What is time-skipping in Temporal testing?

Time-skipping is a feature of the Temporal testing environment that allows you to test long-running workflows (like those spanning weeks or months) in a matter of seconds by manually or automatically advancing the internal clock.

What is the recommended test coverage for Temporal workflows?

According to Temporal best practices included in this skill, you should aim for at least 80% logic coverage for both workflows and activities to ensure production reliability.

How do I mock activities in a Temporal workflow test?

This skill provides patterns for using the Temporal Worker in tests to register mocked activity implementations, allowing you to isolate workflow logic from external API calls or database operations.

Why is replay testing necessary for Temporal?

Replay testing is critical because Temporal workflows must be deterministic. Replay testing ensures that code updates do not break the execution history of existing workflows, preventing non-deterministic errors in production.

Temporal Python Testing

Name: Temporal Python Testing
Author: wshobson

bywshobson

•

23,194

•

Security & Testing

Streamlines the testing of Temporal workflows in Python using pytest, time-skipping, and determinism validation strategies.

This skill provides a comprehensive framework for testing Temporal workflows within Python environments, ensuring robust and deterministic distributed systems. It guides developers through advanced testing patterns, including unit testing with time-skipping to compress month-long workflows into seconds, integration testing with mocked activities, and replay testing to validate production histories. By providing ready-to-use pytest fixtures and architectural guidance, it helps teams achieve high test coverage and reliable CI/CD pipelines for their Temporal-based backend services.

Key Features

01Time-skipping for near-instant execution of long-running workflows

02Replay testing tools to validate workflow determinism

0323,194 GitHub stars

04Async pytest fixtures for streamlined integration testing

05Local development environment setup with Docker Compose

06Comprehensive activity mocking and error injection strategies

Use Cases

01Validating workflow changes against production histories before deployment

02Testing complex business logic in long-running workflows without waiting

03Achieving high test coverage for distributed backend orchestration logic

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add wshobson/agents temporal-python-testing

For use in Claude.ai and ChatGPT

Download Skill