diff --git a/.github/CODEOWNERS b/.github/CODEOWNERS new file mode 100644 index 00000000..0f4298b7 --- /dev/null +++ b/.github/CODEOWNERS @@ -0,0 +1 @@ +* @temporalio/sdk diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index c32f9da1..bfb1353e 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -12,22 +12,16 @@ jobs: strategy: fail-fast: true matrix: - python: ["3.8", "3.12"] + python: ["3.9", "3.12"] os: [ubuntu-latest, macos-intel, macos-arm, windows-latest] include: - os: macos-intel - runsOn: macos-12 + runsOn: macos-13 - os: macos-arm runsOn: macos-14 - # macOS ARM 3.8 does not have an available Python build at - # https://raw.githubusercontent.com/actions/python-versions/main/versions-manifest.json. - # See https://github.com/actions/setup-python/issues/808 and - # https://github.com/actions/python-versions/pull/259. - exclude: - - os: macos-arm - python: "3.8" runs-on: ${{ matrix.runsOn || matrix.os }} steps: + - uses: astral-sh/setup-uv@v5 - name: Print build information run: "echo head_ref: ${{ github.head_ref }}, ref: ${{ github.ref }}, os: ${{ matrix.os }}, python: ${{ matrix.python }}" - uses: actions/checkout@v4 @@ -36,21 +30,27 @@ jobs: - uses: actions/setup-python@v5 with: python-version: ${{ matrix.python }} - # Using fixed Poetry version until - # https://github.com/python-poetry/poetry/pull/7694 is fixed - - run: python -m pip install --upgrade wheel "poetry==1.4.0" poethepoet - - run: poetry install --with pydantic --with dsl --with encryption + - run: uv tool install poethepoet + - run: uv sync --group=dsl --group=encryption --group=trio-async - run: poe lint - run: mkdir junit-xml - - run: poe test -s -o log_cli_level=DEBUG --junit-xml=junit-xml/${{ matrix.python }}--${{ matrix.os }}.xml - - run: poe test -s -o log_cli_level=DEBUG --workflow-environment time-skipping --junit-xml=junit-xml/${{ matrix.python }}--${{ matrix.os }}--time-skipping.xml + - run: poe test -s --junit-xml=junit-xml/${{ matrix.python }}--${{ matrix.os }}.xml + - run: poe test -s --workflow-environment time-skipping --junit-xml=junit-xml/${{ matrix.python }}--${{ matrix.os }}--time-skipping.xml + # This must remain the last step since it downgrades pydantic + - name: Uninstall pydantic + shell: bash + run: | + echo y | uv run pip uninstall pydantic + echo y | uv run pip uninstall pydantic-core + uv run pip install pydantic==1.10 + poe test -s --junit-xml=junit-xml/${{ matrix.python }}--${{ matrix.os }}--pydantic-v1.xml tests/pydantic_converter_v1/workflow_test.py # On latest, run gevent test - name: Gevent test if: ${{ matrix.python == '3.12' }} run: | - poetry install --with gevent - poetry run python gevent_async/test/run_combined.py + uv sync --group gevent + uv run gevent_async/test/run_combined.py - name: Upload junit-xml artifacts uses: actions/upload-artifact@v4 diff --git a/.gitignore b/.gitignore index 033df5fb..41afe5f8 100644 --- a/.gitignore +++ b/.gitignore @@ -1,2 +1,5 @@ .venv +.idea __pycache__ +.vscode +.DS_Store diff --git a/README.md b/README.md index 5cffefce..8bd9986a 100644 --- a/README.md +++ b/README.md @@ -1,23 +1,26 @@ # Temporal Python SDK Samples -This is the set of Python samples for the [Python SDK](https://github.com/temporalio/sdk-python). +This is a collection of samples showing how to use the [Python SDK](https://github.com/temporalio/sdk-python). ## Usage Prerequisites: -* Python >= 3.8 -* [Poetry](https://python-poetry.org) +* [uv](https://docs.astral.sh/uv/) * [Temporal CLI installed](https://docs.temporal.io/cli#install) * [Local Temporal server running](https://docs.temporal.io/cli/server#start-dev) +The SDK requires Python >= 3.9. You can install Python using uv. For example, + + uv python install 3.13 + With this repository cloned, run the following at the root of the directory: - poetry install + uv sync -That loads all required dependencies. Then to run a sample, usually you just run it in Python. For example: +That loads all required dependencies. Then to run a sample, usually you just run it under uv. For example: - poetry run python hello/hello_activity.py + uv run hello/hello_activity.py Some examples require extra dependencies. See each sample's directory for specific instructions. @@ -38,6 +41,7 @@ Some examples require extra dependencies. See each sample's directory for specif * [hello_async_activity_completion](hello/hello_async_activity_completion.py) - Complete an activity outside of the function that was called. * [hello_cancellation](hello/hello_cancellation.py) - Manually react to cancellation inside workflows and activities. + * [hello_change_log_level](hello/hello_change_log_level.py) - Change the level of workflow task failure from WARN to ERROR. * [hello_child_workflow](hello/hello_child_workflow.py) - Execute a child workflow from a workflow. * [hello_continue_as_new](hello/hello_continue_as_new.py) - Use continue as new to restart a workflow. * [hello_cron](hello/hello_cron.py) - Execute a workflow once a minute. @@ -58,19 +62,23 @@ 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. * [langchain](langchain) - Orchestrate workflows for LangChain. -* [message-passing introduction](message_passing/introduction/) - Introduction to queries, signals, and updates. +* [message_passing/introduction](message_passing/introduction/) - Introduction to queries, signals, and updates. +* [message_passing/safe_message_handlers](message_passing/safe_message_handlers/) - Safely handling updates and signals. +* [message_passing/update_with_start/lazy_initialization](message_passing/update_with_start/lazy_initialization/) - Use update-with-start to update a Shopping Cart, starting it if it does not exist. * [open_telemetry](open_telemetry) - Trace workflows with OpenTelemetry. * [patching](patching) - Alter workflows safely with `patch` and `deprecate_patch`. * [polling](polling) - Recommended implementation of an activity that needs to periodically poll an external resource waiting its successful completion. * [prometheus](prometheus) - Configure Prometheus metrics on clients/workers. * [pydantic_converter](pydantic_converter) - Data converter for using Pydantic models. -* [safe_message_handlers](message_passing/safe_message_handlers/) - Safely handling updates and signals. * [schedules](schedules) - Demonstrates a Workflow Execution that occurs according to a schedule. * [sentry](sentry) - Report errors to Sentry. +* [trio_async](trio_async) - Use asyncio Temporal in Trio-based environments. +* [updatable_timer](updatable_timer) - A timer that can be updated while sleeping. * [worker_specific_task_queues](worker_specific_task_queues) - Use unique task queues to ensure activities run on specific workers. * [worker_versioning](worker_versioning) - Use the Worker Versioning feature to more easily version your workflows & other code. @@ -78,7 +86,7 @@ Some examples require extra dependencies. See each sample's directory for specif Running the tests requires `poe` to be installed. - python -m pip install poethepoet + uv tool install poethepoet Once you have `poe` installed you can run: diff --git a/activity_worker/README.md b/activity_worker/README.md index 8b821281..0d904313 100644 --- a/activity_worker/README.md +++ b/activity_worker/README.md @@ -8,6 +8,6 @@ First run the Go workflow worker by running this in the `go_workflow` directory Then in another terminal, run the sample from this directory: - poetry run python activity_worker.py + uv run activity_worker.py The Python code will invoke the Go workflow which will execute the Python activity and return. \ No newline at end of file diff --git a/bedrock/README.md b/bedrock/README.md index b91fa5e5..42a1f4d5 100644 --- a/bedrock/README.md +++ b/bedrock/README.md @@ -20,6 +20,6 @@ These examples use Amazon's Python SDK (Boto3). To configure Boto3 to use your A For these sample, the optional `bedrock` dependency group must be included. To include, run: - poetry install --with bedrock + uv sync --group bedrock There are 3 Bedrock samples, see the README.md in each sub-directory for instructions on running each. \ No newline at end of file diff --git a/bedrock/basic/README.md b/bedrock/basic/README.md index 22a40cdd..88cae861 100644 --- a/bedrock/basic/README.md +++ b/bedrock/basic/README.md @@ -4,7 +4,7 @@ A basic Bedrock workflow. Starts a workflow with a prompt, generates a response To run, first see `samples-python` [README.md](../../README.md), and `bedrock` [README.md](../README.md) for prerequisites specific to this sample. Once set up, run the following from this directory: -1. Run the worker: `poetry run python run_worker.py` +1. Run the worker: `uv run run_worker.py` 2. In another terminal run the client with a prompt: - e.g. `poetry run python send_message.py 'What animals are marsupials?'` \ No newline at end of file + e.g. `uv run send_message.py 'What animals are marsupials?'` \ No newline at end of file diff --git a/bedrock/entity/README.md b/bedrock/entity/README.md index e6104945..5f53840d 100644 --- a/bedrock/entity/README.md +++ b/bedrock/entity/README.md @@ -4,16 +4,16 @@ Multi-Turn Chat using an Entity Workflow. The workflow runs forever unless expli To run, first see `samples-python` [README.md](../../README.md), and `bedrock` [README.md](../README.md) for prerequisites specific to this sample. Once set up, run the following from this directory: -1. Run the worker: `poetry run python run_worker.py` +1. Run the worker: `uv run run_worker.py` 2. In another terminal run the client with a prompt. - Example: `poetry run python send_message.py 'What animals are marsupials?'` + Example: `uv run send_message.py 'What animals are marsupials?'` 3. View the worker's output for the response. 4. Give followup prompts by signaling the workflow. - Example: `poetry run python send_message.py 'Do they lay eggs?'` + Example: `uv run send_message.py 'Do they lay eggs?'` 5. Get the conversation history summary by querying the workflow. - Example: `poetry run python get_history.py` -6. To end the chat session, run `poetry run python end_chat.py` + Example: `uv run get_history.py` +6. To end the chat session, run `uv run end_chat.py` diff --git a/bedrock/signals_and_queries/README.md b/bedrock/signals_and_queries/README.md index 877dedc0..edbca795 100644 --- a/bedrock/signals_and_queries/README.md +++ b/bedrock/signals_and_queries/README.md @@ -4,16 +4,16 @@ Adding signals & queries to the [basic Bedrock sample](../1_basic). Starts a wor To run, first see `samples-python` [README.md](../../README.md), and `bedrock` [README.md](../README.md) for prerequisites specific to this sample. Once set up, run the following from this directory: -1. Run the worker: `poetry run python run_worker.py` +1. Run the worker: `uv run run_worker.py` 2. In another terminal run the client with a prompt. - Example: `poetry run python send_message.py 'What animals are marsupials?'` + Example: `uv run send_message.py 'What animals are marsupials?'` 3. View the worker's output for the response. 4. Give followup prompts by signaling the workflow. - Example: `poetry run python send_message.py 'Do they lay eggs?'` + Example: `uv run send_message.py 'Do they lay eggs?'` 5. Get the conversation history by querying the workflow. - Example: `poetry run python get_history.py` + Example: `uv run get_history.py` 6. The workflow will timeout after inactivity. diff --git a/cloud_export_to_parquet/README.md b/cloud_export_to_parquet/README.md index 873e69b9..fe6b3db9 100644 --- a/cloud_export_to_parquet/README.md +++ b/cloud_export_to_parquet/README.md @@ -4,20 +4,20 @@ This is an example workflow to convert exported file from proto to parquet file. Please make sure your python is 3.9 above. For this sample, run: - poetry install --with cloud_export_to_parquet + uv sync --group=cloud-export-to-parquet Before you start, please modify workflow input in `create_schedule.py` with your s3 bucket and namespace. Also make sure you've the right AWS permission set up in your environment to allow this workflow read and write to your s3 bucket. To run, first see [README.md](../README.md) for prerequisites. Then, run the following from this directory to start the worker: ```bash -poetry run python run_worker.py +uv run run_worker.py ``` This will start the worker. Then, in another terminal, run the following to execute the schedule: ```bash -poetry run python create_schedule.py +uv run create_schedule.py ``` The workflow should convert exported file in your input s3 bucket to parquet in your specified location. diff --git a/context_propagation/README.md b/context_propagation/README.md index bbf47ac0..e1027292 100644 --- a/context_propagation/README.md +++ b/context_propagation/README.md @@ -6,11 +6,11 @@ this example, [contextvars](https://docs.python.org/3/library/contextvars.html) To run, first see [README.md](../README.md) for prerequisites. Then, run the following from this directory to start the worker: - poetry run python worker.py + uv run worker.py This will start the worker. Then, in another terminal, run the following to execute the workflow: - poetry run python starter.py + uv run starter.py The starter terminal should complete with the hello result and the worker terminal should show the logs with the propagated user ID contextual information flowing through the workflows/activities. \ No newline at end of file diff --git a/custom_converter/README.md b/custom_converter/README.md index d4c9f588..8e82e483 100644 --- a/custom_converter/README.md +++ b/custom_converter/README.md @@ -5,11 +5,11 @@ This sample shows how to make a custom payload converter for a type not natively To run, first see [README.md](../README.md) for prerequisites. Then, run the following from this directory to start the worker: - poetry run python worker.py + uv run worker.py This will start the worker. Then, in another terminal, run the following to execute the workflow: - poetry run python starter.py + uv run starter.py The workflow should complete with the hello result. If the custom converter was not set for the custom input and output classes, we would get an error on the client side and on the worker side. \ No newline at end of file diff --git a/custom_decorator/README.md b/custom_decorator/README.md index 65f59482..cfc59111 100644 --- a/custom_decorator/README.md +++ b/custom_decorator/README.md @@ -6,11 +6,11 @@ decorator that automatically configures an activity to heartbeat twice as freque To run, first see [README.md](../README.md) for prerequisites. Then, run the following from this directory to start the worker: - poetry run python worker.py + uv run worker.py This will start the worker. Then, in another terminal, run the following to execute the workflow: - poetry run python starter.py + uv run starter.py The workflow will be started, and then after 5 seconds will be sent a signal to cancel its forever-running activity. The activity has a heartbeat timeout set to 2s, so since it has the `@auto_heartbeater` decorator set, it will heartbeat diff --git a/custom_metric/README.md b/custom_metric/README.md new file mode 100644 index 00000000..de1d51d5 --- /dev/null +++ b/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](../README.md) 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 `uv run custom_metric/starter.py` +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_and_sleep",namespace="default",service_name="temporal-core-sdk",task_queue="custom-metric-task-queue",workflow_type="StartTwoActivitiesWorkflow",le="100"} 1 +custom_activity_schedule_to_start_latency_bucket{activity_type="print_and_sleep",namespace="default",service_name="temporal-core-sdk",task_queue="custom-metric-task-queue",workflow_type="StartTwoActivitiesWorkflow",le="500"} 1 +custom_activity_schedule_to_start_latency_bucket{activity_type="print_and_sleep",namespace="default",service_name="temporal-core-sdk",task_queue="custom-metric-task-queue",workflow_type="StartTwoActivitiesWorkflow",le="1000"} 1 +custom_activity_schedule_to_start_latency_bucket{activity_type="print_and_sleep",namespace="default",service_name="temporal-core-sdk",task_queue="custom-metric-task-queue",workflow_type="StartTwoActivitiesWorkflow",le="5000"} 2 +custom_activity_schedule_to_start_latency_bucket{activity_type="print_and_sleep",namespace="default",service_name="temporal-core-sdk",task_queue="custom-metric-task-queue",workflow_type="StartTwoActivitiesWorkflow",le="10000"} 2 +custom_activity_schedule_to_start_latency_bucket{activity_type="print_and_sleep",namespace="default",service_name="temporal-core-sdk",task_queue="custom-metric-task-queue",workflow_type="StartTwoActivitiesWorkflow",le="100000"} 2 +custom_activity_schedule_to_start_latency_bucket{activity_type="print_and_sleep",namespace="default",service_name="temporal-core-sdk",task_queue="custom-metric-task-queue",workflow_type="StartTwoActivitiesWorkflow",le="1000000"} 2 +custom_activity_schedule_to_start_latency_bucket{activity_type="print_and_sleep",namespace="default",service_name="temporal-core-sdk",task_queue="custom-metric-task-queue",workflow_type="StartTwoActivitiesWorkflow",le="+Inf"} 2 +custom_activity_schedule_to_start_latency_sum{activity_type="print_and_sleep",namespace="default",service_name="temporal-core-sdk",task_queue="custom-metric-task-queue",workflow_type="StartTwoActivitiesWorkflow"} 1010 +custom_activity_schedule_to_start_latency_count{activity_type="print_and_sleep",namespace="default",service_name="temporal-core-sdk",task_queue="custom-metric-task-queue",workflow_type="StartTwoActivitiesWorkflow"} 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 +``` diff --git a/custom_metric/__init__.py b/custom_metric/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/custom_metric/activity.py b/custom_metric/activity.py new file mode 100644 index 00000000..7f2ee116 --- /dev/null +++ b/custom_metric/activity.py @@ -0,0 +1,9 @@ +import time + +from temporalio import activity + + +@activity.defn +def print_and_sleep(): + print("In the activity.") + time.sleep(1) diff --git a/custom_metric/starter.py b/custom_metric/starter.py new file mode 100644 index 00000000..ded3a626 --- /dev/null +++ b/custom_metric/starter.py @@ -0,0 +1,23 @@ +import asyncio +import uuid + +from temporalio.client import Client + +from custom_metric.workflow import StartTwoActivitiesWorkflow + + +async def main(): + + client = await Client.connect( + "localhost:7233", + ) + + await client.start_workflow( + StartTwoActivitiesWorkflow.run, + id="execute-activity-workflow-" + str(uuid.uuid4()), + task_queue="custom-metric-task-queue", + ) + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/custom_metric/worker.py b/custom_metric/worker.py new file mode 100644 index 00000000..9ffad207 --- /dev/null +++ b/custom_metric/worker.py @@ -0,0 +1,71 @@ +import asyncio +from concurrent.futures import ThreadPoolExecutor + +from temporalio import activity +from temporalio.client import Client +from temporalio.runtime import PrometheusConfig, Runtime, TelemetryConfig +from temporalio.worker import ( + ActivityInboundInterceptor, + ExecuteActivityInput, + Interceptor, + Worker, +) + +from custom_metric.activity import print_and_sleep +from custom_metric.workflow import StartTwoActivitiesWorkflow + + +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=[StartTwoActivitiesWorkflow], + activities=[print_and_sleep], + # 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()) diff --git a/custom_metric/workflow.py b/custom_metric/workflow.py new file mode 100644 index 00000000..cf37823b --- /dev/null +++ b/custom_metric/workflow.py @@ -0,0 +1,25 @@ +import asyncio +from datetime import timedelta + +from temporalio import workflow + +with workflow.unsafe.imports_passed_through(): + from custom_metric.activity import print_and_sleep + + +@workflow.defn +class StartTwoActivitiesWorkflow: + @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_and_sleep, + start_to_close_timeout=timedelta(seconds=5), + ) + activity2 = workflow.execute_activity( + print_and_sleep, + start_to_close_timeout=timedelta(seconds=5), + ) + await asyncio.gather(activity1, activity2) + return None diff --git a/dsl/README.md b/dsl/README.md index 4000b3a3..d5051132 100644 --- a/dsl/README.md +++ b/dsl/README.md @@ -6,24 +6,24 @@ samples [in TypeScript](https://github.com/temporalio/samples-typescript/tree/ma For this sample, the optional `dsl` dependency group must be included. To include, run: - poetry install --with dsl + uv sync --group dsl To run, first see [README.md](../README.md) for prerequisites. Then, run the following from this directory to start the worker: - poetry run python worker.py + uv run worker.py This will start the worker. Then, in another terminal, run the following to execute a workflow of steps defined in [workflow1.yaml](workflow1.yaml): - poetry run python starter.py workflow1.yaml + uv run starter.py workflow1.yaml This will run the workflow and show the final variables that the workflow returns. Looking in the worker terminal, each step executed will be visible. Similarly we can do the same for the more advanced [workflow2.yaml](workflow2.yaml) file: - poetry run python starter.py workflow2.yaml + uv run starter.py workflow2.yaml This sample gives a guide of how one can write a workflow to interpret arbitrary steps from a user-provided DSL. Many DSL models are more advanced and are more specific to conform to business logic needs. \ No newline at end of file diff --git a/encryption/README.md b/encryption/README.md index 6c8e9924..09828793 100644 --- a/encryption/README.md +++ b/encryption/README.md @@ -7,16 +7,16 @@ samples [in TypeScript](https://github.com/temporalio/samples-typescript/tree/ma For this sample, the optional `encryption` dependency group must be included. To include, run: - poetry install --with encryption + uv sync --group encryption To run, first see [README.md](../README.md) for prerequisites. Then, run the following from this directory to start the worker: - poetry run python worker.py + uv run worker.py This will start the worker. Then, in another terminal, run the following to execute the workflow: - poetry run python starter.py + uv run starter.py The workflow should complete with the hello result. To view the workflow, use [temporal](https://docs.temporal.io/cli): @@ -31,7 +31,7 @@ Note how the result looks like (with wrapping removed): This is because the data is encrypted and not visible. To make data visible to external Temporal tools like `temporal` and the UI, start a codec server in another terminal: - poetry run python codec_server.py + uv run codec_server.py Now with that running, run `temporal` again with the codec endpoint: diff --git a/gevent_async/README.md b/gevent_async/README.md index 9b9bdff3..d1d9f048 100644 --- a/gevent_async/README.md +++ b/gevent_async/README.md @@ -12,17 +12,17 @@ workflows. For this sample, the optional `gevent` dependency group must be included. To include, run: - poetry install --with gevent + uv sync --group gevent To run the sample, first see [README.md](../README.md) for prerequisites such as having a localhost Temporal server running. Then, run the following from this directory to start the worker: - poetry run python worker.py + uv run worker.py This will start the worker. The worker has a workflow and two activities, one `asyncio` based and one gevent based. Now in another terminal, run the following from this directory to execute the workflow: - poetry run python starter.py + uv run starter.py The workflow should run and complete with the hello result. Note on the worker terminal there will be logs of the workflow and activity executions. \ No newline at end of file diff --git a/hello/README.md b/hello/README.md index 9e13f544..fba44461 100644 --- a/hello/README.md +++ b/hello/README.md @@ -5,7 +5,7 @@ These samples show basic workflow and activity features. To run, first see [README.md](../README.md) for prerequisites. Then, run the following from this directory to run the `hello_activity.py` sample: - poetry run python hello_activity.py + uv run hello_activity.py The result will be: @@ -28,6 +28,7 @@ Replace `hello_activity.py` in the command with any other example filename to ru * [hello_async_activity_completion](hello_async_activity_completion.py) - Complete an activity outside of the function that was called. * [hello_cancellation](hello_cancellation.py) - Manually react to cancellation inside workflows and activities. +* [hello_change_log_level](hello_change_log_level.py) - Change the level of workflow task failure from WARN to ERROR. * [hello_child_workflow](hello_child_workflow.py) - Execute a child workflow from a workflow. * [hello_continue_as_new](hello_continue_as_new.py) - Use continue as new to restart a workflow. * [hello_cron](hello_cron.py) - Execute a workflow once a minute. diff --git a/hello/hello_activity.py b/hello/hello_activity.py index 9801ee1b..13b5fcbb 100644 --- a/hello/hello_activity.py +++ b/hello/hello_activity.py @@ -1,4 +1,5 @@ import asyncio +from concurrent.futures import ThreadPoolExecutor from dataclasses import dataclass from datetime import timedelta @@ -18,7 +19,7 @@ class ComposeGreetingInput: # Basic activity that logs and does string concatenation @activity.defn -async def compose_greeting(input: ComposeGreetingInput) -> str: +def compose_greeting(input: ComposeGreetingInput) -> str: activity.logger.info("Running activity with parameter %s" % input) return f"{input.greeting}, {input.name}!" @@ -50,6 +51,10 @@ async def main(): task_queue="hello-activity-task-queue", workflows=[GreetingWorkflow], activities=[compose_greeting], + # Non-async activities require an executor; + # a thread pool executor is recommended. + # This same thread pool could be passed to multiple workers if desired. + activity_executor=ThreadPoolExecutor(5), ): # While the worker is running, use the client to run the workflow and diff --git a/hello/hello_activity_async.py b/hello/hello_activity_async.py new file mode 100644 index 00000000..fd14a2cf --- /dev/null +++ b/hello/hello_activity_async.py @@ -0,0 +1,71 @@ +import asyncio +from dataclasses import dataclass +from datetime import timedelta + +from temporalio import activity, workflow +from temporalio.client import Client +from temporalio.worker import Worker + + +# While we could use multiple parameters in the activity, Temporal strongly +# encourages using a single dataclass instead which can have fields added to it +# in a backwards-compatible way. +@dataclass +class ComposeGreetingInput: + greeting: str + name: str + + +# Basic activity that logs and does string concatenation +@activity.defn +async def compose_greeting(input: ComposeGreetingInput) -> str: + activity.logger.info("Running activity with parameter %s" % input) + return f"{input.greeting}, {input.name}!" + + +# Basic workflow that logs and invokes an activity +@workflow.defn +class GreetingWorkflow: + @workflow.run + async def run(self, name: str) -> str: + workflow.logger.info("Running workflow with parameter %s" % name) + return await workflow.execute_activity( + compose_greeting, + ComposeGreetingInput("Hello", name), + start_to_close_timeout=timedelta(seconds=10), + ) + + +async def main(): + # Uncomment the lines below to see logging output + # import logging + # logging.basicConfig(level=logging.INFO) + + # Start client + client = await Client.connect("localhost:7233") + + # Run a worker for the workflow + async with Worker( + client, + task_queue="hello-activity-task-queue", + workflows=[GreetingWorkflow], + activities=[compose_greeting], + # If the worker is only running async activities, you don't need + # to supply an activity executor because they run in + # the worker's event loop. + ): + + # While the worker is running, use the client to run the workflow and + # print out its result. Note, in many production setups, the client + # would be in a completely separate process from the worker. + result = await client.execute_workflow( + GreetingWorkflow.run, + "World", + id="hello-activity-workflow-id", + task_queue="hello-activity-task-queue", + ) + print(f"Result: {result}") + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/hello/hello_activity_choice.py b/hello/hello_activity_choice.py index 56b7b7e6..7d01b019 100644 --- a/hello/hello_activity_choice.py +++ b/hello/hello_activity_choice.py @@ -1,4 +1,5 @@ import asyncio +from concurrent.futures import ThreadPoolExecutor from dataclasses import dataclass from datetime import timedelta from enum import IntEnum @@ -12,22 +13,22 @@ @activity.defn -async def order_apples(amount: int) -> str: +def order_apples(amount: int) -> str: return f"Ordered {amount} Apples..." @activity.defn -async def order_bananas(amount: int) -> str: +def order_bananas(amount: int) -> str: return f"Ordered {amount} Bananas..." @activity.defn -async def order_cherries(amount: int) -> str: +def order_cherries(amount: int) -> str: return f"Ordered {amount} Cherries..." @activity.defn -async def order_oranges(amount: int) -> str: +def order_oranges(amount: int) -> str: return f"Ordered {amount} Oranges..." @@ -54,44 +55,27 @@ class ShoppingList: @workflow.defn class PurchaseFruitsWorkflow: @workflow.run - async def run(self, list: ShoppingList) -> str: + async def run(self, shopping_list: ShoppingList) -> str: # Order each thing on the list ordered: List[str] = [] - for item in list.items: + for item in shopping_list.items: if item.fruit is Fruit.APPLE: - ordered.append( - await workflow.execute_activity( - order_apples, - item.amount, - start_to_close_timeout=timedelta(seconds=5), - ) - ) + order_function = order_apples elif item.fruit is Fruit.BANANA: - ordered.append( - await workflow.execute_activity( - order_bananas, - item.amount, - start_to_close_timeout=timedelta(seconds=5), - ) - ) + order_function = order_bananas elif item.fruit is Fruit.CHERRY: - ordered.append( - await workflow.execute_activity( - order_cherries, - item.amount, - start_to_close_timeout=timedelta(seconds=5), - ) - ) + order_function = order_cherries elif item.fruit is Fruit.ORANGE: - ordered.append( - await workflow.execute_activity( - order_oranges, - item.amount, - start_to_close_timeout=timedelta(seconds=5), - ) - ) + order_function = order_oranges else: raise ValueError(f"Unrecognized fruit: {item.fruit}") + ordered.append( + await workflow.execute_activity( + order_function, + item.amount, + start_to_close_timeout=timedelta(seconds=5), + ) + ) return "".join(ordered) @@ -105,6 +89,7 @@ async def main(): task_queue="hello-activity-choice-task-queue", workflows=[PurchaseFruitsWorkflow], activities=[order_apples, order_bananas, order_cherries, order_oranges], + activity_executor=ThreadPoolExecutor(5), ): # While the worker is running, use the client to run the workflow and diff --git a/hello/hello_activity_threaded.py b/hello/hello_activity_heartbeat.py similarity index 77% rename from hello/hello_activity_threaded.py rename to hello/hello_activity_heartbeat.py index e7bf8344..230621d3 100644 --- a/hello/hello_activity_threaded.py +++ b/hello/hello_activity_heartbeat.py @@ -1,5 +1,4 @@ import asyncio -import threading import time from concurrent.futures import ThreadPoolExecutor from dataclasses import dataclass @@ -21,7 +20,7 @@ def compose_greeting(input: ComposeGreetingInput) -> str: # We'll wait for 3 seconds, heartbeating in between (like all long-running # activities should do), then return the greeting for _ in range(0, 3): - print(f"Heartbeating activity on thread {threading.get_ident()}") + print(f"Heartbeating activity") activity.heartbeat() time.sleep(1) return f"{input.greeting}, {input.name}!" @@ -47,12 +46,9 @@ async def main(): # Run a worker for the workflow async with Worker( client, - task_queue="hello-activity-threaded-task-queue", + task_queue="hello-activity-heartbeating-task-queue", workflows=[GreetingWorkflow], activities=[compose_greeting], - # Synchronous activities are not allowed unless we provide some kind of - # executor. This same thread pool could be passed to multiple workers if - # desired. activity_executor=ThreadPoolExecutor(5), ): @@ -62,10 +58,10 @@ async def main(): result = await client.execute_workflow( GreetingWorkflow.run, "World", - id="hello-activity-threaded-workflow-id", - task_queue="hello-activity-threaded-task-queue", + id="hello-activity-heartbeating-workflow-id", + task_queue="hello-activity-heartbeating-task-queue", ) - print(f"Result on thread {threading.get_ident()}: {result}") + print(f"Result: {result}") if __name__ == "__main__": diff --git a/hello/hello_activity_retry.py b/hello/hello_activity_retry.py index 233f9613..f1acd529 100644 --- a/hello/hello_activity_retry.py +++ b/hello/hello_activity_retry.py @@ -1,4 +1,5 @@ import asyncio +from concurrent.futures import ThreadPoolExecutor from dataclasses import dataclass from datetime import timedelta @@ -15,7 +16,7 @@ class ComposeGreetingInput: @activity.defn -async def compose_greeting(input: ComposeGreetingInput) -> str: +def compose_greeting(input: ComposeGreetingInput) -> str: print(f"Invoking activity, attempt number {activity.info().attempt}") # Fail the first 3 attempts, succeed the 4th if activity.info().attempt < 4: @@ -52,6 +53,7 @@ async def main(): task_queue="hello-activity-retry-task-queue", workflows=[GreetingWorkflow], activities=[compose_greeting], + activity_executor=ThreadPoolExecutor(5), ): # While the worker is running, use the client to run the workflow and diff --git a/hello/hello_cancellation.py b/hello/hello_cancellation.py index 3467893c..5bf38a66 100644 --- a/hello/hello_cancellation.py +++ b/hello/hello_cancellation.py @@ -1,29 +1,32 @@ import asyncio +import time import traceback +from concurrent.futures import ThreadPoolExecutor from datetime import timedelta from typing import NoReturn from temporalio import activity, workflow from temporalio.client import Client, WorkflowFailureError +from temporalio.exceptions import CancelledError from temporalio.worker import Worker @activity.defn -async def never_complete_activity() -> NoReturn: +def never_complete_activity() -> NoReturn: # All long-running activities should heartbeat. Heartbeat is how # cancellation is delivered from the server. try: while True: print("Heartbeating activity") activity.heartbeat() - await asyncio.sleep(1) - except asyncio.CancelledError: + time.sleep(1) + except CancelledError: print("Activity cancelled") raise @activity.defn -async def cleanup_activity() -> None: +def cleanup_activity() -> None: print("Executing cleanup activity") @@ -56,6 +59,7 @@ async def main(): task_queue="hello-cancellation-task-queue", workflows=[CancellationWorkflow], activities=[never_complete_activity, cleanup_activity], + activity_executor=ThreadPoolExecutor(5), ): # While the worker is running, use the client to start the workflow. diff --git a/hello/hello_change_log_level.py b/hello/hello_change_log_level.py new file mode 100644 index 00000000..89bb2e1d --- /dev/null +++ b/hello/hello_change_log_level.py @@ -0,0 +1,67 @@ +""" +Changes the log level of workflow task failures from WARN to ERROR. + +Note that the __temporal_error_identifier attribute was added in +version 1.13.0 of the Python SDK. +""" + +import asyncio +import logging +import sys + +from temporalio import workflow +from temporalio.client import Client +from temporalio.worker import Worker + +# --- Begin logging set‑up ---------------------------------------------------------- +logging.basicConfig( + stream=sys.stdout, + level=logging.INFO, + format="%(asctime)s %(levelname)-8s %(name)s %(message)s", +) + + +class CustomLogFilter(logging.Filter): + def filter(self, record: logging.LogRecord) -> bool: + # Note that the __temporal_error_identifier attribute was added in + # version 1.13.0 of the Python SDK. + if ( + hasattr(record, "__temporal_error_identifier") + and getattr(record, "__temporal_error_identifier") == "WorkflowTaskFailure" + ): + record.levelno = logging.ERROR + record.levelname = logging.getLevelName(logging.ERROR) + return True + + +for h in logging.getLogger().handlers: + h.addFilter(CustomLogFilter()) +# --- End logging set‑up ---------------------------------------------------------- + + +LOG_MESSAGE = "This error is an experiment to check the log level" + + +@workflow.defn +class GreetingWorkflow: + @workflow.run + async def run(self): + raise RuntimeError(LOG_MESSAGE) + + +async def main(): + client = await Client.connect("localhost:7233") + async with Worker( + client, + task_queue="hello-change-log-level-task-queue", + workflows=[GreetingWorkflow], + ): + await client.execute_workflow( + GreetingWorkflow.run, + id="hello-change-log-level-workflow-id", + task_queue="hello-change-log-level-task-queue", + ) + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/hello/hello_cron.py b/hello/hello_cron.py index 68b26099..dbb5cba6 100644 --- a/hello/hello_cron.py +++ b/hello/hello_cron.py @@ -1,4 +1,5 @@ import asyncio +from concurrent.futures import ThreadPoolExecutor from dataclasses import dataclass from datetime import timedelta @@ -14,7 +15,7 @@ class ComposeGreetingInput: @activity.defn -async def compose_greeting(input: ComposeGreetingInput) -> str: +def compose_greeting(input: ComposeGreetingInput) -> str: return f"{input.greeting}, {input.name}!" @@ -40,6 +41,7 @@ async def main(): task_queue="hello-cron-task-queue", workflows=[GreetingWorkflow], activities=[compose_greeting], + activity_executor=ThreadPoolExecutor(5), ): print("Running workflow once a minute") diff --git a/hello/hello_exception.py b/hello/hello_exception.py index bfb198d5..628c10c5 100644 --- a/hello/hello_exception.py +++ b/hello/hello_exception.py @@ -1,5 +1,6 @@ import asyncio import logging +from concurrent.futures import ThreadPoolExecutor from dataclasses import dataclass from datetime import timedelta from typing import NoReturn, Optional @@ -18,7 +19,7 @@ class ComposeGreetingInput: @activity.defn -async def compose_greeting(input: ComposeGreetingInput) -> NoReturn: +def compose_greeting(input: ComposeGreetingInput) -> NoReturn: # Always raise exception raise RuntimeError(f"Greeting exception: {input.greeting}, {input.name}!") @@ -46,6 +47,7 @@ async def main(): task_queue="hello-exception-task-queue", workflows=[GreetingWorkflow], activities=[compose_greeting], + activity_executor=ThreadPoolExecutor(5), ): # While the worker is running, use the client to run the workflow and diff --git a/hello/hello_local_activity.py b/hello/hello_local_activity.py index 08c1d9f2..374c29c5 100644 --- a/hello/hello_local_activity.py +++ b/hello/hello_local_activity.py @@ -1,4 +1,5 @@ import asyncio +from concurrent.futures import ThreadPoolExecutor from dataclasses import dataclass from datetime import timedelta @@ -14,7 +15,7 @@ class ComposeGreetingInput: @activity.defn -async def compose_greeting(input: ComposeGreetingInput) -> str: +def compose_greeting(input: ComposeGreetingInput) -> str: return f"{input.greeting}, {input.name}!" @@ -39,6 +40,7 @@ async def main(): task_queue="hello-local-activity-task-queue", workflows=[GreetingWorkflow], activities=[compose_greeting], + activity_executor=ThreadPoolExecutor(5), ): # While the worker is running, use the client to run the workflow and diff --git a/hello/hello_mtls.py b/hello/hello_mtls.py index 1ac6f9d8..3ed15354 100644 --- a/hello/hello_mtls.py +++ b/hello/hello_mtls.py @@ -1,5 +1,6 @@ import argparse import asyncio +from concurrent.futures import ThreadPoolExecutor from dataclasses import dataclass from datetime import timedelta from typing import Optional @@ -18,7 +19,7 @@ class ComposeGreetingInput: # Basic activity that logs and does string concatenation @activity.defn -async def compose_greeting(input: ComposeGreetingInput) -> str: +def compose_greeting(input: ComposeGreetingInput) -> str: return f"{input.greeting}, {input.name}!" @@ -79,6 +80,7 @@ async def main(): task_queue="hello-mtls-task-queue", workflows=[GreetingWorkflow], activities=[compose_greeting], + activity_executor=ThreadPoolExecutor(5), ): # While the worker is running, use the client to run the workflow and diff --git a/hello/hello_parallel_activity.py b/hello/hello_parallel_activity.py index 9de09846..b32b02bb 100644 --- a/hello/hello_parallel_activity.py +++ b/hello/hello_parallel_activity.py @@ -1,4 +1,5 @@ import asyncio +from concurrent.futures import ThreadPoolExecutor from datetime import timedelta from typing import List @@ -8,7 +9,7 @@ @activity.defn -async def say_hello_activity(name: str) -> str: +def say_hello_activity(name: str) -> str: return f"Hello, {name}!" @@ -48,6 +49,7 @@ async def main(): task_queue="hello-parallel-activity-task-queue", workflows=[SayHelloWorkflow], activities=[say_hello_activity], + activity_executor=ThreadPoolExecutor(10), ): # While the worker is running, use the client to run the workflow and diff --git a/hello/hello_patch.py b/hello/hello_patch.py index 0ed19b2f..e511ad5b 100644 --- a/hello/hello_patch.py +++ b/hello/hello_patch.py @@ -1,5 +1,6 @@ import asyncio import sys +from concurrent.futures import ThreadPoolExecutor from dataclasses import dataclass from datetime import timedelta @@ -19,7 +20,7 @@ class ComposeGreetingInput: # Basic activity that logs and does string concatenation @activity.defn -async def compose_greeting(input: ComposeGreetingInput) -> str: +def compose_greeting(input: ComposeGreetingInput) -> str: activity.logger.info("Running activity with parameter %s" % input) return f"{input.greeting}, {input.name}!" @@ -123,6 +124,7 @@ async def main(): task_queue="hello-patch-task-queue", workflows=[workflow_class], # type: ignore activities=[compose_greeting], + activity_executor=ThreadPoolExecutor(5), ): try: result = await client.execute_workflow( diff --git a/langchain/README.md b/langchain/README.md index 5204bbb3..f11161e9 100644 --- a/langchain/README.md +++ b/langchain/README.md @@ -1,10 +1,10 @@ # LangChain Sample -This sample shows you how you can use Temporal to orchestrate workflows for [LangChain](https://www.langchain.com). +This sample shows you how you can use Temporal to orchestrate workflows for [LangChain](https://www.langchain.com). It includes an interceptor that makes LangSmith traces work seamlessly across Temporal clients, workflows and activities. For this sample, the optional `langchain` dependency group must be included. To include, run: - poetry install --with langchain + uv sync --group langchain Export your [OpenAI API key](https://platform.openai.com/api-keys) as an environment variable. Replace `YOUR_API_KEY` with your actual OpenAI API key. @@ -13,16 +13,18 @@ Export your [OpenAI API key](https://platform.openai.com/api-keys) as an environ To run, first see [README.md](../README.md) for prerequisites. Then, run the following from this directory to start the worker: - poetry run python worker.py + uv run worker.py This will start the worker. Then, in another terminal, run the following to execute a workflow: - poetry run python starter.py + uv run starter.py Then, in another terminal, run the following command to translate a phrase: - curl -X POST "http://localhost:8000/translate?phrase=hello%20world&language=Spanish" + curl -X POST "http://localhost:8000/translate?phrase=hello%20world&language1=Spanish&language2=French&language3=Russian" Which should produce some output like: - {"translation":"Hola mundo"} \ No newline at end of file + {"translations":{"French":"Bonjour tout le monde","Russian":"Привет, мир","Spanish":"Hola mundo"}} + +Check [LangSmith](https://smith.langchain.com/) for the corresponding trace. \ No newline at end of file diff --git a/langchain/activities.py b/langchain/activities.py index 47b528d5..a9dec70c 100644 --- a/langchain/activities.py +++ b/langchain/activities.py @@ -13,7 +13,7 @@ class TranslateParams: @activity.defn -async def translate_phrase(params: TranslateParams) -> dict: +async def translate_phrase(params: TranslateParams) -> str: # LangChain setup template = """You are a helpful assistant who translates between languages. Translate the following phrase into the specified language: {phrase} @@ -26,4 +26,9 @@ async def translate_phrase(params: TranslateParams) -> dict: ) chain = chat_prompt | ChatOpenAI() # Use the asynchronous invoke method - return await chain.ainvoke({"phrase": params.phrase, "language": params.language}) + return ( + dict( + await chain.ainvoke({"phrase": params.phrase, "language": params.language}) + ).get("content") + or "" + ) diff --git a/langchain/langchain_interceptor.py b/langchain/langchain_interceptor.py new file mode 100644 index 00000000..bb230b6b --- /dev/null +++ b/langchain/langchain_interceptor.py @@ -0,0 +1,181 @@ +from __future__ import annotations + +from typing import Any, Mapping, Protocol, Type + +from temporalio import activity, api, client, converter, worker, workflow + +with workflow.unsafe.imports_passed_through(): + from contextlib import contextmanager + + from langsmith import trace, tracing_context + from langsmith.run_helpers import get_current_run_tree + +# Header key for LangChain context +LANGCHAIN_CONTEXT_KEY = "langchain-context" + + +class _InputWithHeaders(Protocol): + headers: Mapping[str, api.common.v1.Payload] + + +def set_header_from_context( + input: _InputWithHeaders, payload_converter: converter.PayloadConverter +) -> None: + # Get current LangChain run tree + run_tree = get_current_run_tree() + if run_tree: + headers = run_tree.to_headers() + input.headers = { + **input.headers, + LANGCHAIN_CONTEXT_KEY: payload_converter.to_payload(headers), + } + + +@contextmanager +def context_from_header( + input: _InputWithHeaders, payload_converter: converter.PayloadConverter +): + payload = input.headers.get(LANGCHAIN_CONTEXT_KEY) + if payload: + run_tree = payload_converter.from_payload(payload, dict) + # Set the run tree in the current context + with tracing_context(parent=run_tree): + yield + else: + yield + + +class LangChainContextPropagationInterceptor(client.Interceptor, worker.Interceptor): + """Interceptor that propagates LangChain context through Temporal.""" + + def __init__( + self, + payload_converter: converter.PayloadConverter = converter.default().payload_converter, + ) -> None: + self._payload_converter = payload_converter + + def intercept_client( + self, next: client.OutboundInterceptor + ) -> client.OutboundInterceptor: + return _LangChainContextPropagationClientOutboundInterceptor( + next, self._payload_converter + ) + + def intercept_activity( + self, next: worker.ActivityInboundInterceptor + ) -> worker.ActivityInboundInterceptor: + return _LangChainContextPropagationActivityInboundInterceptor(next) + + def workflow_interceptor_class( + self, input: worker.WorkflowInterceptorClassInput + ) -> Type[_LangChainContextPropagationWorkflowInboundInterceptor]: + return _LangChainContextPropagationWorkflowInboundInterceptor + + +class _LangChainContextPropagationClientOutboundInterceptor(client.OutboundInterceptor): + def __init__( + self, + next: client.OutboundInterceptor, + payload_converter: converter.PayloadConverter, + ) -> None: + super().__init__(next) + self._payload_converter = payload_converter + + async def start_workflow( + self, input: client.StartWorkflowInput + ) -> client.WorkflowHandle[Any, Any]: + with trace(name=f"start_workflow:{input.workflow}"): + set_header_from_context(input, self._payload_converter) + return await super().start_workflow(input) + + +class _LangChainContextPropagationActivityInboundInterceptor( + worker.ActivityInboundInterceptor +): + async def execute_activity(self, input: worker.ExecuteActivityInput) -> Any: + if isinstance(input.fn, str): + name = input.fn + elif callable(input.fn): + defn = activity._Definition.from_callable(input.fn) + name = ( + defn.name if defn is not None and defn.name is not None else "unknown" + ) + else: + name = "unknown" + + with context_from_header(input, activity.payload_converter()): + with trace(name=f"execute_activity:{name}"): + return await self.next.execute_activity(input) + + +class _LangChainContextPropagationWorkflowInboundInterceptor( + worker.WorkflowInboundInterceptor +): + def init(self, outbound: worker.WorkflowOutboundInterceptor) -> None: + self.next.init( + _LangChainContextPropagationWorkflowOutboundInterceptor(outbound) + ) + + async def execute_workflow(self, input: worker.ExecuteWorkflowInput) -> Any: + if isinstance(input.run_fn, str): + name = input.run_fn + elif callable(input.run_fn): + defn = workflow._Definition.from_run_fn(input.run_fn) + name = ( + defn.name if defn is not None and defn.name is not None else "unknown" + ) + else: + name = "unknown" + + with context_from_header(input, workflow.payload_converter()): + # This is a sandbox friendly way to write + # with trace(...): + # return await self.next.execute_workflow(input) + with workflow.unsafe.sandbox_unrestricted(): + t = trace( + name=f"execute_workflow:{name}", run_id=workflow.info().run_id + ) + with workflow.unsafe.imports_passed_through(): + t.__enter__() + try: + return await self.next.execute_workflow(input) + finally: + with workflow.unsafe.sandbox_unrestricted(): + # Cannot use __aexit__ because it's internally uses + # loop.run_in_executor which is not available in the sandbox + t.__exit__() + + +class _LangChainContextPropagationWorkflowOutboundInterceptor( + worker.WorkflowOutboundInterceptor +): + def start_activity( + self, input: worker.StartActivityInput + ) -> workflow.ActivityHandle: + with workflow.unsafe.sandbox_unrestricted(): + t = trace(name=f"start_activity:{input.activity}", run_id=workflow.uuid4()) + with workflow.unsafe.imports_passed_through(): + t.__enter__() + try: + set_header_from_context(input, workflow.payload_converter()) + return self.next.start_activity(input) + finally: + with workflow.unsafe.sandbox_unrestricted(): + t.__exit__() + + async def start_child_workflow( + self, input: worker.StartChildWorkflowInput + ) -> workflow.ChildWorkflowHandle: + with workflow.unsafe.sandbox_unrestricted(): + t = trace( + name=f"start_child_workflow:{input.workflow}", run_id=workflow.uuid4() + ) + with workflow.unsafe.imports_passed_through(): + t.__enter__() + + try: + set_header_from_context(input, workflow.payload_converter()) + return await self.next.start_child_workflow(input) + finally: + with workflow.unsafe.sandbox_unrestricted(): + t.__exit__() diff --git a/langchain/starter.py b/langchain/starter.py index ce7ff2ce..2e3d0d5a 100644 --- a/langchain/starter.py +++ b/langchain/starter.py @@ -1,16 +1,20 @@ from contextlib import asynccontextmanager +from typing import List from uuid import uuid4 import uvicorn from activities import TranslateParams from fastapi import FastAPI, HTTPException +from langchain_interceptor import LangChainContextPropagationInterceptor from temporalio.client import Client -from workflow import LangChainWorkflow +from workflow import LangChainWorkflow, TranslateWorkflowParams @asynccontextmanager async def lifespan(app: FastAPI): - app.state.temporal_client = await Client.connect("localhost:7233") + app.state.temporal_client = await Client.connect( + "localhost:7233", interceptors=[LangChainContextPropagationInterceptor()] + ) yield @@ -18,20 +22,20 @@ async def lifespan(app: FastAPI): @app.post("/translate") -async def translate(phrase: str, language: str): +async def translate(phrase: str, language1: str, language2: str, language3: str): + languages = [language1, language2, language3] client = app.state.temporal_client try: result = await client.execute_workflow( LangChainWorkflow.run, - TranslateParams(phrase, language), + TranslateWorkflowParams(phrase, languages), id=f"langchain-translation-{uuid4()}", task_queue="langchain-task-queue", ) - translation_content = result.get("content", "Translation not available") except Exception as e: raise HTTPException(status_code=500, detail=str(e)) - return {"translation": translation_content} + return {"translations": result} if __name__ == "__main__": diff --git a/langchain/worker.py b/langchain/worker.py index 0fa488b3..1b680432 100644 --- a/langchain/worker.py +++ b/langchain/worker.py @@ -1,9 +1,10 @@ import asyncio from activities import translate_phrase +from langchain_interceptor import LangChainContextPropagationInterceptor from temporalio.client import Client from temporalio.worker import Worker -from workflow import LangChainWorkflow +from workflow import LangChainChildWorkflow, LangChainWorkflow interrupt_event = asyncio.Event() @@ -13,8 +14,9 @@ async def main(): worker = Worker( client, task_queue="langchain-task-queue", - workflows=[LangChainWorkflow], + workflows=[LangChainWorkflow, LangChainChildWorkflow], activities=[translate_phrase], + interceptors=[LangChainContextPropagationInterceptor()], ) print("\nWorker started, ctrl+c to exit\n") @@ -28,7 +30,8 @@ async def main(): if __name__ == "__main__": - loop = asyncio.get_event_loop() + loop = asyncio.new_event_loop() + asyncio.set_event_loop(loop) try: loop.run_until_complete(main()) except KeyboardInterrupt: diff --git a/langchain/workflow.py b/langchain/workflow.py index c005f095..31861c07 100644 --- a/langchain/workflow.py +++ b/langchain/workflow.py @@ -1,4 +1,7 @@ +import asyncio +from dataclasses import dataclass from datetime import timedelta +from typing import List from temporalio import workflow @@ -7,11 +10,44 @@ @workflow.defn -class LangChainWorkflow: +class LangChainChildWorkflow: @workflow.run - async def run(self, params: TranslateParams) -> dict: + async def run(self, params: TranslateParams) -> str: return await workflow.execute_activity( translate_phrase, params, schedule_to_close_timeout=timedelta(seconds=30), ) + + +@dataclass +class TranslateWorkflowParams: + phrase: str + languages: List[str] + + +@workflow.defn +class LangChainWorkflow: + @workflow.run + async def run(self, params: TranslateWorkflowParams) -> dict: + result1, result2, result3 = await asyncio.gather( + workflow.execute_activity( + translate_phrase, + TranslateParams(params.phrase, params.languages[0]), + schedule_to_close_timeout=timedelta(seconds=30), + ), + workflow.execute_activity( + translate_phrase, + TranslateParams(params.phrase, params.languages[1]), + schedule_to_close_timeout=timedelta(seconds=30), + ), + workflow.execute_child_workflow( + LangChainChildWorkflow.run, + TranslateParams(params.phrase, params.languages[2]), + ), + ) + return { + params.languages[0]: result1, + params.languages[1]: result2, + params.languages[2]: result3, + } diff --git a/message_passing/introduction/README.md b/message_passing/introduction/README.md index 0b8be53b..7a2bd351 100644 --- a/message_passing/introduction/README.md +++ b/message_passing/introduction/README.md @@ -10,9 +10,9 @@ Then create two terminals and `cd` to this directory. Run the worker in one terminal: - poetry run python worker.py + uv run worker.py And execute the workflow in the other terminal: - poetry run python starter.py + uv run starter.py diff --git a/message_passing/introduction/activities.py b/message_passing/introduction/activities.py index 29af3987..7f2c9c56 100644 --- a/message_passing/introduction/activities.py +++ b/message_passing/introduction/activities.py @@ -19,7 +19,7 @@ async def call_greeting_service(to_language: Language) -> Optional[str]: Language.FRENCH: "Bonjour, monde", Language.HINDI: "नमस्ते दुनिया", Language.PORTUGUESE: "Olá mundo", - Language.SPANISH: "¡Hola mundo", + Language.SPANISH: "Hola mundo", } await asyncio.sleep(0.2) # Simulate a network call return greetings.get(to_language) diff --git a/message_passing/introduction/workflows.py b/message_passing/introduction/workflows.py index b3cd8de7..97d2b874 100644 --- a/message_passing/introduction/workflows.py +++ b/message_passing/introduction/workflows.py @@ -24,18 +24,20 @@ class ApproveInput: @workflow.defn class GreetingWorkflow: """ - A workflow that that returns a greeting in one of two languages. - - It supports a Query to obtain the current language, an Update to change the - current language and receive the previous language in response, and a Signal - to approve the Workflow so that it is allowed to return its result. + A workflow that that returns a greeting in one of multiple supported + languages. + + It exposes a query to obtain the current language, a signal to approve the + workflow so that it is allowed to return its result, and two updates for + changing the current language and receiving the previous language in + response. + + One of the update handlers is not an `async def`, so it can only mutate and + return local workflow state; the other update handler is `async def` and + executes an activity which calls a remote service, giving access to language + translations which are not available in local workflow state. """ - # 👉 This Workflow does not use any async handlers and so cannot use any - # Activities. It only supports two languages, whose greetings are hardcoded - # in the Workflow definition. See GreetingWorkflowWithAsyncHandler below for - # a Workflow that uses an async Update handler to call an Activity. - def __init__(self) -> None: self.approved_for_release = False self.approver_name: Optional[str] = None @@ -97,12 +99,14 @@ async def set_language_using_activity(self, language: Language) -> Language: language, start_to_close_timeout=timedelta(seconds=10), ) + # 👉 The requested language might not be supported by the remote + # service. If so, we raise ApplicationError, which will fail the + # Update. The WorkflowExecutionUpdateAccepted event will still + # be added to history. (Update validators can be used to reject + # updates before any event is written to history, but they + # cannot be async, and so we cannot use an update validator for + # this purpose.) if greeting is None: - # 👉 An update validator cannot be async, so cannot be used - # to check that the remote call_greeting_service supports - # the requested language. Raising ApplicationError will fail - # the Update, but the WorkflowExecutionUpdateAccepted event - # will still be added to history. raise ApplicationError( f"Greeting service does not support {language.name}" ) diff --git a/message_passing/safe_message_handlers/README.md b/message_passing/safe_message_handlers/README.md index 7d727af3..069d6bca 100644 --- a/message_passing/safe_message_handlers/README.md +++ b/message_passing/safe_message_handlers/README.md @@ -3,7 +3,6 @@ This sample shows off important techniques for handling signals and updates, aka messages. In particular, it illustrates how message handlers can interleave or not be completed before the workflow completes, and how you can manage that. * Here, using workflow.wait_condition, signal and update handlers will only operate when the workflow is within a certain state--between cluster_started and cluster_shutdown. -* You can run start_workflow with an initializer signal that you want to run before anything else other than the workflow's constructor. This pattern is known as "signal-with-start." * Message handlers can block and their actions can be interleaved with one another and with the main workflow. This can easily cause bugs, so you can use a lock to protect shared state from interleaved access. * An "Entity" workflow, i.e. a long-lived workflow, periodically "continues as new". It must do this to prevent its history from growing too large, and it passes its state to the next workflow. You can check `workflow.info().is_continue_as_new_suggested()` to see when it's time. * Most people want their message handlers to finish before the workflow run completes or continues as new. Use `await workflow.wait_condition(lambda: workflow.all_handlers_finished())` to achieve this. @@ -13,10 +12,10 @@ To run, first see [README.md](../../README.md) for prerequisites. Then, run the following from this directory to run the worker: \ - poetry run python worker.py + uv run worker.py Then, in another terminal, run the following to execute the workflow: - poetry run python starter.py + uv run starter.py This will start a worker to run your workflow and activities, then start a ClusterManagerWorkflow and put it through its paces. diff --git a/message_passing/safe_message_handlers/activities.py b/message_passing/safe_message_handlers/activities.py index 3a1c9cd2..da8a8be0 100644 --- a/message_passing/safe_message_handlers/activities.py +++ b/message_passing/safe_message_handlers/activities.py @@ -11,6 +11,16 @@ class AssignNodesToJobInput: job_name: str +@dataclass +class ClusterState: + node_ids: List[str] + + +@activity.defn +async def start_cluster() -> ClusterState: + return ClusterState(node_ids=[f"node-{i}" for i in range(25)]) + + @activity.defn async def assign_nodes_to_job(input: AssignNodesToJobInput) -> None: print(f"Assigning nodes {input.nodes} to job {input.job_name}") @@ -37,7 +47,7 @@ class FindBadNodesInput: @activity.defn async def find_bad_nodes(input: FindBadNodesInput) -> Set[str]: await asyncio.sleep(0.1) - bad_nodes = set([n for n in input.nodes_to_check if int(n) % 5 == 0]) + bad_nodes = set([id for id in input.nodes_to_check if hash(id) % 5 == 0]) if bad_nodes: print(f"Found bad nodes: {bad_nodes}") else: diff --git a/message_passing/safe_message_handlers/starter.py b/message_passing/safe_message_handlers/starter.py index cf712163..7ffe13d9 100644 --- a/message_passing/safe_message_handlers/starter.py +++ b/message_passing/safe_message_handlers/starter.py @@ -16,8 +16,10 @@ async def do_cluster_lifecycle(wf: WorkflowHandle, delay_seconds: Optional[int] = None): - - await wf.signal(ClusterManagerWorkflow.start_cluster) + cluster_status = await wf.execute_update( + ClusterManagerWorkflow.wait_until_cluster_started + ) + print(f"Cluster started with {len(cluster_status.nodes)} nodes") print("Assigning jobs to nodes...") allocation_updates = [] diff --git a/message_passing/safe_message_handlers/worker.py b/message_passing/safe_message_handlers/worker.py index a900c7bb..34e71290 100644 --- a/message_passing/safe_message_handlers/worker.py +++ b/message_passing/safe_message_handlers/worker.py @@ -8,6 +8,7 @@ ClusterManagerWorkflow, assign_nodes_to_job, find_bad_nodes, + start_cluster, unassign_nodes_for_job, ) @@ -21,7 +22,12 @@ async def main(): client, task_queue="safe-message-handlers-task-queue", workflows=[ClusterManagerWorkflow], - activities=[assign_nodes_to_job, unassign_nodes_for_job, find_bad_nodes], + activities=[ + assign_nodes_to_job, + unassign_nodes_for_job, + find_bad_nodes, + start_cluster, + ], ): logging.info("ClusterManagerWorkflow worker started, ctrl+c to exit") await interrupt_event.wait() diff --git a/message_passing/safe_message_handlers/workflow.py b/message_passing/safe_message_handlers/workflow.py index 338a3065..ca549a61 100644 --- a/message_passing/safe_message_handlers/workflow.py +++ b/message_passing/safe_message_handlers/workflow.py @@ -14,6 +14,7 @@ UnassignNodesForJobInput, assign_nodes_to_job, find_bad_nodes, + start_cluster, unassign_nodes_for_job, ) @@ -65,18 +66,27 @@ class ClusterManagerAssignNodesToJobResult: # These updates must run atomically. @workflow.defn class ClusterManagerWorkflow: - def __init__(self) -> None: - self.state = ClusterManagerState() + @workflow.init + def __init__(self, input: ClusterManagerInput) -> None: + if input.state: + self.state = input.state + else: + self.state = ClusterManagerState() + + if input.test_continue_as_new: + self.max_history_length: Optional[int] = 120 + self.sleep_interval_seconds = 1 + else: + self.max_history_length = None + self.sleep_interval_seconds = 600 + # Protects workflow state from interleaved access self.nodes_lock = asyncio.Lock() - self.max_history_length: Optional[int] = None - self.sleep_interval_seconds: int = 600 - @workflow.signal - async def start_cluster(self) -> None: - self.state.cluster_started = True - self.state.nodes = {str(k): None for k in range(25)} - workflow.logger.info("Cluster started") + @workflow.update + async def wait_until_cluster_started(self) -> ClusterManagerState: + await workflow.wait_condition(lambda: self.state.cluster_started) + return self.state @workflow.signal async def shutdown_cluster(self) -> None: @@ -135,7 +145,7 @@ async def _assign_nodes_to_job( self.state.jobs_assigned.add(job_name) # Even though it returns nothing, this is an update because the client may want to track it, for example - # to wait for nodes to be unassignd before reassigning them. + # to wait for nodes to be unassigned before reassigning them. @workflow.update async def delete_job(self, input: ClusterManagerDeleteJobInput) -> None: await workflow.wait_condition(lambda: self.state.cluster_started) @@ -202,30 +212,15 @@ async def perform_health_checks(self) -> None: f"Health check failed with error {type(e).__name__}:{e}" ) - # The cluster manager is a long-running "entity" workflow so we need to periodically checkpoint its state and - # continue-as-new. - def init(self, input: ClusterManagerInput) -> None: - if input.state: - self.state = input.state - if input.test_continue_as_new: - self.max_history_length = 120 - self.sleep_interval_seconds = 1 - - def should_continue_as_new(self) -> bool: - if workflow.info().is_continue_as_new_suggested(): - return True - # This is just for ease-of-testing. In production, we trust temporal to tell us when to continue as new. - if ( - self.max_history_length - and workflow.info().get_current_history_length() > self.max_history_length - ): - return True - return False - @workflow.run async def run(self, input: ClusterManagerInput) -> ClusterManagerResult: - self.init(input) - await workflow.wait_condition(lambda: self.state.cluster_started) + cluster_state = await workflow.execute_activity( + start_cluster, schedule_to_close_timeout=timedelta(seconds=10) + ) + self.state.nodes = {k: None for k in cluster_state.node_ids} + self.state.cluster_started = True + workflow.logger.info("Cluster started") + # Perform health checks at intervals. while True: await self.perform_health_checks() @@ -239,6 +234,8 @@ async def run(self, input: ClusterManagerInput) -> ClusterManagerResult: pass if self.state.cluster_shutdown: break + # The cluster manager is a long-running "entity" workflow so we need to periodically checkpoint its state and + # continue-as-new. if self.should_continue_as_new(): # We don't want to leave any job assignment or deletion handlers half-finished when we continue as new. await workflow.wait_condition(lambda: workflow.all_handlers_finished()) @@ -255,3 +252,14 @@ async def run(self, input: ClusterManagerInput) -> ClusterManagerResult: len(self.get_assigned_nodes()), len(self.get_bad_nodes()), ) + + def should_continue_as_new(self) -> bool: + if workflow.info().is_continue_as_new_suggested(): + return True + # This is just for ease-of-testing. In production, we trust temporal to tell us when to continue as new. + if ( + self.max_history_length + and workflow.info().get_current_history_length() > self.max_history_length + ): + return True + return False diff --git a/message_passing/update_with_start/lazy_initialization/README.md b/message_passing/update_with_start/lazy_initialization/README.md new file mode 100644 index 00000000..0dbe1844 --- /dev/null +++ b/message_passing/update_with_start/lazy_initialization/README.md @@ -0,0 +1,18 @@ +# Update With Start: Lazy init + +This sample illustrates the use of update-with-start to send Updates to a Workflow, starting the Workflow if +it is not running yet ("lazy init"). The Workflow represents a Shopping Cart in an e-commerce application, and +update-with-start is used to add items to the cart, receiving back the updated cart subtotal. + +To run, first see the main [README.md](../../../README.md) for prerequisites. + +Then run the following from this directory: + + uv run worker.py + +Then, in another terminal: + + uv run starter.py + +This will start a worker to run your workflow and activities, then simulate a backend application receiving +requests to add items to a shopping cart, before finalizing the order. diff --git a/message_passing/update_with_start/lazy_initialization/__init__.py b/message_passing/update_with_start/lazy_initialization/__init__.py new file mode 100644 index 00000000..ac3632ee --- /dev/null +++ b/message_passing/update_with_start/lazy_initialization/__init__.py @@ -0,0 +1 @@ +TASK_QUEUE = "update-with-start-lazy-initialization" diff --git a/message_passing/update_with_start/lazy_initialization/activities.py b/message_passing/update_with_start/lazy_initialization/activities.py new file mode 100644 index 00000000..fa730e47 --- /dev/null +++ b/message_passing/update_with_start/lazy_initialization/activities.py @@ -0,0 +1,20 @@ +import asyncio +from dataclasses import dataclass +from typing import Optional + +from temporalio import activity + + +@dataclass +class ShoppingCartItem: + sku: str + quantity: int + + +@activity.defn +async def get_price(item: ShoppingCartItem) -> Optional[int]: + await asyncio.sleep(0.1) + price = None if item.sku == "sku-456" else 599 + if price is None: + return None + return price * item.quantity diff --git a/message_passing/update_with_start/lazy_initialization/starter.py b/message_passing/update_with_start/lazy_initialization/starter.py new file mode 100644 index 00000000..b3274f9d --- /dev/null +++ b/message_passing/update_with_start/lazy_initialization/starter.py @@ -0,0 +1,78 @@ +import asyncio +import uuid +from typing import Optional, Tuple + +from temporalio import common +from temporalio.client import ( + Client, + WithStartWorkflowOperation, + WorkflowHandle, + WorkflowUpdateFailedError, +) +from temporalio.exceptions import ApplicationError + +from message_passing.update_with_start.lazy_initialization import TASK_QUEUE +from message_passing.update_with_start.lazy_initialization.workflows import ( + ShoppingCartItem, + ShoppingCartWorkflow, +) + + +async def handle_add_item_request( + session_id: str, item_id: str, quantity: int, temporal_client: Client +) -> Tuple[Optional[int], WorkflowHandle]: + """ + Handle a client request to add an item to the shopping cart. The user is not logged in, but a session ID is + available from a cookie, and we use this as the cart ID. The Temporal client was created at service-start + time and is shared by all request handlers. + + A Workflow Type exists that can be used to represent a shopping cart. The method uses update-with-start to + add an item to the shopping cart, creating the cart if it doesn't already exist. + + Note that the workflow handle is available, even if the Update fails. + """ + cart_id = f"cart-{session_id}" + start_op = WithStartWorkflowOperation( + ShoppingCartWorkflow.run, + id=cart_id, + id_conflict_policy=common.WorkflowIDConflictPolicy.USE_EXISTING, + task_queue=TASK_QUEUE, + ) + try: + price = await temporal_client.execute_update_with_start_workflow( + ShoppingCartWorkflow.add_item, + ShoppingCartItem(sku=item_id, quantity=quantity), + start_workflow_operation=start_op, + ) + except WorkflowUpdateFailedError as err: + if ( + isinstance(err.cause, ApplicationError) + and err.cause.type == "ItemUnavailableError" + ): + price = None + else: + raise err + + workflow_handle = await start_op.workflow_handle() + + return price, workflow_handle + + +async def main(): + print("🛒") + session_id = f"session-{uuid.uuid4()}" + temporal_client = await Client.connect("localhost:7233") + subtotal_1, _ = await handle_add_item_request( + session_id, "sku-123", 1, temporal_client + ) + subtotal_2, wf_handle = await handle_add_item_request( + session_id, "sku-456", 1, temporal_client + ) + print(f"subtotals were, {[subtotal_1, subtotal_2]}") + await wf_handle.signal(ShoppingCartWorkflow.checkout) + final_order = await wf_handle.result() + print(f"final order: {final_order}") + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/message_passing/update_with_start/lazy_initialization/worker.py b/message_passing/update_with_start/lazy_initialization/worker.py new file mode 100644 index 00000000..1964b43e --- /dev/null +++ b/message_passing/update_with_start/lazy_initialization/worker.py @@ -0,0 +1,35 @@ +import asyncio +import logging + +from temporalio.client import Client +from temporalio.worker import Worker + +from message_passing.update_with_start.lazy_initialization import TASK_QUEUE, workflows +from message_passing.update_with_start.lazy_initialization.activities import get_price + +interrupt_event = asyncio.Event() + + +async def main(): + logging.basicConfig(level=logging.INFO) + + client = await Client.connect("localhost:7233") + + async with Worker( + client, + task_queue=TASK_QUEUE, + workflows=[workflows.ShoppingCartWorkflow], + activities=[get_price], + ): + logging.info("Worker started, ctrl+c to exit") + await interrupt_event.wait() + logging.info("Shutting down") + + +if __name__ == "__main__": + loop = asyncio.new_event_loop() + try: + loop.run_until_complete(main()) + except KeyboardInterrupt: + interrupt_event.set() + loop.run_until_complete(loop.shutdown_asyncgens()) diff --git a/message_passing/update_with_start/lazy_initialization/workflows.py b/message_passing/update_with_start/lazy_initialization/workflows.py new file mode 100644 index 00000000..49964ff2 --- /dev/null +++ b/message_passing/update_with_start/lazy_initialization/workflows.py @@ -0,0 +1,60 @@ +from dataclasses import dataclass +from datetime import timedelta +from typing import List, Tuple + +from temporalio import workflow +from temporalio.exceptions import ApplicationError + +with workflow.unsafe.imports_passed_through(): + from message_passing.update_with_start.lazy_initialization.activities import ( + ShoppingCartItem, + get_price, + ) + + +@dataclass +class FinalizedOrder: + id: str + items: List[Tuple[ShoppingCartItem, int]] + total: int + + +@workflow.defn +class ShoppingCartWorkflow: + def __init__(self): + self.items: List[Tuple[ShoppingCartItem, int]] = [] + self.order_submitted = False + + @workflow.run + async def run(self) -> FinalizedOrder: + await workflow.wait_condition( + lambda: workflow.all_handlers_finished() and self.order_submitted + ) + return FinalizedOrder( + id=workflow.info().workflow_id, + items=self.items, + total=sum(price for _, price in self.items), + ) + + @workflow.update + async def add_item(self, item: ShoppingCartItem) -> int: + price = await workflow.execute_activity( + get_price, item, start_to_close_timeout=timedelta(seconds=10) + ) + if price is None: + raise ApplicationError( + f"Item unavailable: {item}", + type="ItemUnavailableError", + ) + self.items.append((item, price)) + + return sum(price for _, price in self.items) + + @add_item.validator + def validate_add_item(self, item: ShoppingCartItem) -> None: + if self.order_submitted: + raise ApplicationError("Order already submitted") + + @workflow.signal + def checkout(self): + self.order_submitted = True diff --git a/message_passing/waiting_for_handlers/README.md b/message_passing/waiting_for_handlers/README.md new file mode 100644 index 00000000..238c1fb8 --- /dev/null +++ b/message_passing/waiting_for_handlers/README.md @@ -0,0 +1,41 @@ +# Waiting for message handlers + +This workflow demonstrates how to wait for signal and update handlers to +finish in the following circumstances: + +- Before a successful return +- On failure +- On cancellation + +Your workflow can also exit via Continue-As-New. In that case you would +usually wait for the handlers to finish immediately before the call to +continue_as_new(); that's not illustrated in this sample. + + +To run, open two terminals and `cd` to this directory in them. + +Run the worker in one terminal: + + uv run worker.py + +And run the workflow-starter code in the other terminal: + + uv run starter.py + + +Here's the output you'll see: + +``` +workflow exit type: SUCCESS + 🟢 caller received update result + 🟢 caller received workflow result + + +workflow exit type: FAILURE + 🟢 caller received update result + 🔴 caught exception while waiting for workflow result: Workflow execution failed: deliberately failing workflow + + +workflow exit type: CANCELLATION + 🟢 caller received update result +``` \ No newline at end of file diff --git a/message_passing/waiting_for_handlers/__init__.py b/message_passing/waiting_for_handlers/__init__.py new file mode 100644 index 00000000..1274f9bf --- /dev/null +++ b/message_passing/waiting_for_handlers/__init__.py @@ -0,0 +1,21 @@ +from dataclasses import dataclass +from enum import IntEnum + +TASK_QUEUE = "my-task-queue" +WORKFLOW_ID = "my-workflow-id" + + +class WorkflowExitType(IntEnum): + SUCCESS = 0 + FAILURE = 1 + CANCELLATION = 2 + + +@dataclass +class WorkflowInput: + exit_type: WorkflowExitType + + +@dataclass +class WorkflowResult: + data: str diff --git a/message_passing/waiting_for_handlers/activities.py b/message_passing/waiting_for_handlers/activities.py new file mode 100644 index 00000000..610db849 --- /dev/null +++ b/message_passing/waiting_for_handlers/activities.py @@ -0,0 +1,8 @@ +import asyncio + +from temporalio import activity + + +@activity.defn +async def activity_executed_by_update_handler(): + await asyncio.sleep(1) diff --git a/message_passing/waiting_for_handlers/starter.py b/message_passing/waiting_for_handlers/starter.py new file mode 100644 index 00000000..908095c5 --- /dev/null +++ b/message_passing/waiting_for_handlers/starter.py @@ -0,0 +1,69 @@ +import asyncio + +from temporalio import client, common + +from message_passing.waiting_for_handlers import ( + TASK_QUEUE, + WORKFLOW_ID, + WorkflowExitType, + WorkflowInput, +) +from message_passing.waiting_for_handlers.workflows import WaitingForHandlersWorkflow + + +async def starter(exit_type: WorkflowExitType): + cl = await client.Client.connect("localhost:7233") + wf_handle = await cl.start_workflow( + WaitingForHandlersWorkflow.run, + WorkflowInput(exit_type=exit_type), + id=WORKFLOW_ID, + task_queue=TASK_QUEUE, + id_conflict_policy=common.WorkflowIDConflictPolicy.TERMINATE_EXISTING, + ) + await _check_run(wf_handle, exit_type) + + +async def _check_run( + wf_handle: client.WorkflowHandle, + exit_type: WorkflowExitType, +): + try: + up_handle = await wf_handle.start_update( + WaitingForHandlersWorkflow.my_update, + wait_for_stage=client.WorkflowUpdateStage.ACCEPTED, + ) + except Exception as e: + print(f" 🔴 caught exception while starting update: {e}: {e.__cause__ or ''}") + + if exit_type == WorkflowExitType.CANCELLATION: + await wf_handle.cancel() + + try: + await up_handle.result() + print(" 🟢 caller received update result") + except Exception as e: + print( + f" 🔴 caught exception while waiting for update result: {e}: {e.__cause__ or ''}" + ) + + try: + await wf_handle.result() + print(" 🟢 caller received workflow result") + except BaseException as e: + print( + f" 🔴 caught exception while waiting for workflow result: {e}: {e.__cause__ or ''}" + ) + + +async def main(): + for exit_type in [ + WorkflowExitType.SUCCESS, + WorkflowExitType.FAILURE, + WorkflowExitType.CANCELLATION, + ]: + print(f"\n\nworkflow exit type: {exit_type.name}") + await starter(exit_type) + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/message_passing/waiting_for_handlers/worker.py b/message_passing/waiting_for_handlers/worker.py new file mode 100644 index 00000000..9eea60a3 --- /dev/null +++ b/message_passing/waiting_for_handlers/worker.py @@ -0,0 +1,40 @@ +import asyncio +import logging + +from temporalio.client import Client +from temporalio.worker import Worker + +from message_passing.waiting_for_handlers import TASK_QUEUE +from message_passing.waiting_for_handlers.activities import ( + activity_executed_by_update_handler, +) +from message_passing.waiting_for_handlers.workflows import WaitingForHandlersWorkflow + +interrupt_event = asyncio.Event() + + +async def main(): + logging.basicConfig(level=logging.INFO) + + client = await Client.connect("localhost:7233") + + async with Worker( + client, + task_queue=TASK_QUEUE, + workflows=[WaitingForHandlersWorkflow], + activities=[ + activity_executed_by_update_handler, + ], + ): + logging.info("Worker started, ctrl+c to exit") + await interrupt_event.wait() + logging.info("Shutting down") + + +if __name__ == "__main__": + loop = asyncio.new_event_loop() + try: + loop.run_until_complete(main()) + except KeyboardInterrupt: + interrupt_event.set() + loop.run_until_complete(loop.shutdown_asyncgens()) diff --git a/message_passing/waiting_for_handlers/workflows.py b/message_passing/waiting_for_handlers/workflows.py new file mode 100644 index 00000000..b4ed2991 --- /dev/null +++ b/message_passing/waiting_for_handlers/workflows.py @@ -0,0 +1,95 @@ +import asyncio +from datetime import timedelta + +from temporalio import exceptions, workflow + +from message_passing.waiting_for_handlers import ( + WorkflowExitType, + WorkflowInput, + WorkflowResult, +) +from message_passing.waiting_for_handlers.activities import ( + activity_executed_by_update_handler, +) + + +def is_workflow_exit_exception(e: BaseException) -> bool: + """ + True if the exception is of a type that will cause the workflow to exit. + + This is as opposed to exceptions that cause a workflow task failure, which + are retried automatically by Temporal. + """ + # 👉 If you have set additional failure_exception_types you should also + # check for these here. + return isinstance(e, (asyncio.CancelledError, exceptions.FailureError)) + + +@workflow.defn +class WaitingForHandlersWorkflow: + @workflow.run + async def run(self, input: WorkflowInput) -> WorkflowResult: + """ + This workflow.run method demonstrates a pattern that can be used to wait for signal and + update handlers to finish in the following circumstances: + + - On successful workflow return + - On workflow cancellation + - On workflow failure + + Your workflow can also exit via Continue-As-New. In that case you would usually wait for + the handlers to finish immediately before the call to continue_as_new(); that's not + illustrated in this sample. + + If you additionally need to perform cleanup or compensation on workflow failure or + cancellation, see the message_passing/waiting_for_handlers_and_compensation sample. + """ + try: + # 👉 Use this `try...except` style, instead of waiting for message + # handlers to finish in a `finally` block. The reason is that some + # exception types cause a workflow task failure as opposed to + # workflow exit, in which case we do *not* want to wait for message + # handlers to finish. + result = await self._my_workflow_application_logic(input) + await workflow.wait_condition(workflow.all_handlers_finished) + return result + # 👉 Catch BaseException since asyncio.CancelledError does not inherit + # from Exception. + except BaseException as e: + if is_workflow_exit_exception(e): + await workflow.wait_condition(workflow.all_handlers_finished) + raise + + # Methods below this point can be ignored unless you are interested in + # the implementation details of this sample. + + def __init__(self) -> None: + self._update_started = False + + @workflow.update + async def my_update(self) -> str: + self._update_started = True + await workflow.execute_activity( + activity_executed_by_update_handler, + start_to_close_timeout=timedelta(seconds=10), + ) + return "update-result" + + async def _my_workflow_application_logic( + self, input: WorkflowInput + ) -> WorkflowResult: + # The main workflow logic is implemented in a separate method in order + # to separate "platform-level" concerns (waiting for handlers to finish + # and error handling) from application logic. + + # Wait until handlers have started, so that we are demonstrating that we + # wait for them to finish. + await workflow.wait_condition(lambda: self._update_started) + if input.exit_type == WorkflowExitType.SUCCESS: + return WorkflowResult(data="workflow-result") + elif input.exit_type == WorkflowExitType.FAILURE: + raise exceptions.ApplicationError("deliberately failing workflow") + elif input.exit_type == WorkflowExitType.CANCELLATION: + # Block forever; the starter will send a workflow cancellation request. + await asyncio.Future() + raise AssertionError("unreachable") diff --git a/message_passing/waiting_for_handlers_and_compensation/README.md b/message_passing/waiting_for_handlers_and_compensation/README.md new file mode 100644 index 00000000..2ef5fe1f --- /dev/null +++ b/message_passing/waiting_for_handlers_and_compensation/README.md @@ -0,0 +1,39 @@ +# Waiting for message handlers, and performing compensation and cleanup in message handlers + +This sample demonstrates how to do the following: + +1. Ensure that all update/signal handlers are finished before a successful + workflow return, and on workflow cancellation and failure. +2. Perform compensation/cleanup in an update handler when the workflow is + cancelled or fails. + +For a simpler sample showing how to do (1) without (2), see [safe_message_handlers](../safe_message_handlers/README.md). + +To run, open two terminals and `cd` to this directory in them. + +Run the worker in one terminal: + + uv run worker.py + +And run the workflow-starter code in the other terminal: + + uv run starter.py + + +Here's the output you'll see: + +``` +workflow exit type: SUCCESS + 🟢 caller received update result + 🟢 caller received workflow result + + +workflow exit type: FAILURE + 🔴 caught exception while waiting for update result: Workflow update failed: The update failed because the workflow run exited + 🔴 caught exception while waiting for workflow result: Workflow execution failed: deliberately failing workflow + + +workflow exit type: CANCELLATION + 🔴 caught exception while waiting for update result: Workflow update failed: The update failed because the workflow run exited + 🔴 caught exception while waiting for workflow result: Workflow execution failed: Workflow cancelled +``` \ No newline at end of file diff --git a/message_passing/waiting_for_handlers_and_compensation/__init__.py b/message_passing/waiting_for_handlers_and_compensation/__init__.py new file mode 100644 index 00000000..1274f9bf --- /dev/null +++ b/message_passing/waiting_for_handlers_and_compensation/__init__.py @@ -0,0 +1,21 @@ +from dataclasses import dataclass +from enum import IntEnum + +TASK_QUEUE = "my-task-queue" +WORKFLOW_ID = "my-workflow-id" + + +class WorkflowExitType(IntEnum): + SUCCESS = 0 + FAILURE = 1 + CANCELLATION = 2 + + +@dataclass +class WorkflowInput: + exit_type: WorkflowExitType + + +@dataclass +class WorkflowResult: + data: str diff --git a/message_passing/waiting_for_handlers_and_compensation/activities.py b/message_passing/waiting_for_handlers_and_compensation/activities.py new file mode 100644 index 00000000..36c5a5cb --- /dev/null +++ b/message_passing/waiting_for_handlers_and_compensation/activities.py @@ -0,0 +1,18 @@ +import asyncio + +from temporalio import activity + + +@activity.defn +async def activity_executed_to_perform_workflow_compensation(): + await asyncio.sleep(1) + + +@activity.defn +async def activity_executed_by_update_handler(): + await asyncio.sleep(1) + + +@activity.defn +async def activity_executed_by_update_handler_to_perform_compensation(): + await asyncio.sleep(1) diff --git a/message_passing/waiting_for_handlers_and_compensation/starter.py b/message_passing/waiting_for_handlers_and_compensation/starter.py new file mode 100644 index 00000000..812bee5f --- /dev/null +++ b/message_passing/waiting_for_handlers_and_compensation/starter.py @@ -0,0 +1,71 @@ +import asyncio + +from temporalio import client, common + +from message_passing.waiting_for_handlers_and_compensation import ( + TASK_QUEUE, + WORKFLOW_ID, + WorkflowExitType, + WorkflowInput, +) +from message_passing.waiting_for_handlers_and_compensation.workflows import ( + WaitingForHandlersAndCompensationWorkflow, +) + + +async def starter(exit_type: WorkflowExitType): + cl = await client.Client.connect("localhost:7233") + wf_handle = await cl.start_workflow( + WaitingForHandlersAndCompensationWorkflow.run, + WorkflowInput(exit_type=exit_type), + id=WORKFLOW_ID, + task_queue=TASK_QUEUE, + id_conflict_policy=common.WorkflowIDConflictPolicy.TERMINATE_EXISTING, + ) + await _check_run(wf_handle, exit_type) + + +async def _check_run( + wf_handle: client.WorkflowHandle, + exit_type: WorkflowExitType, +): + try: + up_handle = await wf_handle.start_update( + WaitingForHandlersAndCompensationWorkflow.my_update, + wait_for_stage=client.WorkflowUpdateStage.ACCEPTED, + ) + except Exception as e: + print(f" 🔴 caught exception while starting update: {e}: {e.__cause__ or ''}") + + if exit_type == WorkflowExitType.CANCELLATION: + await wf_handle.cancel() + + try: + await up_handle.result() + print(" 🟢 caller received update result") + except Exception as e: + print( + f" 🔴 caught exception while waiting for update result: {e}: {e.__cause__ or ''}" + ) + + try: + await wf_handle.result() + print(" 🟢 caller received workflow result") + except Exception as e: + print( + f" 🔴 caught exception while waiting for workflow result: {e}: {e.__cause__ or ''}" + ) + + +async def main(): + for exit_type in [ + WorkflowExitType.SUCCESS, + WorkflowExitType.FAILURE, + WorkflowExitType.CANCELLATION, + ]: + print(f"\n\nworkflow exit type: {exit_type.name}") + await starter(exit_type) + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/message_passing/waiting_for_handlers_and_compensation/worker.py b/message_passing/waiting_for_handlers_and_compensation/worker.py new file mode 100644 index 00000000..7daf768f --- /dev/null +++ b/message_passing/waiting_for_handlers_and_compensation/worker.py @@ -0,0 +1,46 @@ +import asyncio +import logging + +from temporalio.client import Client +from temporalio.worker import Worker + +from message_passing.waiting_for_handlers_and_compensation import TASK_QUEUE +from message_passing.waiting_for_handlers_and_compensation.activities import ( + activity_executed_by_update_handler, + activity_executed_by_update_handler_to_perform_compensation, + activity_executed_to_perform_workflow_compensation, +) +from message_passing.waiting_for_handlers_and_compensation.workflows import ( + WaitingForHandlersAndCompensationWorkflow, +) + +interrupt_event = asyncio.Event() + + +async def main(): + logging.basicConfig(level=logging.INFO) + + client = await Client.connect("localhost:7233") + + async with Worker( + client, + task_queue=TASK_QUEUE, + workflows=[WaitingForHandlersAndCompensationWorkflow], + activities=[ + activity_executed_by_update_handler, + activity_executed_by_update_handler_to_perform_compensation, + activity_executed_to_perform_workflow_compensation, + ], + ): + logging.info("Worker started, ctrl+c to exit") + await interrupt_event.wait() + logging.info("Shutting down") + + +if __name__ == "__main__": + loop = asyncio.new_event_loop() + try: + loop.run_until_complete(main()) + except KeyboardInterrupt: + interrupt_event.set() + loop.run_until_complete(loop.shutdown_asyncgens()) diff --git a/message_passing/waiting_for_handlers_and_compensation/workflows.py b/message_passing/waiting_for_handlers_and_compensation/workflows.py new file mode 100644 index 00000000..450dff2c --- /dev/null +++ b/message_passing/waiting_for_handlers_and_compensation/workflows.py @@ -0,0 +1,176 @@ +import asyncio +from datetime import timedelta +from typing import cast + +from temporalio import exceptions, workflow + +from message_passing.waiting_for_handlers_and_compensation import ( + WorkflowExitType, + WorkflowInput, + WorkflowResult, +) +from message_passing.waiting_for_handlers_and_compensation.activities import ( + activity_executed_by_update_handler, + activity_executed_by_update_handler_to_perform_compensation, + activity_executed_to_perform_workflow_compensation, +) + + +@workflow.defn +class WaitingForHandlersAndCompensationWorkflow: + """ + This Workflow demonstrates how to wait for message handlers to finish and + perform compensation/cleanup: + + 1. It ensures that all signal and update handlers have finished before a + successful return, and on failure and cancellation. + 2. The update handler performs any necessary compensation/cleanup when the + workflow is cancelled or fails. + + If all you need to do is wait for handlers, without performing cleanup or compensation, + then see the simpler sample message_passing/waiting_for_handlers. + """ + + def __init__(self) -> None: + # 👉 If the workflow exits prematurely, this future will be completed + # with the associated exception as its value. Message handlers can then + # "race" this future against a task performing the message handler's own + # application logic; if this future completes before the message handler + # task then the handler should abort and perform compensation. + self.workflow_exit: asyncio.Future[None] = asyncio.Future() + + # The following attributes are implementation detail of this sample and can be + # ignored + self._update_started = False + self._update_compensation_done = False + self._workflow_compensation_done = False + + @workflow.run + async def run(self, input: WorkflowInput) -> WorkflowResult: + try: + # 👉 Use this `try...except` style, instead of waiting for message + # handlers to finish in a `finally` block. The reason is that some + # exception types cause a workflow task failure as opposed to + # workflow exit, in which case we do *not* want to wait for message + # handlers to finish. + + # 👉 The actual workflow application logic is implemented in a + # separate method in order to separate "platform-level" concerns + # (waiting for handlers to finish and ensuring that compensation is + # performed when appropriate) from application logic. + result = await self._my_workflow_application_logic(input) + self.workflow_exit.set_result(None) + await workflow.wait_condition(workflow.all_handlers_finished) + return result + # 👉 Catch BaseException since asyncio.CancelledError does not inherit + # from Exception. + except BaseException as e: + if is_workflow_exit_exception(e): + self.workflow_exit.set_exception(e) + await workflow.wait_condition(workflow.all_handlers_finished) + await self.workflow_compensation() + self._workflow_compensation_done = True + raise + + async def workflow_compensation(self): + await workflow.execute_activity( + activity_executed_to_perform_workflow_compensation, + start_to_close_timeout=timedelta(seconds=10), + ) + self._update_compensation_done = True + + @workflow.update + async def my_update(self) -> str: + """ + An update handler that handles exceptions raised in its own execution + and in that of the main workflow method. + + It ensures that: + - Compensation/cleanup is always performed when appropriate + - The update caller gets the update result, or WorkflowUpdateFailedError + """ + # 👉 "Race" the workflow_exit future against the handler's own + # application logic. Always use `workflow.wait` instead of + # `asyncio.wait` in Workflow code: asyncio's version is + # non-deterministic. (Note that coroutines must be wrapped in tasks in + # order to use workflow.wait.) + update_task = asyncio.create_task(self._my_update_application_logic()) + await workflow.wait( # type: ignore + [update_task, self.workflow_exit], return_when=asyncio.FIRST_EXCEPTION + ) + try: + if update_task.done(): + # 👉 The update has finished (whether successfully or not). + # Regardless of whether the main workflow method is about to + # exit or not, the update caller should receive a response + # informing them of the outcome of the update. So return the + # result, or raise the exception that caused the update handler + # to exit. + return await update_task + else: + # 👉 The main workflow method exited prematurely due to an + # error, and this happened before the update finished. Fail the + # update with the workflow exception as cause. + raise exceptions.ApplicationError( + "The update failed because the workflow run exited" + ) from cast(BaseException, self.workflow_exit.exception()) + # 👉 Catch BaseException since asyncio.CancelledError does not inherit + # from Exception. + except BaseException as e: + if is_workflow_exit_exception(e): + try: + await self.my_update_compensation() + except BaseException as e: + raise exceptions.ApplicationError( + "Update compensation failed" + ) from e + raise + + async def my_update_compensation(self): + await workflow.execute_activity( + activity_executed_by_update_handler_to_perform_compensation, + start_to_close_timeout=timedelta(seconds=10), + ) + self._update_compensation_done = True + + @workflow.query + def workflow_compensation_done(self) -> bool: + return self._workflow_compensation_done + + @workflow.query + def update_compensation_done(self) -> bool: + return self._update_compensation_done + + # Methods below this point are placeholders for the actual application logic + # that you would perform in your main workflow method or update handler. + # They can be ignored unless you are interested in the implementation + # details of this sample. + + async def _my_update_application_logic(self) -> str: + self._update_started = True + await workflow.execute_activity( + activity_executed_by_update_handler, + start_to_close_timeout=timedelta(seconds=10), + ) + return "update-result" + + async def _my_workflow_application_logic( + self, input: WorkflowInput + ) -> WorkflowResult: + # Wait until handlers have started, so that we are demonstrating that we + # wait for them to finish. + await workflow.wait_condition(lambda: self._update_started) + if input.exit_type == WorkflowExitType.SUCCESS: + return WorkflowResult(data="workflow-result") + elif input.exit_type == WorkflowExitType.FAILURE: + raise exceptions.ApplicationError("deliberately failing workflow") + elif input.exit_type == WorkflowExitType.CANCELLATION: + # Block forever; the starter will send a workflow cancellation request. + await asyncio.Future() + raise AssertionError("unreachable") + + +def is_workflow_exit_exception(e: BaseException) -> bool: + # 👉 If you have set additional failure_exception_types you should also + # check for these here. + return isinstance(e, (asyncio.CancelledError, exceptions.FailureError)) diff --git a/open_telemetry/README.md b/open_telemetry/README.md index e742b3dd..06df7326 100644 --- a/open_telemetry/README.md +++ b/open_telemetry/README.md @@ -4,35 +4,34 @@ This sample shows how to configure OpenTelemetry to capture workflow traces and For this sample, the optional `open_telemetry` dependency group must be included. To include, run: - poetry install --with open_telemetry + uv sync --group open-telemetry -To run, first see [README.md](../README.md) for prerequisites. Then run the following to start a Jaeger container -with OTLP collector enabled to collect and view the trace results: +To run, first see [README.md](../README.md) for prerequisites. Then run the following to start an [Aspire](https://hub.docker.com/r/microsoft/dotnet-aspire-dashboard/) OTEL collector - docker run -d --name jaeger \ - -e COLLECTOR_OTLP_ENABLED=true \ - -p 16686:16686 \ - -p 4317:4317 \ - -p 4318:4318 \ - jaegertracing/all-in-one:latest + docker compose up Now, from this directory, start the worker in its own terminal: - poetry run python worker.py + uv run worker.py -This will start the worker. Then, in another terminal, run the following to execute the workflow: +Then, in another terminal, run the following to execute the workflow: - poetry run python starter.py + uv run starter.py -The workflow should complete with the hello result. The workflow trace can now be viewed in Jaeger at -http://localhost:16686/. Under service, select `my-service` and "Find Traces". The workflow should appear and when -clicked, may look something like: +The workflow should complete with the hello result. -![Jaeger Screenshot](jaeger-screenshot.png) +Now view the Aspire UI at http://localhost:18888/. + +To view metrics sent describing the worker and the workflow that was executed, select `Metrics` on the left and under "Select a resource" select "temporal-core-sdk". It may look like this: + +![Aspire metrics screenshot](aspire-metrics-screenshot.png) + + +To view workflow spans, select `Traces` on the left and under "Select a resource" select "temporal-core-sdk". It may look like this: + +![Aspire traces screenshot](aspire-traces-screenshot.png) Note, in-workflow spans do not have a time associated with them. This is by intention since due to replay. In OpenTelemetry, only the process that started the span may end it. But in Temporal a span may cross workers/processes. Therefore we intentionally start-then-end in-workflow spans immediately. So while the start time and hierarchy is -accurate, the duration is not. - -The metrics should have been dumped out in the terminal where the OpenTelemetry collector container is running. +accurate, the duration is not. \ No newline at end of file diff --git a/open_telemetry/aspire-metrics-screenshot.png b/open_telemetry/aspire-metrics-screenshot.png new file mode 100644 index 00000000..ed4ab8e9 Binary files /dev/null and b/open_telemetry/aspire-metrics-screenshot.png differ diff --git a/open_telemetry/aspire-traces-screenshot.png b/open_telemetry/aspire-traces-screenshot.png new file mode 100644 index 00000000..298c07eb Binary files /dev/null and b/open_telemetry/aspire-traces-screenshot.png differ diff --git a/open_telemetry/docker-compose.yaml b/open_telemetry/docker-compose.yaml new file mode 100644 index 00000000..da3c02ae --- /dev/null +++ b/open_telemetry/docker-compose.yaml @@ -0,0 +1,8 @@ +services: + aspire-dashboard: + environment: + Dashboard__Frontend__AuthMode: Unsecured + image: mcr.microsoft.com/dotnet/aspire-dashboard:8.0 + ports: + - 4317:18889 + - 18888:18888 \ No newline at end of file diff --git a/open_telemetry/jaeger-screenshot.png b/open_telemetry/jaeger-screenshot.png deleted file mode 100644 index 8376d49c..00000000 Binary files a/open_telemetry/jaeger-screenshot.png and /dev/null differ diff --git a/open_telemetry/otel-metrics-collector-config.yaml b/open_telemetry/otel-metrics-collector-config.yaml deleted file mode 100644 index 45265f88..00000000 --- a/open_telemetry/otel-metrics-collector-config.yaml +++ /dev/null @@ -1,15 +0,0 @@ -receivers: - otlp: - protocols: - grpc: -exporters: - logging: - loglevel: debug -processors: - batch: -service: - pipelines: - metrics: - receivers: [otlp] - exporters: [logging] - processors: [batch] \ No newline at end of file diff --git a/open_telemetry/worker.py b/open_telemetry/worker.py index f4347152..4b344123 100644 --- a/open_telemetry/worker.py +++ b/open_telemetry/worker.py @@ -1,7 +1,6 @@ import asyncio from datetime import timedelta -import opentelemetry.context from opentelemetry import trace from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import OTLPSpanExporter from opentelemetry.sdk.resources import SERVICE_NAME, Resource diff --git a/openai_agents/README.md b/openai_agents/README.md new file mode 100644 index 00000000..1eceb747 --- /dev/null +++ b/openai_agents/README.md @@ -0,0 +1,62 @@ +# Temporal OpenAI Agents SDK Integration + +⚠️ **Experimental** - This module is not yet stable and may change in the future. + +This directory contains samples demonstrating how to use the [OpenAI Agents SDK](https://github.com/openai/openai-agents-python) with Temporal's durable execution engine. +These samples are adapted from the [OpenAI Agents SDK examples](https://github.com/openai/openai-agents-python/tree/main/examples) and extended with Temporal's durability and orchestration capabilities. + +See the [module documentation](https://github.com/temporalio/sdk-python/blob/main/temporalio/contrib/openai_agents/README.md) for more information. + +## Overview + +The integration combines: +- **Temporal workflows** for orchestrating agent control flow and state management +- **OpenAI Agents SDK** for AI agent creation and tool interactions + +This approach ensures that AI agent workflows are durable, observable, and can handle failures gracefully. + +## Prerequisites + +- Temporal server [running locally](https://docs.temporal.io/cli/server#start-dev) +- Required dependencies installed via `uv sync --group openai-agents` +- OpenAI API key set as environment variable: `export OPENAI_API_KEY=your_key_here` + +## Running the Examples + +1. **Start the worker** (supports all samples): + ```bash + uv run openai_agents/run_worker.py + ``` + +2. **Run individual samples** in separate terminals: + +### Basic Agent Examples + +- **Hello World Agent** - Simple agent that responds in haikus: + ```bash + uv run openai_agents/run_hello_world_workflow.py + ``` + +- **Tools Agent** - Agent with access to external tools (weather API): + ```bash + uv run openai_agents/run_tools_workflow.py + ``` + +### Advanced Multi-Agent Examples + +- **Research Workflow** - Multi-agent research system with specialized roles: + ```bash + uv run openai_agents/run_research_workflow.py + ``` + Features a planner agent, search agent, and writer agent working together. + +- **Customer Service Workflow** - Customer service agent with escalation capabilities (interactive): + ```bash + uv run openai_agents/run_customer_service_client.py --conversation-id my-conversation-123 + ``` + +- **Agents as Tools** - Demonstrate using agents as tools within other agents: + ```bash + uv run openai_agents/run_agents_as_tools_workflow.py + ``` + diff --git a/openai_agents/__init__.py b/openai_agents/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/openai_agents/run_agents_as_tools_workflow.py b/openai_agents/run_agents_as_tools_workflow.py new file mode 100644 index 00000000..7bd61cb5 --- /dev/null +++ b/openai_agents/run_agents_as_tools_workflow.py @@ -0,0 +1,30 @@ +import asyncio + +from temporalio.client import Client +from temporalio.contrib.openai_agents.open_ai_data_converter import ( + open_ai_data_converter, +) + +from openai_agents.workflows.agents_as_tools_workflow import AgentsAsToolsWorkflow + + +async def main(): + # Create client connected to server at the given address + client = await Client.connect( + "localhost:7233", + data_converter=open_ai_data_converter, + ) + + # Execute a workflow + result = await client.execute_workflow( + AgentsAsToolsWorkflow.run, + "Translate to English: '¿Cómo estás?'", + id="my-workflow-id", + task_queue="openai-agents-task-queue", + ) + + print(f"Result: {result}") + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/openai_agents/run_customer_service_client.py b/openai_agents/run_customer_service_client.py new file mode 100644 index 00000000..c4277dc4 --- /dev/null +++ b/openai_agents/run_customer_service_client.py @@ -0,0 +1,81 @@ +import argparse +import asyncio + +from temporalio.client import ( + Client, + WorkflowQueryRejectedError, + WorkflowUpdateFailedError, +) +from temporalio.common import QueryRejectCondition +from temporalio.contrib.openai_agents.open_ai_data_converter import ( + open_ai_data_converter, +) +from temporalio.service import RPCError, RPCStatusCode + +from openai_agents.workflows.customer_service_workflow import ( + CustomerServiceWorkflow, + ProcessUserMessageInput, +) + + +async def main(): + parser = argparse.ArgumentParser() + parser.add_argument("--conversation-id", type=str, required=True) + args = parser.parse_args() + + # Create client connected to server at the given address + client = await Client.connect( + "localhost:7233", + data_converter=open_ai_data_converter, + ) + + handle = client.get_workflow_handle(args.conversation_id) + + # Query the workflow for the chat history + # If the workflow is not open, start a new one + start = False + try: + history = await handle.query( + CustomerServiceWorkflow.get_chat_history, + reject_condition=QueryRejectCondition.NOT_OPEN, + ) + except WorkflowQueryRejectedError as e: + start = True + except RPCError as e: + if e.status == RPCStatusCode.NOT_FOUND: + start = True + else: + raise e + if start: + await client.start_workflow( + CustomerServiceWorkflow.run, + id=args.conversation_id, + task_queue="openai-agents-task-queue", + ) + history = [] + print(*history, sep="\n") + + # Loop to send messages to the workflow + while True: + user_input = input("Enter your message: ") + message_input = ProcessUserMessageInput( + user_input=user_input, chat_length=len(history) + ) + try: + new_history = await handle.execute_update( + CustomerServiceWorkflow.process_user_message, message_input + ) + history.extend(new_history) + print(*new_history, sep="\n") + except WorkflowUpdateFailedError: + print("** Stale conversation. Reloading...") + length = len(history) + history = await handle.query( + CustomerServiceWorkflow.get_chat_history, + reject_condition=QueryRejectCondition.NOT_OPEN, + ) + print(*history[length:], sep="\n") + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/openai_agents/run_hello_world_workflow.py b/openai_agents/run_hello_world_workflow.py new file mode 100644 index 00000000..a7baea57 --- /dev/null +++ b/openai_agents/run_hello_world_workflow.py @@ -0,0 +1,29 @@ +import asyncio + +from temporalio.client import Client +from temporalio.contrib.openai_agents.open_ai_data_converter import ( + open_ai_data_converter, +) + +from openai_agents.workflows.hello_world_workflow import HelloWorldAgent + + +async def main(): + # Create client connected to server at the given address + client = await Client.connect( + "localhost:7233", + data_converter=open_ai_data_converter, + ) + + # Execute a workflow + result = await client.execute_workflow( + HelloWorldAgent.run, + "Tell me about recursion in programming.", + id="my-workflow-id", + task_queue="openai-agents-task-queue", + ) + print(f"Result: {result}") + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/openai_agents/run_research_workflow.py b/openai_agents/run_research_workflow.py new file mode 100644 index 00000000..72836e2c --- /dev/null +++ b/openai_agents/run_research_workflow.py @@ -0,0 +1,30 @@ +import asyncio + +from temporalio.client import Client +from temporalio.contrib.openai_agents.open_ai_data_converter import ( + open_ai_data_converter, +) + +from openai_agents.workflows.research_bot_workflow import ResearchWorkflow + + +async def main(): + # Create client connected to server at the given address + client = await Client.connect( + "localhost:7233", + data_converter=open_ai_data_converter, + ) + + # Execute a workflow + result = await client.execute_workflow( + ResearchWorkflow.run, + "Caribbean vacation spots in April, optimizing for surfing, hiking and water sports", + id="research-workflow", + task_queue="openai-agents-task-queue", + ) + + print(f"Result: {result}") + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/openai_agents/run_tools_workflow.py b/openai_agents/run_tools_workflow.py new file mode 100644 index 00000000..a6683fb7 --- /dev/null +++ b/openai_agents/run_tools_workflow.py @@ -0,0 +1,30 @@ +import asyncio + +from temporalio.client import Client +from temporalio.contrib.openai_agents.open_ai_data_converter import ( + open_ai_data_converter, +) + +from openai_agents.workflows.tools_workflow import ToolsWorkflow + + +async def main(): + # Create client connected to server at the given address + client = await Client.connect( + "localhost:7233", + data_converter=open_ai_data_converter, + ) + + # Execute a workflow + result = await client.execute_workflow( + ToolsWorkflow.run, + "What is the weather in Tokio?", + id="tools-workflow", + task_queue="openai-agents-task-queue", + ) + + print(f"Result: {result}") + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/openai_agents/run_worker.py b/openai_agents/run_worker.py new file mode 100644 index 00000000..acee5406 --- /dev/null +++ b/openai_agents/run_worker.py @@ -0,0 +1,56 @@ +from __future__ import annotations + +import asyncio +import concurrent.futures +from datetime import timedelta + +from temporalio import workflow +from temporalio.client import Client +from temporalio.contrib.openai_agents.invoke_model_activity import ModelActivity +from temporalio.contrib.openai_agents.open_ai_data_converter import ( + open_ai_data_converter, +) +from temporalio.contrib.openai_agents.temporal_openai_agents import ( + set_open_ai_agent_temporal_overrides, +) +from temporalio.worker import Worker + +from openai_agents.workflows.agents_as_tools_workflow import AgentsAsToolsWorkflow +from openai_agents.workflows.customer_service_workflow import CustomerServiceWorkflow +from openai_agents.workflows.get_weather_activity import get_weather +from openai_agents.workflows.hello_world_workflow import HelloWorldAgent +from openai_agents.workflows.research_bot_workflow import ResearchWorkflow +from openai_agents.workflows.tools_workflow import ToolsWorkflow + + +async def main(): + with set_open_ai_agent_temporal_overrides( + start_to_close_timeout=timedelta(seconds=60), + ): + # Create client connected to server at the given address + client = await Client.connect( + "localhost:7233", + data_converter=open_ai_data_converter, + ) + + model_activity = ModelActivity(model_provider=None) + worker = Worker( + client, + task_queue="openai-agents-task-queue", + workflows=[ + HelloWorldAgent, + ToolsWorkflow, + ResearchWorkflow, + CustomerServiceWorkflow, + AgentsAsToolsWorkflow, + ], + activities=[ + model_activity.invoke_model_activity, + get_weather, + ], + ) + await worker.run() + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/openai_agents/workflows/__init__.py b/openai_agents/workflows/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/openai_agents/workflows/agents_as_tools_workflow.py b/openai_agents/workflows/agents_as_tools_workflow.py new file mode 100644 index 00000000..76a68ea4 --- /dev/null +++ b/openai_agents/workflows/agents_as_tools_workflow.py @@ -0,0 +1,87 @@ +from temporalio import workflow + +with workflow.unsafe.imports_passed_through(): + from agents import Agent, ItemHelpers, MessageOutputItem, RunConfig, Runner, trace + +""" +This example shows the agents-as-tools pattern. The frontline agent receives a user message and +then picks which agents to call, as tools. In this case, it picks from a set of translation +agents. +""" + + +def orchestrator_agent() -> Agent: + spanish_agent = Agent( + name="spanish_agent", + instructions="You translate the user's message to Spanish", + handoff_description="An english to spanish translator", + ) + + french_agent = Agent( + name="french_agent", + instructions="You translate the user's message to French", + handoff_description="An english to french translator", + ) + + italian_agent = Agent( + name="italian_agent", + instructions="You translate the user's message to Italian", + handoff_description="An english to italian translator", + ) + + orchestrator_agent = Agent( + name="orchestrator_agent", + instructions=( + "You are a translation agent. You use the tools given to you to translate." + "If asked for multiple translations, you call the relevant tools in order." + "You never translate on your own, you always use the provided tools." + ), + tools=[ + spanish_agent.as_tool( + tool_name="translate_to_spanish", + tool_description="Translate the user's message to Spanish", + ), + french_agent.as_tool( + tool_name="translate_to_french", + tool_description="Translate the user's message to French", + ), + italian_agent.as_tool( + tool_name="translate_to_italian", + tool_description="Translate the user's message to Italian", + ), + ], + ) + return orchestrator_agent + + +def synthesizer_agent() -> Agent: + return Agent( + name="synthesizer_agent", + instructions="You inspect translations, correct them if needed, and produce a final concatenated response.", + ) + + +@workflow.defn +class AgentsAsToolsWorkflow: + @workflow.run + async def run(self, msg: str) -> str: + config = RunConfig() + + # Run the entire orchestration in a single trace + with trace("Orchestrator evaluator"): + orchestrator = orchestrator_agent() + synthesizer = synthesizer_agent() + + orchestrator_result = await Runner.run(orchestrator, msg, run_config=config) + + for item in orchestrator_result.new_items: + if isinstance(item, MessageOutputItem): + text = ItemHelpers.text_message_output(item) + if text: + workflow.logger.info(f" - Translation step: {text}") + + synthesizer_result = await Runner.run( + synthesizer, orchestrator_result.to_input_list(), run_config=config + ) + + return synthesizer_result.final_output diff --git a/openai_agents/workflows/customer_service.py b/openai_agents/workflows/customer_service.py new file mode 100644 index 00000000..6a08f4ed --- /dev/null +++ b/openai_agents/workflows/customer_service.py @@ -0,0 +1,129 @@ +from __future__ import annotations as _annotations + +from agents import Agent, RunContextWrapper, function_tool, handoff +from agents.extensions.handoff_prompt import RECOMMENDED_PROMPT_PREFIX +from pydantic import BaseModel +from temporalio import workflow + +### CONTEXT + + +class AirlineAgentContext(BaseModel): + passenger_name: str | None = None + confirmation_number: str | None = None + seat_number: str | None = None + flight_number: str | None = None + + +### TOOLS + + +@function_tool( + name_override="faq_lookup_tool", + description_override="Lookup frequently asked questions.", +) +async def faq_lookup_tool(question: str) -> str: + if "bag" in question or "baggage" in question: + return ( + "You are allowed to bring one bag on the plane. " + "It must be under 50 pounds and 22 inches x 14 inches x 9 inches." + ) + elif "seats" in question or "plane" in question: + return ( + "There are 120 seats on the plane. " + "There are 22 business class seats and 98 economy seats. " + "Exit rows are rows 4 and 16. " + "Rows 5-8 are Economy Plus, with extra legroom. " + ) + elif "wifi" in question: + return "We have free wifi on the plane, join Airline-Wifi" + return "I'm sorry, I don't know the answer to that question." + + +@function_tool +async def update_seat( + context: RunContextWrapper[AirlineAgentContext], + confirmation_number: str, + new_seat: str, +) -> str: + """ + Update the seat for a given confirmation number. + + Args: + confirmation_number: The confirmation number for the flight. + new_seat: The new seat to update to. + """ + # Update the context based on the customer's input + context.context.confirmation_number = confirmation_number + context.context.seat_number = new_seat + # Ensure that the flight number has been set by the incoming handoff + assert context.context.flight_number is not None, "Flight number is required" + return f"Updated seat to {new_seat} for confirmation number {confirmation_number}" + + +### HOOKS + + +async def on_seat_booking_handoff( + context: RunContextWrapper[AirlineAgentContext], +) -> None: + flight_number = f"FLT-{workflow.random().randint(100, 999)}" + context.context.flight_number = flight_number + + +### AGENTS + + +def init_agents() -> Agent[AirlineAgentContext]: + """ + Initialize the agents for the airline customer service workflow. + :return: triage agent + """ + faq_agent = Agent[AirlineAgentContext]( + name="FAQ Agent", + handoff_description="A helpful agent that can answer questions about the airline.", + instructions=f"""{RECOMMENDED_PROMPT_PREFIX} + You are an FAQ agent. If you are speaking to a customer, you probably were transferred to from the triage agent. + Use the following routine to support the customer. + # Routine + 1. Identify the last question asked by the customer. + 2. Use the faq lookup tool to answer the question. Do not rely on your own knowledge. + 3. If you cannot answer the question, transfer back to the triage agent.""", + tools=[faq_lookup_tool], + ) + + seat_booking_agent = Agent[AirlineAgentContext]( + name="Seat Booking Agent", + handoff_description="A helpful agent that can update a seat on a flight.", + instructions=f"""{RECOMMENDED_PROMPT_PREFIX} + You are a seat booking agent. If you are speaking to a customer, you probably were transferred to from the triage agent. + Use the following routine to support the customer. + # Routine + 1. Ask for their confirmation number. + 2. Ask the customer what their desired seat number is. + 3. Use the update seat tool to update the seat on the flight. + If the customer asks a question that is not related to the routine, transfer back to the triage agent. """, + tools=[update_seat], + ) + + triage_agent = Agent[AirlineAgentContext]( + name="Triage Agent", + handoff_description="A triage agent that can delegate a customer's request to the appropriate agent.", + instructions=( + f"{RECOMMENDED_PROMPT_PREFIX} " + "You are a helpful triaging agent. You can use your tools to delegate questions to other appropriate agents." + ), + handoffs=[ + faq_agent, + handoff(agent=seat_booking_agent, on_handoff=on_seat_booking_handoff), + ], + ) + + faq_agent.handoffs.append(triage_agent) + seat_booking_agent.handoffs.append(triage_agent) + return triage_agent + + +class ProcessUserMessageInput(BaseModel): + user_input: str + chat_length: int diff --git a/openai_agents/workflows/customer_service_workflow.py b/openai_agents/workflows/customer_service_workflow.py new file mode 100644 index 00000000..9a8d38fc --- /dev/null +++ b/openai_agents/workflows/customer_service_workflow.py @@ -0,0 +1,93 @@ +from __future__ import annotations as _annotations + +from temporalio import workflow + +with workflow.unsafe.imports_passed_through(): + from agents import ( + Agent, + HandoffOutputItem, + ItemHelpers, + MessageOutputItem, + RunConfig, + Runner, + ToolCallItem, + ToolCallOutputItem, + TResponseInputItem, + trace, + ) + + from openai_agents.workflows.customer_service import ( + AirlineAgentContext, + ProcessUserMessageInput, + init_agents, + ) + + +@workflow.defn +class CustomerServiceWorkflow: + @workflow.init + def __init__(self, input_items: list[TResponseInputItem] | None = None): + self.run_config = RunConfig() + self.chat_history: list[str] = [] + self.current_agent: Agent[AirlineAgentContext] = init_agents() + self.context = AirlineAgentContext() + self.input_items = [] if input_items is None else input_items + + @workflow.run + async def run(self, input_items: list[TResponseInputItem] | None = None): + await workflow.wait_condition( + lambda: workflow.info().is_continue_as_new_suggested() + and workflow.all_handlers_finished() + ) + workflow.continue_as_new(self.input_items) + + @workflow.query + def get_chat_history(self) -> list[str]: + return self.chat_history + + @workflow.update + async def process_user_message(self, input: ProcessUserMessageInput) -> list[str]: + length = len(self.chat_history) + self.chat_history.append(f"User: {input.user_input}") + with trace("Customer service", group_id=workflow.info().workflow_id): + self.input_items.append({"content": input.user_input, "role": "user"}) + result = await Runner.run( + self.current_agent, + self.input_items, + context=self.context, + run_config=self.run_config, + ) + + for new_item in result.new_items: + agent_name = new_item.agent.name + if isinstance(new_item, MessageOutputItem): + self.chat_history.append( + f"{agent_name}: {ItemHelpers.text_message_output(new_item)}" + ) + elif isinstance(new_item, HandoffOutputItem): + self.chat_history.append( + f"Handed off from {new_item.source_agent.name} to {new_item.target_agent.name}" + ) + elif isinstance(new_item, ToolCallItem): + self.chat_history.append(f"{agent_name}: Calling a tool") + elif isinstance(new_item, ToolCallOutputItem): + self.chat_history.append( + f"{agent_name}: Tool call output: {new_item.output}" + ) + else: + self.chat_history.append( + f"{agent_name}: Skipping item: {new_item.__class__.__name__}" + ) + self.input_items = result.to_input_list() + self.current_agent = result.last_agent + workflow.set_current_details("\n\n".join(self.chat_history)) + return self.chat_history[length:] + + @process_user_message.validator + def validate_process_user_message(self, input: ProcessUserMessageInput) -> None: + if not input.user_input: + raise ValueError("User input cannot be empty.") + if len(input.user_input) > 1000: + raise ValueError("User input is too long. Please limit to 1000 characters.") + if input.chat_length != len(self.chat_history): + raise ValueError("Stale chat history. Please refresh the chat.") diff --git a/openai_agents/workflows/get_weather_activity.py b/openai_agents/workflows/get_weather_activity.py new file mode 100644 index 00000000..c8be473c --- /dev/null +++ b/openai_agents/workflows/get_weather_activity.py @@ -0,0 +1,18 @@ +from dataclasses import dataclass + +from temporalio import activity + + +@dataclass +class Weather: + city: str + temperature_range: str + conditions: str + + +@activity.defn +async def get_weather(city: str) -> Weather: + """ + Get the weather for a given city. + """ + return Weather(city=city, temperature_range="14-20C", conditions="Sunny with wind.") diff --git a/openai_agents/workflows/hello_world_workflow.py b/openai_agents/workflows/hello_world_workflow.py new file mode 100644 index 00000000..aff1478e --- /dev/null +++ b/openai_agents/workflows/hello_world_workflow.py @@ -0,0 +1,18 @@ +from temporalio import workflow + +# Import agent Agent and Runner +with workflow.unsafe.imports_passed_through(): + from agents import Agent, Runner + + +@workflow.defn +class HelloWorldAgent: + @workflow.run + async def run(self, prompt: str) -> str: + agent = Agent( + name="Assistant", + instructions="You only respond in haikus.", + ) + + result = await Runner.run(agent, input=prompt) + return result.final_output diff --git a/openai_agents/workflows/research_agents/__init__.py b/openai_agents/workflows/research_agents/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/openai_agents/workflows/research_agents/planner_agent.py b/openai_agents/workflows/research_agents/planner_agent.py new file mode 100644 index 00000000..3e2f26de --- /dev/null +++ b/openai_agents/workflows/research_agents/planner_agent.py @@ -0,0 +1,29 @@ +from agents import Agent +from pydantic import BaseModel + +PROMPT = ( + "You are a helpful research assistant. Given a query, come up with a set of web searches " + "to perform to best answer the query. Output between 5 and 20 terms to query for." +) + + +class WebSearchItem(BaseModel): + reason: str + "Your reasoning for why this search is important to the query." + + query: str + "The search term to use for the web search." + + +class WebSearchPlan(BaseModel): + searches: list[WebSearchItem] + """A list of web searches to perform to best answer the query.""" + + +def new_planner_agent(): + return Agent( + name="PlannerAgent", + instructions=PROMPT, + model="gpt-4o", + output_type=WebSearchPlan, + ) diff --git a/openai_agents/workflows/research_agents/research_manager.py b/openai_agents/workflows/research_agents/research_manager.py new file mode 100644 index 00000000..19bdd224 --- /dev/null +++ b/openai_agents/workflows/research_agents/research_manager.py @@ -0,0 +1,81 @@ +from __future__ import annotations + +import asyncio + +from temporalio import workflow + +with workflow.unsafe.imports_passed_through(): + # TODO: Restore progress updates + from agents import RunConfig, Runner, custom_span, gen_trace_id, trace + + from openai_agents.workflows.research_agents.planner_agent import ( + WebSearchItem, + WebSearchPlan, + new_planner_agent, + ) + from openai_agents.workflows.research_agents.search_agent import new_search_agent + from openai_agents.workflows.research_agents.writer_agent import ( + ReportData, + new_writer_agent, + ) + + +class ResearchManager: + def __init__(self): + self.run_config = RunConfig() + self.search_agent = new_search_agent() + self.planner_agent = new_planner_agent() + self.writer_agent = new_writer_agent() + + async def run(self, query: str) -> str: + trace_id = gen_trace_id() + with trace("Research trace", trace_id=trace_id): + search_plan = await self._plan_searches(query) + search_results = await self._perform_searches(search_plan) + report = await self._write_report(query, search_results) + + return report.markdown_report + + async def _plan_searches(self, query: str) -> WebSearchPlan: + result = await Runner.run( + self.planner_agent, + f"Query: {query}", + run_config=self.run_config, + ) + return result.final_output_as(WebSearchPlan) + + async def _perform_searches(self, search_plan: WebSearchPlan) -> list[str]: + with custom_span("Search the web"): + num_completed = 0 + tasks = [ + asyncio.create_task(self._search(item)) for item in search_plan.searches + ] + results = [] + for task in workflow.as_completed(tasks): + result = await task + if result is not None: + results.append(result) + num_completed += 1 + return results + + async def _search(self, item: WebSearchItem) -> str | None: + input = f"Search term: {item.query}\nReason for searching: {item.reason}" + try: + result = await Runner.run( + self.search_agent, + input, + run_config=self.run_config, + ) + return str(result.final_output) + except Exception: + return None + + async def _write_report(self, query: str, search_results: list[str]) -> ReportData: + input = f"Original query: {query}\nSummarized search results: {search_results}" + result = await Runner.run( + self.writer_agent, + input, + run_config=self.run_config, + ) + + return result.final_output_as(ReportData) diff --git a/openai_agents/workflows/research_agents/search_agent.py b/openai_agents/workflows/research_agents/search_agent.py new file mode 100644 index 00000000..43c30ed8 --- /dev/null +++ b/openai_agents/workflows/research_agents/search_agent.py @@ -0,0 +1,20 @@ +from agents import Agent, WebSearchTool +from agents.model_settings import ModelSettings + +INSTRUCTIONS = ( + "You are a research assistant. Given a search term, you search the web for that term and " + "produce a concise summary of the results. The summary must 2-3 paragraphs and less than 300 " + "words. Capture the main points. Write succinctly, no need to have complete sentences or good " + "grammar. This will be consumed by someone synthesizing a report, so its vital you capture the " + "essence and ignore any fluff. Do not include any additional commentary other than the summary " + "itself." +) + + +def new_search_agent(): + return Agent( + name="Search agent", + instructions=INSTRUCTIONS, + tools=[WebSearchTool()], + model_settings=ModelSettings(tool_choice="required"), + ) diff --git a/openai_agents/workflows/research_agents/writer_agent.py b/openai_agents/workflows/research_agents/writer_agent.py new file mode 100644 index 00000000..9d8a34b0 --- /dev/null +++ b/openai_agents/workflows/research_agents/writer_agent.py @@ -0,0 +1,33 @@ +# Agent used to synthesize a final report from the individual summaries. +from agents import Agent +from pydantic import BaseModel + +PROMPT = ( + "You are a senior researcher tasked with writing a cohesive report for a research query. " + "You will be provided with the original query, and some initial research done by a research " + "assistant.\n" + "You should first come up with an outline for the report that describes the structure and " + "flow of the report. Then, generate the report and return that as your final output.\n" + "The final output should be in markdown format, and it should be lengthy and detailed. Aim " + "for 5-10 pages of content, at least 1000 words." +) + + +class ReportData(BaseModel): + short_summary: str + """A short 2-3 sentence summary of the findings.""" + + markdown_report: str + """The final report""" + + follow_up_questions: list[str] + """Suggested topics to research further""" + + +def new_writer_agent(): + return Agent( + name="WriterAgent", + instructions=PROMPT, + model="o3-mini", + output_type=ReportData, + ) diff --git a/openai_agents/workflows/research_bot_workflow.py b/openai_agents/workflows/research_bot_workflow.py new file mode 100644 index 00000000..c0779c02 --- /dev/null +++ b/openai_agents/workflows/research_bot_workflow.py @@ -0,0 +1,10 @@ +from temporalio import workflow + +from openai_agents.workflows.research_agents.research_manager import ResearchManager + + +@workflow.defn +class ResearchWorkflow: + @workflow.run + async def run(self, query: str) -> str: + return await ResearchManager().run(query) diff --git a/openai_agents/workflows/tools_workflow.py b/openai_agents/workflows/tools_workflow.py new file mode 100644 index 00000000..0b981f59 --- /dev/null +++ b/openai_agents/workflows/tools_workflow.py @@ -0,0 +1,30 @@ +from __future__ import annotations + +from datetime import timedelta + +from temporalio import workflow +from temporalio.contrib.openai_agents.temporal_tools import activity_as_tool + +# Import our activity, passing it through the sandbox +with workflow.unsafe.imports_passed_through(): + from agents import Agent, Runner + + from openai_agents.workflows.get_weather_activity import get_weather + + +@workflow.defn +class ToolsWorkflow: + @workflow.run + async def run(self, question: str) -> str: + agent = Agent( + name="Hello world", + instructions="You are a helpful agent.", + tools=[ + activity_as_tool( + get_weather, start_to_close_timeout=timedelta(seconds=10) + ) + ], + ) + + result = await Runner.run(agent, input=question) + return result.final_output diff --git a/patching/README.md b/patching/README.md index 61106f31..ac7c55c2 100644 --- a/patching/README.md +++ b/patching/README.md @@ -8,15 +8,15 @@ To run, first see [README.md](../README.md) for prerequisites. Then follow the p This stage is for existing running workflows. To simulate our initial workflow, run the worker in a separate terminal: - poetry run python worker.py --workflow initial + uv run worker.py --workflow initial Now we can start this workflow: - poetry run python starter.py --start-workflow initial-workflow-id + uv run starter.py --start-workflow initial-workflow-id This will output "Started workflow with ID initial-workflow-id and ...". Now query this workflow: - poetry run python starter.py --query-workflow initial-workflow-id + uv run starter.py --query-workflow initial-workflow-id This will output "Query result for ID initial-workflow-id: pre-patch". @@ -25,21 +25,21 @@ This will output "Query result for ID initial-workflow-id: pre-patch". This stage is for needing to run old and new workflows at the same time. To simulate our patched workflow, stop the worker from before and start it again with the patched workflow: - poetry run python worker.py --workflow patched + uv run worker.py --workflow patched Now let's start another workflow with this patched code: - poetry run python starter.py --start-workflow patched-workflow-id + uv run starter.py --start-workflow patched-workflow-id This will output "Started workflow with ID patched-workflow-id and ...". Now query the old workflow that's still running: - poetry run python starter.py --query-workflow initial-workflow-id + uv run starter.py --query-workflow initial-workflow-id This will output "Query result for ID initial-workflow-id: pre-patch" since it is pre-patch. But if we execute a query against the new code: - poetry run python starter.py --query-workflow patched-workflow-id + uv run starter.py --query-workflow patched-workflow-id We get "Query result for ID patched-workflow-id: post-patch". This is how old workflow code can take old paths and new workflow code can take new paths. @@ -50,22 +50,22 @@ Once we know that all workflows that started with the initial code from "Stage 1 the patch so we can deprecate it. To use the patch deprecated workflow, stop the workflow from before and start it again with: - poetry run python worker.py --workflow patch-deprecated + uv run worker.py --workflow patch-deprecated All workflows in "Stage 2" and any new workflows will work. Now let's start another workflow with this patch deprecated code: - poetry run python starter.py --start-workflow patch-deprecated-workflow-id + uv run starter.py --start-workflow patch-deprecated-workflow-id This will output "Started workflow with ID patch-deprecated-workflow-id and ...". Now query the patched workflow that's still running: - poetry run python starter.py --query-workflow patched-workflow-id + uv run starter.py --query-workflow patched-workflow-id This will output "Query result for ID patched-workflow-id: post-patch". And if we execute a query against the latest workflow: - poetry run python starter.py --query-workflow patch-deprecated-workflow-id + uv run starter.py --query-workflow patch-deprecated-workflow-id As expected, this will output "Query result for ID patch-deprecated-workflow-id: post-patch". @@ -75,22 +75,22 @@ Once we know we don't even have any workflows running on "Stage 2" or before (i. both code paths), we can just remove the patch deprecation altogether. To use the patch complete workflow, stop the workflow from before and start it again with: - poetry run python worker.py --workflow patch-complete + uv run worker.py --workflow patch-complete All workflows in "Stage 3" and any new workflows will work. Now let's start another workflow with this patch complete code: - poetry run python starter.py --start-workflow patch-complete-workflow-id + uv run starter.py --start-workflow patch-complete-workflow-id This will output "Started workflow with ID patch-complete-workflow-id and ...". Now query the patch deprecated workflow that's still running: - poetry run python starter.py --query-workflow patch-deprecated-workflow-id + uv run starter.py --query-workflow patch-deprecated-workflow-id This will output "Query result for ID patch-deprecated-workflow-id: post-patch". 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Then, run the following from this directory to run the sample: - poetry run python run_worker.py + uv run run_worker.py Then, in another terminal, run the following to execute the workflow: - poetry run python run_frequent.py + uv run run_frequent.py The Workflow will continue to poll the service and heartbeat on every iteration until it succeeds. diff --git a/polling/frequent/activities.py b/polling/frequent/activities.py index 2b49e379..a112b417 100644 --- a/polling/frequent/activities.py +++ b/polling/frequent/activities.py @@ -1,28 +1,19 @@ import asyncio -import time -from dataclasses import dataclass from temporalio import activity -from polling.test_service import TestService - - -@dataclass -class ComposeGreetingInput: - greeting: str - name: str +from polling.test_service import ComposeGreetingInput, get_service_result @activity.defn async def compose_greeting(input: ComposeGreetingInput) -> str: - test_service = TestService() while True: try: try: - result = await test_service.get_service_result(input) + result = await get_service_result(input) activity.logger.info(f"Exiting activity ${result}") return result - except Exception as e: + except Exception: # swallow exception since service is down activity.logger.debug("Failed, trying again shortly", exc_info=True) diff --git a/polling/infrequent/README.md b/polling/infrequent/README.md index c1b06d7f..b6afeb56 100644 --- a/polling/infrequent/README.md +++ b/polling/infrequent/README.md @@ -13,11 +13,11 @@ To run, first see [README.md](../../README.md) for prerequisites. Then, run the following from this directory to run the sample: - poetry run python run_worker.py + uv run run_worker.py Then, in another terminal, run the following to execute the workflow: - poetry run python run_infrequent.py + uv run run_infrequent.py Since the test service simulates being _down_ for four polling attempts and then returns _OK_ on the fifth poll attempt, the Workflow will perform four Activity retries with a 60-second poll interval, and then return the service result on the successful fifth attempt. diff --git a/polling/infrequent/activities.py b/polling/infrequent/activities.py index 2bd71587..b3db1aed 100644 --- a/polling/infrequent/activities.py +++ b/polling/infrequent/activities.py @@ -1,19 +1,10 @@ -from dataclasses import dataclass - from temporalio import activity -from polling.test_service import TestService - - -@dataclass -class ComposeGreetingInput: - greeting: str - name: str +from polling.test_service import ComposeGreetingInput, get_service_result @activity.defn async def compose_greeting(input: ComposeGreetingInput) -> str: - test_service = TestService() # If this raises an exception because it's not done yet, the activity will # continually be scheduled for retry - return await test_service.get_service_result(input) + return await get_service_result(input) diff --git a/polling/periodic_sequence/README.md b/polling/periodic_sequence/README.md index f8416588..d632862d 100644 --- a/polling/periodic_sequence/README.md +++ b/polling/periodic_sequence/README.md @@ -8,11 +8,11 @@ To run, first see [README.md](../../README.md) for prerequisites. Then, run the following from this directory to run the sample: - poetry run python run_worker.py + uv run run_worker.py Then, in another terminal, run the following to execute the workflow: - poetry run python run_periodic.py + uv run run_periodic.py This will start a Workflow and Child Workflow to periodically poll an Activity. diff --git a/polling/periodic_sequence/activities.py b/polling/periodic_sequence/activities.py index 1a1196c6..87b69890 100644 --- a/polling/periodic_sequence/activities.py +++ b/polling/periodic_sequence/activities.py @@ -1,14 +1,8 @@ -from dataclasses import dataclass +from typing import Any, NoReturn from temporalio import activity -@dataclass -class ComposeGreetingInput: - greeting: str - name: str - - @activity.defn -async def compose_greeting(input: ComposeGreetingInput) -> str: +async def compose_greeting(input: Any) -> NoReturn: raise RuntimeError("Service is down") diff --git a/polling/periodic_sequence/workflows.py b/polling/periodic_sequence/workflows.py index d38d41ce..3c6d7555 100644 --- a/polling/periodic_sequence/workflows.py +++ b/polling/periodic_sequence/workflows.py @@ -6,10 +6,8 @@ from temporalio.exceptions import ActivityError with workflow.unsafe.imports_passed_through(): - from polling.periodic_sequence.activities import ( - ComposeGreetingInput, - compose_greeting, - ) + from polling.periodic_sequence.activities import compose_greeting + from polling.test_service import ComposeGreetingInput @workflow.defn @@ -40,6 +38,5 @@ async def run(self, name: str) -> str: except ActivityError: workflow.logger.error("Activity failed, retrying in 1 seconds") await asyncio.sleep(1) - workflow.continue_as_new(name) - raise Exception("Polling failed after all attempts") + workflow.continue_as_new(name) diff --git a/polling/test_service.py b/polling/test_service.py index 3744998a..63494572 100644 --- a/polling/test_service.py +++ b/polling/test_service.py @@ -1,14 +1,30 @@ -class TestService: - def __init__(self): - self.try_attempts = 0 - self.error_attempts = 5 - - async def get_service_result(self, input): - print( - f"Attempt {self.try_attempts}" - f" of {self.error_attempts} to invoke service" - ) - self.try_attempts += 1 - if self.try_attempts % self.error_attempts == 0: - return f"{input.greeting}, {input.name}!" - raise Exception("service is down") +from dataclasses import dataclass +from typing import Counter + +from temporalio import activity +from temporalio.exceptions import ApplicationError, ApplicationErrorCategory + +attempts = Counter[str]() +ERROR_ATTEMPTS = 5 + + +@dataclass +class ComposeGreetingInput: + greeting: str + name: str + + +async def get_service_result(input): + workflow_id = activity.info().workflow_id + attempts[workflow_id] += 1 + + print(f"Attempt {attempts[workflow_id]} of {ERROR_ATTEMPTS} to invoke service") + if attempts[workflow_id] == ERROR_ATTEMPTS: + return f"{input.greeting}, {input.name}!" + raise ApplicationError( + message="service is down", + # Set the error as BENIGN to indicate it is an expected error. + # BENIGN errors have activity failure logs downgraded to DEBUG level + # and do not emit activity failure metrics. + category=ApplicationErrorCategory.BENIGN, + ) diff --git a/prometheus/README.md b/prometheus/README.md index 6f605d62..091d5171 100644 --- a/prometheus/README.md +++ b/prometheus/README.md @@ -5,13 +5,13 @@ This sample shows how to have SDK Prometheus metrics made available via HTTP. To run, first see [README.md](../README.md) for prerequisites. Then, run the following from this directory to start the worker: - poetry run python worker.py + uv run worker.py This will start the worker and the metrics will be visible for this process at http://127.0.0.1:9000/metrics. Then, in another terminal, run the following to execute a workflow: - poetry run python starter.py + uv run starter.py After executing the workflow, the process will stay open so the metrics if this separate process can be accessed at http://127.0.0.1:9001/metrics. \ No newline at end of file diff --git a/pydantic_converter/README.md b/pydantic_converter/README.md index 5914fa3d..bdbf0329 100644 --- a/pydantic_converter/README.md +++ b/pydantic_converter/README.md @@ -1,31 +1,19 @@ # Pydantic Converter Sample -This sample shows how to create a custom Pydantic converter to properly serialize Pydantic models. +This sample shows how to use the Pydantic data converter. -For this sample, the optional `pydantic` dependency group must be included. To include, run: +For this sample, the optional `pydantic_converter` dependency group must be included. To include, run: - poetry install --with pydantic + uv sync --group pydantic-converter To run, first see [README.md](../README.md) for prerequisites. Then, run the following from this directory to start the worker: - poetry run python worker.py + uv run worker.py This will start the worker. Then, in another terminal, run the following to execute the workflow: - poetry run python starter.py + uv run starter.py In the worker terminal, the workflow and its activity will log that it received the Pydantic models. In the starter terminal, the Pydantic models in the workflow result will be logged. - -### Notes - -This is the preferred way to use Pydantic models with Temporal Python SDK. The converter code is small and meant to -embed into other projects. - -This sample also demonstrates use of `datetime` inside of Pydantic models. Due to a known issue with the Temporal -sandbox, this class is seen by Pydantic as `date` instead of `datetime` upon deserialization. This is due to a -[known Python issue](https://github.com/python/cpython/issues/89010) where, when we proxy the `datetime` class in the -sandbox to prevent non-deterministic calls like `now()`, `issubclass` fails for the proxy type causing Pydantic to think -it's a `date` instead. In `worker.py`, we have shown a workaround of disabling restrictions on `datetime` which solves -this issue but no longer protects against workflow developers making non-deterministic calls in that module. \ No newline at end of file diff --git a/pydantic_converter/starter.py b/pydantic_converter/starter.py index 5aceca6e..7cc4cc2d 100644 --- a/pydantic_converter/starter.py +++ b/pydantic_converter/starter.py @@ -4,8 +4,8 @@ from ipaddress import IPv4Address from temporalio.client import Client +from temporalio.contrib.pydantic import pydantic_data_converter -from pydantic_converter.converter import pydantic_data_converter from pydantic_converter.worker import MyPydanticModel, MyWorkflow @@ -29,7 +29,7 @@ async def main(): some_date=datetime(2001, 2, 3, 4, 5, 6), ), ], - id=f"pydantic_converter-workflow-id", + id="pydantic_converter-workflow-id", task_queue="pydantic_converter-task-queue", ) logging.info("Got models from client: %s" % result) diff --git a/pydantic_converter/worker.py b/pydantic_converter/worker.py index b7e0bedf..eac0966c 100644 --- a/pydantic_converter/worker.py +++ b/pydantic_converter/worker.py @@ -1,5 +1,4 @@ import asyncio -import dataclasses import logging from datetime import datetime, timedelta from ipaddress import IPv4Address @@ -8,17 +7,12 @@ from temporalio import activity, workflow from temporalio.client import Client from temporalio.worker import Worker -from temporalio.worker.workflow_sandbox import ( - SandboxedWorkflowRunner, - SandboxRestrictions, -) -# We always want to pass through external modules to the sandbox that we know -# are safe for workflow use +# Always pass through external modules to the sandbox that you know are safe for +# workflow use with workflow.unsafe.imports_passed_through(): from pydantic import BaseModel - - from pydantic_converter.converter import pydantic_data_converter + from temporalio.contrib.pydantic import pydantic_data_converter class MyPydanticModel(BaseModel): @@ -42,29 +36,6 @@ async def run(self, models: List[MyPydanticModel]) -> List[MyPydanticModel]: ) -# Due to known issues with Pydantic's use of issubclass and our inability to -# override the check in sandbox, Pydantic will think datetime is actually date -# in the sandbox. At the expense of protecting against datetime.now() use in -# workflows, we're going to remove datetime module restrictions. See sdk-python -# README's discussion of known sandbox issues for more details. -def new_sandbox_runner() -> SandboxedWorkflowRunner: - # TODO(cretz): Use with_child_unrestricted when https://github.com/temporalio/sdk-python/issues/254 - # is fixed and released - invalid_module_member_children = dict( - SandboxRestrictions.invalid_module_members_default.children - ) - del invalid_module_member_children["datetime"] - return SandboxedWorkflowRunner( - restrictions=dataclasses.replace( - SandboxRestrictions.default, - invalid_module_members=dataclasses.replace( - SandboxRestrictions.invalid_module_members_default, - children=invalid_module_member_children, - ), - ) - ) - - interrupt_event = asyncio.Event() @@ -81,7 +52,6 @@ async def main(): task_queue="pydantic_converter-task-queue", workflows=[MyWorkflow], activities=[my_activity], - workflow_runner=new_sandbox_runner(), ): # Wait until interrupted print("Worker started, ctrl+c to exit") diff --git a/pydantic_converter_v1/README.md b/pydantic_converter_v1/README.md new file mode 100644 index 00000000..a38b00fc --- /dev/null +++ b/pydantic_converter_v1/README.md @@ -0,0 +1,31 @@ +# Pydantic v1 Converter Sample + +**This sample shows how to use Pydantic v1 with Temporal. This is not recommended: use Pydantic v2 if possible, and use the +main [pydantic_converter](../pydantic_converter/README.md) sample.** + +To install, run: + + uv sync --group pydantic-converter + uv run pip uninstall pydantic pydantic-core + uv run pip install pydantic==1.10 + +To run, first see the root [README.md](../README.md) for prerequisites. Then, run the following from this directory to start the +worker: + + uv run worker.py + +This will start the worker. Then, in another terminal, run the following to execute the workflow: + + uv run starter.py + +In the worker terminal, the workflow and its activity will log that it received the Pydantic models. In the starter +terminal, the Pydantic models in the workflow result will be logged. + +### Notes + +This sample also demonstrates use of `datetime` inside of Pydantic v1 models. Due to a known issue with the Temporal +sandbox, this class is seen by Pydantic v1 as `date` instead of `datetime` upon deserialization. This is due to a +[known Python issue](https://github.com/python/cpython/issues/89010) where, when we proxy the `datetime` class in the +sandbox to prevent non-deterministic calls like `now()`, `issubclass` fails for the proxy type causing Pydantic v1 to think +it's a `date` instead. In `worker.py`, we have shown a workaround of disabling restrictions on `datetime` which solves +this issue but no longer protects against workflow developers making non-deterministic calls in that module. \ No newline at end of file diff --git a/pydantic_converter_v1/__init__.py b/pydantic_converter_v1/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/pydantic_converter/converter.py b/pydantic_converter_v1/converter.py similarity index 89% rename from pydantic_converter/converter.py rename to pydantic_converter_v1/converter.py index a3c1cee6..81997e81 100644 --- a/pydantic_converter/converter.py +++ b/pydantic_converter_v1/converter.py @@ -42,9 +42,11 @@ class PydanticPayloadConverter(CompositePayloadConverter): def __init__(self) -> None: super().__init__( *( - c - if not isinstance(c, JSONPlainPayloadConverter) - else PydanticJSONPayloadConverter() + ( + c + if not isinstance(c, JSONPlainPayloadConverter) + else PydanticJSONPayloadConverter() + ) for c in DefaultPayloadConverter.default_encoding_payload_converters ) ) diff --git a/pydantic_converter_v1/starter.py b/pydantic_converter_v1/starter.py new file mode 100644 index 00000000..8ab58bdc --- /dev/null +++ b/pydantic_converter_v1/starter.py @@ -0,0 +1,39 @@ +import asyncio +import logging +from datetime import datetime +from ipaddress import IPv4Address + +from temporalio.client import Client + +from pydantic_converter_v1.converter import pydantic_data_converter +from pydantic_converter_v1.worker import MyPydanticModel, MyWorkflow + + +async def main(): + logging.basicConfig(level=logging.INFO) + # Connect client using the Pydantic converter + client = await Client.connect( + "localhost:7233", data_converter=pydantic_data_converter + ) + + # Run workflow + result = await client.execute_workflow( + MyWorkflow.run, + [ + MyPydanticModel( + some_ip=IPv4Address("127.0.0.1"), + some_date=datetime(2000, 1, 2, 3, 4, 5), + ), + MyPydanticModel( + some_ip=IPv4Address("127.0.0.2"), + some_date=datetime(2001, 2, 3, 4, 5, 6), + ), + ], + id="pydantic_converter-workflow-id", + task_queue="pydantic_converter-task-queue", + ) + logging.info("Got models from client: %s" % result) + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/pydantic_converter_v1/worker.py b/pydantic_converter_v1/worker.py new file mode 100644 index 00000000..5c22b6f1 --- /dev/null +++ b/pydantic_converter_v1/worker.py @@ -0,0 +1,98 @@ +import asyncio +import dataclasses +import logging +from datetime import datetime, timedelta +from ipaddress import IPv4Address +from typing import List + +from temporalio import activity, workflow +from temporalio.client import Client +from temporalio.worker import Worker +from temporalio.worker.workflow_sandbox import ( + SandboxedWorkflowRunner, + SandboxRestrictions, +) + +# We always want to pass through external modules to the sandbox that we know +# are safe for workflow use +with workflow.unsafe.imports_passed_through(): + from pydantic import BaseModel + + from pydantic_converter_v1.converter import pydantic_data_converter + + +class MyPydanticModel(BaseModel): + some_ip: IPv4Address + some_date: datetime + + +@activity.defn +async def my_activity(models: List[MyPydanticModel]) -> List[MyPydanticModel]: + activity.logger.info("Got models in activity: %s" % models) + return models + + +@workflow.defn +class MyWorkflow: + @workflow.run + async def run(self, models: List[MyPydanticModel]) -> List[MyPydanticModel]: + workflow.logger.info("Got models in workflow: %s" % models) + return await workflow.execute_activity( + my_activity, models, start_to_close_timeout=timedelta(minutes=1) + ) + + +# Due to known issues with Pydantic's use of issubclass and our inability to +# override the check in sandbox, Pydantic will think datetime is actually date +# in the sandbox. At the expense of protecting against datetime.now() use in +# workflows, we're going to remove datetime module restrictions. See sdk-python +# README's discussion of known sandbox issues for more details. +def new_sandbox_runner() -> SandboxedWorkflowRunner: + # TODO(cretz): Use with_child_unrestricted when https://github.com/temporalio/sdk-python/issues/254 + # is fixed and released + invalid_module_member_children = dict( + SandboxRestrictions.invalid_module_members_default.children + ) + del invalid_module_member_children["datetime"] + return SandboxedWorkflowRunner( + restrictions=dataclasses.replace( + SandboxRestrictions.default, + invalid_module_members=dataclasses.replace( + SandboxRestrictions.invalid_module_members_default, + children=invalid_module_member_children, + ), + ) + ) + + +interrupt_event = asyncio.Event() + + +async def main(): + logging.basicConfig(level=logging.INFO) + # Connect client using the Pydantic converter + client = await Client.connect( + "localhost:7233", data_converter=pydantic_data_converter + ) + + # Run a worker for the workflow + async with Worker( + client, + task_queue="pydantic_converter-task-queue", + workflows=[MyWorkflow], + activities=[my_activity], + workflow_runner=new_sandbox_runner(), + ): + # Wait until interrupted + print("Worker started, ctrl+c to exit") + await interrupt_event.wait() + print("Shutting down") + + +if __name__ == "__main__": + loop = asyncio.new_event_loop() + try: + loop.run_until_complete(main()) + except KeyboardInterrupt: + interrupt_event.set() + loop.run_until_complete(loop.shutdown_asyncgens()) diff --git a/pyproject.toml b/pyproject.toml index eecb7428..b82bd912 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,85 +1,133 @@ -[tool.poetry] +[project] name = "temporalio-samples" version = "0.1a1" description = "Temporal.io Python SDK samples" -license = "MIT" -authors = ["Temporal Technologies Inc "] +authors = [{ name = "Temporal Technologies Inc", email = "sdk@temporal.io" }] +requires-python = "~=3.9" readme = "README.md" -homepage = "https://github.com/temporalio/samples-python" -repository = "https://github.com/temporalio/samples-python" -documentation = "https://docs.temporal.io/docs/python" -packages = [ - { include = "**/*.py", from = "." } -] +license = "MIT" +dependencies = ["temporalio>=1.13.0,<2"] -[tool.poetry.urls] +[project.urls] +Homepage = "https://github.com/temporalio/samples-python" +Repository = "https://github.com/temporalio/samples-python" +Documentation = "https://docs.temporal.io/docs/python" "Bug Tracker" = "https://github.com/temporalio/samples-python/issues" -[tool.poetry.dependencies] -python = "^3.8" -temporalio = "^1.7.0" - -[tool.poetry.dev-dependencies] -black = "^22.3.0" -isort = "^5.10.1" -mypy = "^0.981" -pytest = "^7.1.2" -pytest-asyncio = "^0.18.3" -frozenlist = "^1.4.0" - -# All sample-specific dependencies are in optional groups below, named after the -# sample they apply to - -[tool.poetry.group.bedrock] -optional = true -[tool.poetry.group.bedrock.dependencies] -boto3 = "^1.34.92" - -[tool.poetry.group.dsl] -optional = true -dependencies = { pyyaml = "^6.0.1", types-pyyaml = "^6.0.12", dacite = "^1.8.1" } - -[tool.poetry.group.encryption] -optional = true -dependencies = { cryptography = "^38.0.1", aiohttp = "^3.8.1" } +[dependency-groups] +dev = [ + "black>=22.3.0,<23", + "isort>=5.10.1,<6", + "mypy>=1.4.1,<2", + "pytest>=7.1.2,<8", + "pytest-asyncio>=0.18.3,<0.19", + "frozenlist>=1.4.0,<2", + "types-pyyaml>=6.0.12.20241230,<7", +] +bedrock = ["boto3>=1.34.92,<2"] +dsl = [ + "pyyaml>=6.0.1,<7", + "types-pyyaml>=6.0.12,<7", + "dacite>=1.8.1,<2", +] +encryption = [ + "cryptography>=38.0.1,<39", + "aiohttp>=3.8.1,<4", +] +gevent = ["gevent==25.4.2 ; python_version >= '3.8'"] +langchain = [ + "langchain>=0.1.7,<0.2 ; python_version >= '3.8.1' and python_version < '4.0'", + "langchain-openai>=0.0.6,<0.0.7 ; python_version >= '3.8.1' and python_version < '4.0'", + "langsmith>=0.1.22,<0.2 ; python_version >= '3.8.1' and python_version < '4.0'", + "openai>=1.4.0,<2", + "fastapi>=0.115.12", + "tqdm>=4.62.0,<5", + "uvicorn[standard]>=0.24.0.post1,<0.25", +] +open-telemetry = [ + "temporalio[opentelemetry]", + "opentelemetry-exporter-otlp-proto-grpc==1.18.0", +] +openai-agents = [ + "openai-agents >= 0.0.19", + "temporalio[openai-agents] >= 1.13.0", +] +pydantic-converter = ["pydantic>=2.10.6,<3"] +sentry = ["sentry-sdk>=1.11.0,<2"] +trio-async = [ + "trio>=0.28.0,<0.29", + "trio-asyncio>=0.15.0,<0.16", +] +cloud-export-to-parquet = [ + "pandas>=2.2.2,<3 ; python_version >= '3.9' and python_version < '4.0'", + "numpy>=1.26.0,<2 ; python_version >= '3.9' and python_version < '3.13'", + "boto3>=1.34.89,<2", + "pyarrow>=19.0.1", +] -[tool.poetry.group.gevent] -optional = true -dependencies = { gevent = { version = "^23.9.1", python = ">=3.8" } } +[tool.uv] +default-groups = [ + "dev", + "bedrock", + "dsl", + "encryption", + "gevent", + "langchain", + "open-telemetry", + "pydantic-converter", + "sentry", + "trio-async", +] -[tool.poetry.group.langchain] -optional = true -[tool.poetry.group.langchain.dependencies] -langchain = {version = "^0.1.7", python = ">=3.8.1,<4.0"} -langchain-openai = {version = "^0.0.6", python = ">=3.8.1,<4.0"} -openai = "^1.4.0" -fastapi = "^0.105.0" -tqdm = "^4.62.0" -uvicorn = { version = "^0.24.0.post1", extras = ["standard"]} +[tool.hatch.build.targets.sdist] +include = ["./**/*.py"] -[tool.poetry.group.open_telemetry] -optional = true -[tool.poetry.group.open_telemetry.dependencies] -temporalio = { version = "*", extras = ["opentelemetry"] } -opentelemetry-exporter-otlp-proto-grpc = "1.18.0" +[tool.hatch.build.targets.wheel] +include = ["./**/*.py"] +packages = [ + "activity_worker", + "bedrock", + "cloud_export_to_parquet", + "context_propagation", + "custom_converter", + "custom_decorator", + "custom_metric", + "dsl", + "encryption", + "gevent_async", + "hello", + "langchain", + "message_passing", + "open_telemetry", + "patching", + "polling", + "prometheus", + "pydantic_converter", + "pydantic_converter_v1", + "pyproject.toml", + "replay", + "schedules", + "sentry", + "sleep_for_days", + "tests", + "trio_async", + "updatable_timer", + "worker_specific_task_queues", + "worker_versioning", +] -[tool.poetry.group.pydantic] -optional = true -dependencies = { pydantic = "^1.10.4" } +[tool.hatch.build.targets.wheel.sources] +"./**/*.py" = "**/*.py" -[tool.poetry.group.sentry] -optional = true -dependencies = { sentry-sdk = "^1.11.0" } +[build-system] +requires = ["hatchling"] +build-backend = "hatchling.build" [tool.poe.tasks] -format = [{cmd = "black ."}, {cmd = "isort ."}] -lint = [{cmd = "black --check ."}, {cmd = "isort --check-only ."}, {ref = "lint-types" }] -lint-types = "mypy --check-untyped-defs --namespace-packages ." -test = "pytest" - -[build-system] -requires = ["poetry-core>=1.0.0"] -build-backend = "poetry.core.masonry.api" +format = [{cmd = "uv run black ."}, {cmd = "uv run isort ."}] +lint = [{cmd = "uv run black --check ."}, {cmd = "uv run isort --check-only ."}, {ref = "lint-types" }] +lint-types = "uv run mypy --check-untyped-defs --namespace-packages ." +test = "uv run pytest" [tool.pytest.ini_options] asyncio_mode = "auto" @@ -102,12 +150,3 @@ ignore_errors = true [[tool.mypy.overrides]] module = "opentelemetry.*" ignore_errors = true - -[tool.poetry.group.cloud_export_to_parquet] -optional = true -[tool.poetry.group.cloud_export_to_parquet.dependencies] -pandas = {version = "^2.2.2",python = ">=3.9,<4.0"} -numpy = {version = "^1.26.0",python = ">=3.9,<3.13"} -pyarrow = "^16.0.0" -boto3 = "^1.34.89" - diff --git a/replay/README.md b/replay/README.md index 3a67868a..4b220f9d 100644 --- a/replay/README.md +++ b/replay/README.md @@ -6,15 +6,15 @@ workflow histories. To run, first see [README.md](../README.md) for prerequisites. Then, run the following from this directory to start the worker: - poetry run python worker.py + uv run worker.py This will start the worker. Then, in another terminal, run the following to execute a workflow: - poetry run python starter.py + uv run starter.py Next, run the replayer: - poetry run python replayer.py + uv run replayer.py Which should produce some output like: diff --git a/resource_pool/README.md b/resource_pool/README.md new file mode 100644 index 00000000..143de0f3 --- /dev/null +++ b/resource_pool/README.md @@ -0,0 +1,48 @@ +# Resource Pool Sample + +This sample shows how to use a long-lived `ResourcePoolWorkflow` to allocate `resources` to `ResourceUserWorkflows`. +Each `ResourceUserWorkflow` runs several activities while it has ownership of a resource. Note that +`ResourcePoolWorkflow` is making resource allocation decisions based on in-memory state. + +Run the following from this directory to start the worker: + + uv run worker.py + +This will start the worker. Then, in another terminal, run the following to execute several `ResourceUserWorkflows`. + + uv run starter.py + +You should see output indicating that the `ResourcePoolWorkflow` serialized access to each resource. + +You can query the set of current resource resource holders with: + + tctl wf query -w resource_pool --qt get_current_holders + +# Other approaches + +There are simpler ways to manage concurrent access to resources. Consider using resource-specific workers/task queues, +and limiting the number of activity slots on the workers. The golang SDK also [sessions](https://docs.temporal.io/develop/go/sessions) +that allow workflows to pin themselves to workers. + +The technique in this sample is capable of more complex resource allocation than the options above, but it doesn't scale +as well. Specifically, it can: +- Manage access to a set of resources that is decoupled from the set of workers and task queues +- Run arbitrary code to place workloads on resources as they become available + +# Caveats + +This sample uses true locking (not leasing!) to avoid complexity and scaling concerns associated with heartbeating via +signals. Locking carries a risk where failure to unlock permanently removing a resource from the pool. However, with +Temporal's durable execution guarantees, this can only happen if: + +- A ResourceUserWorkflows times out (prohibited in the sample code) +- An operator terminates a ResourceUserWorkflows. (Temporal recommends canceling workflows instead of terminating them whenever possible.) +- You shut down your workers and never restart them (unhandled, but irrelevant) + +If a leak were to happen, you could discover the identity of the leaker using the query above, then: + + tctl wf signal -w resource_pool --name release_resource --input '{ "release_key": "" } + +Performance: A single ResourcePoolWorkflow scales to tens, but not hundreds, of request/release events per second. It is +best suited for allocating resources to long-running workflows. Actual performance will depend on your temporal server's +persistence layer. \ No newline at end of file diff --git a/resource_pool/__init__.py b/resource_pool/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/resource_pool/pool_client/__init__.py b/resource_pool/pool_client/__init__.py new file mode 100644 index 00000000..b8471d8a --- /dev/null +++ b/resource_pool/pool_client/__init__.py @@ -0,0 +1,2 @@ +from .resource_pool_client import ResourcePoolClient +from .resource_pool_workflow import ResourcePoolWorkflow diff --git a/resource_pool/pool_client/resource_pool_client.py b/resource_pool/pool_client/resource_pool_client.py new file mode 100644 index 00000000..b7183afa --- /dev/null +++ b/resource_pool/pool_client/resource_pool_client.py @@ -0,0 +1,101 @@ +from contextlib import asynccontextmanager +from datetime import timedelta +from typing import AsyncGenerator, Optional + +from temporalio import workflow + +from resource_pool.pool_client.resource_pool_workflow import ResourcePoolWorkflow +from resource_pool.shared import ( + AcquiredResource, + AcquireRequest, + AcquireResponse, + DetachedResource, +) + + +# Use this class in workflow code that that needs to run on locked resources. +class ResourcePoolClient: + def __init__(self, pool_workflow_id: str) -> None: + self.pool_workflow_id = pool_workflow_id + self.acquired_resources: list[AcquiredResource] = [] + + signal_name = f"assign_resource_{self.pool_workflow_id}" + if workflow.get_signal_handler(signal_name) is None: + workflow.set_signal_handler(signal_name, self._handle_acquire_response) + else: + raise RuntimeError( + f"{signal_name} already registered - if you use multiple ResourcePoolClients within the " + f"same workflow, they must use different pool_workflow_ids" + ) + + def _handle_acquire_response(self, response: AcquireResponse) -> None: + self.acquired_resources.append( + AcquiredResource( + resource=response.resource, release_key=response.release_key + ) + ) + + async def _send_acquire_signal(self) -> None: + await workflow.get_external_workflow_handle_for( + ResourcePoolWorkflow.run, self.pool_workflow_id + ).signal("acquire_resource", AcquireRequest(workflow.info().workflow_id)) + + async def _send_release_signal(self, acquired_resource: AcquiredResource) -> None: + await workflow.get_external_workflow_handle_for( + ResourcePoolWorkflow.run, self.pool_workflow_id + ).signal( + "release_resource", + AcquireResponse( + resource=acquired_resource.resource, + release_key=acquired_resource.release_key, + ), + ) + + @asynccontextmanager + async def acquire_resource( + self, + *, + reattach: Optional[DetachedResource] = None, + max_wait_time: timedelta = timedelta(minutes=5), + ) -> AsyncGenerator[AcquiredResource, None]: + _warn_when_workflow_has_timeouts() + + if reattach is None: + await self._send_acquire_signal() + await workflow.wait_condition( + lambda: len(self.acquired_resources) > 0, timeout=max_wait_time + ) + resource = self.acquired_resources.pop(0) + else: + resource = AcquiredResource( + resource=reattach.resource, release_key=reattach.release_key + ) + + # Can't happen, but the typechecker doesn't know about workflow.wait_condition + if resource is None: + raise RuntimeError("resource was None when it can't be") + + # During the yield, the calling workflow owns the resource. Note that this is a lock, not a lease! Our + # finally block will release the resource if an activity fails. This is why we asserted the lack of + # workflow-level timeouts above - the finally block wouldn't run if there was a timeout. + try: + yield resource + finally: + if not resource.detached: + await self._send_release_signal(resource) + + +def _warn_when_workflow_has_timeouts() -> None: + def has_timeout(timeout: Optional[timedelta]) -> bool: + # After continue_as_new, timeouts are 0, even if they were None before continue_as_new (and were not set in the + # continue_as_new call). + return timeout is not None and timeout > timedelta(0) + + if has_timeout(workflow.info().run_timeout): + workflow.logger.warning( + f"ResourceLockingWorkflow cannot have a run_timeout (found {workflow.info().run_timeout}) - this will leak locks" + ) + if has_timeout(workflow.info().execution_timeout): + workflow.logger.warning( + f"ResourceLockingWorkflow cannot have an execution_timeout (found {workflow.info().execution_timeout}) - this will leak locks" + ) diff --git a/resource_pool/pool_client/resource_pool_workflow.py b/resource_pool/pool_client/resource_pool_workflow.py new file mode 100644 index 00000000..2321f82d --- /dev/null +++ b/resource_pool/pool_client/resource_pool_workflow.py @@ -0,0 +1,149 @@ +from dataclasses import dataclass +from typing import Optional + +from temporalio import workflow +from temporalio.exceptions import ApplicationError + +from resource_pool.shared import AcquireRequest, AcquireResponse + + +# Internal to this workflow, we'll associate randomly generated release signal names with each acquire request. +@dataclass +class InternalAcquireRequest(AcquireRequest): + release_signal: Optional[str] + + +@dataclass +class ResourcePoolWorkflowInput: + # Key is resource, value is current holder of the resource (None if not held) + resources: dict[str, Optional[InternalAcquireRequest]] + waiters: list[InternalAcquireRequest] + + +@workflow.defn +class ResourcePoolWorkflow: + @workflow.init + def __init__(self, input: ResourcePoolWorkflowInput) -> None: + self.resources = input.resources + self.waiters = input.waiters + self.release_key_to_resource: dict[str, str] = {} + + for resource, holder in self.resources.items(): + if holder is not None and holder.release_signal is not None: + self.release_key_to_resource[holder.release_signal] = resource + + @workflow.signal + async def add_resources(self, resources: list[str]) -> None: + for resource in resources: + if resource in self.resources: + workflow.logger.warning( + f"Ignoring attempt to add already-existing resource: {resource}" + ) + else: + self.resources[resource] = None + + @workflow.signal + async def acquire_resource(self, request: AcquireRequest) -> None: + self.waiters.append( + InternalAcquireRequest(workflow_id=request.workflow_id, release_signal=None) + ) + workflow.logger.info( + f"workflow_id={request.workflow_id} is waiting for a resource" + ) + + @workflow.signal + async def release_resource(self, acquire_response: AcquireResponse) -> None: + release_key = acquire_response.release_key + resource = self.release_key_to_resource.get(release_key) + if resource is None: + workflow.logger.warning(f"Ignoring unknown release_key: {release_key}") + return + + holder = self.resources[resource] + if holder is None: + workflow.logger.warning( + f"Ignoring request to release resource that is not held: {resource}" + ) + return + + # Remove the current holder + workflow.logger.info( + f"workflow_id={holder.workflow_id} released resource {resource}" + ) + self.resources[resource] = None + del self.release_key_to_resource[release_key] + + @workflow.query + def get_current_holders(self) -> dict[str, Optional[InternalAcquireRequest]]: + return self.resources + + async def assign_resource( + self, resource: str, internal_request: InternalAcquireRequest + ) -> None: + workflow.logger.info( + f"workflow_id={internal_request.workflow_id} acquired resource {resource}" + ) + + requester = workflow.get_external_workflow_handle(internal_request.workflow_id) + try: + release_signal = str(workflow.uuid4()) + await requester.signal( + f"assign_resource_{workflow.info().workflow_id}", + AcquireResponse(release_key=release_signal, resource=resource), + ) + + internal_request.release_signal = release_signal + self.resources[resource] = internal_request + self.release_key_to_resource[release_signal] = resource + except ApplicationError as e: + if e.type == "ExternalWorkflowExecutionNotFound": + workflow.logger.info( + f"Could not assign resource {resource} to {internal_request.workflow_id}: {e.message}" + ) + else: + raise e + + async def assign_next_resource(self) -> bool: + if len(self.waiters) == 0: + return False + + next_free_resource = self.get_free_resource() + if next_free_resource is None: + return False + + next_waiter = self.waiters.pop(0) + await self.assign_resource(next_free_resource, next_waiter) + return True + + def get_free_resource(self) -> Optional[str]: + return next( + (resource for resource, holder in self.resources.items() if holder is None), + None, + ) + + def can_assign_resource(self) -> bool: + return len(self.waiters) > 0 and self.get_free_resource() is not None + + def should_continue_as_new(self) -> bool: + return ( + workflow.info().is_continue_as_new_suggested() + and workflow.all_handlers_finished() + ) + + @workflow.run + async def run(self, _: ResourcePoolWorkflowInput) -> None: + while True: + await workflow.wait_condition( + lambda: self.can_assign_resource() or self.should_continue_as_new() + ) + + if await self.assign_next_resource(): + continue + + if self.should_continue_as_new(): + workflow.continue_as_new( + ResourcePoolWorkflowInput( + resources=self.resources, + waiters=self.waiters, + ) + ) diff --git a/resource_pool/resource_user_workflow.py b/resource_pool/resource_user_workflow.py new file mode 100644 index 00000000..80ee7fba --- /dev/null +++ b/resource_pool/resource_user_workflow.py @@ -0,0 +1,88 @@ +import asyncio +from dataclasses import dataclass, field +from datetime import timedelta +from typing import Optional + +from temporalio import activity, workflow + +from resource_pool.pool_client import ResourcePoolClient +from resource_pool.shared import DetachedResource + + +@dataclass +class UseResourceActivityInput: + resource: str + iteration: str + + +@activity.defn +async def use_resource(input: UseResourceActivityInput) -> None: + info = activity.info() + activity.logger.info( + f"{info.workflow_id} starts using {input.resource} the {input.iteration} time" + ) + await asyncio.sleep(3) + activity.logger.info( + f"{info.workflow_id} done using {input.resource} the {input.iteration} time" + ) + + +@dataclass +class ResourceUserWorkflowInput: + # The id of the resource pool workflow to request a resource from + resource_pool_workflow_id: str + + # If set, this workflow will fail after the "first" or "second" activity. + iteration_to_fail_after: Optional[str] + + # If True, this workflow will continue as new after the last activity. The next iteration will run more activities, + # but will not continue as new. + should_continue_as_new: bool + + # Used to transfer resource ownership between iterations during continue_as_new + already_acquired_resource: Optional[DetachedResource] = field(default=None) + + +class FailWorkflowException(Exception): + pass + + +# Wait this long for a resource before giving up +MAX_RESOURCE_WAIT_TIME = timedelta(minutes=5) + + +@workflow.defn(failure_exception_types=[FailWorkflowException]) +class ResourceUserWorkflow: + @workflow.run + async def run(self, input: ResourceUserWorkflowInput) -> None: + pool_client = ResourcePoolClient(input.resource_pool_workflow_id) + + async with pool_client.acquire_resource( + reattach=input.already_acquired_resource + ) as acquired_resource: + for iteration in ["first", "second"]: + await workflow.execute_activity( + use_resource, + UseResourceActivityInput(acquired_resource.resource, iteration), + start_to_close_timeout=timedelta(seconds=10), + ) + + if iteration == input.iteration_to_fail_after: + workflow.logger.info( + f"Failing after iteration {input.iteration_to_fail_after}" + ) + raise FailWorkflowException() + + # This workflow only continues as new so it can demonstrate how to pass acquired resources across + # iterations. Ordinarily, such a short workflow would not use continue as new. + if input.should_continue_as_new: + detached_resource = acquired_resource.detach() + + next_input = ResourceUserWorkflowInput( + resource_pool_workflow_id=input.resource_pool_workflow_id, + iteration_to_fail_after=input.iteration_to_fail_after, + should_continue_as_new=False, + already_acquired_resource=detached_resource, + ) + + workflow.continue_as_new(next_input) diff --git a/resource_pool/shared.py b/resource_pool/shared.py new file mode 100644 index 00000000..3930bb72 --- /dev/null +++ b/resource_pool/shared.py @@ -0,0 +1,31 @@ +from dataclasses import dataclass, field + +RESOURCE_POOL_WORKFLOW_ID = "resource_pool" + + +@dataclass +class AcquireRequest: + workflow_id: str + + +@dataclass +class AcquireResponse: + release_key: str + resource: str + + +@dataclass +class DetachedResource: + resource: str + release_key: str + + +@dataclass +class AcquiredResource: + resource: str + release_key: str + detached: bool = field(default=False) + + def detach(self) -> DetachedResource: + self.detached = True + return DetachedResource(resource=self.resource, release_key=self.release_key) diff --git a/resource_pool/starter.py b/resource_pool/starter.py new file mode 100644 index 00000000..2ae1ab44 --- /dev/null +++ b/resource_pool/starter.py @@ -0,0 +1,66 @@ +import asyncio +from typing import Any + +from temporalio.client import Client, WorkflowFailureError, WorkflowHandle +from temporalio.common import WorkflowIDConflictPolicy + +from resource_pool.pool_client.resource_pool_workflow import ( + ResourcePoolWorkflow, + ResourcePoolWorkflowInput, +) +from resource_pool.resource_user_workflow import ( + ResourceUserWorkflow, + ResourceUserWorkflowInput, +) +from resource_pool.shared import RESOURCE_POOL_WORKFLOW_ID + + +async def main() -> None: + # Connect client + client = await Client.connect("localhost:7233") + + # Initialize the resource pool + resource_pool_handle = await client.start_workflow( + workflow=ResourcePoolWorkflow.run, + arg=ResourcePoolWorkflowInput( + resources={"resource_a": None, "resource_b": None}, + waiters=[], + ), + id=RESOURCE_POOL_WORKFLOW_ID, + task_queue="resource_pool-task-queue", + id_conflict_policy=WorkflowIDConflictPolicy.USE_EXISTING, + ) + + # Start the ResourceUserWorkflows + resource_user_handles: list[WorkflowHandle[Any, Any]] = [] + for i in range(0, 4): + input = ResourceUserWorkflowInput( + resource_pool_workflow_id=RESOURCE_POOL_WORKFLOW_ID, + iteration_to_fail_after=None, + should_continue_as_new=False, + ) + if i == 0: + input.should_continue_as_new = True + if i == 1: + input.iteration_to_fail_after = "first" + + handle = await client.start_workflow( + workflow=ResourceUserWorkflow.run, + arg=input, + id=f"resource-user-workflow-{i}", + task_queue="resource_pool-task-queue", + ) + resource_user_handles.append(handle) + + for handle in resource_user_handles: + try: + await handle.result() + except WorkflowFailureError: + pass + + # Clean up after ourselves. In the real world, the resource pool workflow would run forever. + await resource_pool_handle.terminate() + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/resource_pool/worker.py b/resource_pool/worker.py new file mode 100644 index 00000000..cb3a06dd --- /dev/null +++ b/resource_pool/worker.py @@ -0,0 +1,31 @@ +import asyncio +import logging + +from temporalio.client import Client +from temporalio.worker import Worker + +from resource_pool.pool_client.resource_pool_workflow import ResourcePoolWorkflow +from resource_pool.resource_user_workflow import ResourceUserWorkflow, use_resource + + +async def main() -> None: + logging.basicConfig(level=logging.INFO) + + # Start client + client = await Client.connect("localhost:7233") + + # Run a worker for the workflow + worker = Worker( + client, + task_queue="resource_pool-task-queue", + workflows=[ResourcePoolWorkflow, ResourceUserWorkflow], + activities=[ + use_resource, + ], + ) + + await worker.run() + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/schedules/README.md b/schedules/README.md index 9bf40ca0..8327d769 100644 --- a/schedules/README.md +++ b/schedules/README.md @@ -4,18 +4,18 @@ These samples show how to schedule a Workflow Execution and control certain acti To run, first see [README.md](../README.md) for prerequisites. Then, run the following from this directory to run the `schedules/` sample: - poetry run python run_worker.py - poetry run python start_schedule.py + uv run run_worker.py + uv run start_schedule.py Replace `start_schedule.py` in the command with any other example filename to run it instead. - poetry run python backfill_schedule.py - poetry run python delete_schedule.py - poetry run python describe_schedule.py - poetry run python list_schedule.py - poetry run python pause_schedule.py + uv run backfill_schedule.py + uv run delete_schedule.py + uv run describe_schedule.py + uv run list_schedule.py + uv run pause_schedule.py python run python trigger_schedule.py - poetry run python update_schedule.py + uv run update_schedule.py - create: Creates a new Schedule. Newly created Schedules return a Schedule ID to be used in other Schedule commands. - backfill: Backfills the Schedule by going through the specified time periods as if they passed right now. diff --git a/sentry/README.md b/sentry/README.md index 45977731..30667d5e 100644 --- a/sentry/README.md +++ b/sentry/README.md @@ -4,16 +4,16 @@ This sample shows how to configure [Sentry](https://sentry.io) to intercept and For this sample, the optional `sentry` dependency group must be included. To include, run: - poetry install --with sentry + uv sync --group sentry To run, first see [README.md](../README.md) for prerequisites. Set `SENTRY_DSN` environment variable to the Sentry DSN. Then, run the following from this directory to start the worker: - poetry run python worker.py + uv run worker.py This will start the worker. Then, in another terminal, run the following to execute the workflow: - poetry run python starter.py + uv run starter.py The workflow should complete with the hello result. If you alter the workflow or the activity to raise an `ApplicationError` instead, it should appear in Sentry. \ No newline at end of file diff --git a/sentry/interceptor.py b/sentry/interceptor.py index f1737ed2..eceba41d 100644 --- a/sentry/interceptor.py +++ b/sentry/interceptor.py @@ -37,8 +37,10 @@ async def execute_activity(self, input: ExecuteActivityInput) -> Any: try: return await super().execute_activity(input) except Exception as e: - if len(input.args) == 1 and is_dataclass(input.args[0]): - set_context("temporal.activity.input", asdict(input.args[0])) + if len(input.args) == 1: + [arg] = input.args + if is_dataclass(arg) and not isinstance(arg, type): + set_context("temporal.activity.input", asdict(arg)) set_context("temporal.activity.info", activity.info().__dict__) capture_exception() raise e @@ -58,8 +60,10 @@ async def execute_workflow(self, input: ExecuteWorkflowInput) -> Any: try: return await super().execute_workflow(input) except Exception as e: - if len(input.args) == 1 and is_dataclass(input.args[0]): - set_context("temporal.workflow.input", asdict(input.args[0])) + if len(input.args) == 1: + [arg] = input.args + if is_dataclass(arg) and not isinstance(arg, type): + set_context("temporal.workflow.input", asdict(arg)) set_context("temporal.workflow.info", workflow.info().__dict__) if not workflow.unsafe.is_replaying(): diff --git a/sleep_for_days/README.md b/sleep_for_days/README.md new file mode 100644 index 00000000..766aefc9 --- /dev/null +++ b/sleep_for_days/README.md @@ -0,0 +1,18 @@ +# Sleep for Days + +This sample demonstrates how to create a Temporal workflow that runs forever, sending an email every 30 days. + +To run, first see the main [README.md](../../README.md) for prerequisites. + +Then create two terminals and `cd` to this directory. + +Run the worker in one terminal: + + uv run worker.py + +And execute the workflow in the other terminal: + + uv run starter.py + +This sample will run indefinitely until you send a signal to `complete`. See how to send a signal via Temporal CLI [here](https://docs.temporal.io/cli/workflow#signal). + diff --git a/sleep_for_days/__init__.py b/sleep_for_days/__init__.py new file mode 100644 index 00000000..04611d30 --- /dev/null +++ b/sleep_for_days/__init__.py @@ -0,0 +1 @@ +TASK_QUEUE = "sleep-for-days-task-queue" diff --git a/sleep_for_days/activities.py b/sleep_for_days/activities.py new file mode 100644 index 00000000..30972098 --- /dev/null +++ b/sleep_for_days/activities.py @@ -0,0 +1,18 @@ +from dataclasses import dataclass + +from temporalio import activity + + +@dataclass +class SendEmailInput: + email_msg: str + + +@activity.defn() +async def send_email(input: SendEmailInput) -> str: + """ + A stub Activity for sending an email. + """ + result = f"Email message: {input.email_msg}, sent" + activity.logger.info(result) + return result diff --git a/sleep_for_days/starter.py b/sleep_for_days/starter.py new file mode 100644 index 00000000..765842b2 --- /dev/null +++ b/sleep_for_days/starter.py @@ -0,0 +1,23 @@ +import asyncio +import uuid +from typing import Optional + +from temporalio.client import Client + +from sleep_for_days import TASK_QUEUE +from sleep_for_days.workflows import SleepForDaysWorkflow + + +async def main(client: Optional[Client] = None): + client = client or await Client.connect("localhost:7233") + wf_handle = await client.start_workflow( + SleepForDaysWorkflow.run, + id=f"sleep-for-days-workflow-id-{uuid.uuid4()}", + task_queue=TASK_QUEUE, + ) + # Wait for workflow completion (runs indefinitely until it receives a signal) + print(await wf_handle.result()) + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/sleep_for_days/worker.py b/sleep_for_days/worker.py new file mode 100644 index 00000000..d03ec726 --- /dev/null +++ b/sleep_for_days/worker.py @@ -0,0 +1,27 @@ +import asyncio +import logging + +from temporalio.client import Client +from temporalio.worker import Worker + +from sleep_for_days import TASK_QUEUE +from sleep_for_days.activities import send_email +from sleep_for_days.workflows import SleepForDaysWorkflow + + +async def main(): + client = await Client.connect("localhost:7233") + + worker = Worker( + client, + task_queue=TASK_QUEUE, + workflows=[SleepForDaysWorkflow], + activities=[send_email], + ) + + await worker.run() + + +if __name__ == "__main__": + logging.basicConfig(level=logging.INFO) + asyncio.run(main()) diff --git a/sleep_for_days/workflows.py b/sleep_for_days/workflows.py new file mode 100644 index 00000000..eff0b273 --- /dev/null +++ b/sleep_for_days/workflows.py @@ -0,0 +1,37 @@ +import asyncio +from dataclasses import dataclass +from datetime import timedelta + +from temporalio import workflow + +with workflow.unsafe.imports_passed_through(): + from sleep_for_days.activities import SendEmailInput, send_email + + +@workflow.defn() +class SleepForDaysWorkflow: + def __init__(self) -> None: + self.is_complete = False + + @workflow.run + async def run(self) -> str: + while not self.is_complete: + await workflow.execute_activity( + send_email, + SendEmailInput("30 days until the next email"), + start_to_close_timeout=timedelta(seconds=10), + ) + await workflow.wait( + [ + asyncio.create_task(workflow.sleep(timedelta(days=30))), + asyncio.create_task( + workflow.wait_condition(lambda: self.is_complete) + ), + ], + return_when=asyncio.FIRST_COMPLETED, + ) + return "done!" + + @workflow.signal + def complete(self): + self.is_complete = True diff --git a/tests/conftest.py b/tests/conftest.py index 95294fb4..e63a059b 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -41,7 +41,12 @@ def event_loop(): async def env(request) -> AsyncGenerator[WorkflowEnvironment, None]: env_type = request.config.getoption("--workflow-environment") if env_type == "local": - env = await WorkflowEnvironment.start_local() + env = await WorkflowEnvironment.start_local( + dev_server_extra_args=[ + "--dynamic-config-value", + "frontend.enableExecuteMultiOperation=true", + ] + ) elif env_type == "time-skipping": env = await WorkflowEnvironment.start_time_skipping() else: diff --git a/tests/custom_metric/__init__.py b/tests/custom_metric/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/tests/custom_metric/workflow_test.py b/tests/custom_metric/workflow_test.py new file mode 100644 index 00000000..bac5c07f --- /dev/null +++ b/tests/custom_metric/workflow_test.py @@ -0,0 +1,34 @@ +import uuid +from concurrent.futures import ThreadPoolExecutor + +from temporalio import activity +from temporalio.client import Client +from temporalio.worker import Worker + +from custom_metric.worker import StartTwoActivitiesWorkflow + +_TASK_QUEUE = "custom-metric-task-queue" + +activity_counter = 0 + + +async def test_custom_metric_workflow(client: Client): + @activity.defn(name="print_and_sleep") + async def print_message_mock(): + global activity_counter + activity_counter += 1 + + async with Worker( + client, + task_queue=_TASK_QUEUE, + workflows=[StartTwoActivitiesWorkflow], + activities=[print_message_mock], + activity_executor=ThreadPoolExecutor(5), + ): + result = await client.execute_workflow( + StartTwoActivitiesWorkflow.run, + id=str(uuid.uuid4()), + task_queue=_TASK_QUEUE, + ) + assert result is None + assert activity_counter == 2 diff --git a/tests/hello/hello_activity_choice_test.py b/tests/hello/hello_activity_choice_test.py index 236634de..1dadbb88 100644 --- a/tests/hello/hello_activity_choice_test.py +++ b/tests/hello/hello_activity_choice_test.py @@ -20,13 +20,12 @@ ] -@pytest.mark.asyncio @pytest.mark.parametrize( "activity_func, order_amount, expected_result", activity_test_data ) -async def test_order_fruit(activity_func, order_amount, expected_result): +def test_order_fruit(activity_func, order_amount, expected_result): activity_environment = ActivityEnvironment() - result = await activity_environment.run(activity_func, order_amount) + result = activity_environment.run(activity_func, order_amount) assert result == expected_result diff --git a/tests/hello/hello_activity_test.py b/tests/hello/hello_activity_test.py index 4bd8e40e..5bf9c1b8 100644 --- a/tests/hello/hello_activity_test.py +++ b/tests/hello/hello_activity_test.py @@ -1,4 +1,5 @@ import uuid +from concurrent.futures import ThreadPoolExecutor from temporalio import activity from temporalio.client import Client @@ -18,6 +19,7 @@ async def test_execute_workflow(client: Client): client, task_queue=task_queue_name, workflows=[GreetingWorkflow], + activity_executor=ThreadPoolExecutor(5), activities=[compose_greeting], ): assert "Hello, World!" == await client.execute_workflow( diff --git a/tests/hello/hello_cancellation_test.py b/tests/hello/hello_cancellation_test.py index 2d4b946e..b511b50b 100644 --- a/tests/hello/hello_cancellation_test.py +++ b/tests/hello/hello_cancellation_test.py @@ -1,5 +1,6 @@ import asyncio import uuid +from concurrent.futures import ThreadPoolExecutor import pytest from temporalio.client import Client, WorkflowExecutionStatus, WorkflowFailureError @@ -21,6 +22,7 @@ async def test_cancel_workflow(client: Client): task_queue=task_queue_name, workflows=[CancellationWorkflow], activities=[cleanup_activity, never_complete_activity], + activity_executor=ThreadPoolExecutor(5), ): handle = await client.start_workflow( CancellationWorkflow.run, diff --git a/tests/hello/hello_change_log_level_test.py b/tests/hello/hello_change_log_level_test.py new file mode 100644 index 00000000..e3cd2334 --- /dev/null +++ b/tests/hello/hello_change_log_level_test.py @@ -0,0 +1,43 @@ +import asyncio +import io +import logging +import uuid + +from temporalio.client import Client +from temporalio.worker import Worker + +from hello.hello_change_log_level import LOG_MESSAGE, GreetingWorkflow + + +async def test_workflow_with_log_capture(client: Client): + + log_stream = io.StringIO() + handler = logging.StreamHandler(log_stream) + handler.setLevel(logging.ERROR) + + logger = logging.getLogger() + logger.addHandler(handler) + logger.setLevel(logging.DEBUG) + + task_queue = f"tq-{uuid.uuid4()}" + + async with Worker( + client, + task_queue=task_queue, + workflows=[GreetingWorkflow], + ): + handle = await client.start_workflow( + GreetingWorkflow.run, + id=f"wf-{uuid.uuid4()}", + task_queue=task_queue, + ) + await asyncio.sleep( + 0.2 + ) # small wait to ensure the workflow has started, failed, and logged + await handle.terminate() + + logger.removeHandler(handler) + handler.flush() + + logs = log_stream.getvalue() + assert LOG_MESSAGE in logs diff --git a/tests/hello/hello_update_test.py b/tests/hello/hello_update_test.py index 2a079387..f7664ecb 100644 --- a/tests/hello/hello_update_test.py +++ b/tests/hello/hello_update_test.py @@ -9,10 +9,6 @@ async def test_update_workflow(client: Client, env: WorkflowEnvironment): - if env.supports_time_skipping: - pytest.skip( - "Time-skipping test server currently has issue with update: https://github.com/temporalio/sdk-java/issues/1903" - ) task_queue_name = str(uuid.uuid4()) async with Worker(client, task_queue=task_queue_name, workflows=[GreetingWorkflow]): handle = await client.start_workflow( diff --git a/tests/message_passing/lazy_initialization/test_lazy_initialization.py b/tests/message_passing/lazy_initialization/test_lazy_initialization.py new file mode 100644 index 00000000..dcf94582 --- /dev/null +++ b/tests/message_passing/lazy_initialization/test_lazy_initialization.py @@ -0,0 +1,60 @@ +import pytest +from temporalio import common +from temporalio.client import Client, WithStartWorkflowOperation +from temporalio.testing import WorkflowEnvironment +from temporalio.worker import Worker + +from message_passing.update_with_start.lazy_initialization.workflows import ( + ShoppingCartItem, + ShoppingCartWorkflow, + get_price, +) + + +async def test_shopping_cart_workflow(client: Client, env: WorkflowEnvironment): + if env.supports_time_skipping: + pytest.skip( + "Java test server: https://github.com/temporalio/sdk-java/issues/1903" + ) + async with Worker( + client, + task_queue="lazy-initialization-test", + workflows=[ShoppingCartWorkflow], + activities=[get_price], + ): + cart_id = "cart--session-1234" + make_start_op = lambda: WithStartWorkflowOperation( + ShoppingCartWorkflow.run, + id=cart_id, + id_conflict_policy=common.WorkflowIDConflictPolicy.USE_EXISTING, + task_queue="lazy-initialization-test", + ) + start_op_1 = make_start_op() + price = await client.execute_update_with_start_workflow( + ShoppingCartWorkflow.add_item, + ShoppingCartItem(sku="item-1", quantity=2), + start_workflow_operation=start_op_1, + ) + + assert price == 1198 + + workflow_handle = await start_op_1.workflow_handle() + + start_op_2 = make_start_op() + price = await client.execute_update_with_start_workflow( + ShoppingCartWorkflow.add_item, + ShoppingCartItem(sku="item-2", quantity=1), + start_workflow_operation=start_op_2, + ) + assert price == 1797 + + workflow_handle = await start_op_2.workflow_handle() + + await workflow_handle.signal(ShoppingCartWorkflow.checkout) + + finalized_order = await workflow_handle.result() + assert finalized_order.items == [ + (ShoppingCartItem(sku="item-1", quantity=2), 1198), + (ShoppingCartItem(sku="item-2", quantity=1), 599), + ] + assert finalized_order.total == 1797 diff --git a/tests/message_passing/safe_message_handlers/workflow_test.py b/tests/message_passing/safe_message_handlers/workflow_test.py index 92345be7..8fd28d8d 100644 --- a/tests/message_passing/safe_message_handlers/workflow_test.py +++ b/tests/message_passing/safe_message_handlers/workflow_test.py @@ -1,5 +1,6 @@ import asyncio import uuid +from typing import Callable, Sequence import pytest from temporalio.client import Client, WorkflowUpdateFailedError @@ -10,6 +11,7 @@ from message_passing.safe_message_handlers.activities import ( assign_nodes_to_job, find_bad_nodes, + start_cluster, unassign_nodes_for_job, ) from message_passing.safe_message_handlers.workflow import ( @@ -19,6 +21,13 @@ ClusterManagerWorkflow, ) +ACTIVITIES: Sequence[Callable] = [ + assign_nodes_to_job, + unassign_nodes_for_job, + find_bad_nodes, + start_cluster, +] + async def test_safe_message_handlers(client: Client, env: WorkflowEnvironment): if env.supports_time_skipping: @@ -30,7 +39,7 @@ async def test_safe_message_handlers(client: Client, env: WorkflowEnvironment): client, task_queue=task_queue, workflows=[ClusterManagerWorkflow], - activities=[assign_nodes_to_job, unassign_nodes_for_job, find_bad_nodes], + activities=ACTIVITIES, ): cluster_manager_handle = await client.start_workflow( ClusterManagerWorkflow.run, @@ -38,7 +47,9 @@ async def test_safe_message_handlers(client: Client, env: WorkflowEnvironment): id=f"ClusterManagerWorkflow-{uuid.uuid4()}", task_queue=task_queue, ) - await cluster_manager_handle.signal(ClusterManagerWorkflow.start_cluster) + await cluster_manager_handle.execute_update( + ClusterManagerWorkflow.wait_until_cluster_started + ) allocation_updates = [] for i in range(6): @@ -68,8 +79,8 @@ async def test_safe_message_handlers(client: Client, env: WorkflowEnvironment): await cluster_manager_handle.signal(ClusterManagerWorkflow.shutdown_cluster) - result = await cluster_manager_handle.result() - assert result.num_currently_assigned_nodes == 0 + cluster_manager_result = await cluster_manager_handle.result() + assert cluster_manager_result.num_currently_assigned_nodes == 0 async def test_update_idempotency(client: Client, env: WorkflowEnvironment): @@ -82,7 +93,7 @@ async def test_update_idempotency(client: Client, env: WorkflowEnvironment): client, task_queue=task_queue, workflows=[ClusterManagerWorkflow], - activities=[assign_nodes_to_job, unassign_nodes_for_job, find_bad_nodes], + activities=ACTIVITIES, ): cluster_manager_handle = await client.start_workflow( ClusterManagerWorkflow.run, @@ -91,7 +102,9 @@ async def test_update_idempotency(client: Client, env: WorkflowEnvironment): task_queue=task_queue, ) - await cluster_manager_handle.signal(ClusterManagerWorkflow.start_cluster) + await cluster_manager_handle.execute_update( + ClusterManagerWorkflow.wait_until_cluster_started + ) result_1 = await cluster_manager_handle.execute_update( ClusterManagerWorkflow.assign_nodes_to_job, @@ -121,7 +134,7 @@ async def test_update_failure(client: Client, env: WorkflowEnvironment): client, task_queue=task_queue, workflows=[ClusterManagerWorkflow], - activities=[assign_nodes_to_job, unassign_nodes_for_job, find_bad_nodes], + activities=ACTIVITIES, ): cluster_manager_handle = await client.start_workflow( ClusterManagerWorkflow.run, @@ -130,7 +143,9 @@ async def test_update_failure(client: Client, env: WorkflowEnvironment): task_queue=task_queue, ) - await cluster_manager_handle.signal(ClusterManagerWorkflow.start_cluster) + await cluster_manager_handle.execute_update( + ClusterManagerWorkflow.wait_until_cluster_started + ) await cluster_manager_handle.execute_update( ClusterManagerWorkflow.assign_nodes_to_job, diff --git a/tests/message_passing/waiting_for_handlers/waiting_for_handlers_test.py b/tests/message_passing/waiting_for_handlers/waiting_for_handlers_test.py new file mode 100644 index 00000000..e6d200e3 --- /dev/null +++ b/tests/message_passing/waiting_for_handlers/waiting_for_handlers_test.py @@ -0,0 +1,80 @@ +from enum import Enum + +import pytest +from temporalio import client, worker +from temporalio.testing import WorkflowEnvironment + +from message_passing.waiting_for_handlers import WorkflowExitType, WorkflowInput +from message_passing.waiting_for_handlers.activities import ( + activity_executed_by_update_handler, +) +from message_passing.waiting_for_handlers.starter import TASK_QUEUE +from message_passing.waiting_for_handlers.workflows import WaitingForHandlersWorkflow + + +class UpdateExpect(Enum): + SUCCESS = "success" + FAILURE = "failure" + + +class WorkflowExpect(Enum): + SUCCESS = "success" + FAILURE = "failure" + + +@pytest.mark.parametrize( + ["exit_type_name", "update_expect", "workflow_expect"], + [ + (WorkflowExitType.SUCCESS.name, UpdateExpect.SUCCESS, WorkflowExpect.SUCCESS), + (WorkflowExitType.FAILURE.name, UpdateExpect.SUCCESS, WorkflowExpect.FAILURE), + ( + WorkflowExitType.CANCELLATION.name, + UpdateExpect.SUCCESS, + WorkflowExpect.FAILURE, + ), + ], +) +async def test_waiting_for_handlers( + env: WorkflowEnvironment, + exit_type_name: str, + update_expect: UpdateExpect, + workflow_expect: WorkflowExpect, +): + [exit_type] = [t for t in WorkflowExitType if t.name == exit_type_name] + if env.supports_time_skipping: + pytest.skip( + "Java test server: https://github.com/temporalio/sdk-java/issues/1903" + ) + async with worker.Worker( + env.client, + task_queue=TASK_QUEUE, + workflows=[WaitingForHandlersWorkflow], + activities=[ + activity_executed_by_update_handler, + ], + ): + wf_handle = await env.client.start_workflow( + WaitingForHandlersWorkflow.run, + WorkflowInput(exit_type=exit_type), + id="waiting-for-handlers-test", + task_queue=TASK_QUEUE, + ) + up_handle = await wf_handle.start_update( + WaitingForHandlersWorkflow.my_update, + wait_for_stage=client.WorkflowUpdateStage.ACCEPTED, + ) + + if exit_type == WorkflowExitType.CANCELLATION: + await wf_handle.cancel() + + if update_expect == UpdateExpect.SUCCESS: + await up_handle.result() + else: + with pytest.raises(client.WorkflowUpdateFailedError): + await up_handle.result() + + if workflow_expect == WorkflowExpect.SUCCESS: + await wf_handle.result() + else: + with pytest.raises(client.WorkflowFailureError): + await wf_handle.result() diff --git a/tests/message_passing/waiting_for_handlers_and_compensation/waiting_for_handlers_and_compensation_test.py b/tests/message_passing/waiting_for_handlers_and_compensation/waiting_for_handlers_and_compensation_test.py new file mode 100644 index 00000000..2b10d396 --- /dev/null +++ b/tests/message_passing/waiting_for_handlers_and_compensation/waiting_for_handlers_and_compensation_test.py @@ -0,0 +1,106 @@ +import uuid +from enum import Enum + +import pytest +from temporalio import client, worker +from temporalio.testing import WorkflowEnvironment + +from message_passing.waiting_for_handlers_and_compensation import ( + WorkflowExitType, + WorkflowInput, +) +from message_passing.waiting_for_handlers_and_compensation.activities import ( + activity_executed_by_update_handler, + activity_executed_by_update_handler_to_perform_compensation, + activity_executed_to_perform_workflow_compensation, +) +from message_passing.waiting_for_handlers_and_compensation.starter import TASK_QUEUE +from message_passing.waiting_for_handlers_and_compensation.workflows import ( + WaitingForHandlersAndCompensationWorkflow, +) + + +class UpdateExpect(Enum): + SUCCESS = "success" + FAILURE = "failure" + + +class WorkflowExpect(Enum): + SUCCESS = "success" + FAILURE = "failure" + + +@pytest.mark.parametrize( + ["exit_type_name", "update_expect", "workflow_expect"], + [ + (WorkflowExitType.SUCCESS.name, UpdateExpect.SUCCESS, WorkflowExpect.SUCCESS), + (WorkflowExitType.FAILURE.name, UpdateExpect.FAILURE, WorkflowExpect.FAILURE), + ( + WorkflowExitType.CANCELLATION.name, + UpdateExpect.FAILURE, + WorkflowExpect.FAILURE, + ), + ], +) +async def test_waiting_for_handlers_and_compensation( + env: WorkflowEnvironment, + exit_type_name: str, + update_expect: UpdateExpect, + workflow_expect: WorkflowExpect, +): + [exit_type] = [t for t in WorkflowExitType if t.name == exit_type_name] + if env.supports_time_skipping: + pytest.skip( + "Java test server: https://github.com/temporalio/sdk-java/issues/1903" + ) + async with worker.Worker( + env.client, + task_queue=TASK_QUEUE, + workflows=[WaitingForHandlersAndCompensationWorkflow], + activities=[ + activity_executed_by_update_handler, + activity_executed_by_update_handler_to_perform_compensation, + activity_executed_to_perform_workflow_compensation, + ], + ): + wf_handle = await env.client.start_workflow( + WaitingForHandlersAndCompensationWorkflow.run, + WorkflowInput(exit_type=exit_type), + id=str(uuid.uuid4()), + task_queue=TASK_QUEUE, + ) + up_handle = await wf_handle.start_update( + WaitingForHandlersAndCompensationWorkflow.my_update, + wait_for_stage=client.WorkflowUpdateStage.ACCEPTED, + ) + + if exit_type == WorkflowExitType.CANCELLATION: + await wf_handle.cancel() + + if update_expect == UpdateExpect.SUCCESS: + await up_handle.result() + assert not ( + await wf_handle.query( + WaitingForHandlersAndCompensationWorkflow.update_compensation_done + ) + ) + else: + with pytest.raises(client.WorkflowUpdateFailedError): + await up_handle.result() + assert await wf_handle.query( + WaitingForHandlersAndCompensationWorkflow.update_compensation_done + ) + + if workflow_expect == WorkflowExpect.SUCCESS: + await wf_handle.result() + assert not ( + await wf_handle.query( + WaitingForHandlersAndCompensationWorkflow.workflow_compensation_done + ) + ) + else: + with pytest.raises(client.WorkflowFailureError): + await wf_handle.result() + assert await wf_handle.query( + WaitingForHandlersAndCompensationWorkflow.workflow_compensation_done + ) diff --git a/tests/polling/infrequent/__init__.py b/tests/polling/infrequent/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/tests/polling/infrequent/workflow_test.py b/tests/polling/infrequent/workflow_test.py new file mode 100644 index 00000000..31f3f987 --- /dev/null +++ b/tests/polling/infrequent/workflow_test.py @@ -0,0 +1,31 @@ +import uuid + +import pytest +from temporalio.client import Client +from temporalio.testing import WorkflowEnvironment +from temporalio.worker import Worker + +from polling.infrequent.activities import compose_greeting +from polling.infrequent.workflows import GreetingWorkflow + + +async def test_infrequent_polling_workflow(client: Client, env: WorkflowEnvironment): + if not env.supports_time_skipping: + pytest.skip("Too slow to test with time-skipping disabled") + + # Start a worker that hosts the workflow and activity implementations. + task_queue = f"tq-{uuid.uuid4()}" + async with Worker( + client, + task_queue=task_queue, + workflows=[GreetingWorkflow], + activities=[compose_greeting], + ): + handle = await client.start_workflow( + GreetingWorkflow.run, + "Temporal", + id=f"infrequent-polling-{uuid.uuid4()}", + task_queue=task_queue, + ) + result = await handle.result() + assert result == "Hello, Temporal!" diff --git a/tests/pydantic_converter/workflow_test.py b/tests/pydantic_converter/workflow_test.py index a547caf0..c673164e 100644 --- a/tests/pydantic_converter/workflow_test.py +++ b/tests/pydantic_converter/workflow_test.py @@ -3,15 +3,10 @@ from ipaddress import IPv4Address from temporalio.client import Client +from temporalio.contrib.pydantic import pydantic_data_converter from temporalio.worker import Worker -from pydantic_converter.converter import pydantic_data_converter -from pydantic_converter.worker import ( - MyPydanticModel, - MyWorkflow, - my_activity, - new_sandbox_runner, -) +from pydantic_converter.worker import MyPydanticModel, MyWorkflow, my_activity async def test_workflow_with_pydantic_model(client: Client): @@ -35,7 +30,6 @@ async def test_workflow_with_pydantic_model(client: Client): task_queue=task_queue_name, workflows=[MyWorkflow], activities=[my_activity], - workflow_runner=new_sandbox_runner(), ): result = await client.execute_workflow( MyWorkflow.run, diff --git a/tests/pydantic_converter_v1/__init__.py b/tests/pydantic_converter_v1/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/tests/pydantic_converter_v1/workflow_test.py b/tests/pydantic_converter_v1/workflow_test.py new file mode 100644 index 00000000..fd0af800 --- /dev/null +++ b/tests/pydantic_converter_v1/workflow_test.py @@ -0,0 +1,46 @@ +import uuid +from datetime import datetime +from ipaddress import IPv4Address + +from temporalio.client import Client +from temporalio.worker import Worker + +from pydantic_converter_v1.converter import pydantic_data_converter +from pydantic_converter_v1.worker import ( + MyPydanticModel, + MyWorkflow, + my_activity, + new_sandbox_runner, +) + + +async def test_workflow_with_pydantic_model(client: Client): + # Replace data converter in client + new_config = client.config() + new_config["data_converter"] = pydantic_data_converter + client = Client(**new_config) + task_queue_name = str(uuid.uuid4()) + + orig_models = [ + MyPydanticModel( + some_ip=IPv4Address("127.0.0.1"), some_date=datetime(2000, 1, 2, 3, 4, 5) + ), + MyPydanticModel( + some_ip=IPv4Address("127.0.0.2"), some_date=datetime(2001, 2, 3, 4, 5, 6) + ), + ] + + async with Worker( + client, + task_queue=task_queue_name, + workflows=[MyWorkflow], + activities=[my_activity], + workflow_runner=new_sandbox_runner(), + ): + result = await client.execute_workflow( + MyWorkflow.run, + orig_models, + id=str(uuid.uuid4()), + task_queue=task_queue_name, + ) + assert orig_models == result diff --git a/tests/resource_pool/__init__.py b/tests/resource_pool/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/tests/resource_pool/workflow_test.py b/tests/resource_pool/workflow_test.py new file mode 100644 index 00000000..42a6fbde --- /dev/null +++ b/tests/resource_pool/workflow_test.py @@ -0,0 +1,120 @@ +import asyncio +from collections import defaultdict +from typing import Any, Optional, Sequence + +from temporalio import activity +from temporalio.client import Client, WorkflowFailureError, WorkflowHandle +from temporalio.common import WorkflowIDConflictPolicy +from temporalio.worker import Worker + +from resource_pool.pool_client.resource_pool_workflow import ( + ResourcePoolWorkflow, + ResourcePoolWorkflowInput, +) +from resource_pool.resource_user_workflow import ( + ResourceUserWorkflow, + ResourceUserWorkflowInput, + UseResourceActivityInput, +) +from resource_pool.shared import RESOURCE_POOL_WORKFLOW_ID + +TASK_QUEUE = "resource_pool-task-queue" + + +async def test_resource_pool_workflow(client: Client): + # key is resource, value is a description of resource usage + resource_usage: defaultdict[str, list[Sequence[str]]] = defaultdict(list) + + # Mock out the activity to count executions + @activity.defn(name="use_resource") + async def use_resource_mock(input: UseResourceActivityInput) -> None: + workflow_id = activity.info().workflow_id + resource_usage[input.resource].append((workflow_id, "start")) + # We need a small sleep here to bait out races + await asyncio.sleep(0.05) + resource_usage[input.resource].append((workflow_id, "end")) + + async with Worker( + client, + task_queue=TASK_QUEUE, + workflows=[ResourcePoolWorkflow, ResourceUserWorkflow], + activities=[use_resource_mock], + ): + await run_all_workflows(client) + + # Did any workflow run in more than one place? + workflow_id_to_resource: dict[str, str] = {} + for resource, events in resource_usage.items(): + for workflow_id, event in events: + if workflow_id in workflow_id_to_resource: + existing_resource = workflow_id_to_resource[workflow_id] + assert ( + existing_resource == resource + ), f"{workflow_id} ran on both {resource} and {existing_resource}" + else: + workflow_id_to_resource[workflow_id] = resource + + # Did any resource have more than one workflow on it at a time? + for resource, events in resource_usage.items(): + holder: Optional[str] = None + for workflow_id, event in events: + if event == "start": + assert ( + holder is None + ), f"{workflow_id} started on {resource} held by {holder}" + holder = workflow_id + else: + assert ( + holder == workflow_id + ), f"{workflow_id} ended on {resource} held by {holder}" + holder = None + + # Are all the resources free, per the query? + handle: WorkflowHandle[ + ResourcePoolWorkflow, None + ] = client.get_workflow_handle_for( + ResourcePoolWorkflow.run, RESOURCE_POOL_WORKFLOW_ID + ) + query_result = await handle.query(ResourcePoolWorkflow.get_current_holders) + assert query_result == {"r_a": None, "r_b": None, "r_c": None} + + +async def run_all_workflows(client: Client): + resource_pool_handle = await client.start_workflow( + workflow=ResourcePoolWorkflow.run, + arg=ResourcePoolWorkflowInput( + resources={"r_a": None, "r_b": None, "r_c": None}, + waiters=[], + ), + id=RESOURCE_POOL_WORKFLOW_ID, + task_queue=TASK_QUEUE, + id_conflict_policy=WorkflowIDConflictPolicy.USE_EXISTING, + ) + + resource_user_handles: list[WorkflowHandle[Any, Any]] = [] + for i in range(0, 8): + input = ResourceUserWorkflowInput( + resource_pool_workflow_id=RESOURCE_POOL_WORKFLOW_ID, + iteration_to_fail_after=None, + should_continue_as_new=False, + ) + if i == 0: + input.should_continue_as_new = True + if i == 1: + input.iteration_to_fail_after = "first" + + handle = await client.start_workflow( + workflow=ResourceUserWorkflow.run, + arg=input, + id=f"resource-user-workflow-{i}", + task_queue=TASK_QUEUE, + ) + resource_user_handles.append(handle) + + for handle in resource_user_handles: + try: + await handle.result() + except WorkflowFailureError: + pass + + await resource_pool_handle.terminate() diff --git a/tests/sleep_for_days/__init__.py b/tests/sleep_for_days/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/tests/sleep_for_days/workflow_test.py b/tests/sleep_for_days/workflow_test.py new file mode 100644 index 00000000..fa3f0686 --- /dev/null +++ b/tests/sleep_for_days/workflow_test.py @@ -0,0 +1,53 @@ +import uuid +from datetime import timedelta + +from temporalio import activity +from temporalio.testing import WorkflowEnvironment +from temporalio.worker import Worker + +from sleep_for_days.starter import TASK_QUEUE +from sleep_for_days.workflows import SendEmailInput, SleepForDaysWorkflow + + +async def test_sleep_for_days_workflow(): + num_activity_executions = 0 + + # Mock out the activity to count executions + @activity.defn(name="send_email") + async def send_email_mock(input: SendEmailInput) -> str: + nonlocal num_activity_executions + num_activity_executions += 1 + return input.email_msg + + async with await WorkflowEnvironment.start_time_skipping() as env: + # if env.supports_time_skipping: + # pytest.skip( + # "Java test server: https://github.com/temporalio/sdk-java/issues/1903" + # ) + async with Worker( + env.client, + task_queue=TASK_QUEUE, + workflows=[SleepForDaysWorkflow], + activities=[send_email_mock], + ): + handle = await env.client.start_workflow( + SleepForDaysWorkflow.run, + id=str(uuid.uuid4()), + task_queue=TASK_QUEUE, + ) + + start_time = await env.get_current_time() + # Time-skip 5 minutes. + await env.sleep(timedelta(minutes=5)) + # Check that the activity has been called, we're now waiting for the sleep to finish. + assert num_activity_executions == 1 + # Time-skip 3 days. + await env.sleep(timedelta(days=90)) + # Expect 3 more activity calls. + assert num_activity_executions == 4 + # Send the signal to complete the workflow. + await handle.signal(SleepForDaysWorkflow.complete) + # Expect no more activity calls to have been made - workflow is complete. + assert num_activity_executions == 4 + # Expect more than 90 days to have passed. + assert (await env.get_current_time() - start_time) > timedelta(days=90) diff --git a/tests/trio_async/__init__.py b/tests/trio_async/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/tests/trio_async/workflow_test.py b/tests/trio_async/workflow_test.py new file mode 100644 index 00000000..e6981bee --- /dev/null +++ b/tests/trio_async/workflow_test.py @@ -0,0 +1,40 @@ +import uuid + +import trio_asyncio +from temporalio.client import Client +from temporalio.worker import Worker + +from trio_async import activities, workflows + + +async def test_workflow_with_trio(client: Client): + @trio_asyncio.aio_as_trio + async def inside_trio(client: Client) -> list[str]: + # Create Trio thread executor + with trio_asyncio.TrioExecutor(max_workers=200) as thread_executor: + task_queue = f"tq-{uuid.uuid4()}" + # Run worker + async with Worker( + client, + task_queue=task_queue, + activities=[ + activities.say_hello_activity_async, + activities.say_hello_activity_sync, + ], + workflows=[workflows.SayHelloWorkflow], + activity_executor=thread_executor, + workflow_task_executor=thread_executor, + ): + # Run workflow and return result + return await client.execute_workflow( + workflows.SayHelloWorkflow.run, + "some-user", + id=f"wf-{uuid.uuid4()}", + task_queue=task_queue, + ) + + result = trio_asyncio.run(inside_trio, client) + assert result == [ + "Hello, some-user! (from asyncio)", + "Hello, some-user! (from thread)", + ] diff --git a/tests/updatable_timer/__init__.py b/tests/updatable_timer/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/tests/updatable_timer/updatable_timer_test.py b/tests/updatable_timer/updatable_timer_test.py new file mode 100644 index 00000000..f1e38245 --- /dev/null +++ b/tests/updatable_timer/updatable_timer_test.py @@ -0,0 +1,33 @@ +import datetime +import logging +import math +import uuid + +from temporalio.client import Client, WorkflowExecutionStatus +from temporalio.testing import WorkflowEnvironment +from temporalio.worker import Worker + +from updatable_timer.workflow import Workflow + + +async def test_updatable_timer_workflow(client: Client): + logging.basicConfig(level=logging.DEBUG) + + task_queue_name = str(uuid.uuid4()) + async with await WorkflowEnvironment.start_time_skipping() as env: + async with Worker(env.client, task_queue=task_queue_name, workflows=[Workflow]): + in_a_day = float( + (datetime.datetime.now() + datetime.timedelta(days=1)).timestamp() + ) + in_an_hour = float( + (datetime.datetime.now() + datetime.timedelta(hours=1)).timestamp() + ) + handle = await env.client.start_workflow( + Workflow.run, in_a_day, id=str(uuid.uuid4()), task_queue=task_queue_name + ) + wake_up_time1 = await handle.query(Workflow.get_wake_up_time) + assert math.isclose(wake_up_time1, in_a_day) + await handle.signal(Workflow.update_wake_up_time, in_an_hour) + wake_up_time2 = await handle.query(Workflow.get_wake_up_time) + assert math.isclose(wake_up_time2, in_an_hour) + await handle.result() diff --git a/trio_async/README.md b/trio_async/README.md new file mode 100644 index 00000000..01891215 --- /dev/null +++ b/trio_async/README.md @@ -0,0 +1,23 @@ +# Trio Async Sample + +This sample shows how to use Temporal asyncio with [Trio](https://trio.readthedocs.io) using +[Trio asyncio](https://trio-asyncio.readthedocs.io). Specifically it demonstrates using a traditional Temporal client +and worker in a Trio setting, and how Trio-based code can run in both asyncio async activities and threaded sync +activities. + +For this sample, the optional `trio_async` dependency group must be included. To include, run: + + uv sync --group trio_async + +To run, first see [README.md](../README.md) for prerequisites. Then, run the following from this directory to start the +worker: + + uv run worker.py + +This will start the worker. Then, in another terminal, run the following to execute the workflow: + + uv run starter.py + +The starter should complete with: + + INFO:root:Workflow result: ['Hello, Temporal! (from asyncio)', 'Hello, Temporal! (from thread)'] \ No newline at end of file diff --git a/trio_async/__init__.py b/trio_async/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/trio_async/activities.py b/trio_async/activities.py new file mode 100644 index 00000000..c253c93e --- /dev/null +++ b/trio_async/activities.py @@ -0,0 +1,51 @@ +import asyncio +import time + +import trio +import trio_asyncio +from temporalio import activity + + +# An asyncio-based async activity +@activity.defn +async def say_hello_activity_async(name: str) -> str: + # Demonstrate a sleep in both asyncio and Trio, showing that both asyncio + # and Trio primitives can be used + + # First asyncio + activity.logger.info("Sleeping in asyncio") + await asyncio.sleep(0.1) + + # Now Trio. We have to invoke the function separately decorated. + # We cannot use the @trio_as_aio decorator on the activity itself because + # it doesn't use functools wrap or similar so it doesn't respond to things + # like __name__ that @activity.defn needs. + return await say_hello_in_trio_from_asyncio(name) + + +@trio_asyncio.trio_as_aio +async def say_hello_in_trio_from_asyncio(name: str) -> str: + activity.logger.info("Sleeping in Trio (from asyncio)") + await trio.sleep(0.1) + return f"Hello, {name}! (from asyncio)" + + +# A thread-based sync activity +@activity.defn +def say_hello_activity_sync(name: str) -> str: + # Demonstrate a sleep in both threaded and Trio, showing that both + # primitives can be used + + # First, thread-blocking + activity.logger.info("Sleeping normally") + time.sleep(0.1) + + # Now Trio. We have to use Trio's thread sync tools to run trio calls from + # a different thread. + return trio.from_thread.run(say_hello_in_trio_from_sync, name) + + +async def say_hello_in_trio_from_sync(name: str) -> str: + activity.logger.info("Sleeping in Trio (from thread)") + await trio.sleep(0.1) + return f"Hello, {name}! (from thread)" diff --git a/trio_async/starter.py b/trio_async/starter.py new file mode 100644 index 00000000..67f7568b --- /dev/null +++ b/trio_async/starter.py @@ -0,0 +1,28 @@ +import logging + +import trio_asyncio +from temporalio.client import Client + +from trio_async import workflows + + +@trio_asyncio.aio_as_trio # Note this decorator which allows asyncio primitives +async def main(): + logging.basicConfig(level=logging.INFO) + + # Connect client + client = await Client.connect("localhost:7233") + + # Execute the workflow + result = await client.execute_workflow( + workflows.SayHelloWorkflow.run, + "Temporal", + id=f"trio-async-workflow-id", + task_queue="trio-async-task-queue", + ) + logging.info(f"Workflow result: {result}") + + +if __name__ == "__main__": + # Note how we're using Trio event loop, not asyncio + trio_asyncio.run(main) diff --git a/trio_async/worker.py b/trio_async/worker.py new file mode 100644 index 00000000..29f059b4 --- /dev/null +++ b/trio_async/worker.py @@ -0,0 +1,66 @@ +import asyncio +import logging +import os +import sys + +import trio_asyncio +from temporalio.client import Client +from temporalio.worker import Worker + +from trio_async import activities, workflows + + +@trio_asyncio.aio_as_trio # Note this decorator which allows asyncio primitives +async def main(): + logging.basicConfig(level=logging.INFO) + + # Connect client + client = await Client.connect("localhost:7233") + + # Temporal runs threaded activities and workflow tasks via run_in_executor. + # Due to how trio_asyncio works, you can only do run_in_executor with their + # specific executor. We make sure to give it 200 max since we are using it + # for both activities and workflow tasks and by default the worker supports + # 100 max concurrent activity tasks and 100 max concurrent workflow tasks. + with trio_asyncio.TrioExecutor(max_workers=200) as thread_executor: + + # Run a worker for the workflow + async with Worker( + client, + task_queue="trio-async-task-queue", + activities=[ + activities.say_hello_activity_async, + activities.say_hello_activity_sync, + ], + workflows=[workflows.SayHelloWorkflow], + activity_executor=thread_executor, + workflow_task_executor=thread_executor, + ): + # Wait until interrupted + logging.info("Worker started, ctrl+c to exit") + try: + await asyncio.Future() + except asyncio.CancelledError: + # Ignore, happens on ctrl+C + pass + finally: + logging.info("Shutting down") + + +if __name__ == "__main__": + # Note how we're using Trio event loop, not asyncio + try: + trio_asyncio.run(main) + except KeyboardInterrupt: + # Ignore ctrl+c + pass + except BaseException as err: + # On Python 3.11+ Trio represents keyboard interrupt inside an exception + # group + is_interrupt = ( + sys.version_info >= (3, 11) + and isinstance(err, BaseExceptionGroup) + and err.subgroup(KeyboardInterrupt) + ) + if not is_interrupt: + raise diff --git a/trio_async/workflows.py b/trio_async/workflows.py new file mode 100644 index 00000000..adcb4761 --- /dev/null +++ b/trio_async/workflows.py @@ -0,0 +1,30 @@ +from datetime import timedelta + +from temporalio import workflow + +with workflow.unsafe.imports_passed_through(): + from trio_async.activities import say_hello_activity_async, say_hello_activity_sync + + +@workflow.defn +class SayHelloWorkflow: + @workflow.run + async def run(self, name: str) -> list[str]: + # Workflows don't use default asyncio event loop or Trio, they use a + # custom event loop. Therefore Trio primitives should never be used in a + # workflow, only asyncio helpers (which delegate to the custom loop). + return [ + # That these are two different activities for async or sync means + # nothing to the workflow, we just have both to demonstrate the + # activity side + await workflow.execute_activity( + say_hello_activity_async, + name, + start_to_close_timeout=timedelta(minutes=5), + ), + await workflow.execute_activity( + say_hello_activity_sync, + name, + start_to_close_timeout=timedelta(minutes=5), + ), + ] diff --git a/updatable_timer/README.md b/updatable_timer/README.md new file mode 100644 index 00000000..04960265 --- /dev/null +++ b/updatable_timer/README.md @@ -0,0 +1,42 @@ +# Updatable Timer Sample + +Demonstrates a helper class which relies on `workflow.wait_condition` to implement a blocking sleep that can be updated at any moment. + +The sample is composed of the three executables: + +* `worker.py` hosts the Workflow Executions. +* `starter.py` starts Workflow Executions. +* `wake_up_timer_updater.py` Signals the Workflow Execution with the new time to wake up. + +First start the Worker: + +```bash +uv run worker.py +``` +Check the output of the Worker window. The expected output is: + +``` +Worker started, ctrl+c to exit +``` + +Then in a different terminal window start the Workflow Execution: + +```bash +uv run starter.py +``` +Check the output of the Worker window. The expected output is: +``` +Workflow started: run_id=... +``` + +Then run the updater as many times as you want to change timer to 10 seconds from now: + +```bash +uv run wake_up_time_updater.py +``` + +Check the output of the worker window. The expected output is: + +``` +Updated wake up time to 10 seconds from now +``` \ No newline at end of file diff --git a/updatable_timer/__init__.py b/updatable_timer/__init__.py new file mode 100644 index 00000000..a5ee5055 --- /dev/null +++ b/updatable_timer/__init__.py @@ -0,0 +1 @@ +TASK_QUEUE = "updatable-timer" diff --git a/updatable_timer/starter.py b/updatable_timer/starter.py new file mode 100644 index 00000000..88b4d0d4 --- /dev/null +++ b/updatable_timer/starter.py @@ -0,0 +1,32 @@ +import asyncio +import logging +from datetime import datetime, timedelta +from typing import Optional + +from temporalio import exceptions +from temporalio.client import Client + +from updatable_timer import TASK_QUEUE +from updatable_timer.workflow import Workflow + + +async def main(client: Optional[Client] = None): + logging.basicConfig(level=logging.INFO) + + client = client or await Client.connect("localhost:7233") + try: + handle = await client.start_workflow( + Workflow.run, + (datetime.now() + timedelta(days=1)).timestamp(), + id=f"updatable-timer-workflow", + task_queue=TASK_QUEUE, + ) + logging.info(f"Workflow started: run_id={handle.result_run_id}") + except exceptions.WorkflowAlreadyStartedError as e: + logging.info( + f"Workflow already running: workflow_id={e.workflow_id}, run_id={e.run_id}" + ) + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/updatable_timer/updatable_timer_lib.py b/updatable_timer/updatable_timer_lib.py new file mode 100644 index 00000000..b90ae868 --- /dev/null +++ b/updatable_timer/updatable_timer_lib.py @@ -0,0 +1,39 @@ +import asyncio +from datetime import datetime, timedelta + +from temporalio import workflow + + +class UpdatableTimer: + def __init__(self, wake_up_time: datetime) -> None: + self.wake_up_time = wake_up_time + self.wake_up_time_updated = False + + async def sleep(self) -> None: + workflow.logger.info(f"sleep_until: {self.wake_up_time}") + while True: + now = workflow.now() + + sleep_interval = self.wake_up_time - now + if sleep_interval <= timedelta(0): + break + workflow.logger.info(f"Going to sleep for {sleep_interval}") + + try: + self.wake_up_time_updated = False + await workflow.wait_condition( + lambda: self.wake_up_time_updated, + timeout=sleep_interval, + ) + except asyncio.TimeoutError: + # checks condition at the beginning of the loop + continue + workflow.logger.info(f"sleep_until completed") + + def update_wake_up_time(self, wake_up_time: datetime) -> None: + workflow.logger.info(f"update_wake_up_time: {wake_up_time}") + self.wake_up_time = wake_up_time + self.wake_up_time_updated = True + + def get_wake_up_time(self) -> datetime: + return self.wake_up_time diff --git a/updatable_timer/wake_up_time_updater.py b/updatable_timer/wake_up_time_updater.py new file mode 100644 index 00000000..f406c186 --- /dev/null +++ b/updatable_timer/wake_up_time_updater.py @@ -0,0 +1,26 @@ +import asyncio +import logging +from datetime import datetime, timedelta +from typing import Optional + +from temporalio.client import Client + +from updatable_timer.workflow import Workflow + + +async def main(client: Optional[Client] = None): + logging.basicConfig(level=logging.INFO) + + client = client or await Client.connect("localhost:7233") + handle = client.get_workflow_handle(workflow_id="updatable-timer-workflow") + # signal workflow about the wake up time change + await handle.signal( + Workflow.update_wake_up_time, + (datetime.now() + timedelta(seconds=10)).timestamp(), + ) + + logging.info("Updated wake up time to 10 seconds from now") + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/updatable_timer/worker.py b/updatable_timer/worker.py new file mode 100644 index 00000000..096fa1ff --- /dev/null +++ b/updatable_timer/worker.py @@ -0,0 +1,35 @@ +import asyncio +import logging + +from temporalio.client import Client +from temporalio.worker import Worker + +from updatable_timer import TASK_QUEUE +from updatable_timer.workflow import Workflow + +interrupt_event = asyncio.Event() + + +async def main(): + logging.basicConfig(level=logging.INFO) + + client = await Client.connect("localhost:7233") + async with Worker( + client, + task_queue=TASK_QUEUE, + workflows=[Workflow], + ): + logging.info("Worker started, ctrl+c to exit") + # Wait until interrupted + await interrupt_event.wait() + logging.info("Interrupt received, shutting down...") + + +if __name__ == "__main__": + loop = asyncio.new_event_loop() + asyncio.set_event_loop(loop) + try: + loop.run_until_complete(main()) + except KeyboardInterrupt: + interrupt_event.set() + loop.run_until_complete(loop.shutdown_asyncgens()) diff --git a/updatable_timer/workflow.py b/updatable_timer/workflow.py new file mode 100644 index 00000000..749df6fc --- /dev/null +++ b/updatable_timer/workflow.py @@ -0,0 +1,32 @@ +from datetime import datetime, timezone +from typing import Optional + +from temporalio import workflow + +from updatable_timer.updatable_timer_lib import UpdatableTimer + + +@workflow.defn +class Workflow: + @workflow.init + def __init__(self, wake_up_time: float) -> None: + self.timer = UpdatableTimer( + datetime.fromtimestamp(wake_up_time, tz=timezone.utc) + ) + + @workflow.run + async def run(self, wake_up_time: float): + await self.timer.sleep() + + @workflow.signal + async def update_wake_up_time(self, wake_up_time: float) -> None: + workflow.logger.info(f"update_wake_up_time: {wake_up_time}") + + self.timer.update_wake_up_time( + datetime.fromtimestamp(wake_up_time, tz=timezone.utc) + ) + + @workflow.query + def get_wake_up_time(self) -> float: + workflow.logger.info(f"get_wake_up_time") + return float(self.timer.get_wake_up_time().timestamp()) diff --git a/uv.lock b/uv.lock new file mode 100644 index 00000000..21e6c17e --- /dev/null +++ b/uv.lock @@ -0,0 +1,3360 @@ +version = 1 +revision = 2 +requires-python = ">=3.9, <4" +resolution-markers = [ + "python_full_version >= '3.12.4'", + "python_full_version >= '3.12' and python_full_version < 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upload-time = "2024-11-28T08:50:35.681Z" }, +] diff --git a/worker_specific_task_queues/README.md b/worker_specific_task_queues/README.md index 8e8e577a..01f72890 100644 --- a/worker_specific_task_queues/README.md +++ b/worker_specific_task_queues/README.md @@ -24,16 +24,16 @@ Activities have been artificially slowed with `time.sleep(3)` to simulate doing To run, first see [README.md](../README.md) for prerequisites. Then, run the following from this directory to start the worker: - poetry run python worker.py + uv run worker.py This will start the worker. Then, in another terminal, run the following to execute the workflow: - poetry run python starter.py + uv run starter.py #### Example output: ```bash -(temporalio-samples-py3.10) user@machine:~/samples-python/activities_sticky_queues$ poetry run python starter.py +(temporalio-samples-py3.10) user@machine:~/samples-python/activities_sticky_queues$ uv run starter.py Output checksums: 49d7419e6cba3575b3158f62d053f922aa08b23c64f05411cda3213b56c84ba4 49d7419e6cba3575b3158f62d053f922aa08b23c64f05411cda3213b56c84ba4 diff --git a/worker_versioning/README.md b/worker_versioning/README.md index 04f958bf..21af863f 100644 --- a/worker_versioning/README.md +++ b/worker_versioning/README.md @@ -5,7 +5,7 @@ feature to deploy incompatible changes to workflow code more easily. To run, first see [README.md](../README.md) for prerequisites. Then, run the following from this directory: - poetry run python example.py + uv run example.py This will add some Build IDs to a Task Queue, and will also run Workers with those versions to show how you can mark add versions, mark them as compatible (or not) with one another, and run Workers at specific versions. You'll