fix(periods): rename periods_remaining to period_count_remaining

Consistent naming with the period_count_* family introduced in the
previous commit (period_count_total, period_count_today,
period_count_tomorrow).

periods_remaining was the last attribute in the navigation triplet
using the old plural form. Renamed to period_count_remaining to follow
the established pattern: all countable period metrics use the
period_count_* prefix.

BREAKING CHANGE: periods_remaining renamed to period_count_remaining.

Impact: All four period count attributes now share the same prefix
(period_count_total, period_count_today, period_count_tomorrow,
period_count_remaining), making automation templates more predictable.

custom_components/tibber_prices/binary_sensor/attributes.py

@@ -127,7 +127,7 @@ def get_price_intervals_attributes(
         | {
             "period_position": i,
             "period_count_total": total_filtered,
-            "periods_remaining": total_filtered - i,
+            "period_count_remaining": total_filtered - i,
         }
         for i, period in enumerate(filtered_periods, 1)
     ]
@@ -266,8 +266,8 @@ def add_detail_attributes(attributes: dict, current_period: dict) -> None:
         attributes["period_position"] = current_period["period_position"]
     if "period_count_total" in current_period:
         attributes["period_count_total"] = current_period["period_count_total"]
-    if "periods_remaining" in current_period:
+    if "period_count_remaining" in current_period:
-        attributes["periods_remaining"] = current_period["periods_remaining"]
+        attributes["period_count_remaining"] = current_period["period_count_remaining"]
 
 
 def add_period_count_attributes(
@@ -421,7 +421,7 @@ def build_final_attributes_simple(
     2. Core decision attributes (level, rating_level, rating_difference_%)
     3. Price statistics (price_mean, price_median, price_min, price_max, price_spread, volatility)
     4. Price differences (period_price_diff_from_daily_min, period_price_diff_from_daily_min_%)
-    5. Detail information (period_interval_count, period_position, period_count_total, periods_remaining)
+    5. Detail information (period_interval_count, period_position, period_count_total, period_count_remaining)
     6. Relaxation information (relaxation_active, relaxation_level, relaxation_threshold_original_%,
        relaxation_threshold_applied_%) - only if current period was relaxed
     7. Calculation summary (min_periods_configured, flat_days_detected,

custom_components/tibber_prices/binary_sensor/core.py

@@ -73,7 +73,7 @@ class TibberPricesBinarySensor(TibberPricesEntity, BinarySensorEntity, RestoreEn
             "period_price_diff_from_daily_min",
             "period_price_diff_from_daily_min_%",
             "period_count_total",
-            "periods_remaining",
+            "period_count_remaining",
         }
     )
 

custom_components/tibber_prices/binary_sensor/types.py

@@ -105,7 +105,7 @@ class PeriodSummary(TypedDict, total=False):
     period_interval_count: int  # Number of intervals in period
     period_position: int  # Period position (1-based)
     period_count_total: int  # Total number of periods
-    periods_remaining: int  # Remaining periods after this one
+    period_count_remaining: int  # Remaining periods after this one
 
     # Relaxation information (priority 6 - only if period was relaxed)
     relaxation_active: bool  # Whether this period was found via relaxation
@@ -125,7 +125,7 @@ class PeriodAttributes(BaseAttributes, total=False):
     2. Core decision attributes (level, rating_level, rating_difference_%)
     3. Price statistics (price_mean, price_median, price_min, price_max, price_spread, volatility)
     4. Price comparison (period_price_diff_from_daily_min, period_price_diff_from_daily_min_%)
-    5. Detail information (period_interval_count, period_position, period_count_total, periods_remaining)
+    5. Detail information (period_interval_count, period_position, period_count_total, period_count_remaining)
     6. Relaxation information (only if period was relaxed)
     7. Meta information (periods list)
     """
@@ -156,7 +156,7 @@ class PeriodAttributes(BaseAttributes, total=False):
     period_interval_count: int  # Number of intervals in current/next period
     period_position: int  # Period position (1-based)
     period_count_total: int  # Total number of periods found
-    periods_remaining: int  # Remaining periods after current/next one
+    period_count_remaining: int  # Remaining periods after current/next one
 
     # Relaxation information (priority 6 - only if period was relaxed)
     relaxation_active: bool  # Whether current/next period was found via relaxation

custom_components/tibber_prices/coordinator/period_handlers/period_overlap.py

@@ -56,7 +56,7 @@ def recalculate_period_metadata(periods: list[dict], *, time: TibberPricesTimeSe
     """
     Recalculate period metadata after merging periods.
 
-    Updates period_position, period_count_total, and periods_remaining for all periods
+    Updates period_position, period_count_total, and period_count_remaining for all periods
     based on chronological order.
 
     This must be called after resolve_period_overlaps() to ensure metadata
@@ -79,7 +79,7 @@ def recalculate_period_metadata(periods: list[dict], *, time: TibberPricesTimeSe
     for position, period in enumerate(periods, 1):
         period["period_position"] = position
         period["period_count_total"] = total_periods
-        period["periods_remaining"] = total_periods - position
+        period["period_count_remaining"] = total_periods - position
 
 
 def merge_adjacent_periods(period1: dict, period2: dict) -> dict:

custom_components/tibber_prices/coordinator/period_handlers/period_statistics.py

@@ -179,7 +179,7 @@ def build_period_summary_dict(
         "period_interval_count": period_data.period_length,
         "period_position": period_data.period_idx,
         "period_count_total": period_data.total_periods,
-        "periods_remaining": period_data.total_periods - period_data.period_idx,
+        "period_count_remaining": period_data.total_periods - period_data.period_idx,
     }
 
     # Add period price difference attributes based on sensor type (step 4)

custom_components/tibber_prices/sensor/core.py

@@ -173,7 +173,7 @@ class TibberPricesSensor(TibberPricesEntity, RestoreSensor):
             "period_price_diff_from_daily_min",
             "period_price_diff_from_daily_min_%",
             "period_count_total",
-            "periods_remaining",
+            "period_count_remaining",
         }
     )
 

docs/developer/docs/recorder-optimization.md

@@ -137,7 +137,7 @@ class TibberPricesSensor(TibberPricesEntity, SensorEntity):
 
 ### 7. Redundant/Derived Data
 
-**Attributes:** `price_spread`, `volatility`, `diff_%`, `rating_difference_%`, `period_price_diff_from_daily_min`, `period_price_diff_from_daily_min_%`, `period_count_total`, `periods_remaining`
+**Attributes:** `price_spread`, `volatility`, `diff_%`, `rating_difference_%`, `period_price_diff_from_daily_min`, `period_price_diff_from_daily_min_%`, `period_count_total`, `period_count_remaining`
 
 **Reason:**
 - Can be calculated from other attributes
@@ -146,7 +146,7 @@ class TibberPricesSensor(TibberPricesEntity, SensorEntity):
 
 **Impact:** ~100-200 bytes saved per state change
 
-**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).
+**Example:** `price_spread = price_max - price_min` (both are recorded, so spread can be calculated). `period_count_remaining = period_count_total - period_position` (both components are recorded).
 
 ## Attributes That ARE Recorded