Why is replay testing important?

Replay testing ensures that changes to your workflow code do not break determinism. It validates that your updated code can still process existing histories from production without errors.

Do I need a running Temporal server for these tests?

No, this skill demonstrates how to use the WorkflowEnvironment to run tests in-memory, which is faster and more reliable for unit and integration testing than a full server.

How does time-skipping work in Temporal Python tests?

Time-skipping allows you to test workflows that would normally take weeks or months in just seconds by using a specialized test environment that advances the internal clock automatically or manually.

What is the recommended test coverage for Temporal workflows?

For production-grade workflows and activities, it is recommended to maintain at least 80% logic coverage using a mix of unit, integration, and replay tests.

Temporal Python Testing

Name: Temporal Python Testing
Author: EngineerWithAI

byEngineerWithAI

보안 및 테스팅

Implements comprehensive testing strategies for Temporal workflows in Python using pytest, time-skipping, and replay validation.

소개

This skill provides a complete framework for testing Temporal workflows and activities within Python environments. It guides developers through unit testing with time-skipping to accelerate long-running processes, integration testing with sophisticated activity mocking, and replay testing to guarantee workflow determinism. Designed to help teams achieve high test coverage, it includes ready-to-use pytest fixtures, local development configurations, and CI/CD integration patterns tailored for the Temporal Python SDK.

주요 기능

Time-skipping capabilities to test month-long workflows in seconds
0 GitHub stars
Determinism validation through production history replay testing
Standardized pytest fixtures for Workflow and Activity environments
Local development setup with Docker Compose and coverage tools
Comprehensive activity mocking and error injection strategies

사용 사례

Setting up automated testing pipelines for Temporal-based microservices
Validating workflow versioning and determinism before production deployment
Debugging complex workflow logic without waiting for real-time timers

소개

주요 기능

Time-skipping capabilities to test month-long workflows in seconds
0 GitHub stars
Determinism validation through production history replay testing
Standardized pytest fixtures for Workflow and Activity environments
Local development setup with Docker Compose and coverage tools
Comprehensive activity mocking and error injection strategies

사용 사례

Setting up automated testing pipelines for Temporal-based microservices
Validating workflow versioning and determinism before production deployment
Debugging complex workflow logic without waiting for real-time timers