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DECNET/tests/orchestrator/test_realism_config_refresh.py

75 lines
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Python

"""The orchestrator pulls operator-tuned weights from realism_config.
§3c contract: the planner reads in-memory module globals, but the
operator's tuning lives in the DB (admin PUT /api/v1/realism/config).
The orchestrator worker bridges the two by calling
``_refresh_realism_config(repo)`` at startup and every Nth tick.
"""
from __future__ import annotations
import json
from unittest.mock import AsyncMock
import pytest
from decnet.orchestrator.worker import _refresh_realism_config
from decnet.realism import planner
@pytest.fixture(autouse=True)
def _reset_planner():
yield
planner.reset_to_defaults()
@pytest.mark.asyncio
async def test_refresh_no_row_keeps_defaults():
repo = AsyncMock()
repo.get_realism_config = AsyncMock(return_value=None)
await _refresh_realism_config(repo)
assert planner.current_payload()["canary_probability"] == pytest.approx(0.03)
@pytest.mark.asyncio
async def test_refresh_applies_stored_payload():
repo = AsyncMock()
repo.get_realism_config = AsyncMock(return_value={
"key": "weights",
"value": json.dumps({"canary_probability": 0.12}),
})
await _refresh_realism_config(repo)
assert planner.current_payload()["canary_probability"] == pytest.approx(0.12)
@pytest.mark.asyncio
async def test_refresh_swallows_db_error():
"""A wedged DB must not bring down the orchestrator's tick loop."""
repo = AsyncMock()
repo.get_realism_config = AsyncMock(side_effect=RuntimeError("boom"))
await _refresh_realism_config(repo) # does not raise
# planner unchanged
assert planner.current_payload()["canary_probability"] == pytest.approx(0.03)
@pytest.mark.asyncio
async def test_refresh_swallows_malformed_json():
repo = AsyncMock()
repo.get_realism_config = AsyncMock(return_value={
"key": "weights",
"value": "not-json",
})
await _refresh_realism_config(repo)
assert planner.current_payload()["canary_probability"] == pytest.approx(0.03)
@pytest.mark.asyncio
async def test_refresh_swallows_invalid_payload():
repo = AsyncMock()
repo.get_realism_config = AsyncMock(return_value={
"key": "weights",
"value": json.dumps({"canary_probability": 9.0}),
})
await _refresh_realism_config(repo)
# Planner config not corrupted by a bad refresh.
assert planner.current_payload()["canary_probability"] == pytest.approx(0.03)