How does time-skipping work in Temporal Python testing?

Time-skipping uses a virtual clock within the WorkflowEnvironment, allowing tests to instantly fast-forward through timers and sleep statements without actual delay.

What is the recommended test coverage for production workflows?

The skill recommends a target of at least 80% logic coverage for both workflows and activities to ensure production stability.

Can I test individual activities in isolation?

Yes, this skill provides patterns for using ActivityEnvironment to run and assert activity results independently of a workflow.

Why is replay testing important for Temporal workflows?

Replay testing ensures that new code changes are compatible with existing workflow histories, preventing non-determinism errors when running workflows are updated.

Temporal Python Testing

Name: Temporal Python Testing
Author: Tahir-yamin

byTahir-yamin

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보안 및 테스팅

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

소개

This skill provides a comprehensive framework for testing Temporal workflows in Python, ensuring that distributed systems are reliable and deterministic. It guides developers through implementing time-skipping to test long-running workflows in seconds, mocking activities to isolate business logic, and using replay testing to prevent non-determinism errors before production deployment. By providing structured patterns for pytest fixtures and environment setup, it helps teams achieve high code coverage and robust CI/CD integration for complex workflow orchestration.

주요 기능

Comprehensive activity mocking strategies for isolated logic testing
Determinism validation through production history replay testing
Automated time-skipping to test long-running workflows in milliseconds
Pre-configured pytest fixtures for rapid environment setup
3 GitHub stars
Step-by-step guides for local development and CI/CD pipeline integration

사용 사례

Validating workflow changes against production histories to prevent breaking changes
Testing month-long business processes without waiting for real-world time
Debugging complex distributed state machines using isolated unit and integration tests

소개

주요 기능

Comprehensive activity mocking strategies for isolated logic testing
Determinism validation through production history replay testing
Automated time-skipping to test long-running workflows in milliseconds
Pre-configured pytest fixtures for rapid environment setup
3 GitHub stars
Step-by-step guides for local development and CI/CD pipeline integration

사용 사례

Validating workflow changes against production histories to prevent breaking changes
Testing month-long business processes without waiting for real-world time
Debugging complex distributed state machines using isolated unit and integration tests