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.

242 stars

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

$curl -o ~/.claude/skills/temporal-python-testing/SKILL.md --create-dirs "https://raw.githubusercontent.com/aiskillstore/marketplace/main/skills/sickn33/temporal-python-testing/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/temporal-python-testing/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How temporal-python-testing Compares

Feature / Agenttemporal-python-testingStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/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.

Related Guides

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-python

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