added custom metric sample

.gitignore

@@ -1,3 +1,5 @@
 .venv
 .idea
 __pycache__
+.vscode
+.DS_Store

README.md

@@ -61,6 +61,7 @@ Some examples require extra dependencies. See each sample's directory for specif
 * [context_propagation](context_propagation) - Context propagation through workflows/activities via interceptor.
 * [custom_converter](custom_converter) - Use a custom payload converter to handle custom types.
 * [custom_decorator](custom_decorator) - Custom decorator to auto-heartbeat a long-running activity.
+* [custom_metric](custom_metric) - Custom metric to record the workflow type in the activity schedule to start latency.
 * [dsl](dsl) - DSL workflow that executes steps defined in a YAML file.
 * [encryption](encryption) - Apply end-to-end encryption for all input/output.
 * [gevent_async](gevent_async) - Combine gevent and Temporal.

custom_metric/README.md

@@ -0,0 +1,36 @@
+# Custom Metric
+
+This sample deminstrates two things: (1) how to make a custom metric, and (2) how to use an interceptor.
+The custom metric in this sample is an activity schedule-to-start-latency with a workflow type tag.
+
+Please see the top-level README for prerequisites such as Python, uv, starting the local temporal development server, etc.
+
+1. Run the worker with `uv run custom_metric/worker.py`
+2. Request execution of the workflow with `temporal workflow start --type ExecuteActivityWorkflow --task-queue custom-metric-task-queue`
+3. Go to `http://127.0.0.1:9090/metrics` in your browser
+
+You'll get something like the following:
+
+```txt
+custom_activity_schedule_to_start_latency_bucket{activity_type="print_message",namespace="default",service_name="temporal-core-sdk",task_queue="custom-metric-task-queue",workflow_type="ExecuteActivityWorkflow",le="100"} 1
+custom_activity_schedule_to_start_latency_bucket{activity_type="print_message",namespace="default",service_name="temporal-core-sdk",task_queue="custom-metric-task-queue",workflow_type="ExecuteActivityWorkflow",le="500"} 1
+custom_activity_schedule_to_start_latency_bucket{activity_type="print_message",namespace="default",service_name="temporal-core-sdk",task_queue="custom-metric-task-queue",workflow_type="ExecuteActivityWorkflow",le="1000"} 1
+custom_activity_schedule_to_start_latency_bucket{activity_type="print_message",namespace="default",service_name="temporal-core-sdk",task_queue="custom-metric-task-queue",workflow_type="ExecuteActivityWorkflow",le="5000"} 2
+custom_activity_schedule_to_start_latency_bucket{activity_type="print_message",namespace="default",service_name="temporal-core-sdk",task_queue="custom-metric-task-queue",workflow_type="ExecuteActivityWorkflow",le="10000"} 2
+custom_activity_schedule_to_start_latency_bucket{activity_type="print_message",namespace="default",service_name="temporal-core-sdk",task_queue="custom-metric-task-queue",workflow_type="ExecuteActivityWorkflow",le="100000"} 2
+custom_activity_schedule_to_start_latency_bucket{activity_type="print_message",namespace="default",service_name="temporal-core-sdk",task_queue="custom-metric-task-queue",workflow_type="ExecuteActivityWorkflow",le="1000000"} 2
+custom_activity_schedule_to_start_latency_bucket{activity_type="print_message",namespace="default",service_name="temporal-core-sdk",task_queue="custom-metric-task-queue",workflow_type="ExecuteActivityWorkflow",le="+Inf"} 2
+custom_activity_schedule_to_start_latency_sum{activity_type="print_message",namespace="default",service_name="temporal-core-sdk",task_queue="custom-metric-task-queue",workflow_type="ExecuteActivityWorkflow"} 1010
+custom_activity_schedule_to_start_latency_count{activity_type="print_message",namespace="default",service_name="temporal-core-sdk",task_queue="custom-metric-task-queue",workflow_type="ExecuteActivityWorkflow"} 2
+...
+temporal_activity_schedule_to_start_latency_bucket{namespace="default",service_name="temporal-core-sdk",task_queue="custom-metric-task-queue",le="100"} 1
+temporal_activity_schedule_to_start_latency_bucket{namespace="default",service_name="temporal-core-sdk",task_queue="custom-metric-task-queue",le="500"} 1
+temporal_activity_schedule_to_start_latency_bucket{namespace="default",service_name="temporal-core-sdk",task_queue="custom-metric-task-queue",le="1000"} 1
+temporal_activity_schedule_to_start_latency_bucket{namespace="default",service_name="temporal-core-sdk",task_queue="custom-metric-task-queue",le="5000"} 2
+temporal_activity_schedule_to_start_latency_bucket{namespace="default",service_name="temporal-core-sdk",task_queue="custom-metric-task-queue",le="10000"} 2
+temporal_activity_schedule_to_start_latency_bucket{namespace="default",service_name="temporal-core-sdk",task_queue="custom-metric-task-queue",le="100000"} 2
+temporal_activity_schedule_to_start_latency_bucket{namespace="default",service_name="temporal-core-sdk",task_queue="custom-metric-task-queue",le="1000000"} 2
+temporal_activity_schedule_to_start_latency_bucket{namespace="default",service_name="temporal-core-sdk",task_queue="custom-metric-task-queue",le="+Inf"} 2
+temporal_activity_schedule_to_start_latency_sum{namespace="default",service_name="temporal-core-sdk",task_queue="custom-metric-task-queue"} 1010
+temporal_activity_schedule_to_start_latency_count{namespace="default",service_name="temporal-core-sdk",task_queue="custom-metric-task-queue"} 2
+```

custom_metric/worker.py

@@ -0,0 +1,97 @@
+import asyncio
+import time
+from concurrent.futures import ThreadPoolExecutor
+from datetime import timedelta
+
+from temporalio import activity, workflow
+from temporalio.client import Client
+from temporalio.runtime import PrometheusConfig, Runtime, TelemetryConfig
+from temporalio.worker import (
+    ActivityInboundInterceptor,
+    ExecuteActivityInput,
+    Interceptor,
+    Worker,
+)
+
+
+@activity.defn
+def print_message():
+    print("In the activity.")
+    time.sleep(1)
+
+
+@workflow.defn
+class ExecuteActivityWorkflow:
+
+    @workflow.run
+    async def run(self):
+        # Request two concurrent activities with only one task slot so
+        # we can see nontrivial schedule to start times.
+        activity1 = workflow.execute_activity(
+            print_message,
+            start_to_close_timeout=timedelta(seconds=5),
+        )
+        activity2 = workflow.execute_activity(
+            print_message,
+            start_to_close_timeout=timedelta(seconds=5),
+        )
+        await asyncio.gather(activity1, activity2)
+        return None
+
+
+class SimpleWorkerInterceptor(Interceptor):
+
+    def intercept_activity(
+        self, next: ActivityInboundInterceptor
+    ) -> ActivityInboundInterceptor:
+        return CustomScheduleToStartInterceptor(next)
+
+
+class CustomScheduleToStartInterceptor(ActivityInboundInterceptor):
+
+    async def execute_activity(self, input: ExecuteActivityInput):
+
+        schedule_to_start = (
+            activity.info().started_time
+            - activity.info().current_attempt_scheduled_time
+        )
+        # Could do the original schedule time instead of current attempt
+        # schedule_to_start_second_option = activity.info().started_time - activity.info().scheduled_time
+
+        meter = activity.metric_meter()
+        histogram = meter.create_histogram_timedelta(
+            "custom_activity_schedule_to_start_latency",
+            description="Time between activity scheduling and start",
+            unit="duration",
+        )
+        histogram.record(
+            schedule_to_start, {"workflow_type": activity.info().workflow_type}
+        )
+        return await self.next.execute_activity(input)
+
+
+async def main():
+    runtime = Runtime(
+        telemetry=TelemetryConfig(metrics=PrometheusConfig(bind_address="0.0.0.0:9090"))
+    )
+    client = await Client.connect(
+        "localhost:7233",
+        runtime=runtime,
+    )
+    worker = Worker(
+        client,
+        task_queue="custom-metric-task-queue",
+        interceptors=[SimpleWorkerInterceptor()],
+        workflows=[ExecuteActivityWorkflow],
+        activities=[print_message],
+        # only one activity executor with two concurrently scheduled activities
+        # to force a nontrivial schedule to start times
+        activity_executor=ThreadPoolExecutor(1),
+        max_concurrent_activities=1,
+    )
+
+    await worker.run()
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

tests/custom_metric/workflow_test.py

@@ -0,0 +1,35 @@
+import uuid
+
+from temporalio import activity
+from temporalio.testing import WorkflowEnvironment
+from temporalio.worker import Worker
+
+from custom_metric.worker import ExecuteActivityWorkflow
+
+_TASK_QUEUE = "custom-metric-task-queue"
+
+activity_counter = 0
+
+
+async def test_sleep_for_days_workflow():
+
+    @activity.defn(name="print_message")
+    async def print_message_mock():
+        global activity_counter
+        activity_counter += 1
+
+    async with await WorkflowEnvironment.start_time_skipping() as env:
+
+        async with Worker(
+            env.client,
+            task_queue=_TASK_QUEUE,
+            workflows=[ExecuteActivityWorkflow],
+            activities=[print_message_mock],
+        ):
+            result = await env.client.execute_workflow(
+                ExecuteActivityWorkflow.run,
+                id=str(uuid.uuid4()),
+                task_queue=_TASK_QUEUE,
+            )
+            assert result is None
+            assert activity_counter == 2