temporal-python-testing
Helps your agent test complex workflows efficiently. It allows checking if code works as expected in different situations.
What it does
This tool helps test your programs (called 'workflows') that run on the Temporal platform. It allows simulating time to speed up tests and testing specific parts of your code in isolation.
When to use it
- ✓When you want to test if a 'workflow' works correctly.
- ✓When you want to test 'workflows' that depend on other parts of the system.
- ✓When you want to ensure your 'workflow' behaves the same way in different situations.
Example of what to ask your AI
“How can I test my workflow by simulating time passing faster?”
Want more? Open the sections below.
How to use
The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.
Skill link
Ready-to-paste message
How it works
It uses a library called pytest to organize tests. To speed up time, it 'skips' time instead of waiting. To test isolated parts, it replaces dependencies with fake versions ('mocks').
Installation
Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.
In the terminal (Claude Code, Codex, Cursor), in your project folder:
npx skills add wshobson/agents --skill temporal-python-testingOr download just the file:
curl -L https://raw.githubusercontent.com/wshobson/agents/main/plugins/backend-development/skills/temporal-python-testing/SKILL.md -o SKILL.mdTechnical content (original SKILL.md)
Original text by the author, straight from GitHub.
Temporal Python Testing Strategies
Comprehensive testing approaches for Temporal workflows using pytest, progressive disclosure resources for specific testing scenarios.
When to Use This Skill
- Unit testing workflows - Fast tests with time-skipping
- Integration testing - Workflows with mocked activities
- Replay testing - Validate determinism against production histories
- Local development - Set up Temporal server and pytest
- CI/CD integration - Automated testing pipelines
- Coverage strategies - Achieve ≥80% test coverage
Testing Philosophy
Recommended Approach (Source: docs.temporal.io/develop/python/testing-suite):
- Write majority as integration tests
- Use pytest with async fixtures
- Time-skipping enables fast feedback (month-long workflows → seconds)
- Mock activities to isolate workflow logic
- Validate determinism with replay testing
Three Test Types:
- Unit: Workflows with time-skipping, activities with ActivityEnvironment
- Integration: Workers with mocked activities
- End-to-end: Full Temporal server with real activities (use sparingly)
Available Resources
This skill provides detailed guidance through progressive disclosure. Load specific resources based on your testing needs:
Unit Testing Resources
File: resources/unit-testing.md
When to load: Testing individual workflows or activities in isolation
Contains:
- WorkflowEnvironment with time-skipping
- ActivityEnvironment for activity testing
- Fast execution of long-running workflows
- Manual time advancement patterns
- pytest fixtures and patterns
Integration Testing Resources
File: resources/integration-testing.md
When to load: Testing workflows with mocked external dependencies
Contains:
- Activity mocking strategies
- Error injection patterns
- Multi-activity workflow testing
- Signal and query testing
- Coverage strategies
Replay Testing Resources
File: resources/replay-testing.md
When to load: Validating determinism or deploying workflow changes
Contains:
- Determinism validation
- Production history replay
- CI/CD integration patterns
- Version compatibility testing
Local Development Resources
File: resources/local-setup.md
When to load: Setting up development environment
Contains:
- Docker Compose configuration
- pytest setup and configuration
- Coverage tool integration
- Development workflow
Quick Start Guide
Basic Workflow Test
import pytest
from temporalio.testing import WorkflowEnvironment
from temporalio.worker import Worker
@pytest.fixture
async def workflow_env():
env = await WorkflowEnvironment.start_time_skipping()
yield env
await env.shutdown()
@pytest.mark.asyncio
async def test_workflow(workflow_env):
async with Worker(
workflow_env.client,
task_queue="test-queue",
workflows=[YourWorkflow],
activities=[your_activity],
):
result = await workflow_env.client.execute_workflow(
YourWorkflow.run,
args,
id="test-wf-id",
task_queue="test-queue",
)
assert result == expected
Basic Activity Test
from temporalio.testing import ActivityEnvironment
async def test_activity():
env = ActivityEnvironment()
result = await env.run(your_activity, "test-input")
assert result == expected_output
Coverage Targets
Recommended Coverage (Source: docs.temporal.io best practices):
- Workflows: ≥80% logic coverage
- Activities: ≥80% logic coverage
- Integration: Critical paths with mocked activities
- Replay: All workflow versions before deployment
Key Testing Principles
- Time-Skipping - Month-long workflows test in seconds
- Mock Activities - Isolate workflow logic from external dependencies
- Replay Testing - Validate determinism before deployment
- High Coverage - ≥80% target for production workflows
- Fast Feedback - Unit tests run in milliseconds
How to Use Resources
Load specific resource when needed:
- "Show me unit testing patterns" → Load
resources/unit-testing.md - "How do I mock activities?" → Load
resources/integration-testing.md - "Setup local Temporal server" → Load
resources/local-setup.md - "Validate determinism" → Load
resources/replay-testing.md
Additional References
- Python SDK Testing: docs.temporal.io/develop/python/testing-suite
…
FAQ
What is 'time-skipping'?
It's a technique that allows your tests to run much faster by simulating that days or months have passed in seconds, without having to wait for real time to elapse.
What are 'mocked activities'?
These are fake versions of parts of your code (activities) that your 'workflow' calls. This allows testing the 'workflow' without needing those other parts to actually work, focusing only on the 'workflow''s logic.
What is 'replay testing'?
It's a test that runs your 'workflow' again using a history of how it has run before. This helps ensure the 'workflow' is consistent and doesn't change its behavior unexpectedly.
Details
Original description by the author
Test Temporal workflows with pytest, time-skipping, and mocking strategies. Covers unit testing, integration testing, replay testing, and local development setup. Use when implementing Temporal workflow tests or debugging test failures.
repo: wshobson/agents
Popularity
- GitHub stars
- 41k
- Ranking position
- #4809
- License
- MIT
- Updated
- 10/15/2026
Comments
- …
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