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Samples for working with the Temporal Python SDK

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Temporal Python SDK Samples

This is the set of Python samples for the Python SDK.

Usage

Prerequisites:

With this repository cloned, run the following at the root of the directory:

poetry install

That loads all required dependencies. Then to run a sample, usually you just run it in Python. For example:

poetry run python hello/hello_activity.py

Some examples require extra dependencies. See each sample's directory for specific instructions.

Samples

  • activity_worker - Use Python activities from a workflow in another language.
  • bedrock - Orchestrate a chatbot with Amazon Bedrock.
  • cloud_export_to_parquet - Set up schedule workflow to process exported files on an hourly basis
  • context_propagation - Context propagation through workflows/activities via interceptor.
  • custom_converter - Use a custom payload converter to handle custom types.
  • custom_decorator - Custom decorator to auto-heartbeat a long-running activity.
  • dsl - DSL workflow that executes steps defined in a YAML file.
  • encryption - Apply end-to-end encryption for all input/output.
  • gevent_async - Combine gevent and Temporal.
  • langchain - Orchestrate workflows for LangChain.
  • message-passing introduction - Introduction to queries, signals, and updates.
  • open_telemetry - Trace workflows with OpenTelemetry.
  • patching - Alter workflows safely with patch and deprecate_patch.
  • polling - Recommended implementation of an activity that needs to periodically poll an external resource waiting its successful completion.
  • prometheus - Configure Prometheus metrics on clients/workers.
  • pydantic_converter - Data converter for using Pydantic models.
  • safe_message_handlers - Safely handling updates and signals.
  • schedules - Demonstrates a Workflow Execution that occurs according to a schedule.
  • sentry - Report errors to Sentry.
  • worker_specific_task_queues - Use unique task queues to ensure activities run on specific workers.
  • worker_versioning - Use the Worker Versioning feature to more easily version your workflows & other code.

Test

Running the tests requires poe to be installed.

python -m pip install poethepoet

Once you have poe installed you can run:

poe test