Temporal Python Testing

About

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

• Time-skipping for near-instant execution of long-running workflows
• Replay testing tools to validate workflow determinism
• 23,194 GitHub stars
• Async pytest fixtures for streamlined integration testing
• Local development environment setup with Docker Compose
• Comprehensive activity mocking and error injection strategies

Use Cases

• Validating workflow changes against production histories before deployment
• Testing complex business logic in long-running workflows without waiting
• Achieving high test coverage for distributed backend orchestration logic