temporal-python-testing

Comprehensive testing approaches for Temporal workflows using pytest, progressive disclosure resources for specific testing scenarios.

31,392 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. Comprehensive testing approaches for Temporal workflows using pytest, progressive disclosure resources for specific testing scenarios.

Comprehensive testing approaches for Temporal workflows using pytest, progressive disclosure resources for specific testing scenarios.

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: Comprehensive testing approaches for Temporal workflows using pytest, progressive disclosure resources for specific testing scenarios.

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/sickn33/antigravity-awesome-skills/main/plugins/antigravity-awesome-skills-claude/skills/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?

Comprehensive testing approaches for Temporal workflows using pytest, progressive disclosure resources for specific testing scenarios.

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

## Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

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