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temporal-python-testing

作者 wu-uk · GitHub ↗ · v0.1.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install fix-build-agentops-temporal-python-testing
功能描述
Test Temporal workflows with pytest, time-skipping, and mocking strategies. Covers unit testing, integration testing, replay testing, and local development s...
使用说明 (SKILL.md)

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
安全使用建议
This is a coherent, instruction-only guide for testing Temporal Python workflows. Before using it: 1) Review any example scripts (especially scripts/export_histories.py and CI examples) — they show connecting to a production Temporal endpoint and exporting workflow histories, which can contain sensitive data; only run these if you have explicit permission and proper credentials. 2) Do not run examples that target production from an untrusted environment; secure exported .pb files and logs. 3) The documents contain small example bugs/typos (e.g., missing imports like 'workflow' in health_check.py, a truncated CI cleanup command), so treat the code as examples to adapt rather than copy-paste. 4) Verify Docker images and dependencies come from official sources (e.g., temporalio/*, postgres) before pulling. If you need higher assurance, request the author/source repository or a signed release before running scripts that interact with production.
能力标签
cryptocan-make-purchases
能力评估
Purpose & Capability
Name/description (Temporal Python testing) match the provided instructions and resource files: unit, integration, replay, and local setup guidance. Examples and CI patterns are coherent with testing and replay use-cases.
Instruction Scope
Instructions include legitimately sensitive operations for replay testing: connecting to a production Temporal endpoint and exporting workflow histories. Those steps are within the stated purpose (replay/determinism testing) but they entail handling potentially sensitive data and require production access — the guide doesn't provide or request credentials, so users must supply and protect them.
Install Mechanism
Instruction-only skill with no install spec and no code files to be written or installed by the platform. Lowest-risk install profile.
Credentials
The skill declares no required environment variables or credentials, which is consistent for an instructional guide. However example scripts connect to 'production.temporal.io:7233' and call client.list_workflows / fetch_history; those operations require production access/credentials in practice. The absence of declared creds is not malicious but users should be aware they must provide appropriate credentials and guard exported history files.
Persistence & Privilege
always is false, no install actions, and the skill does not request persistent privileges or try to modify other skills or system-wide settings.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install fix-build-agentops-temporal-python-testing
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /fix-build-agentops-temporal-python-testing 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v0.1.0
Bulk publish from all-task-skills-dedup
元数据
Slug fix-build-agentops-temporal-python-testing
版本 0.1.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

temporal-python-testing 是什么?

Test Temporal workflows with pytest, time-skipping, and mocking strategies. Covers unit testing, integration testing, replay testing, and local development s... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 78 次。

如何安装 temporal-python-testing?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install fix-build-agentops-temporal-python-testing」即可一键安装,无需额外配置。

temporal-python-testing 是免费的吗?

是的,temporal-python-testing 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

temporal-python-testing 支持哪些平台?

temporal-python-testing 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 temporal-python-testing?

由 wu-uk(@wu-uk)开发并维护,当前版本 v0.1.0。

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