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fix-build-agentops-temporal-python-testingFIX 构建 agentops temporal Python 测试

Agent Skill

用于辅助 Python 项目开发、测试、依赖管理和常见框架工作流。它适合让 Agent 阅读 Python 代码、定位测试问题、整理运行命令、生成脚本或分析数据处理逻辑。使用时需要确认项目虚拟环境、依赖版本和测试入口;涉及执行脚本、读写文件、访问数据库或调用外部 API 时,应先明确运行目录和输入输出范围,避免误改生产数据。

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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

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请帮我安装这个 Agent Skill:fix-build-agentops-temporal-python-testing(FIX 构建 agentops temporal Python 测试)
来源仓库:https://github.com/wu-uk/fix-build-agentops-temporal-python-testing
安装命令:
openclaw skills install fix-build-agentops-temporal-python-testing
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

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openclaw skills install fix-build-agentops-temporal-python-testing

简介

fix-build-agentops-temporal-python-testing 用于辅助 Python 测试开发。

  • 适用于 pytest、时间跳跃和模拟策略的测试场景。
  • 使用时需确认虚拟环境、依赖版本和测试入口。
  • 涉及脚本执行或文件操作时,应明确运行目录和输入输出范围。
  • 适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。

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

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

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能力 5

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安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

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