How does this skill help with workflow determinism?

It provides replay testing resources that allow you to validate your code against production history to ensure changes don't break deterministic execution rules.

Does it cover activity testing in isolation?

Yes, it provides guidance on using ActivityEnvironment to test individual activities independently of the workflow logic.

Is local development environment setup supported?

Absolutely. The skill includes resources for setting up a local Temporal server using Docker Compose to facilitate local integration and end-to-end testing.

What is time-skipping in Temporal testing?

Time-skipping allows you to test workflows that would normally take weeks or months in just seconds by advancing the virtual clock during execution.

Can I use this skill with standard pytest?

Yes, the skill includes specific patterns and fixtures designed for pytest, including integration with the pytest-asyncio plugin for asynchronous workflow testing.

Temporal Python Testing

Name: Temporal Python Testing
Author: Microck

byMicrock

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安全与测试

Provides comprehensive strategies and resources for testing Temporal workflows and activities using pytest, time-skipping, and mocking patterns.

关于

Temporal Python Testing is a specialized skill designed to streamline the quality assurance process for Temporal-based applications. It guides developers through implementing robust testing suites, including unit tests with fast time-skipping, integration tests with mocked activities, and replay tests to ensure workflow determinism. Whether you are setting up a local development environment with Docker or aiming for high test coverage in CI/CD pipelines, this skill offers the specific patterns, pytest fixtures, and debugging strategies needed to build reliable, production-ready workflows.

主要功能

Mocking strategies for isolating workflow logic from external dependencies
81 GitHub stars
Coverage strategies to achieve ≥80% test coverage for mission-critical workflows
Local development setup guides for Docker Compose and pytest configurations
Replay testing resources to validate workflow determinism against production histories
Fast unit testing with WorkflowEnvironment time-skipping for long-running processes

使用场景

Debugging workflow failures by replaying production execution histories locally
Writing integration tests for complex, multi-activity workflows with mocked dependencies
Automating Temporal test suites within CI/CD pipelines for high-reliability deployments

关于

主要功能

Mocking strategies for isolating workflow logic from external dependencies
81 GitHub stars
Coverage strategies to achieve ≥80% test coverage for mission-critical workflows
Local development setup guides for Docker Compose and pytest configurations
Replay testing resources to validate workflow determinism against production histories
Fast unit testing with WorkflowEnvironment time-skipping for long-running processes

使用场景

Debugging workflow failures by replaying production execution histories locally
Writing integration tests for complex, multi-activity workflows with mocked dependencies
Automating Temporal test suites within CI/CD pipelines for high-reliability deployments