temporal-python-testing
Enables your agent to effectively test Temporal workflows using pytest. It helps ensure workflows function correctly across various scenarios.
What it does
This skill helps you test your programs (called 'workflows') that run on the Temporal platform using the pytest tool. It teaches you how to perform fast and reliable tests.
When to use it
- ✓When you want to test if a 'workflow' works correctly on its own.
- ✓When you want to test how a 'workflow' interacts with other parts of your program.
- ✓When you want to ensure your 'workflow' always behaves the same way.
Example of what to ask your AI
“How can I test my workflow so it runs very fast, even if it takes a long time in real life?”
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 tool called pytest to run your tests. To speed up tests, it simulates time passing, allowing long workflows to be tested in seconds. It also teaches you how to 'fake' external parts of your program, so you can focus only on your 'workflow'.
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 sickn33/agentic-awesome-skills --skill temporal-python-testingOr download just the file:
curl -L https://raw.githubusercontent.com/sickn33/agentic-awesome-skills/main/plugins/agentic-awesome-skills-claude/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.
Do not use this skill when
- The task is unrelated to temporal python testing strategies
- You need a different domain or tool outside this scope
Instructions
- Clarify goals, constraints, and required inputs.
- Apply relevant best practices and validate outcomes.
- Provide actionable steps and verification.
Use this skill when
- 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:
…
FAQ
What is a 'workflow' in Temporal?
A 'workflow' is a program that runs on the Temporal platform to orchestrate complex and resilient tasks.
Why mock activities?
Mocking means creating a fake version of a part of your program to test another part in isolation. This helps focus on the 'workflow' without worrying if other parts are working.
What is 'replay testing'?
It's a test that runs your 'workflow' with a real execution history to ensure it always produces the same result, which is crucial for reliability.
Details
Original description by the author
Comprehensive testing approaches for Temporal workflows using pytest, progressive disclosure resources for specific testing scenarios.
Popularity
- GitHub stars
- 48k
- Ranking position
- #4344
- License
- MIT
- Updated
- 10/15/2026
Comments
- …
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