
Temporal Python Testing
FreeStreamline testing for Temporal workflows with pytest.
Free · Opens the source repo
What Temporal Python Testing does
The Temporal Python Testing skill provides a structured approach to testing Temporal workflows using pytest, focusing on various testing strategies such as unit, integration, and replay testing. This skill is designed for developers working with Temporal, offering detailed guidance on setting up tests efficiently and effectively. By leveraging time-skipping and mocking strategies, users can achieve rapid feedback and validate the correctness of their workflows.
This skill includes comprehensive resources that cover the entire testing lifecycle. For unit testing, it emphasizes the use of time-skipping to speed up tests, allowing developers to run long-running workflows in seconds. Integration testing resources focus on mocking external activities, enabling users to isolate workflow logic and test critical paths without relying on actual dependencies. Replay testing is also covered, providing methods to validate determinism against production histories, which is crucial for ensuring reliable workflow execution.
In addition to testing strategies, the skill includes setup instructions for local development, ensuring that users can create a conducive environment for testing. It also outlines best practices for achieving high coverage targets, reinforcing the importance of thorough testing in production environments. The progressive disclosure of resources allows users to access specific information based on their immediate needs, making it a flexible tool for developers at various stages of the testing process.
When to use it
Use this skill when developing and testing Temporal workflows, particularly when you need to implement unit, integration, or replay tests.
When not to use it
Avoid this skill for tasks unrelated to Temporal workflows or when using testing tools outside the scope of pytest and Temporal.
What you can build with it
Unit Testing Workflows
Quickly test individual workflows using time-skipping to validate logic without long execution times.
Integration Testing with Mocks
Test workflows that depend on external activities by mocking those dependencies to isolate workflow behavior.
Replay Testing for Determinism
Validate that your workflows produce consistent results by replaying historical execution data.
How to install Temporal Python Testing
View source1. Install with the skills CLI
npx skills add rmyndharis/antigravity-skills/temporal-python-testing --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by rmyndharisTemporal 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:
- "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
Frequently asked questions about Temporal Python Testing
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