mirror of
https://github.com/jpawlowski/hass.tibber_prices.git
synced 2026-05-28 18:43:40 +00:00
fix(periods): replace redundant total attributes with per-day counts
Removed periods_found_total and replaced with period_count_today / period_count_tomorrow. The old attribute counted all periods including yesterday (coordinator scope), causing a discrepancy vs. the displayed list (sensor scope, today+tomorrow only). Renamed periods_total → period_count_total for naming consistency with the new per-day attributes. Recalculate period_position / period_count_total / periods_remaining after the today+tomorrow filter so all three navigation attributes reflect the filtered scope. period_count_tomorrow is always present (0 when no tomorrow data or no periods found), enabling automations without default(0) guards. Removed internal periods_found key from relaxation metadata — it was only consumed by add_calculation_summary_attributes which is now removed. BREAKING CHANGE: periods_found_total removed (replace with period_count_today + period_count_tomorrow). periods_total renamed to period_count_total. Impact: Period navigation attributes (position/total/remaining) now correctly reflect today+tomorrow scope. Per-day counts allow automations to distinguish "2 periods today, 0 tomorrow" from "1+1".
This commit is contained in:
Julian Pawlowski
parent
9e1ba10f0b
commit
779e22a84e
11 changed files with 46 additions and 44 deletions
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@ -119,6 +119,19 @@ def get_price_intervals_attributes(
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if not filtered_periods:
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return build_no_periods_result(time=time)
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# Recalculate position metadata after filtering (coordinator stamped values include yesterday)
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# Use shallow copies so coordinator dicts are not mutated
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total_filtered = len(filtered_periods)
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filtered_periods = [
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period
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"period_position": i,
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"period_count_total": total_filtered,
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"periods_remaining": total_filtered - i,
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}
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for i, period in enumerate(filtered_periods, 1)
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]
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# Find current or next period based on current time
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current_period = None
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@ -251,8 +264,8 @@ def add_detail_attributes(attributes: dict, current_period: dict) -> None:
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attributes["period_interval_count"] = current_period["period_interval_count"]
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if "period_position" in current_period:
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attributes["period_position"] = current_period["period_position"]
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if "periods_total" in current_period:
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attributes["periods_total"] = current_period["periods_total"]
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if "period_count_total" in current_period:
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attributes["period_count_total"] = current_period["period_count_total"]
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if "periods_remaining" in current_period:
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attributes["periods_remaining"] = current_period["periods_remaining"]
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@ -298,7 +311,6 @@ def add_period_count_attributes(
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count_tomorrow += 1
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_ = now # used for clarity only
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if count_today > 0 or count_tomorrow > 0:
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attributes["period_count_today"] = count_today
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attributes["period_count_tomorrow"] = count_tomorrow
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@ -324,13 +336,11 @@ def add_calculation_summary_attributes(attributes: dict, period_metadata: dict)
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"""
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Add calculation summary attributes (priority 7).
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Provides diagnostic visibility into the period calculation: how many periods
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were requested vs. found, whether any flat days triggered adaptive min_periods,
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and whether relaxation could not satisfy all days.
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Provides diagnostic visibility into the period calculation: whether any flat days
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triggered adaptive min_periods, and whether relaxation could not satisfy all days.
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Only adds non-default/interesting values to avoid clutter:
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- min_periods_configured: always added (useful reference for automations)
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- periods_found_total: always added
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- flat_days_detected: only when > 0 (explains why fewer periods than configured)
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- relaxation_incomplete: only when True (diagnostic flag for troubleshooting)
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@ -342,9 +352,6 @@ def add_calculation_summary_attributes(attributes: dict, period_metadata: dict)
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if "min_periods_requested" in relaxation_meta:
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attributes["min_periods_configured"] = relaxation_meta["min_periods_requested"]
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if "periods_found" in relaxation_meta:
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attributes["periods_found_total"] = relaxation_meta["periods_found"]
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flat_days = relaxation_meta.get("flat_days_detected", 0)
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if flat_days > 0:
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attributes["flat_days_detected"] = flat_days
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@ -414,10 +421,10 @@ def build_final_attributes_simple(
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2. Core decision attributes (level, rating_level, rating_difference_%)
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3. Price statistics (price_mean, price_median, price_min, price_max, price_spread, volatility)
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4. Price differences (period_price_diff_from_daily_min, period_price_diff_from_daily_min_%)
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5. Detail information (period_interval_count, period_position, periods_total, periods_remaining)
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5. Detail information (period_interval_count, period_position, period_count_total, periods_remaining)
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6. Relaxation information (relaxation_active, relaxation_level, relaxation_threshold_original_%,
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relaxation_threshold_applied_%) - only if current period was relaxed
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7. Calculation summary (min_periods_configured, periods_found_total, flat_days_detected,
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7. Calculation summary (min_periods_configured, flat_days_detected,
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relaxation_incomplete) - diagnostic info about the overall calculation
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8. Meta information (periods list)
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@ -464,7 +471,7 @@ def build_final_attributes_simple(
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# 6. Relaxation information (only if current period was relaxed)
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add_relaxation_attributes(attributes, current_period)
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# 7. Calculation summary (diagnostic: min_periods_configured, periods_found_total, etc.)
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# 7. Calculation summary (diagnostic: min_periods_configured, flat_days_detected, etc.)
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if period_metadata:
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add_calculation_summary_attributes(attributes, period_metadata)
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@ -64,7 +64,6 @@ class TibberPricesBinarySensor(TibberPricesEntity, BinarySensorEntity, RestoreEn
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"relaxation_threshold_applied_%",
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# Calculation Summary (diagnostic, changes daily → not useful in history)
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"min_periods_configured",
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"periods_found_total",
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"flat_days_detected",
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"relaxation_incomplete",
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# Redundant/Derived
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@ -73,7 +72,7 @@ class TibberPricesBinarySensor(TibberPricesEntity, BinarySensorEntity, RestoreEn
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"rating_difference_%",
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"period_price_diff_from_daily_min",
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"period_price_diff_from_daily_min_%",
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"periods_total",
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"period_count_total",
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"periods_remaining",
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}
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)
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@ -104,7 +104,7 @@ class PeriodSummary(TypedDict, total=False):
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# Detail information (priority 5)
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period_interval_count: int # Number of intervals in period
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period_position: int # Period position (1-based)
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periods_total: int # Total number of periods
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period_count_total: int # Total number of periods
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periods_remaining: int # Remaining periods after this one
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# Relaxation information (priority 6 - only if period was relaxed)
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@ -125,7 +125,7 @@ class PeriodAttributes(BaseAttributes, total=False):
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2. Core decision attributes (level, rating_level, rating_difference_%)
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3. Price statistics (price_mean, price_median, price_min, price_max, price_spread, volatility)
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4. Price comparison (period_price_diff_from_daily_min, period_price_diff_from_daily_min_%)
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5. Detail information (period_interval_count, period_position, periods_total, periods_remaining)
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5. Detail information (period_interval_count, period_position, period_count_total, periods_remaining)
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6. Relaxation information (only if period was relaxed)
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7. Meta information (periods list)
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"""
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@ -155,7 +155,7 @@ class PeriodAttributes(BaseAttributes, total=False):
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# Detail information (priority 5)
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period_interval_count: int # Number of intervals in current/next period
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period_position: int # Period position (1-based)
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periods_total: int # Total number of periods found
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period_count_total: int # Total number of periods found
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periods_remaining: int # Remaining periods after current/next one
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# Relaxation information (priority 6 - only if period was relaxed)
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@ -56,7 +56,7 @@ def recalculate_period_metadata(periods: list[dict], *, time: TibberPricesTimeSe
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"""
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Recalculate period metadata after merging periods.
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Updates period_position, periods_total, and periods_remaining for all periods
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Updates period_position, period_count_total, and periods_remaining for all periods
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based on chronological order.
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This must be called after resolve_period_overlaps() to ensure metadata
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@ -78,7 +78,7 @@ def recalculate_period_metadata(periods: list[dict], *, time: TibberPricesTimeSe
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for position, period in enumerate(periods, 1):
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period["period_position"] = position
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period["periods_total"] = total_periods
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period["period_count_total"] = total_periods
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period["periods_remaining"] = total_periods - position
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@ -178,7 +178,7 @@ def build_period_summary_dict(
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# 5. Detail information (additional context)
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"period_interval_count": period_data.period_length,
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"period_position": period_data.period_idx,
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"periods_total": period_data.total_periods,
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"period_count_total": period_data.total_periods,
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"periods_remaining": period_data.total_periods - period_data.period_idx,
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}
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@ -639,7 +639,6 @@ def calculate_periods_with_relaxation( # noqa: PLR0912, PLR0913, PLR0915 - Per-
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"relaxation_active": False,
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"relaxation_attempted": False,
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"min_periods_requested": min_periods if enable_relaxation else 0,
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"periods_found": 0,
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},
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},
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"reference_data": {},
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@ -840,8 +839,6 @@ def calculate_periods_with_relaxation( # noqa: PLR0912, PLR0913, PLR0915 - Per-
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final_result = baseline_result.copy()
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final_result["periods"] = all_periods
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total_periods = len(all_periods)
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# Add relaxation info to metadata
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if "metadata" not in final_result:
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final_result["metadata"] = {}
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@ -849,7 +846,6 @@ def calculate_periods_with_relaxation( # noqa: PLR0912, PLR0913, PLR0915 - Per-
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"relaxation_active": relaxation_was_needed,
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"relaxation_attempted": relaxation_was_needed,
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"min_periods_requested": min_periods,
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"periods_found": total_periods,
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"phases_used": list(set(all_phases_used)), # Unique phases used across all days
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"days_processed": total_days,
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"days_meeting_requirement": days_meeting_requirement,
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@ -1023,5 +1019,4 @@ def relax_all_prices( # noqa: PLR0913 - Comprehensive filter relaxation require
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return final_result, {
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"phases_used": phases_used,
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"periods_found": len(existing_periods),
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}
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@ -172,7 +172,7 @@ class TibberPricesSensor(TibberPricesEntity, RestoreSensor):
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"rating_difference_%",
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"period_price_diff_from_daily_min",
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"period_price_diff_from_daily_min_%",
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"periods_total",
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"period_count_total",
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"periods_remaining",
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}
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)
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@ -834,8 +834,7 @@ INFO: Day 2025-11-11: Baseline satisfied (1 period, effective minimum is 1)
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**Sensor Attributes:**
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```yaml
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min_periods_configured: 2 # User's setting
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periods_found_total: 1 # Actual result
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flat_days_detected: 1 # Explains the difference
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flat_days_detected: 1 # Explains why only 1 period found
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```
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**Why not for Peak Price?**
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@ -957,7 +956,6 @@ When debugging period calculation issues:
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| Attribute | Type | When shown | Meaning |
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|---|---|---|---|
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| `min_periods_configured` | int | Always | User's configured target per day |
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| `periods_found_total` | int | Always | Actual periods found across all days |
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| `flat_days_detected` | int | Only when > 0 | Days where CV ≤ 10% reduced target to 1 |
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| `relaxation_incomplete` | bool | Only when true | Relaxation exhausted, target not reached |
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| `relaxation_active` | bool | Only when true | This specific period needed relaxed filters |
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@ -137,7 +137,7 @@ class TibberPricesSensor(TibberPricesEntity, SensorEntity):
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### 7. Redundant/Derived Data
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**Attributes:** `price_spread`, `volatility`, `diff_%`, `rating_difference_%`, `period_price_diff_from_daily_min`, `period_price_diff_from_daily_min_%`, `periods_total`, `periods_remaining`
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**Attributes:** `price_spread`, `volatility`, `diff_%`, `rating_difference_%`, `period_price_diff_from_daily_min`, `period_price_diff_from_daily_min_%`, `period_count_total`, `periods_remaining`
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**Reason:**
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- Can be calculated from other attributes
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@ -146,7 +146,7 @@ class TibberPricesSensor(TibberPricesEntity, SensorEntity):
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**Impact:** ~100-200 bytes saved per state change
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**Example:** `price_spread = price_max - price_min` (both are recorded, so spread can be calculated)
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**Example:** `price_spread = price_max - price_min` (both are recorded, so spread can be calculated). `periods_remaining = period_count_total - period_position` (both components are recorded).
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## Attributes That ARE Recorded
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@ -166,6 +166,8 @@ These attributes **remain in history** because they provide essential analytical
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### Period Data
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- `start`, `end`, `duration_minutes` - Core period timing
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- `price_mean`, `price_median`, `price_min`, `price_max` - Core price statistics
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- `period_position` - Position of current period in the day's sequence
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- `period_count_today`, `period_count_tomorrow` - How many periods per day (useful in automations)
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### High-Level Status
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- `relaxation_active` - Whether relaxation was used (boolean, useful for analyzing when periods needed relaxation)
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@ -523,7 +523,7 @@ This is **expected behavior** on days with very uniform electricity prices. When
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```yaml
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min_periods_configured: 2
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periods_found_total: 1
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period_count_today: 1
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flat_days_detected: 1 # Uniform prices today → 1 period is the right answer
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```
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@ -656,7 +656,8 @@ relaxation_level: "price_diff_18.0%+level_any" # Found at 18% flex, level filte
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# Calculation summary (always shown – diagnostic overview of this calculation run):
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min_periods_configured: 2 # What you configured as target
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periods_found_total: 3 # What was actually found across all days
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period_count_today: 2 # How many periods are scheduled today
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period_count_tomorrow: 2 # How many periods are scheduled tomorrow (when data available)
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# Optional (only shown when relevant):
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period_interval_smoothed_count: 2 # Number of price spikes smoothed
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@ -669,7 +670,7 @@ relaxation_incomplete: true # Some days couldn't reach the configured ta
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#### What the diagnostic attributes mean
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**`min_periods_configured` / `periods_found_total`**
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**`min_periods_configured` / `period_count_today`**
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These two values together quickly show whether the calculation achieved its goal:
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@ -678,18 +679,18 @@ These two values together quickly show whether the calculation achieved its goal
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```yaml
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min_periods_configured: 2 # You asked for 2 periods per day
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periods_found_total: 6 # 3 days × 2 periods = fully satisfied ✅
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period_count_today: 2 # ✅ Today: target reached
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period_count_tomorrow: 2 # ✅ Tomorrow: target reached
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```
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```yaml
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min_periods_configured: 2
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periods_found_total: 5 # 3 days, but one day got only 1 period
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period_count_today: 1 # ⚠️ Today: only 1 period found
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period_count_tomorrow: 2 # ✅ Tomorrow: target reached
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```
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</details>
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Note that `periods_found_total` counts **all periods across today and tomorrow** – so 4 on a two-day view means 2 per day on average.
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**`flat_days_detected`**
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This is the most important diagnostic for days with very uniform prices (e.g. sunny spring/summer days with high solar generation):
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@ -699,7 +700,7 @@ This is the most important diagnostic for days with very uniform prices (e.g. su
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```yaml
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min_periods_configured: 2
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periods_found_total: 1
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period_count_today: 1
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flat_days_detected: 1 # ← This explains why you got 1 instead of 2
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```
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@ -718,7 +719,7 @@ This flag appears when even after all relaxation attempts, at least one day coul
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```yaml
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min_periods_configured: 2
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periods_found_total: 1
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period_count_today: 1
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relaxation_incomplete: true # ← Relaxation tried everything, still short
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```
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@ -130,7 +130,7 @@ Check the period sensor attributes to understand what happened:
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relaxation_active: true # This day needed relaxation
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relaxation_level: "price_diff_18.0%+level_any" # Found at 18% flex, level filter removed
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min_periods_configured: 2 # Your target
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periods_found_total: 3 # What was actually found
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period_count_today: 3 # What was actually found today
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```
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</details>
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