Can I use this for local development setup?

Yes, it includes specific resources for configuring a local Temporal server with Docker and setting up pytest fixtures for a seamless developer experience.

What is the recommended test coverage for Temporal workflows?

Industry best practices suggest a target of at least 80% logic coverage for both workflows and activities to ensure high reliability in production environments.

Does this skill support activity mocking?

Yes, it provides detailed integration testing patterns for mocking external dependencies and injecting errors to test how your workflows handle activity failures.

What is time-skipping in Temporal testing?

Time-skipping allows you to execute workflows that would normally take days or months in just seconds by advancing the internal clock during tests, providing rapid feedback.

How does this skill help with workflow determinism?

It provides replay testing strategies to validate that your workflow code remains deterministic when compared against existing production execution histories, preventing runtime errors.

Temporal Python Testing

Name: Temporal Python Testing
Author: 3commas-io

by3commas-io

セキュリティとテスト

Implements comprehensive testing strategies for Temporal Python workflows using time-skipping, activity mocking, and determinism validation.

概要

This skill provides a robust framework for testing Temporal applications in Python, enabling developers to simulate complex, long-running workflows in seconds through advanced time-skipping techniques. It guides users through the entire testing lifecycle—from unit and integration tests with pytest to critical replay testing for validating determinism—ensuring distributed systems achieve high code coverage and production-grade reliability.

主な機能

Determinism validation via replay testing against production histories
Time-skipping for near-instant execution of long-running workflows
Activity mocking and error injection patterns for isolation
0 GitHub stars
Standardized local development setup using Docker and pytest
Strategies for achieving 80%+ test coverage across workflows and activities

ユースケース

Setting up automated CI/CD pipelines for Temporal-based microservices
Testing a multi-month subscription workflow in a matter of seconds
Validating workflow logic determinism before deploying breaking changes

概要

主な機能

Determinism validation via replay testing against production histories
Time-skipping for near-instant execution of long-running workflows
Activity mocking and error injection patterns for isolation
0 GitHub stars
Standardized local development setup using Docker and pytest
Strategies for achieving 80%+ test coverage across workflows and activities

ユースケース

Setting up automated CI/CD pipelines for Temporal-based microservices
Testing a multi-month subscription workflow in a matter of seconds
Validating workflow logic determinism before deploying breaking changes