How does time-skipping help in Temporal testing?

Time-skipping allows tests to advance through 'sleep' or 'timer' periods instantly, making it possible to test workflows that span months in just a few seconds.

What is replay testing in Temporal?

Replay testing validates that changes to workflow code remain deterministic by re-running historical execution logs against the new code to ensure they produce identical results.

Does this skill integrate with standard Python testing tools?

Absolutely, it is designed to work seamlessly with pytest and async fixtures, which is the standard approach for testing Temporal Python applications.

Can I use this skill to test activities in isolation?

Yes, it includes specific patterns for using ActivityEnvironment to test activities independently of workflows, including mocking the environment and inputs.

Temporal Python Testing

Name: Temporal Python Testing
Author: Activer007

byActiver007

セキュリティとテスト

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

概要

This skill provides a comprehensive framework for testing Temporal workflows in Python, enabling developers to implement robust unit, integration, and replay tests. It leverages time-skipping to compress long-running workflows into seconds, offers strategies for mocking activities to isolate workflow logic, and ensures determinism through automated replay testing against production histories. By following these patterns, teams can achieve high test coverage and prevent breaking changes in complex distributed systems.

主な機能

Automated pytest fixtures for efficient unit and integration testing
Replay testing tools to validate workflow determinism before deployment
Activity mocking strategies to isolate and test workflow logic
0 GitHub stars
Advanced time-skipping for fast feedback on long-running workflows
Comprehensive local development setup with Docker and coverage tools

ユースケース

Verifying complex workflow logic without waiting for real-time timers
Validating workflow determinism to prevent breaking changes in production
Simulating activity failures and error injection to test system resilience

概要

主な機能

Automated pytest fixtures for efficient unit and integration testing
Replay testing tools to validate workflow determinism before deployment
Activity mocking strategies to isolate and test workflow logic
0 GitHub stars
Advanced time-skipping for fast feedback on long-running workflows
Comprehensive local development setup with Docker and coverage tools

ユースケース

Verifying complex workflow logic without waiting for real-time timers
Validating workflow determinism to prevent breaking changes in production
Simulating activity failures and error injection to test system resilience