Skills temporal-python-testing

🧪

temporal-python-testing

Name: temporal-python-testing
Author: wshobson

Safe ⚙️ External commands🌐 Network access📁 Filesystem access

Test Temporal workflows with pytest and mocks

Temporal workflow tests are often slow or flaky. This skill provides fast, deterministic testing patterns using time-skipping, activity mocking, and replay validation for reliable CI/CD pipelines.

Supports: Claude Codex Code(CC)

📊 69 Adequate

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Using "temporal-python-testing". Create a test plan for Temporal workflows with unit, integration, and replay coverage.

Expected outcome:

Use WorkflowEnvironment with time skipping for fast unit workflow tests
Mock external dependencies in integration tests and verify error handling paths
Export production histories and replay against new code before deployment

Using "temporal-python-testing". How do I test a workflow that has retry logic and multiple activities?

Expected outcome:

Create a test with mocked activities to isolate workflow logic
Use ActivityEnvironment to test activity-specific error handling
Verify retry behavior by counting activity invocations
Test both success and failure paths with assertions

Using "temporal-python-testing". What are common mistakes when testing Temporal workflows?

Expected outcome:

Calling real external APIs instead of mocking them
Using random() or datetime.now() which breaks replay determinism
Skipping replay tests before deploying workflow changes
Not using time-skipping for long-running workflow tests

Security Audit

Safe

v4 • 1/17/2026

Educational documentation for Temporal workflow testing. Static scanner false positives: markdown code block backticks flagged as shell execution, legitimate docs URLs as hardcoded URLs, and test code patterns as cryptographic/C2 indicators. Previous Claude audit (skill-report.json) confirmed safe with no risk factors. All 149 findings are false positives from documentation patterns.

Files scanned

2,131

Lines analyzed

findings

Total audits

Risk Factors

⚙️ External commands (125)

🌐 Network access (6)

resources/local-setup.md:48 resources/local-setup.md:69 resources/local-setup.md:502 resources/replay-testing.md:123 resources/replay-testing.md:123 skill-report.json:6

📁 Filesystem access (4)

resources/replay-testing.md:455 resources/replay-testing.md:195 resources/replay-testing.md:291 resources/replay-testing.md:323

Audited by: claude View Audit History →

Quality Score

Architecture

100

Maintainability

Content

Community

100

Security

Spec Compliance

What You Can Build

Add fast unit tests

Create quick workflow and activity tests with time skipping that run in milliseconds instead of hours.

Validate integration flows

Mock external services and verify complex workflow orchestration paths with error injection.

Run replay checks

Confirm workflow determinism before deployment and validate version compatibility.

Try These Prompts

Start unit tests

Show me a minimal pytest setup to test a workflow with time skipping and a simple activity. Include fixtures and assertions.

Mock activities

Provide an integration test example that mocks activities and verifies workflow branching logic based on activity results.

Replay safety check

Explain how to replay workflow histories from production and detect non-deterministic changes that could break running workflows.

CI coverage plan

Outline a complete CI plan with pytest markers, coverage thresholds, and automated replay tests for safe deployments.

Best Practices

Use time skipping for all workflow unit tests to run month-long workflows in seconds
Mock external dependencies in integration tests to isolate workflow logic
Run replay tests before deploying any workflow changes to ensure determinism

Avoid

Calling real external APIs inside workflow tests instead of mocking
Using random() or datetime.now() in workflow code without Temporal helpers
Skipping replay tests after significant workflow refactors or logic changes

Frequently Asked Questions

What Python versions are supported?

Examples target Python 3.10 or newer with the Temporal Python SDK v1.5.0 or later.

Are there limits on test size?

No fixed limits, but large replay test suites should be batched in CI for performance.

Can I integrate this with existing pytest setups?

Yes, the guidance uses standard pytest fixtures and markers that work with existing configurations.

Does this skill access my data or credentials?

No, it provides guidance only and does not read files, environment variables, or secrets.

What if tests fail due to nondeterminism?

Use workflow.get_version() for safe changes and avoid random or datetime without Temporal helpers.

How does this compare to end-to-end tests?

It emphasizes faster unit and integration tests with mocking, using replay tests for safety validation.

Developer Details

Author

wshobson

License

MIT

Repository

https://github.com/wshobson/agents/tree/main/plugins/backend-development/skills/temporal-python-testing

Ref

main

File structure

📁 resources/

📄 integration-testing.md

📄 local-setup.md

📄 replay-testing.md

📄 unit-testing.md

📄 SKILL.md