Can I test activities separately from workflows?

Yes, this skill includes patterns for using ActivityEnvironment, which lets you invoke and validate activity logic in isolation without starting a full workflow.

What is replay testing and why is it important?

Replay testing runs existing workflow execution histories against your updated code. It is critical for ensuring that code changes haven't broken determinism, which would cause running workflows to fail.

Does this skill provide local setup instructions?

Yes, it includes detailed resources for configuring a local Temporal server using Docker Compose and setting up pytest for immediate development use.

How does time-skipping benefit Temporal workflow testing?

Time-skipping allows the testing environment to automatically advance the clock when a workflow is waiting (e.g., on a sleep or timer), enabling you to test long-running processes in milliseconds.

Temporal Python Testing

Name: Temporal Python Testing
Author: HermeticOrmus

byHermeticOrmus

보안 및 테스팅

Streamlines the testing of Temporal workflows using pytest, time-skipping techniques, and deterministic replay validation.

소개

This skill provides a comprehensive framework for testing Temporal workflows and activities within the Python ecosystem. It simplifies complex testing scenarios by offering structured guidance on unit testing with time-skipping, integration testing with mocked activities, and replay testing to ensure workflow determinism. Whether you are setting up a local development environment with Docker Compose or integrating automated tests into a CI/CD pipeline, this skill ensures your distributed systems are robust, reliable, and maintain at least 80% code coverage.

주요 기능

Pre-configured pytest fixtures for Temporal WorkflowEnvironment
Step-by-step local development and Docker Compose setup
0 GitHub stars
Comprehensive activity mocking and environment isolation patterns
Deterministic replay testing to prevent production breakages
Time-skipping for near-instant execution of long-running workflows

사용 사례

Testing month-long business processes in seconds using time-skipping
Isolating workflow logic from external API dependencies through activity mocking
Validating workflow determinism before deploying code changes to production

소개

주요 기능

Pre-configured pytest fixtures for Temporal WorkflowEnvironment
Step-by-step local development and Docker Compose setup
0 GitHub stars
Comprehensive activity mocking and environment isolation patterns
Deterministic replay testing to prevent production breakages
Time-skipping for near-instant execution of long-running workflows

사용 사례

Testing month-long business processes in seconds using time-skipping
Isolating workflow logic from external API dependencies through activity mocking
Validating workflow determinism before deploying code changes to production