Temporal Python Testing Strategies

SkillAI & models

temporal-python-testing is a skill that helps an AI agent write and fix pytest tests for Temporal workflows. It covers unit testing, integration testing, replay testing, and local development setup. Use it when implementing Temporal workflow tests or debugging test failures.

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Details

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Have a Python project with Temporal workflows and pytest available.

Temporal Python Testing StrategiesStart free

What your AI can do with it

  • Write pytest tests for Temporal workflows
  • Apply time-skipping to test timers and delays
  • Use mocking strategies for activities and clients
  • Set up local development for Temporal tests
  • Debug failing Temporal workflow tests

Getting started

  1. Have a Python project with Temporal workflows and pytest available.
  2. Add the skill to your agent's configuration.
  3. Point the agent at your workflow test files or describe the failing test.
  4. Ask the agent to write or fix tests using time-skipping and mocking.

What this skill tells your AI

The instructions your AI receives, as published by wshobson/agents in plugins/backend-development/skills/temporal-python-testing/SKILL.md and read by ahel’s review.

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

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

  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

Signals

GitHub stars
40k
Forks
4k
Last commit
Sep 2026

ahel review

  • K1binfo
    installs-packages (in resources/local-setup.md)
  • K1binfo
    installs-packages (in resources/replay-testing.md)

Automated review, not a security audit. Ruleset v1+k2.

Questions

What testing approaches does it cover?
It covers unit testing, integration testing, replay testing, and local development setup for Temporal workflows.
Does it help with debugging test failures?
Yes, it is intended for debugging test failures in Temporal workflow tests.
What test framework does it use?
It uses pytest.
Does it support time-skipping?
Yes, it covers time-skipping for testing Temporal workflows.
Does it cover mocking?
Yes, it covers mocking strategies.
Advanced
Item type
skill
Key
temporal-python-testing
Source
github.com/wshobson/agents