Comprehensive testing approaches for Temporal workflows using pytest, progressive disclosure resources for specific testing scenarios.
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Comprehensive testing approaches for Temporal workflows using pytest, progressive disclosure resources for specific testing scenarios.
resources/implementation-playbook.md.Recommended Approach (Source: docs.temporal.io/develop/python/testing-suite):
Three Test Types:
This skill provides detailed guidance through progressive disclosure. Load specific resources based on your testing needs:
File: resources/unit-testing.md
When to load: Testing individual workflows or activities in isolation
Contains:
File: resources/integration-testing.md
When to load: Testing workflows with mocked external dependencies
Contains:
File: resources/replay-testing.md
When to load: Validating determinism or deploying workflow changes
Contains:
File: resources/local-setup.md
When to load: Setting up development environment
Contains:
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
from temporalio.testing import ActivityEnvironment
async def test_activity():
env = ActivityEnvironment()
result = await env.run(your_activity, "test-input")
assert result == expected_output
Recommended Coverage (Source: docs.temporal.io best practices):
Load specific resource when needed:
resources/unit-testing.mdresources/integration-testing.mdresources/local-setup.mdresources/replay-testing.mdPrerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
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sickn33/antigravity-awesome-skills
Useful defaults in temporal-python-testing — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
I recommend temporal-python-testing for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
temporal-python-testing is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
We added temporal-python-testing from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Registry listing for temporal-python-testing matched our evaluation — installs cleanly and behaves as described in the markdown.
temporal-python-testing reduced setup friction for our internal harness; good balance of opinion and flexibility.
Solid pick for teams standardizing on skills: temporal-python-testing is focused, and the summary matches what you get after install.
I recommend temporal-python-testing for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Useful defaults in temporal-python-testing — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Keeps context tight: temporal-python-testing is the kind of skill you can hand to a new teammate without a long onboarding doc.
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