temporal-python-testing
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.
Best use case
temporal-python-testing is best used when you need a repeatable AI agent workflow instead of a one-off prompt. It is especially useful for teams working in multi. 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.
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.
Users should expect a more consistent workflow output, faster repeated execution, and less time spent rewriting prompts from scratch.
Practical example
Example input
Use the "temporal-python-testing" skill to help with this workflow task. Context: 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.
Example output
A structured workflow result with clearer steps, more consistent formatting, and an output that is easier to reuse in the next run.
When to use this skill
- Use this skill when you want a reusable workflow rather than writing the same prompt again and again.
When not to use this skill
- Do not use this when you only need a one-off answer and do not need a reusable workflow.
- Do not use it if you cannot install or maintain the related files, repository context, or supporting tools.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/temporal-python-testing/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How temporal-python-testing Compares
| Feature / Agent | temporal-python-testing | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
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.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# 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.
- If detailed examples are required, open `resources/implementation-playbook.md`.
## 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**:
1. **Unit**: Workflows with time-skipping, activities with ActivityEnvironment
2. **Integration**: Workers with mocked activities
3. **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
```python
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
```python
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
1. **Time-Skipping** - Month-long workflows test in seconds
2. **Mock Activities** - Isolate workflow logic from external dependencies
3. **Replay Testing** - Validate determinism before deployment
4. **High Coverage** - ≥80% target for production workflows
5. **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
- Testing Patterns: github.com/temporalio/temporal/blob/main/docs/development/testing.md
- Python Samples: github.com/temporalio/samples-pythonRelated Skills
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