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https://github.com/jpawlowski/hass.tibber_prices.git
synced 2026-03-29 21:03:40 +00:00
refactor(services): process chartdata intervals as unified timeline instead of per-day
Changed from iterating over each day separately to collecting all intervals for selected days into one continuous list before processing. Changes: - Collect all intervals via get_intervals_for_day_offsets() with all day_offsets at once - Remove outer `for day in days:` loop around interval processing - Build date->day_key mapping during average calculation for lookup - Add _get_day_key_for_interval() helper for average_field assignment - Simplify midnight handling: only extend at END of entire selection - Remove complex "next day lookup" logic at midnight boundaries The segment boundary handling (bridge points, NULL insertion) now works automatically across midnight since intervals are processed as one list. Impact: Fixes bridge point rendering at midnight when rating levels change between days. Simplifies code structure by removing ~60 lines of per-day midnight-specific logic.
This commit is contained in:
Julian Pawlowski
parent
5cc71901b9
commit
ada17f6d90
1 changed files with 295 additions and 290 deletions
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@ -455,19 +455,26 @@ async def handle_chartdata(call: ServiceCall) -> dict[str, Any]: # noqa: PLR091
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all_timestamps = {interval["startsAt"] for interval in day_intervals if interval.get("startsAt")}
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all_timestamps = sorted(all_timestamps)
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# Calculate average if requested
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day_averages = {}
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if include_average:
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for day in days:
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# Use helper to get intervals for this day
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# Build minimal coordinator_data for single day query
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# Map day key to offset: yesterday=-1, today=0, tomorrow=1
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day_offset = {"yesterday": -1, "today": 0, "tomorrow": 1}[day]
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day_intervals = get_intervals_for_day_offsets(coordinator.data, [day_offset])
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# Calculate average if requested (per day for average_field)
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# Also build a mapping from date -> day_key for later lookup
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day_averages: dict[str, float] = {}
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date_to_day_key: dict[Any, str] = {} # Maps date object to "yesterday"/"today"/"tomorrow"
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# Collect prices from intervals
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for day in days:
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# Use helper to get intervals for this day
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# Map day key to offset: yesterday=-1, today=0, tomorrow=1
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day_offset = {"yesterday": -1, "today": 0, "tomorrow": 1}[day]
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day_intervals = get_intervals_for_day_offsets(coordinator.data, [day_offset])
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# Build date -> day_key mapping from actual interval data
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for interval in day_intervals:
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start_time = interval.get("startsAt")
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if start_time and hasattr(start_time, "date"):
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date_to_day_key[start_time.date()] = day
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# Calculate average if requested
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if include_average:
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prices = [p["total"] for p in day_intervals if p.get("total") is not None]
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if prices:
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avg = sum(prices) / len(prices)
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# Apply same transformations as to regular prices
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@ -476,309 +483,307 @@ async def handle_chartdata(call: ServiceCall) -> dict[str, Any]: # noqa: PLR091
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avg = round(avg, round_decimals)
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day_averages[day] = avg
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for day in days:
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# Use helper to get intervals for this day
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# Map day key to offset: yesterday=-1, today=0, tomorrow=1
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day_offset = {"yesterday": -1, "today": 0, "tomorrow": 1}[day]
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day_prices = get_intervals_for_day_offsets(coordinator.data, [day_offset])
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# Collect ALL intervals for the selected days as one continuous list
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# This simplifies processing - no special midnight handling needed
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day_offsets = [{"yesterday": -1, "today": 0, "tomorrow": 1}[day] for day in days]
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all_prices = get_intervals_for_day_offsets(coordinator.data, day_offsets)
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if resolution == "interval":
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# Original 15-minute intervals
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if insert_nulls == "all" and (level_filter or rating_level_filter):
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# Mode 'all': Insert NULL for all timestamps where filter doesn't match
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# Build a map of timestamp -> interval for quick lookup
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interval_map = {
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interval.get("startsAt"): interval for interval in day_prices if interval.get("startsAt")
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# Helper to get day key from interval timestamp for average lookup
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def _get_day_key_for_interval(interval_start: Any) -> str | None:
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"""Determine which day key (yesterday/today/tomorrow) an interval belongs to."""
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if not interval_start or not hasattr(interval_start, "date"):
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return None
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# Use pre-built mapping from actual interval data (TimeService-compatible)
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return date_to_day_key.get(interval_start.date())
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if resolution == "interval":
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# Original 15-minute intervals
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if insert_nulls == "all" and (level_filter or rating_level_filter):
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# Mode 'all': Insert NULL for all timestamps where filter doesn't match
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# Build a map of timestamp -> interval for quick lookup
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interval_map = {interval.get("startsAt"): interval for interval in all_prices if interval.get("startsAt")}
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# Process all timestamps, filling gaps with NULL
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for start_time in all_timestamps:
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interval = interval_map.get(start_time)
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if interval is None:
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# No data for this timestamp - skip entirely
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continue
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price = interval.get("total")
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if price is None:
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continue
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# Check if this interval matches the filter
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matches_filter = False
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if level_filter and "level" in interval:
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matches_filter = interval["level"] in level_filter
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elif rating_level_filter and "rating_level" in interval:
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matches_filter = interval["rating_level"] in rating_level_filter
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# If filter is set but doesn't match, insert NULL price
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if not matches_filter:
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price = None
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elif price is not None:
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# Convert to subunit currency (cents/øre) if requested
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price = round(price * 100, 2) if subunit_currency else round(price, 4)
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# Apply custom rounding if specified
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if round_decimals is not None:
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price = round(price, round_decimals)
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data_point = {
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start_time_field: start_time.isoformat() if hasattr(start_time, "isoformat") else start_time,
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price_field: price,
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}
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# Process all timestamps, filling gaps with NULL
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for start_time in all_timestamps:
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interval = interval_map.get(start_time)
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# Add level if requested (only when price is not NULL)
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if include_level and "level" in interval and price is not None:
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data_point[level_field] = interval["level"]
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if interval is None:
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# No data for this timestamp - skip entirely
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# Add rating_level if requested (only when price is not NULL)
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if include_rating_level and "rating_level" in interval and price is not None:
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data_point[rating_level_field] = interval["rating_level"]
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# Add average if requested
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day_key = _get_day_key_for_interval(start_time)
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if include_average and day_key and day_key in day_averages:
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data_point[average_field] = day_averages[day_key]
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chart_data.append(data_point)
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elif insert_nulls == "segments" and (level_filter or rating_level_filter):
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# Mode 'segments': Add NULL points at segment boundaries for clean gaps
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# Process ALL intervals as one continuous list - no special midnight handling needed
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filter_field = "rating_level" if rating_level_filter else "level"
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filter_values = rating_level_filter if rating_level_filter else level_filter
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for i in range(len(all_prices) - 1):
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interval = all_prices[i]
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next_interval = all_prices[i + 1]
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start_time = interval.get("startsAt")
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price = interval.get("total")
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next_price = next_interval.get("total")
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next_start_time = next_interval.get("startsAt")
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if start_time is None or price is None:
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continue
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interval_value = interval.get(filter_field)
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next_value = next_interval.get(filter_field)
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# Check if current interval matches filter
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if interval_value in filter_values: # type: ignore[operator]
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# Convert price
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converted_price = round(price * 100, 2) if subunit_currency else round(price, 4)
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if round_decimals is not None:
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converted_price = round(converted_price, round_decimals)
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# Add current point
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data_point = {
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start_time_field: start_time.isoformat() if hasattr(start_time, "isoformat") else start_time,
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price_field: converted_price,
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}
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if include_level and "level" in interval:
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data_point[level_field] = interval["level"]
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if include_rating_level and "rating_level" in interval:
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data_point[rating_level_field] = interval["rating_level"]
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# Add average if requested
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day_key = _get_day_key_for_interval(start_time)
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if include_average and day_key and day_key in day_averages:
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data_point[average_field] = day_averages[day_key]
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chart_data.append(data_point)
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# Check if next interval is different level (segment boundary)
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if next_value != interval_value:
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next_start_serialized = (
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next_start_time.isoformat()
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if next_start_time and hasattr(next_start_time, "isoformat")
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else next_start_time
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)
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if connect_segments and next_price is not None:
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# Connect segments visually by adding bridge point + NULL
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# Bridge point: extends current series to boundary with next price
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# NULL point: stops series so it doesn't continue into next segment
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converted_next_price = (
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round(next_price * 100, 2) if subunit_currency else round(next_price, 4)
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)
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if round_decimals is not None:
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converted_next_price = round(converted_next_price, round_decimals)
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# 1. Bridge point: boundary with next price, still current level
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# This makes the line go up/down to meet the next series
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bridge_point = {
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start_time_field: next_start_serialized,
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price_field: converted_next_price,
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}
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if include_level and "level" in interval:
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bridge_point[level_field] = interval["level"]
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if include_rating_level and "rating_level" in interval:
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bridge_point[rating_level_field] = interval["rating_level"]
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if include_average and day_key and day_key in day_averages:
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bridge_point[average_field] = day_averages[day_key]
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chart_data.append(bridge_point)
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# 2. NULL point: stops the current series
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# Without this, ApexCharts continues drawing within the series
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null_point = {start_time_field: next_start_serialized, price_field: None}
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chart_data.append(null_point)
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else:
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# Original behavior: Hold current price until next timestamp
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hold_point = {
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start_time_field: next_start_serialized,
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price_field: converted_price,
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}
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if include_level and "level" in interval:
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hold_point[level_field] = interval["level"]
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if include_rating_level and "rating_level" in interval:
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hold_point[rating_level_field] = interval["rating_level"]
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if include_average and day_key and day_key in day_averages:
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hold_point[average_field] = day_averages[day_key]
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chart_data.append(hold_point)
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# Add NULL point to create gap
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null_point = {start_time_field: next_start_serialized, price_field: None}
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chart_data.append(null_point)
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# Handle LAST interval of the entire selection (not per-day)
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# The main loop processes up to n-1, so we need to add the last interval
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if all_prices:
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last_interval = all_prices[-1]
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last_start_time = last_interval.get("startsAt")
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last_price = last_interval.get("total")
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last_value = last_interval.get(filter_field)
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if last_start_time and last_price is not None and last_value in filter_values: # type: ignore[operator]
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# Add the last interval as a data point
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converted_last_price = round(last_price * 100, 2) if subunit_currency else round(last_price, 4)
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if round_decimals is not None:
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converted_last_price = round(converted_last_price, round_decimals)
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last_data_point = {
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start_time_field: last_start_time.isoformat()
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if hasattr(last_start_time, "isoformat")
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else last_start_time,
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price_field: converted_last_price,
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}
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if include_level and "level" in last_interval:
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last_data_point[level_field] = last_interval["level"]
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if include_rating_level and "rating_level" in last_interval:
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last_data_point[rating_level_field] = last_interval["rating_level"]
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day_key = _get_day_key_for_interval(last_start_time)
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if include_average and day_key and day_key in day_averages:
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last_data_point[average_field] = day_averages[day_key]
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chart_data.append(last_data_point)
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# Extend to end of selected time range (midnight after last day)
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last_dt = last_start_time
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if last_dt:
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# Calculate midnight after the last interval
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next_midnight = last_dt.replace(hour=0, minute=0, second=0, microsecond=0)
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next_midnight = next_midnight + timedelta(days=1)
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midnight_timestamp = next_midnight.isoformat()
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# Add hold point at midnight
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end_point = {start_time_field: midnight_timestamp, price_field: converted_last_price}
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if include_level and "level" in last_interval:
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end_point[level_field] = last_interval["level"]
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if include_rating_level and "rating_level" in last_interval:
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end_point[rating_level_field] = last_interval["rating_level"]
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if include_average and day_key and day_key in day_averages:
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end_point[average_field] = day_averages[day_key]
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chart_data.append(end_point)
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# Add NULL to end series
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null_point = {start_time_field: midnight_timestamp, price_field: None}
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chart_data.append(null_point)
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else:
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# Mode 'none' (default): Only return matching intervals, no NULL insertion
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for interval in all_prices:
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start_time = interval.get("startsAt")
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price = interval.get("total")
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if start_time is not None and price is not None:
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# Apply period filter if specified
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if (
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period_filter is not None
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and period_timestamps is not None
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and start_time not in period_timestamps
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):
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continue
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price = interval.get("total")
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if price is None:
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# Apply level filter if specified
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if level_filter is not None and "level" in interval and interval["level"] not in level_filter:
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continue
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# Check if this interval matches the filter
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matches_filter = False
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if level_filter and "level" in interval:
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matches_filter = interval["level"] in level_filter
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elif rating_level_filter and "rating_level" in interval:
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matches_filter = interval["rating_level"] in rating_level_filter
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# Apply rating_level filter if specified
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if (
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rating_level_filter is not None
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and "rating_level" in interval
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and interval["rating_level"] not in rating_level_filter
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):
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continue
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# If filter is set but doesn't match, insert NULL price
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if not matches_filter:
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price = None
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elif price is not None:
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# Convert to subunit currency (cents/øre) if requested
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price = round(price * 100, 2) if subunit_currency else round(price, 4)
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# Apply custom rounding if specified
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if round_decimals is not None:
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price = round(price, round_decimals)
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# Convert to subunit currency (cents/øre) if requested
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price = round(price * 100, 2) if subunit_currency else round(price, 4)
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# Apply custom rounding if specified
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if round_decimals is not None:
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price = round(price, round_decimals)
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data_point = {
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start_time_field: start_time.isoformat() if hasattr(start_time, "isoformat") else start_time,
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price_field: price,
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}
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# Add level if requested (only when price is not NULL)
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if include_level and "level" in interval and price is not None:
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# Add level if requested
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if include_level and "level" in interval:
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data_point[level_field] = interval["level"]
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# Add rating_level if requested (only when price is not NULL)
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if include_rating_level and "rating_level" in interval and price is not None:
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# Add rating_level if requested
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if include_rating_level and "rating_level" in interval:
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data_point[rating_level_field] = interval["rating_level"]
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# Add average if requested
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if include_average and day in day_averages:
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data_point[average_field] = day_averages[day]
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day_key = _get_day_key_for_interval(start_time)
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if include_average and day_key and day_key in day_averages:
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data_point[average_field] = day_averages[day_key]
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chart_data.append(data_point)
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elif insert_nulls == "segments" and (level_filter or rating_level_filter):
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# Mode 'segments': Add NULL points at segment boundaries for clean gaps
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# Determine which field to check based on filter type
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filter_field = "rating_level" if rating_level_filter else "level"
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filter_values = rating_level_filter if rating_level_filter else level_filter
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for i in range(len(day_prices) - 1):
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interval = day_prices[i]
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next_interval = day_prices[i + 1]
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start_time = interval.get("startsAt")
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price = interval.get("total")
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next_price = next_interval.get("total")
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next_start_time = next_interval.get("startsAt")
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if start_time is None or price is None:
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continue
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interval_value = interval.get(filter_field)
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next_value = next_interval.get(filter_field)
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# Check if current interval matches filter
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if interval_value in filter_values: # type: ignore[operator]
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# Convert price
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converted_price = round(price * 100, 2) if subunit_currency else round(price, 4)
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if round_decimals is not None:
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converted_price = round(converted_price, round_decimals)
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# Add current point
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data_point = {
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start_time_field: start_time.isoformat()
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if hasattr(start_time, "isoformat")
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else start_time,
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price_field: converted_price,
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}
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if include_level and "level" in interval:
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data_point[level_field] = interval["level"]
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if include_rating_level and "rating_level" in interval:
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data_point[rating_level_field] = interval["rating_level"]
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if include_average and day in day_averages:
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data_point[average_field] = day_averages[day]
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chart_data.append(data_point)
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# Check if next interval is different level (segment boundary)
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if next_value != interval_value:
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next_start_serialized = (
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next_start_time.isoformat()
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if next_start_time and hasattr(next_start_time, "isoformat")
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else next_start_time
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)
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if connect_segments and next_price is not None:
|
||||
# Connect segments visually by adding bridge point + NULL
|
||||
# Bridge point: extends current series to boundary with next price
|
||||
# NULL point: stops series so it doesn't continue into next segment
|
||||
|
||||
converted_next_price = (
|
||||
round(next_price * 100, 2) if subunit_currency else round(next_price, 4)
|
||||
)
|
||||
if round_decimals is not None:
|
||||
converted_next_price = round(converted_next_price, round_decimals)
|
||||
|
||||
# 1. Bridge point: boundary with next price, still current level
|
||||
# This makes the line go up/down to meet the next series
|
||||
bridge_point = {
|
||||
start_time_field: next_start_serialized,
|
||||
price_field: converted_next_price,
|
||||
}
|
||||
if include_level and "level" in interval:
|
||||
bridge_point[level_field] = interval["level"]
|
||||
if include_rating_level and "rating_level" in interval:
|
||||
bridge_point[rating_level_field] = interval["rating_level"]
|
||||
if include_average and day in day_averages:
|
||||
bridge_point[average_field] = day_averages[day]
|
||||
chart_data.append(bridge_point)
|
||||
|
||||
# 2. NULL point: stops the current series
|
||||
# Without this, ApexCharts continues drawing within the series
|
||||
null_point = {start_time_field: next_start_serialized, price_field: None}
|
||||
chart_data.append(null_point)
|
||||
else:
|
||||
# Original behavior: Hold current price until next timestamp
|
||||
hold_point = {
|
||||
start_time_field: next_start_serialized,
|
||||
price_field: converted_price,
|
||||
}
|
||||
if include_level and "level" in interval:
|
||||
hold_point[level_field] = interval["level"]
|
||||
if include_rating_level and "rating_level" in interval:
|
||||
hold_point[rating_level_field] = interval["rating_level"]
|
||||
if include_average and day in day_averages:
|
||||
hold_point[average_field] = day_averages[day]
|
||||
chart_data.append(hold_point)
|
||||
|
||||
# Add NULL point to create gap
|
||||
null_point = {start_time_field: next_start_serialized, price_field: None}
|
||||
chart_data.append(null_point)
|
||||
|
||||
# Handle last interval of the day - extend to midnight
|
||||
if day_prices:
|
||||
last_interval = day_prices[-1]
|
||||
last_start_time = last_interval.get("startsAt")
|
||||
last_price = last_interval.get("total")
|
||||
last_value = last_interval.get(filter_field)
|
||||
|
||||
if last_start_time and last_price is not None and last_value in filter_values: # type: ignore[operator]
|
||||
# Timestamp is already datetime in local timezone
|
||||
last_dt = last_start_time # Already datetime object
|
||||
if last_dt:
|
||||
# Calculate next day at 00:00
|
||||
next_day = last_dt.replace(hour=0, minute=0, second=0, microsecond=0)
|
||||
next_day = next_day + timedelta(days=1)
|
||||
midnight_timestamp = next_day.isoformat()
|
||||
|
||||
# Try to get real price from tomorrow's first interval
|
||||
next_day_name = None
|
||||
if day == "yesterday":
|
||||
next_day_name = "today"
|
||||
elif day == "today":
|
||||
next_day_name = "tomorrow"
|
||||
# For "tomorrow", we don't have a "day after tomorrow"
|
||||
|
||||
midnight_price = None
|
||||
midnight_interval = None
|
||||
|
||||
if next_day_name:
|
||||
# Use helper to get first interval of next day
|
||||
# Map day key to offset: yesterday=-1, today=0, tomorrow=1
|
||||
next_day_offset = {"yesterday": -1, "today": 0, "tomorrow": 1}[next_day_name]
|
||||
next_day_intervals = get_intervals_for_day_offsets(coordinator.data, [next_day_offset])
|
||||
if next_day_intervals:
|
||||
first_next = next_day_intervals[0]
|
||||
first_next_value = first_next.get(filter_field)
|
||||
# Only use tomorrow's price if it matches the same filter
|
||||
if first_next_value == last_value:
|
||||
midnight_price = first_next.get("total")
|
||||
midnight_interval = first_next
|
||||
|
||||
# Fallback: use last interval's price if no tomorrow data or different level
|
||||
if midnight_price is None:
|
||||
midnight_price = last_price
|
||||
midnight_interval = last_interval
|
||||
|
||||
# Convert price
|
||||
converted_price = (
|
||||
round(midnight_price * 100, 2) if subunit_currency else round(midnight_price, 4)
|
||||
)
|
||||
if round_decimals is not None:
|
||||
converted_price = round(converted_price, round_decimals)
|
||||
|
||||
# Add point at midnight with appropriate price (extends graph to end of day)
|
||||
end_point = {start_time_field: midnight_timestamp, price_field: converted_price}
|
||||
if midnight_interval is not None:
|
||||
if include_level and "level" in midnight_interval:
|
||||
end_point[level_field] = midnight_interval["level"]
|
||||
if include_rating_level and "rating_level" in midnight_interval:
|
||||
end_point[rating_level_field] = midnight_interval["rating_level"]
|
||||
if include_average and day in day_averages:
|
||||
end_point[average_field] = day_averages[day]
|
||||
chart_data.append(end_point)
|
||||
else:
|
||||
# Mode 'none' (default): Only return matching intervals, no NULL insertion
|
||||
for interval in day_prices:
|
||||
start_time = interval.get("startsAt")
|
||||
price = interval.get("total")
|
||||
|
||||
if start_time is not None and price is not None:
|
||||
# Apply period filter if specified
|
||||
if (
|
||||
period_filter is not None
|
||||
and period_timestamps is not None
|
||||
and start_time not in period_timestamps
|
||||
):
|
||||
continue
|
||||
|
||||
# Apply level filter if specified
|
||||
if level_filter is not None and "level" in interval and interval["level"] not in level_filter:
|
||||
continue
|
||||
|
||||
# Apply rating_level filter if specified
|
||||
if (
|
||||
rating_level_filter is not None
|
||||
and "rating_level" in interval
|
||||
and interval["rating_level"] not in rating_level_filter
|
||||
):
|
||||
continue
|
||||
|
||||
# Convert to subunit currency (cents/øre) if requested
|
||||
price = round(price * 100, 2) if subunit_currency else round(price, 4)
|
||||
|
||||
# Apply custom rounding if specified
|
||||
if round_decimals is not None:
|
||||
price = round(price, round_decimals)
|
||||
|
||||
data_point = {
|
||||
start_time_field: start_time.isoformat()
|
||||
if hasattr(start_time, "isoformat")
|
||||
else start_time,
|
||||
price_field: price,
|
||||
}
|
||||
|
||||
# Add level if requested
|
||||
if include_level and "level" in interval:
|
||||
data_point[level_field] = interval["level"]
|
||||
|
||||
# Add rating_level if requested
|
||||
if include_rating_level and "rating_level" in interval:
|
||||
data_point[rating_level_field] = interval["rating_level"]
|
||||
|
||||
# Add average if requested
|
||||
if include_average and day in day_averages:
|
||||
data_point[average_field] = day_averages[day]
|
||||
|
||||
chart_data.append(data_point)
|
||||
|
||||
elif resolution == "hourly":
|
||||
# Hourly averages (4 intervals per hour: :00, :15, :30, :45)
|
||||
chart_data.extend(
|
||||
aggregate_hourly_exact(
|
||||
day_prices,
|
||||
start_time_field,
|
||||
price_field,
|
||||
coordinator=coordinator,
|
||||
use_subunit_currency=subunit_currency,
|
||||
round_decimals=round_decimals,
|
||||
include_level=include_level,
|
||||
include_rating_level=include_rating_level,
|
||||
level_filter=level_filter,
|
||||
rating_level_filter=rating_level_filter,
|
||||
include_average=include_average,
|
||||
level_field=level_field,
|
||||
rating_level_field=rating_level_field,
|
||||
average_field=average_field,
|
||||
day_average=day_averages.get(day),
|
||||
threshold_low=threshold_low,
|
||||
period_timestamps=period_timestamps,
|
||||
threshold_high=threshold_high,
|
||||
)
|
||||
elif resolution == "hourly":
|
||||
# Hourly averages (4 intervals per hour: :00, :15, :30, :45)
|
||||
# Process all intervals together for hourly aggregation
|
||||
chart_data.extend(
|
||||
aggregate_hourly_exact(
|
||||
all_prices,
|
||||
start_time_field,
|
||||
price_field,
|
||||
coordinator=coordinator,
|
||||
use_subunit_currency=subunit_currency,
|
||||
round_decimals=round_decimals,
|
||||
include_level=include_level,
|
||||
include_rating_level=include_rating_level,
|
||||
level_filter=level_filter,
|
||||
rating_level_filter=rating_level_filter,
|
||||
include_average=include_average,
|
||||
level_field=level_field,
|
||||
rating_level_field=rating_level_field,
|
||||
average_field=average_field,
|
||||
day_average=None, # Not used when processing all days together
|
||||
threshold_low=threshold_low,
|
||||
period_timestamps=period_timestamps,
|
||||
threshold_high=threshold_high,
|
||||
)
|
||||
)
|
||||
|
||||
# Remove trailing null values ONLY for insert_nulls='segments' mode.
|
||||
# For 'all' mode, trailing nulls are intentional (show no-match until end of day).
|
||||
|
|
|
|||
Loading…
Reference in a new issue