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temporal-python-testing

Test Temporal Python workflows with pytest, time-skipping, and activity mocking.

Updated Apr 4, 2026
Search Tags:#workflow#testing#pytest#mocking#unit-testing#temporal#time-skipping
One-click install
npx skills add https://github.com/emilneuraz-ai/neuraz-web --skill temporal-python-testing-emilneuraz-ai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: temporal-python-testing
Source: https://github.com/emilneuraz-ai/neuraz-web/tree/main/.agents/skills/.agents/skills/temporal-python-testing
Command: npx skills add https://github.com/emilneuraz-ai/neuraz-web --skill temporal-python-testing-emilneuraz-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Temporal testing can be slow and flaky without deterministic time control and isolated environments. This Skill offers structured guidance to test Temporal Python workflows using pytest, time-skipping, and mocking to deliver fast, reliable feedback.

Core Features & Use Cases

  • Time-skipping enables rapid execution of long-running workflows by skipping forward in time.
  • Mocked activities isolate workflow orchestration from external systems for focused testing.
  • Covers unit, integration, and replay testing to ensure determinism, compatibility, and robust validation.

Quick Start

Run a simple pytest workflow test that uses time-skipping to validate a short-running variant of a Temporal workflow.

Frequently Asked Questions about temporal-python-testing

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I test Temporal Python workflows deterministically with pytest?▼

Test Temporal Python workflows deterministically by using pytest with time-skipping to fast-forward long-running processes and mocking activities to isolate orchestration from external systems, ensuring fast and reliable feedback.

What is time-skipping in Temporal workflow testing and when should I use it?▼

Time-skipping in Temporal workflow testing rapidly executes long-running workflows by skipping forward in time. Use it to validate timer-dependent logic and orchestration flows quickly without waiting for real clock time to pass.

What's the best way to set up replay testing for Temporal Python workflows?▼

Set up Temporal Python workflow replay testing by using structured testing patterns to replay historical event data against current workflow code. This validates compatibility and ensures that code changes do not break existing executions.

Do I need a running Temporal server to execute Python workflow tests?▼

Yes, you need access to a Temporal server to run integration tests. However, unit tests can isolate workflow logic by mocking activities, and time-skipping accelerates execution without requiring real-time delays on the server.

Why are my Temporal Python tests flaky and how can I fix them?▼

Temporal Python tests become flaky without deterministic time control and isolated environments. Fix them by applying time-skipping to control workflow timers and mocking activities to remove external system variability.

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