python-testing

name	python-testing
description	DeepSearch pytest guide for targeted tests, fixtures, async mocks, live-test gates, and artifact-safe test data.

Python Testing

Use this when adding or updating DeepSearch tests.

Workflow

1. Locate nearby tests for the touched source.
2. Add the smallest test that captures the behavior.
3. Mock LLM/search/storage/network boundaries by default.
4. Run targeted pytest before broad tests.

Commands

uv run pytest tests/path/to/test_file.py
uv run pytest -m "not llm"
RUN_LLM_TESTS=1 uv run pytest -m llm

Run live tests only when explicitly requested and credentials are configured.

Fixtures

• Prefer the nearest conftest.py.
• Use tmp_path for generated reports, markdown/html/docx files, logs, and databases.
• Use monkeypatch for environment variables and runtime config.
• Use AsyncMock for async LLM/search calls.

Async Tests

Pytest uses strict asyncio mode. Mark async tests explicitly and ensure background tasks are awaited or cancelled.

import pytest
from unittest.mock import AsyncMock

@pytest.mark.asyncio
async def test_node_uses_llm(monkeypatch):
    fake_call = AsyncMock(return_value={"result": "ok"})
    monkeypatch.setattr("module.path.call_llm", fake_call)

    result = await run_node()

    assert result["result"] == "ok"
    fake_call.assert_awaited_once()

Live-Test Boundary

• Mark real LLM/search tests with @pytest.mark.llm.
• Skip unless RUN_LLM_TESTS=1.
• Never make live credentials required for normal uv run pytest.