How does this skill help with workflow determinism?

It provides replay testing resources that allow you to run existing production histories against your current code to ensure that changes haven't introduced non-deterministic behavior.

What is the recommended test coverage target?

Following Temporal best practices, this skill aims for at least 80% logic coverage for both workflows and activities to ensure high reliability in production.

Can I integrate these tests into a CI/CD pipeline?

Yes, the skill includes patterns for automated testing pipelines, coverage tool integration, and Docker Compose configurations suitable for CI/CD environments.

Does it support mocking external dependencies?

Yes, it provides specific strategies for mocking activities, allowing you to isolate workflow logic from external APIs, databases, or other side effects.

What is time-skipping in Temporal testing?

Time-skipping is a feature of the Temporal test environment that allows you to skip forward in time, enabling workflows that would naturally take days or months to be validated in milliseconds.

Temporal Python Testing

Name: Temporal Python Testing
Author: carloscroc

bycarloscroc

セキュリティとテスト

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

概要

This skill provides a comprehensive framework for testing Temporal workflows using the Python SDK and pytest. It guides developers through unit, integration, and replay testing, leveraging specialized tools like time-skipping to run long-running processes in seconds and activity mocking to isolate business logic. Whether you are setting up a local development environment with Docker or integrating determinism checks into your CI/CD pipeline, this skill ensures your distributed workflows are resilient, deterministically sound, and production-ready.

主な機能

Advanced time-skipping for rapid testing of long-running workflows
Specific strategies for achieving over 80% test coverage in backend logic
Determinism validation through production history replay testing
0 GitHub stars
Pre-configured pytest fixtures and WorkflowEnvironment templates
Robust activity mocking and error injection patterns for integration tests

ユースケース

Isolating workflow logic from flaky external API dependencies via activity mocking
Ensuring workflow determinism and version compatibility before production deployment
Validating complex, multi-month business processes in seconds using time-skipping

概要

主な機能

Advanced time-skipping for rapid testing of long-running workflows
Specific strategies for achieving over 80% test coverage in backend logic
Determinism validation through production history replay testing
0 GitHub stars
Pre-configured pytest fixtures and WorkflowEnvironment templates
Robust activity mocking and error injection patterns for integration tests

ユースケース

Isolating workflow logic from flaky external API dependencies via activity mocking
Ensuring workflow determinism and version compatibility before production deployment
Validating complex, multi-month business processes in seconds using time-skipping