Moving durabletask tests into specific dir and more

Signed-off-by: Ryan Lettieri <[email protected]>

Author: RyanLettieri

.github/workflows/pr-validation.yml

@@ -34,6 +34,7 @@ jobs:
       run: |
         flake8 . --count --show-source --statistics --exit-zero
     - name: Pytest unit tests
+      working-directory: examples/durabletask-azuremanaged
       run: |
         pytest -m "not e2e" --verbose
 
@@ -45,6 +46,7 @@ jobs:
 
     # Install and run the durabletask-go sidecar for running e2e tests
     - name: Pytest e2e tests
+      working-directory: examples/durabletask-azuremanaged
       run: |
         go install github.com/microsoft/durabletask-go@main
         durabletask-go --port 4001 &

.github/workflows/publish-dts-sdk.yml

@@ -1,9 +1,16 @@
 name: Publish Durable Task Scheduler to PyPI
 
+# on:
+#   push:
+#     tags:
+#       - 'azuremanaged-v*'  # Only run for tags starting with "azuremanaged-v"
+
 on:
   push:
-    tags:
-      - 'azuremanaged-v*'  # Only run for tags starting with "azuremanaged-v"
+    branches: [ "main" ]
+  pull_request:
+    branches: [ "main" ]
+
 
 jobs:
   lint:
@@ -47,9 +54,15 @@ jobs:
           echo "TASKHUB=default" >> $GITHUB_ENV
           echo "ENDPOINT=http://localhost:8080" >> $GITHUB_ENV
 
+      - name: Install dependencies
+        working-directory: examples/durabletask-azuremanaged
+        run: |
+          python -m pip install --upgrade pip
+          pip install -r requirements.txt
+
       - name: Run the tests
-        working-directory: durabletask-azuremanaged
-        run: python -m dts_activity_sequence
+        working-directory: tests/durabletask-azuremanaged
+        run: python -m test_activity_sequence
 
 
   publish:

tests/__init__.py renamed to tests/durabletask-azuremanaged/__init__.py

@@ -0,0 +1,69 @@
+"""End-to-end sample that demonstrates how to configure an orchestrator
+that calls an activity function in a sequence and prints the outputs."""
+import os
+
+from durabletask import client, task
+from durabletask.azuremanaged.client import DurableTaskSchedulerClient
+from durabletask.azuremanaged.worker import DurableTaskSchedulerWorker
+
+import pytest
+
+
+pytestmark = pytest.mark.dts
+
+def hello(ctx: task.ActivityContext, name: str) -> str:
+    """Activity function that returns a greeting"""
+    return f'Hello {name}!'
+
+
+def sequence(ctx: task.OrchestrationContext, _):
+    """Orchestrator function that calls the 'hello' activity function in a sequence"""
+    # call "hello" activity function in a sequence
+    result1 = yield ctx.call_activity(hello, input='Tokyo')
+    result2 = yield ctx.call_activity(hello, input='Seattle')
+    result3 = yield ctx.call_activity(hello, input='London')
+
+    # return an array of results
+    return [result1, result2, result3]
+
+
+# Read the environment variable
+taskhub_name = os.getenv("TASKHUB")
+
+# Check if the variable exists
+if taskhub_name:
+    print(f"The value of TASKHUB is: {taskhub_name}")
+else:
+    print("TASKHUB is not set. Please set the TASKHUB environment variable to the name of the taskhub you wish to use")
+    print("If you are using windows powershell, run the following: $env:TASKHUB=\"<taskhubname>\"")
+    print("If you are using bash, run the following: export TASKHUB=\"<taskhubname>\"")
+    exit()
+
+# Read the environment variable
+endpoint = os.getenv("ENDPOINT")
+
+# Check if the variable exists
+if endpoint:
+    print(f"The value of ENDPOINT is: {endpoint}")
+else:
+    print("ENDPOINT is not set. Please set the ENDPOINT environment variable to the endpoint of the scheduler")
+    print("If you are using windows powershell, run the following: $env:ENDPOINT=\"<schedulerEndpoint>\"")
+    print("If you are using bash, run the following: export ENDPOINT=\"<schedulerEndpoint>\"")
+    exit()
+
+# configure and start the worker
+with DurableTaskSchedulerWorker(host_address=endpoint, secure_channel=True,
+                                taskhub=taskhub_name, token_credential=None) as w:
+    w.add_orchestrator(sequence)
+    w.add_activity(hello)
+    w.start()
+
+    # Construct the client and run the orchestrations
+    c = DurableTaskSchedulerClient(host_address=endpoint, secure_channel=True,
+                                   taskhub=taskhub_name, token_credential=None)
+    instance_id = c.schedule_new_orchestration(sequence)
+    state = c.wait_for_orchestration_completion(instance_id, timeout=60)
+    if state and state.runtime_status == client.OrchestrationStatus.COMPLETED:
+        print(f'Orchestration completed! Result: {state.serialized_output}')
+    elif state:
+        print(f'Orchestration failed: {state.failure_details}')