ipIterPrompt

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 implemen

wshobson · agentsUpdated 2026-05-272,327 copies

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. Imported from wshobson/agents (MIT).

SKILL.md

---
name: temporal-python-testing
description: 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.
---

# 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**:

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-python

Run this skill on a real model without leaving the page. Every run is saved to your history for this skill.

How to use

  1. 1Save the content below as SKILL.md in your agent's skills directory (e.g. .claude/skills/<name>/SKILL.md).
  2. 2Or paste it directly into the conversation as context before asking the agent to do the task.
  3. 3Adjust any project-specific paths or conventions mentioned in the skill to match your setup.

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