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1d065b11cd
_resolve_time_with_day_offset() was calling dt_util.now() internally instead of using the injected now parameter. This caused incorrect date calculations in tests and any caller that passes a specific reference time. Also add missing price_rank_* sensor keys to TIME_SENSITIVE_ENTITY_KEYS in coordinator/constants.py so quarter-hour refresh is registered for all 11 price rank sensors (current/next/previous interval and hour variants). Rename dt as dt_utils → dt as dt_util (ICN001) across 11 files to follow the project-wide import alias convention. Apply ruff auto-fixes for import ordering and collapsing single-item imports throughout the codebase. Released-Bug: no
196 lines
7.1 KiB
Python
196 lines
7.1 KiB
Python
"""Tests for Bug #7: Min/Max functions returning 0.0 instead of None."""
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from datetime import UTC, datetime, timedelta
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import pytest
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from custom_components.tibber_prices.coordinator.time_service import TibberPricesTimeService
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from custom_components.tibber_prices.utils.average import (
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calculate_leading_24h_max,
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calculate_leading_24h_min,
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calculate_trailing_24h_max,
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calculate_trailing_24h_min,
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)
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@pytest.fixture
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def time_service() -> TibberPricesTimeService:
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"""Create a TibberPricesTimeService instance for testing."""
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return TibberPricesTimeService()
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def test_trailing_24h_min_with_empty_window(time_service: TibberPricesTimeService) -> None:
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"""
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Test that trailing min returns None when no data in window.
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Bug #7: Previously returned 0.0, which could be misinterpreted as
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a maximum value with negative prices.
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"""
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# Data exists, but outside the 24h window
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old_data = [
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{
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"startsAt": datetime(2025, 11, 1, 10, 0, tzinfo=UTC), # 20 days ago
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"total": -15.0, # Negative price
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}
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]
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interval_start = datetime(2025, 11, 21, 14, 0, tzinfo=UTC) # Today
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# Should return None (no data in window), not 0.0
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result = calculate_trailing_24h_min(old_data, interval_start, time=time_service)
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assert result is None
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def test_trailing_24h_max_with_empty_window(time_service: TibberPricesTimeService) -> None:
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"""Test that trailing max returns None when no data in window."""
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old_data = [
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{
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"startsAt": datetime(2025, 11, 1, 10, 0, tzinfo=UTC), # 20 days ago
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"total": -15.0,
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}
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]
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interval_start = datetime(2025, 11, 21, 14, 0, tzinfo=UTC)
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result = calculate_trailing_24h_max(old_data, interval_start, time=time_service)
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assert result is None
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def test_leading_24h_min_with_empty_window(time_service: TibberPricesTimeService) -> None:
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"""Test that leading min returns None when no data in window."""
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old_data = [
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{
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"startsAt": datetime(2025, 11, 1, 10, 0, tzinfo=UTC), # Past data
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"total": -15.0,
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}
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]
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interval_start = datetime(2025, 11, 21, 14, 0, tzinfo=UTC) # Today - no future data
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result = calculate_leading_24h_min(old_data, interval_start, time=time_service)
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assert result is None
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def test_leading_24h_max_with_empty_window(time_service: TibberPricesTimeService) -> None:
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"""Test that leading max returns None when no data in window."""
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old_data = [
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{
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"startsAt": datetime(2025, 11, 1, 10, 0, tzinfo=UTC), # Past data
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"total": -15.0,
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}
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]
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interval_start = datetime(2025, 11, 21, 14, 0, tzinfo=UTC)
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result = calculate_leading_24h_max(old_data, interval_start, time=time_service)
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assert result is None
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def test_trailing_24h_min_with_negative_prices(time_service: TibberPricesTimeService) -> None:
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"""
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Test trailing min with negative prices returns actual minimum, not 0.0.
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This demonstrates why Bug #7 was critical: with negative prices,
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0.0 would appear to be a maximum, not an error indicator.
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"""
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interval_start = datetime(2025, 11, 21, 14, 0, tzinfo=UTC)
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window_start = interval_start - timedelta(hours=24)
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# All negative prices
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data = [{"startsAt": window_start + timedelta(hours=i), "total": -10.0 - i} for i in range(24)]
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result = calculate_trailing_24h_min(data, interval_start, time=time_service)
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# Should return actual minimum (-33.0), not 0.0
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assert result == -33.0
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assert result != 0.0 # Emphasize this was the bug
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def test_trailing_24h_max_with_negative_prices(time_service: TibberPricesTimeService) -> None:
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"""Test trailing max with negative prices."""
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interval_start = datetime(2025, 11, 21, 14, 0, tzinfo=UTC)
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window_start = interval_start - timedelta(hours=24)
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# All negative prices
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data = [{"startsAt": window_start + timedelta(hours=i), "total": -10.0 - i} for i in range(24)]
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result = calculate_trailing_24h_max(data, interval_start, time=time_service)
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# Maximum of negative numbers is least negative
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assert result == -10.0
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def test_trailing_24h_min_distinguishes_zero_from_none(
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time_service: TibberPricesTimeService,
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) -> None:
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"""
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Test that function distinguishes between 0.0 price and no data.
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Bug #7: Previously, both cases returned 0.0, making them indistinguishable.
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"""
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interval_start = datetime(2025, 11, 21, 14, 0, tzinfo=UTC)
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window_start = interval_start - timedelta(hours=24)
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# Case 1: Price is actually 0.0
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data_with_zero = [{"startsAt": window_start + timedelta(hours=i), "total": 0.0 + i} for i in range(24)]
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result_with_zero = calculate_trailing_24h_min(data_with_zero, interval_start, time=time_service)
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assert result_with_zero == 0.0 # Actual price
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# Case 2: No data in window
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empty_data: list[dict] = []
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result_no_data = calculate_trailing_24h_min(empty_data, interval_start, time=time_service)
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assert result_no_data is None # No data
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# CRITICAL: These must be distinguishable!
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assert result_with_zero != result_no_data
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def test_trailing_24h_functions_with_partial_window(
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time_service: TibberPricesTimeService,
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) -> None:
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"""
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Test that functions work correctly with partial 24h window.
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This tests the edge case where data exists but doesn't cover full 24h.
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"""
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interval_start = datetime(2025, 11, 21, 14, 0, tzinfo=UTC)
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window_start = interval_start - timedelta(hours=24)
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# Only 12 hours of data (half the window)
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data = [{"startsAt": window_start + timedelta(hours=i), "total": float(i)} for i in range(12)]
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result_min = calculate_trailing_24h_min(data, interval_start, time=time_service)
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result_max = calculate_trailing_24h_max(data, interval_start, time=time_service)
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# Should calculate based on available data
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assert result_min == 0.0
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assert result_max == 11.0
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def test_leading_24h_functions_with_negative_and_positive_mix(
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time_service: TibberPricesTimeService,
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) -> None:
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"""Test leading functions with mix of negative and positive prices."""
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interval_start = datetime(2025, 11, 21, 14, 0, tzinfo=UTC)
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# Mix of negative and positive prices
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data = [{"startsAt": interval_start + timedelta(hours=i), "total": -10.0 + i} for i in range(24)]
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result_min = calculate_leading_24h_min(data, interval_start, time=time_service)
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result_max = calculate_leading_24h_max(data, interval_start, time=time_service)
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assert result_min == -10.0 # Most negative
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assert result_max == 13.0 # Most positive
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def test_empty_price_list_returns_none(time_service: TibberPricesTimeService) -> None:
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"""Test that all functions return None with completely empty price list."""
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interval_start = datetime(2025, 11, 21, 14, 0, tzinfo=UTC)
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empty_data: list[dict] = []
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assert calculate_trailing_24h_min(empty_data, interval_start, time=time_service) is None
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assert calculate_trailing_24h_max(empty_data, interval_start, time=time_service) is None
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assert calculate_leading_24h_min(empty_data, interval_start, time=time_service) is None
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assert calculate_leading_24h_max(empty_data, interval_start, time=time_service) is None
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