Files
heating-mpc-ha/tests/test_data_quality.py
T
buzeraandClaude Opus 5.5 d73e32a4b9 Never publish a plan computed from inputs that have since changed
Confirmed: the check run after the optimizer compared only zone sensors,
outdoor temperature, thermostat and relay. A window opening, a UPS load
change or a wind change during the calculation went unnoticed; nothing
prevented an older update that finished late from overwriting a newer
result; and an update in flight during unload still saved.

- Every input a prediction uses is captured as a normalized snapshot
  (zone and outdoor temperatures, wind speed/direction/gust, heat-source
  power, window states, relay state and switch time, thermostat mode and
  target) and compared after the calculation with tolerances (0.25 °C,
  50 W, 1 m/s, 2 m/s gusts, 20° direction around the circle; exact for
  relay, thermostat and windows). A meaningful change discards the plan
  and lists the inputs in changed_inputs; noise does not. No immediate
  recalculation: an off-schedule poll would break the 5-minute learning
  interval; the next regular poll computes a fresh plan.
- Updates are numbered; one overtaken by a newer update, or running when
  the entry unloads, keeps the newer data and skips saving and
  optimizing. Configuration changes reload the entry, so they are covered.
- A per-entry storage lock makes a reloaded coordinator restore only
  after the previous one's save finished, and integration removal waits
  for it too, so a late save cannot recreate a deleted model file.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-27 03:37:51 +02:00

77 lines
4.4 KiB
Python

"""Timestamp boundaries and UI translation coverage without HA dependencies."""
import importlib.util
import json
import unittest
from datetime import datetime, timedelta, timezone
from pathlib import Path
ROOT = Path(__file__).resolve().parents[1] / 'custom_components' / 'heating_mpc'
spec = importlib.util.spec_from_file_location('quality', ROOT / 'data_quality.py')
quality = importlib.util.module_from_spec(spec)
spec.loader.exec_module(quality)
spec = importlib.util.spec_from_file_location('heating_mpc_const', ROOT / 'const.py')
const = importlib.util.module_from_spec(spec)
spec.loader.exec_module(const)
class FreshnessTests(unittest.TestCase):
def test_age_boundaries(self):
now = datetime(2026, 10, 26, tzinfo=timezone.utc)
for seconds, expected in ((0, 'valid'), (1800, 'valid'), (1801, 'stale'), (-1, 'future_timestamp')):
with self.subTest(seconds=seconds):
result = quality.freshness(now - timedelta(seconds=seconds), now, 1800)
self.assertEqual(result['status'], expected)
self.assertEqual(result['age_seconds'], seconds)
def test_missing_naive_and_malformed_times(self):
now = datetime.now(timezone.utc)
for timestamp in (None, 'bad', datetime.now()):
self.assertEqual(quality.freshness(timestamp, now, 1800)['status'], 'invalid_timestamp')
def test_invalid_limits_rejected(self):
now = datetime.now(timezone.utc)
for limit in (0, -1, float('inf'), float('nan')):
with self.assertRaises(ValueError):
quality.freshness(now, now, limit)
def test_report_age_history_keeps_24_hour_maximum(self):
history = quality.ReportAgeHistory()
start = datetime(2026, 10, 26, tzinfo=timezone.utc)
self.assertEqual(history.observe('sensor.a', start, 2400), 2400)
self.assertEqual(history.observe('sensor.b', start, 60), 60)
for minutes in range(5, 24 * 60, 5):
result = history.observe('sensor.a', start + timedelta(minutes=minutes), 300)
self.assertEqual(result, 2400) # still inside the 24-hour window
later = start + timedelta(hours=24, minutes=5)
self.assertEqual(history.observe('sensor.a', later, 300), 300)
self.assertEqual(history.observe('sensor.b', later, 30), 30)
def test_inputs_differ_ignores_noise_but_not_meaningful_changes(self):
before = {('temperature', 'sensor.room'): 20.0, ('power', 'sensor.ups'): 210.0,
('wind_direction', 'sensor.dir'): 355.0, ('wind', 'sensor.wind'): 4.0,
('window', 'binary_sensor.w'): False, ('thermostat', 'climate.t'): ('heat', 22, None)}
noise = {**before, ('temperature', 'sensor.room'): 20.1, ('power', 'sensor.ups'): 240.0,
('wind_direction', 'sensor.dir'): 5.0, ('wind', 'sensor.wind'): 4.6}
self.assertEqual(quality.inputs_differ(before, noise), []) # 10° across north is small
for key, value in ((('temperature', 'sensor.room'), 20.5), (('power', 'sensor.ups'), 610.0),
(('wind_direction', 'sensor.dir'), 40.0), (('window', 'binary_sensor.w'), True),
(('window', 'binary_sensor.w'), None), (('thermostat', 'climate.t'), ('heat', 21, None)),
(('temperature', 'sensor.room'), None)):
with self.subTest(key=key, value=value):
self.assertEqual(quality.inputs_differ(before, {**before, key: value}), [key])
self.assertEqual(quality.inputs_differ(before, {**before, ('power', 'sensor.new'): 5.0}),
[('power', 'sensor.new')])
def test_freshness_settings_translated(self):
for name in ('strings.json', 'translations/en.json', 'translations/ro.json'):
data = json.loads((ROOT / name).read_text())
for section, step in (('config', 'user'), ('options', 'init')):
labels = data[section]['step'][step]['data']
for key in ('room_max_age_minutes', 'weather_max_age_minutes', 'room_stale_use_last_value'):
self.assertTrue(labels[key])
help_text = data[section]['step'][step]['data_description']
self.assertIn('24', help_text['room_stale_use_last_value'])
# Every poll outcome has a translated state name.
states = data['entity']['sensor']['last_sample']['state']
self.assertEqual(set(states), set(const.SAMPLE_RESULTS))