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temporal-python-testing

Test Temporal workflows with pytest, time-skipping, and mocks.

1|Updated Apr 27, 2026
Search Tags:#testing#pytest#mocking#temporal#replay#time-skipping
One-click install
npx skills add https://github.com/haxlys/skills --skill temporal-python-testing-haxlys
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: temporal-python-testing
Source: https://github.com/haxlys/skills/tree/main/vendored/wshobson-agents/plugins/backend-development/skills/temporal-python-testing
Command: npx skills add https://github.com/haxlys/skills --skill temporal-python-testing-haxlys

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Testing Temporal workflows can be slow and brittle without available tooling and patterns for fast feedback. This Skill provides structured guidance to implement time-skipping, activity mocking, and replay testing to accelerate development and improve determinism.

Core Features & Use Cases

  • Time-skipping enables fast progression of long-running workflows
  • Mocked activities and controlled environments for reliable unit/integration tests
  • Replay testing and local development setups to validate production parity
  • Progressive resource guidance (unit, integration, replay, local setup)

Quick Start

Load the unit-testing resources to begin building fast, deterministic Temporal workflow tests.

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 workflows faster using time-skipping?▼

Time-skipping accelerates Temporal workflow testing by fast-forwarding long-running processes. This approach enforces deterministic outcomes and provides rapid feedback during local development.

What is the best way to mock activities for Temporal workflow unit tests?▼

Mocking activities provides controlled environments for reliable Temporal workflow unit tests. This ensures deterministic behavior by isolating workflow logic from external service dependencies.

Can I use pytest with Temporal replay testing for local development?▼

Yes, pytest integrates with Temporal replay testing to validate production parity. This combination supports reliable local development by replaying workflow histories against current code changes.

Does replay testing ensure deterministic outcomes for Temporal workflows?▼

Replay testing validates deterministic outcomes by executing historical Temporal workflow event logs against updated code. This verifies that recent changes do not break existing workflow logic.

Why are my Temporal workflow integration tests slow and brittle?▼

Temporal workflow integration tests become slow without time-skipping and brittle without mocked activities. Structured testing patterns resolve this by enforcing determinism and controlling test environments.

Do I need a local Temporal server setup to run workflow tests?▼

A local Temporal server setup is recommended for integration and replay testing. This environment validates production parity while allowing fast, deterministic local development execution.

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