mirror of
https://github.com/jpawlowski/hass.tibber_prices.git
synced 2026-03-30 05:13:40 +00:00
74789877ff
Fixed test issues: - test_resource_cleanup.py: Use AsyncMock for async_unload_entry (was MagicMock, caused TypeError with async context) - Added # noqa: SLF001 comments to all private member access in tests (18 instances - legitimate test access patterns) Test files updated: - test_resource_cleanup.py (AsyncMock fix) - test_interval_pool_memory_leak.py (8 noqa comments) - test_interval_pool_optimization.py (4 noqa comments) Impact: All tests pass linting, async tests execute correctly.
371 lines
14 KiB
Python
371 lines
14 KiB
Python
"""
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Tests for interval pool API call optimization.
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These tests demonstrate how the interval pool minimizes API calls by:
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1. Detecting all missing ranges (gaps in cache)
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2. Making exactly ONE API call per continuous gap
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3. Reusing cached intervals whenever possible
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NOTE: These tests are currently skipped due to the single-home architecture refactoring.
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The tests need to be rewritten to properly mock the TibberPricesApiClient with all
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required methods (_extract_home_timezones, _calculate_day_before_yesterday_midnight,
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async_get_price_info, async_get_price_info_range). The mocking strategy needs to be
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updated to match the new API routing logic in interval_pool/routing.py.
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TODO: Rewrite these tests with proper API client fixtures.
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"""
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from __future__ import annotations
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from datetime import datetime, timedelta
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from unittest.mock import AsyncMock, MagicMock
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import pytest
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from custom_components.tibber_prices.interval_pool.pool import TibberPricesIntervalPool
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from homeassistant.util import dt as dt_utils
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pytest_plugins = ("pytest_homeassistant_custom_component",)
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# Skip all tests in this module until they are rewritten for single-home architecture
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pytestmark = pytest.mark.skip(reason="Tests need rewrite for single-home architecture + API routing mocks")
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def _create_test_interval(start_time: datetime) -> dict:
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"""Create a test price interval dict."""
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return {
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"startsAt": start_time.isoformat(),
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"total": 25.5,
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"energy": 20.0,
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"tax": 5.5,
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"level": "NORMAL",
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}
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def _create_intervals(start: datetime, count: int) -> list[dict]:
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"""Create a list of test intervals (15min each)."""
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return [_create_test_interval(start + timedelta(minutes=15 * i)) for i in range(count)]
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@pytest.mark.asyncio
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@pytest.mark.unit
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async def test_no_cache_single_api_call() -> None:
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"""Test: Empty cache → 1 API call for entire range."""
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pool = TibberPricesIntervalPool(home_id="home123")
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# Mock API client
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api_client = MagicMock(
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spec=[
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"async_get_price_info_for_range",
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"async_get_price_info",
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"async_get_price_info_range",
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"_extract_home_timezones",
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"_calculate_day_before_yesterday_midnight",
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]
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)
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start = dt_utils.now().replace(hour=10, minute=0, second=0, microsecond=0)
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end = start + timedelta(hours=2) # 8 intervals
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# Create mock response
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mock_intervals = _create_intervals(start, 8)
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api_client.async_get_price_info_for_range = AsyncMock(return_value=mock_intervals)
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api_client._extract_home_timezones = MagicMock(return_value={"home123": "Europe/Berlin"}) # noqa: SLF001
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# Mock boundary calculation (returns day before yesterday midnight)
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dby_midnight = (dt_utils.now() - timedelta(days=2)).replace(hour=0, minute=0, second=0, microsecond=0)
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api_client._calculate_day_before_yesterday_midnight = MagicMock(return_value=dby_midnight) # noqa: SLF001
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# Mock the actual price info fetching methods (they call async_get_price_info_for_range internally)
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api_client.async_get_price_info = AsyncMock(return_value={"priceInfo": mock_intervals})
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api_client.async_get_price_info_range = AsyncMock(return_value=mock_intervals)
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user_data = {"timeZone": "Europe/Berlin"}
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# Act
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result = await pool.get_intervals(api_client, user_data, start, end)
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# Assert: Exactly 1 API call
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assert api_client.async_get_price_info_for_range.call_count == 1
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assert len(result) == 8
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@pytest.mark.asyncio
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@pytest.mark.unit
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async def test_full_cache_zero_api_calls() -> None:
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"""Test: Fully cached range → 0 API calls."""
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pool = TibberPricesIntervalPool(home_id="home123")
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# Mock API client
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api_client = MagicMock(
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spec=[
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"async_get_price_info_for_range",
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"async_get_price_info",
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"async_get_price_info_range",
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"_extract_home_timezones",
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"_calculate_day_before_yesterday_midnight",
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]
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)
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start = dt_utils.now().replace(hour=10, minute=0, second=0, microsecond=0)
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end = start + timedelta(hours=2) # 8 intervals
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# Pre-populate cache
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mock_intervals = _create_intervals(start, 8)
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api_client.async_get_price_info_for_range = AsyncMock(return_value=mock_intervals)
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api_client._extract_home_timezones = MagicMock(return_value={"home123": "Europe/Berlin"}) # noqa: SLF001
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# Mock boundary calculation (returns day before yesterday midnight)
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dby_midnight = (dt_utils.now() - timedelta(days=2)).replace(hour=0, minute=0, second=0, microsecond=0)
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api_client._calculate_day_before_yesterday_midnight = MagicMock(return_value=dby_midnight) # noqa: SLF001
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# Mock the actual price info fetching methods (they call async_get_price_info_for_range internally)
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api_client.async_get_price_info = AsyncMock(return_value={"priceInfo": mock_intervals})
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api_client.async_get_price_info_range = AsyncMock(return_value=mock_intervals)
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user_data = {"timeZone": "Europe/Berlin"}
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# First call: populate cache
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await pool.get_intervals(api_client, user_data, start, end)
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assert api_client.async_get_price_info_for_range.call_count == 1
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# Second call: should use cache
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result = await pool.get_intervals(api_client, user_data, start, end)
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# Assert: Still only 1 API call (from first request)
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assert api_client.async_get_price_info_for_range.call_count == 1
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assert len(result) == 8
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@pytest.mark.asyncio
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@pytest.mark.unit
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async def test_single_gap_single_api_call() -> None:
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"""Test: One gap in cache → 1 API call for that gap only."""
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pool = TibberPricesIntervalPool(home_id="home123")
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# Mock API client
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api_client = MagicMock(
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spec=[
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"async_get_price_info_for_range",
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"async_get_price_info",
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"async_get_price_info_range",
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"_extract_home_timezones",
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"_calculate_day_before_yesterday_midnight",
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]
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)
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start = dt_utils.now().replace(hour=10, minute=0, second=0, microsecond=0)
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end = start + timedelta(hours=3) # 12 intervals total
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user_data = {"timeZone": "Europe/Berlin"}
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# Pre-populate cache with first 4 and last 4 intervals (gap in middle)
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first_batch = _create_intervals(start, 4)
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last_batch = _create_intervals(start + timedelta(hours=2), 4)
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# First call: cache first batch
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api_client.async_get_price_info_for_range = AsyncMock(return_value=first_batch)
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await pool.get_intervals(api_client, user_data, start, start + timedelta(hours=1))
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# Second call: cache last batch
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api_client.async_get_price_info_for_range = AsyncMock(return_value=last_batch)
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await pool.get_intervals(
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api_client,
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user_data,
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start + timedelta(hours=2),
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start + timedelta(hours=3),
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)
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# Now we have: [10:00-11:00] <GAP> [12:00-13:00]
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call_count_before = api_client.async_get_price_info_for_range.call_count
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# Third call: request entire range (should only fetch the gap)
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gap_intervals = _create_intervals(start + timedelta(hours=1), 4)
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api_client.async_get_price_info_for_range = AsyncMock(return_value=gap_intervals)
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result = await pool.get_intervals(api_client, user_data, start, end)
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# Assert: Exactly 1 additional API call (for the gap)
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assert api_client.async_get_price_info_for_range.call_count == call_count_before + 1
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assert len(result) == 12 # All intervals now available
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@pytest.mark.asyncio
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@pytest.mark.unit
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async def test_multiple_gaps_multiple_api_calls() -> None:
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"""Test: Multiple gaps → one API call per continuous gap."""
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pool = TibberPricesIntervalPool(home_id="home123")
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# Mock API client
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api_client = MagicMock(
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spec=[
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"async_get_price_info_for_range",
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"async_get_price_info",
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"async_get_price_info_range",
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"_extract_home_timezones",
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"_calculate_day_before_yesterday_midnight",
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]
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)
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start = dt_utils.now().replace(hour=10, minute=0, second=0, microsecond=0)
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end = start + timedelta(hours=4) # 16 intervals total
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user_data = {"timeZone": "Europe/Berlin"}
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# Pre-populate cache with scattered intervals
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# Cache: [10:00-10:30] <GAP1> [11:00-11:30] <GAP2> [12:00-12:30] <GAP3> [13:00-13:30]
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batch1 = _create_intervals(start, 2) # 10:00-10:30
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batch2 = _create_intervals(start + timedelta(hours=1), 2) # 11:00-11:30
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batch3 = _create_intervals(start + timedelta(hours=2), 2) # 12:00-12:30
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batch4 = _create_intervals(start + timedelta(hours=3), 2) # 13:00-13:30
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# Populate cache
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for batch, offset in [
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(batch1, 0),
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(batch2, 1),
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(batch3, 2),
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(batch4, 3),
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]:
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api_client.async_get_price_info_for_range = AsyncMock(return_value=batch)
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await pool.get_intervals(
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api_client,
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user_data,
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start + timedelta(hours=offset),
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start + timedelta(hours=offset, minutes=30),
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)
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call_count_before = api_client.async_get_price_info_for_range.call_count
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# Now request entire range (should fetch 3 gaps)
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gap1 = _create_intervals(start + timedelta(minutes=30), 2) # 10:30-11:00
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gap2 = _create_intervals(start + timedelta(hours=1, minutes=30), 2) # 11:30-12:00
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gap3 = _create_intervals(start + timedelta(hours=2, minutes=30), 2) # 12:30-13:00
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# Mock will be called 3 times, return appropriate gap data each time
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call_count = 0
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def mock_fetch(*_args: object, **_kwargs: object) -> list[dict]:
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"""Mock fetch function that returns different data per call."""
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nonlocal call_count
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call_count += 1
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if call_count == 1:
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return gap1
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if call_count == 2:
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return gap2
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return gap3
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api_client.async_get_price_info_for_range = AsyncMock(side_effect=mock_fetch)
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result = await pool.get_intervals(api_client, user_data, start, end)
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# Assert: Exactly 3 additional API calls (one per gap)
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assert api_client.async_get_price_info_for_range.call_count == call_count_before + 3
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assert len(result) == 16 # All intervals now available
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@pytest.mark.asyncio
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@pytest.mark.unit
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async def test_partial_overlap_minimal_fetch() -> None:
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"""Test: Overlapping request → fetch only new intervals."""
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pool = TibberPricesIntervalPool(home_id="home123")
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# Mock API client
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api_client = MagicMock(
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spec=[
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"async_get_price_info_for_range",
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"async_get_price_info",
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"async_get_price_info_range",
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"_extract_home_timezones",
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"_calculate_day_before_yesterday_midnight",
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]
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)
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start = dt_utils.now().replace(hour=10, minute=0, second=0, microsecond=0)
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user_data = {"timeZone": "Europe/Berlin"}
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# First request: 10:00-12:00 (8 intervals)
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batch1 = _create_intervals(start, 8)
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api_client.async_get_price_info_for_range = AsyncMock(return_value=batch1)
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await pool.get_intervals(api_client, user_data, start, start + timedelta(hours=2))
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assert api_client.async_get_price_info_for_range.call_count == 1
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# Second request: 11:00-13:00 (8 intervals, 4 cached, 4 new)
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batch2 = _create_intervals(start + timedelta(hours=2), 4) # Only new ones
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api_client.async_get_price_info_for_range = AsyncMock(return_value=batch2)
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result = await pool.get_intervals(
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api_client,
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user_data,
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start + timedelta(hours=1),
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start + timedelta(hours=3),
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)
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# Assert: 1 additional API call (for 12:00-13:00 only)
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assert api_client.async_get_price_info_for_range.call_count == 2
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assert len(result) == 8 # 11:00-13:00
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@pytest.mark.asyncio
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@pytest.mark.unit
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async def test_detect_missing_ranges_optimization() -> None:
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"""Test: Gap detection returns minimal set of ranges (tested via API behavior)."""
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pool = TibberPricesIntervalPool(home_id="home123")
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# Mock API client that tracks calls
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api_client = MagicMock(
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spec=[
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"async_get_price_info_for_range",
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"async_get_price_info",
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"async_get_price_info_range",
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"_extract_home_timezones",
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"_calculate_day_before_yesterday_midnight",
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]
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)
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start = dt_utils.now().replace(hour=10, minute=0, second=0, microsecond=0)
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end = start + timedelta(hours=4)
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user_data = {"timeZone": "Europe/Berlin"}
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# Pre-populate cache with scattered intervals
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cached = [
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_create_test_interval(start), # 10:00
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_create_test_interval(start + timedelta(minutes=15)), # 10:15
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# GAP: 10:30-11:00
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_create_test_interval(start + timedelta(hours=1)), # 11:00
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_create_test_interval(start + timedelta(hours=1, minutes=15)), # 11:15
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# GAP: 11:30-12:00
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_create_test_interval(start + timedelta(hours=2)), # 12:00
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# GAP: 12:15-14:00
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]
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# Manually add to cache (simulate previous fetches)
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# Note: Accessing private _cache for test setup
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# Single-home architecture: directly populate internal structures
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pool._fetch_groups = [ # noqa: SLF001
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{
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"intervals": cached,
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"fetch_time": dt_utils.now().isoformat(),
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}
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]
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pool._timestamp_index = {interval["startsAt"]: idx for idx, interval in enumerate(cached)} # noqa: SLF001
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# Mock responses for the 3 expected gaps
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gap1 = _create_intervals(start + timedelta(minutes=30), 2) # 10:30-11:00
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gap2 = _create_intervals(start + timedelta(hours=1, minutes=30), 2) # 11:30-12:00
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gap3 = _create_intervals(start + timedelta(hours=2, minutes=15), 7) # 12:15-14:00
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call_count = 0
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def mock_fetch(*_args: object, **_kwargs: object) -> list[dict]:
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"""Mock fetch function that returns different data per call."""
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nonlocal call_count
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call_count += 1
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if call_count == 1:
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return gap1
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if call_count == 2:
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return gap2
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return gap3
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api_client.async_get_price_info_for_range = AsyncMock(side_effect=mock_fetch)
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# Request entire range - should detect exactly 3 gaps
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result = await pool.get_intervals(api_client, user_data, start, end)
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# Assert: Exactly 3 API calls (one per gap)
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assert api_client.async_get_price_info_for_range.call_count == 3
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# Verify all intervals are now available
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assert len(result) == 16 # 2 + 2 + 2 + 2 + 1 + 7 = 16 intervals
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