endpoint, metadata=metadata,
+                                              secure_channel=uri.tls)
 
-    def schedule_new_workflow(self,
-                              workflow: Workflow, *,
-                              input: Optional[TInput] = None,
+    def schedule_new_workflow(self, workflow: Workflow, *, input: Optional[TInput] = None,
                               instance_id: Optional[str] = None,
                               start_at: Optional[datetime] = None) -> str:
         """Schedules a new workflow instance for execution.
@@ -67,9 +75,8 @@ def schedule_new_workflow(self,
         Returns:
             The ID of the scheduled workflow instance.
         """
-        return self.__obj.schedule_new_orchestration(workflow.__name__,
-                                                     input=input, instance_id=instance_id,
-                                                     start_at=start_at)
+        return self.__obj.schedule_new_orchestration(workflow.__name__, input=input,
+                                                     instance_id=instance_id, start_at=start_at)
 
     def get_workflow_state(self, instance_id: str, *,
                            fetch_payloads: bool = True) -> Optional[WorkflowState]:
@@ -88,8 +95,7 @@ def get_workflow_state(self, instance_id: str, *,
         state = self.__obj.get_orchestration_state(instance_id, fetch_payloads=fetch_payloads)
         return WorkflowState(state) if state else None
 
-    def wait_for_workflow_start(self, instance_id: str, *,
-                                fetch_payloads: bool = False,
+    def wait_for_workflow_start(self, instance_id: str, *, fetch_payloads: bool = False,
                                 timeout_in_seconds: int = 60) -> Optional[WorkflowState]:
         """Waits for a workflow to start running and returns a WorkflowState object that contains
            metadata about the started workflow.
@@ -109,13 +115,11 @@ def wait_for_workflow_start(self, instance_id: str, *,
             WorkflowState record that describes the workflow instance and its execution status.
             If the specified workflow isn't found, the WorkflowState.Exists value will be false.
         """
-        state = self.__obj.wait_for_orchestration_start(instance_id,
-                                                        fetch_payloads=fetch_payloads,
+        state = self.__obj.wait_for_orchestration_start(instance_id, fetch_payloads=fetch_payloads,
                                                         timeout=timeout_in_seconds)
         return WorkflowState(state) if state else None
 
-    def wait_for_workflow_completion(self, instance_id: str, *,
-                                     fetch_payloads: bool = True,
+    def wait_for_workflow_completion(self, instance_id: str, *, fetch_payloads: bool = True,
                                      timeout_in_seconds: int = 60) -> Optional[WorkflowState]:
         """Waits for a workflow to complete and returns a WorkflowState object that contains
            metadata about the started instance.
@@ -172,8 +176,7 @@ def raise_workflow_event(self, instance_id: str, event_name: str, *,
         """
         return self.__obj.raise_orchestration_event(instance_id, event_name, data=data)
 
-    def terminate_workflow(self, instance_id: str, *,
-                           output: Optional[Any] = None):
+    def terminate_workflow(self, instance_id: str, *, output: Optional[Any] = None):
         """Terminates a running workflow instance and updates its runtime status to
            WorkflowRuntimeStatus.Terminated This method internally enqueues a "terminate" message in
            the task hub. When the task hub worker processes this message, it will update the runtime

ext/dapr-ext-workflow/dapr/ext/workflow/workflow_runtime.py

@@ -21,8 +21,11 @@
 from dapr.ext.workflow.dapr_workflow_context import DaprWorkflowContext
 from dapr.ext.workflow.workflow_activity_context import Activity, WorkflowActivityContext
 from dapr.ext.workflow.util import getAddress
+
+from dapr.clients import DaprInternalError
 from dapr.clients.http.client import DAPR_API_TOKEN_HEADER
 from dapr.conf import settings
+from dapr.conf.helpers import GrpcEndpoint
 
 T = TypeVar('T')
 TInput = TypeVar('TInput')
@@ -39,7 +42,13 @@ def __init__(self, host: Optional[str] = None, port: Optional[str] = None):
             metadata = ((DAPR_API_TOKEN_HEADER, settings.DAPR_API_TOKEN),)
         address = getAddress(host, port)
 
-        self.__worker = worker.TaskHubGrpcWorker(host_address=address, metadata=metadata)
+        try:
+            uri = GrpcEndpoint(address)
+        except ValueError as error:
+            raise DaprInternalError(f'{error}') from error
+
+        self.__worker = worker.TaskHubGrpcWorker(host_address=uri.endpoint, metadata=metadata,
+                                                 secure_channel=uri.tls)
 
     def register_workflow(self, fn: Workflow):
         def orchestrationWrapper(ctx: task.OrchestrationContext, inp: Optional[TInput] = None):