mirror of
https://github.com/jpawlowski/hass.tibber_prices.git
synced 2026-03-29 21:03:40 +00:00
feat(apexcharts): add server-side metadata with dynamic yaxis and gradient
Implemented comprehensive metadata calculation for chart data export service with automatic Y-axis scaling and gradient positioning based on actual price statistics. Changes: - Added 'metadata' parameter to get_chartdata service (include/only/none) - Implemented _calculate_metadata() with per-day price statistics * min/max/avg/median prices * avg_position and median_position (0-1 scale for gradient stops) * yaxis_suggested bounds (floor(min)-1, ceil(max)+1) * time_range with day boundaries * currency info with symbol and unit - Integrated metadata into rolling_window modes via config-template-card * Pre-calculated yaxis bounds (no async issues in templates) * Dynamic gradient stops based on avg_position * Server-side calculation ensures consistency Visual refinements: - Best price overlay opacity reduced to 0.05 (ultra-subtle green hint) - Stroke width increased to 1.5 for better visibility - Gradient opacity adjusted to 0.45 with "light" shade - Marker configuration: size 0, hover size 2, strokeWidth 1 - Header display: Only show LOW/HIGH rating_levels (min/max prices) * Conditional logic excludes NORMAL and level types * Entity state shows meaningful extrema values - NOW marker label removed for rolling_window_autozoom mode * Static position at 120min lookback makes label misleading Code cleanup: - Removed redundant all_series_config (server-side data formatting) - Currency names capitalized (Cents, Øre, Öre, Pence) Translation updates: - Added metadata selector translations (de, en, nb, nl, sv) - Added metadata field description in services - Synchronized all language files Impact: Users get dynamic Y-axis scaling based on actual price data, eliminating manual configuration. Rolling window charts automatically adjust axis bounds and gradient positioning. Header shows only meaningful extreme values (daily min/max). All data transformation happens server-side for optimal performance and consistency.
This commit is contained in:
Julian Pawlowski
parent
2f1929fbdc
commit
c8e9f7ec2a
9 changed files with 486 additions and 54 deletions
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@ -162,12 +162,12 @@ HOME_TYPES = {
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# Currency mapping: ISO code -> (major_symbol, minor_symbol, minor_name)
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# For currencies with Home Assistant constants, use those; otherwise define custom ones
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CURRENCY_INFO = {
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"EUR": (CURRENCY_EURO, "ct", "cents"),
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"NOK": ("kr", "øre", "øre"),
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"SEK": ("kr", "öre", "öre"),
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"DKK": ("kr", "øre", "øre"),
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"USD": (CURRENCY_DOLLAR, "¢", "cents"),
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"GBP": ("£", "p", "pence"),
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"EUR": (CURRENCY_EURO, "ct", "Cents"),
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"NOK": ("kr", "øre", "Øre"),
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"SEK": ("kr", "öre", "Öre"),
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"DKK": ("kr", "øre", "Øre"),
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"USD": (CURRENCY_DOLLAR, "¢", "Cents"),
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"GBP": ("£", "p", "Pence"),
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}
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@ -173,6 +173,16 @@ get_chartdata:
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example: prices
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selector:
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text:
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metadata:
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required: false
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default: include
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selector:
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select:
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options:
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- include
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- only
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- none
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translation_key: metadata
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arrays_of_objects:
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collapsed: true
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fields:
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@ -18,7 +18,7 @@ Response: YAML configuration dict for ApexCharts card
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from __future__ import annotations
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from typing import TYPE_CHECKING, Any, Final
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from typing import Any, Final
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import voluptuous as vol
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@ -35,6 +35,7 @@ from custom_components.tibber_prices.const import (
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format_price_unit_minor,
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get_translation,
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)
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from homeassistant.core import ServiceCall
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from homeassistant.exceptions import ServiceValidationError
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from homeassistant.helpers import config_validation as cv
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from homeassistant.helpers.entity_registry import (
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@ -45,11 +46,9 @@ from homeassistant.helpers.entity_registry import (
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)
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from .formatters import get_level_translation
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from .get_chartdata import handle_chartdata
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from .helpers import get_entry_and_data
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if TYPE_CHECKING:
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from homeassistant.core import ServiceCall
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# Service constants
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APEXCHARTS_YAML_SERVICE_NAME: Final = "get_apexcharts_yaml"
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ATTR_DAY: Final = "day"
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@ -261,21 +260,41 @@ async def handle_apexcharts_yaml(call: ServiceCall) -> dict[str, Any]: # noqa:
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# For rolling_window and rolling_window_autozoom, omit day parameter (dynamic selection)
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day_param = "" if day in ("rolling_window", "rolling_window_autozoom", None) else f"day: ['{day}'], "
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data_generator = (
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f"const response = await hass.callWS({{ "
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f"type: 'call_service', "
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f"domain: 'tibber_prices', "
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f"service: 'get_chartdata', "
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f"return_response: true, "
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f"service_data: {{ entry_id: '{entry_id}', {day_param}{filter_param}, "
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f"output_format: 'array_of_arrays', insert_nulls: 'segments', minor_currency: true, "
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f"connect_segments: true }} }}); "
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f"return response.response.data;"
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)
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# All series use same configuration (no extremas on data_generator series)
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# Hide all levels in header since data_generator series don't show meaningful state values
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# (the entity state is the min/max/avg price, not the current price for this level)
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show_config = {"legend_value": False, "in_header": False}
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# For rolling window modes, we'll capture metadata for dynamic config
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# For static day modes, just return data array
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if day in ("rolling_window", "rolling_window_autozoom", None):
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data_generator = (
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f"const response = await hass.callWS({{ "
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f"type: 'call_service', "
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f"domain: 'tibber_prices', "
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f"service: 'get_chartdata', "
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f"return_response: true, "
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f"service_data: {{ entry_id: '{entry_id}', {day_param}{filter_param}, "
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f"output_format: 'array_of_arrays', insert_nulls: 'segments', minor_currency: true, "
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f"connect_segments: true }} }}); "
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f"return response.response.data;"
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)
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else:
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# Static day modes: just return data (no metadata needed)
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data_generator = (
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f"const response = await hass.callWS({{ "
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f"type: 'call_service', "
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f"domain: 'tibber_prices', "
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f"service: 'get_chartdata', "
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f"return_response: true, "
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f"service_data: {{ entry_id: '{entry_id}', {day_param}{filter_param}, "
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f"output_format: 'array_of_arrays', insert_nulls: 'segments', minor_currency: true, "
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f"connect_segments: true }} }}); "
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f"return response.response.data;"
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)
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# Configure show options based on level_type and level_key
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# rating_level LOW/HIGH: Show raw state in header (entity state = min/max price of day)
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# rating_level NORMAL: Hide from header (not meaningful as extrema)
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# level (VERY_CHEAP/CHEAP/etc): Hide from header (entity state is aggregated value)
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if level_type == "rating_level" and level_key in (PRICE_RATING_LOW, PRICE_RATING_HIGH):
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show_config = {"legend_value": False, "in_header": "raw"}
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else:
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show_config = {"legend_value": False, "in_header": False}
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series.append(
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{
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@ -286,13 +305,12 @@ async def handle_apexcharts_yaml(call: ServiceCall) -> dict[str, Any]: # noqa:
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"yaxis_id": "price",
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"show": show_config,
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"data_generator": data_generator,
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"stroke_width": 1,
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"stroke_width": 1.5,
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}
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)
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# Note: Extrema markers don't work with data_generator approach
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# ApexCharts requires entity time-series data for extremas feature
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# Min/Max sensors are single values, not time-series
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# ApexCharts card requires direct entity data for extremas feature, not dynamically generated data
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# Get translated name for best price periods (needed for tooltip formatter)
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best_price_name = (
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@ -334,12 +352,11 @@ async def handle_apexcharts_yaml(call: ServiceCall) -> dict[str, Any]: # noqa:
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"entity": best_price_entity,
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"name": best_price_name,
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"type": "area",
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"color": "rgba(46, 204, 113, 0.2)", # Semi-transparent green
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"color": "rgba(46, 204, 113, 0.05)", # Ultra-subtle green overlay (barely visible)
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"yaxis_id": "highlight", # Use separate Y-axis (0-1) for full-height overlay
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"show": {"legend_value": False, "in_header": False, "in_legend": False},
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"data_generator": best_price_generator,
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"stroke_width": 0,
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"curve": "stepline",
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}
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)
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@ -391,7 +408,7 @@ async def handle_apexcharts_yaml(call: ServiceCall) -> dict[str, Any]: # noqa:
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"header": {
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"show": True,
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"title": title,
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"show_states": True,
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"show_states": False,
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},
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"apex_config": {
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"chart": {
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@ -399,16 +416,16 @@ async def handle_apexcharts_yaml(call: ServiceCall) -> dict[str, Any]: # noqa:
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"toolbar": {"show": True, "tools": {"zoom": True, "pan": True}},
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"zoom": {"enabled": True},
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},
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"stroke": {"curve": "stepline", "width": 2},
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"stroke": {"curve": "stepline"},
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"fill": {
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"type": "gradient",
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"opacity": 0.4,
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"opacity": 0.45,
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"gradient": {
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"shade": "dark",
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"shade": "light",
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"type": "vertical",
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"shadeIntensity": 0.5,
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"shadeIntensity": 0.2,
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"opacityFrom": 0.7,
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"opacityTo": 0.2,
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"opacityTo": 0.25,
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},
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},
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"dataLabels": {"enabled": False},
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@ -418,18 +435,21 @@ async def handle_apexcharts_yaml(call: ServiceCall) -> dict[str, Any]: # noqa:
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},
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"legend": {
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"show": False,
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"position": "top",
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"horizontalAlign": "left",
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"markers": {"radius": 2},
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"position": "bottom",
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"horizontalAlign": "center",
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},
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"grid": {
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"show": True,
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"borderColor": "#f5f5f5",
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"strokeDashArray": 0,
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"xaxis": {"lines": {"show": True}},
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"xaxis": {"lines": {"show": False}},
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"yaxis": {"lines": {"show": True}},
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},
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"markers": {"size": 0},
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"markers": {
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"size": 0, # No markers on data points
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"hover": {"size": 2}, # Show marker only on hover
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"strokeWidth": 1,
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},
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},
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"yaxis": [
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{
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@ -446,11 +466,11 @@ async def handle_apexcharts_yaml(call: ServiceCall) -> dict[str, Any]: # noqa:
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"opposite": True,
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},
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],
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"now": {"show": True, "color": "#8e24aa", "label": "🕒 LIVE"},
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"all_series_config": {
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"stroke_width": 1,
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"group_by": {"func": "raw", "duration": "15min"},
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},
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"now": (
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{"show": True, "color": "#8e24aa"}
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if day == "rolling_window_autozoom"
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else {"show": True, "color": "#8e24aa", "label": "🕒 LIVE"}
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),
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"series": series,
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}
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@ -529,6 +549,30 @@ async def handle_apexcharts_yaml(call: ServiceCall) -> dict[str, Any]: # noqa:
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if current_price_sensor:
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trigger_entities.append(current_price_sensor)
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# Pre-calculate metadata server-side for dynamic yaxis and gradient
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# This avoids async issues with config-template-card variables
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# Create service call to get metadata
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metadata_call = ServiceCall(
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hass=hass,
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domain="tibber_prices",
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service="get_chartdata",
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data={
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"entry_id": entry_id,
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"minor_currency": True,
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"metadata": "only",
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},
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context=call.context,
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return_response=True,
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)
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metadata_response = await handle_chartdata(metadata_call)
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metadata = metadata_response.get("metadata", {})
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# Extract values with fallbacks
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yaxis_min = metadata.get("yaxis_suggested", {}).get("min", 0)
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yaxis_max = metadata.get("yaxis_suggested", {}).get("max", 100)
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avg_position = metadata.get("price_stats", {}).get("combined", {}).get("avg_position", 0.5)
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gradient_stop = round(avg_position * 100)
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return {
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"type": "custom:config-template-card",
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"variables": {
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@ -539,6 +583,42 @@ async def handle_apexcharts_yaml(call: ServiceCall) -> dict[str, Any]: # noqa:
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**result,
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"span": {"start": "minute", "offset": "-120min"},
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"graph_span": "${v_graph_span}",
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"yaxis": [
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{
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"id": "price",
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"decimals": 2,
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"min": yaxis_min,
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"max": yaxis_max,
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"apex_config": {
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"title": {"text": price_unit},
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"decimalsInFloat": 0,
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"forceNiceScale": False,
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},
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},
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{
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"id": "highlight",
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"min": 0,
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"max": 1,
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"show": False,
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"opposite": True,
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},
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],
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"apex_config": {
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**result["apex_config"],
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"fill": {
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"type": "gradient",
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"opacity": 0.45,
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"gradient": {
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"shade": "light",
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"type": "vertical",
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"shadeIntensity": 0.2,
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"opacityFrom": 0.7,
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"opacityTo": 0.25,
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"gradientToColors": ["#transparent"],
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"stops": [gradient_stop, 100],
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},
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},
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},
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},
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}
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# Rolling window modes (day is None or rolling_window): Dynamic offset
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@ -549,6 +629,31 @@ async def handle_apexcharts_yaml(call: ServiceCall) -> dict[str, Any]: # noqa:
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# If 'on' (tomorrow data available) → offset +1d (show today+tomorrow)
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# If 'off' (no tomorrow data) → offset +0d (show yesterday+today)
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template_value = f"states['{tomorrow_data_sensor}'].state === 'on' ? '+1d' : '+0d'"
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# Pre-calculate metadata server-side for dynamic yaxis and gradient
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# This avoids async issues with config-template-card variables
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# Create service call to get metadata
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metadata_call = ServiceCall(
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hass=hass,
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domain="tibber_prices",
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service="get_chartdata",
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data={
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"entry_id": entry_id,
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"minor_currency": True,
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"metadata": "only",
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},
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context=call.context,
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return_response=True,
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)
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metadata_response = await handle_chartdata(metadata_call)
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metadata = metadata_response.get("metadata", {})
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# Extract values with fallbacks
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yaxis_min = metadata.get("yaxis_suggested", {}).get("min", 0)
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yaxis_max = metadata.get("yaxis_suggested", {}).get("max", 100)
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avg_position = metadata.get("price_stats", {}).get("combined", {}).get("avg_position", 0.5)
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gradient_stop = round(avg_position * 100)
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return {
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"type": "custom:config-template-card",
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"variables": {
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@ -561,6 +666,42 @@ async def handle_apexcharts_yaml(call: ServiceCall) -> dict[str, Any]: # noqa:
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"end": "day",
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"offset": "${v_offset}",
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},
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"yaxis": [
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{
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"id": "price",
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"decimals": 2,
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"min": yaxis_min,
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"max": yaxis_max,
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"apex_config": {
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"title": {"text": price_unit},
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"decimalsInFloat": 0,
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"forceNiceScale": False,
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},
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},
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{
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"id": "highlight",
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"min": 0,
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"max": 1,
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"show": False,
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"opposite": True,
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},
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],
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"apex_config": {
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**result["apex_config"],
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"fill": {
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"type": "gradient",
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"opacity": 0.45,
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"gradient": {
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"shade": "light",
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"type": "vertical",
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"shadeIntensity": 0.2,
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"opacityFrom": 0.7,
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"opacityTo": 0.25,
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"gradientToColors": ["#transparent"],
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"stops": [gradient_stop, 100],
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},
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},
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},
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},
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}
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@ -21,8 +21,9 @@ Response: JSON with chart-ready data
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from __future__ import annotations
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import math
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import re
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from datetime import timedelta
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from datetime import datetime, timedelta
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from typing import TYPE_CHECKING, Any, Final
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import voluptuous as vol
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@ -41,6 +42,9 @@ from custom_components.tibber_prices.const import (
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PRICE_RATING_HIGH,
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PRICE_RATING_LOW,
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PRICE_RATING_NORMAL,
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format_price_unit_major,
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format_price_unit_minor,
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get_currency_info,
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)
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from custom_components.tibber_prices.coordinator.helpers import (
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get_intervals_for_day_offsets,
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@ -53,6 +57,161 @@ from .helpers import get_entry_and_data, has_tomorrow_data
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if TYPE_CHECKING:
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from homeassistant.core import ServiceCall
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def _calculate_metadata( # noqa: PLR0912, PLR0913, PLR0915
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chart_data: list[dict[str, Any]],
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price_field: str,
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start_time_field: str,
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currency: str,
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*,
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resolution: str,
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minor_currency: bool = False,
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) -> dict[str, Any]:
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"""
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Calculate metadata for chart visualization.
|
||||
|
||||
Args:
|
||||
chart_data: The chart data array
|
||||
price_field: Name of the price field in chart_data
|
||||
start_time_field: Name of the start time field
|
||||
currency: Currency code (e.g., "EUR", "NOK")
|
||||
resolution: Resolution type ("interval" or "hourly")
|
||||
minor_currency: Whether prices are in minor currency units
|
||||
|
||||
Returns:
|
||||
Metadata dictionary with price statistics, yaxis suggestions, and time info
|
||||
|
||||
"""
|
||||
# Get currency info (returns tuple: major_symbol, minor_symbol, minor_name)
|
||||
major_symbol, minor_symbol, minor_name = get_currency_info(currency)
|
||||
|
||||
# Build currency object with only the active unit
|
||||
if minor_currency:
|
||||
currency_obj = {
|
||||
"code": currency,
|
||||
"symbol": minor_symbol,
|
||||
"name": minor_name, # Already capitalized in CURRENCY_INFO
|
||||
"unit": format_price_unit_minor(currency),
|
||||
}
|
||||
else:
|
||||
currency_obj = {
|
||||
"code": currency,
|
||||
"symbol": major_symbol,
|
||||
"unit": format_price_unit_major(currency),
|
||||
}
|
||||
|
||||
# Extract all prices (excluding None values)
|
||||
prices = [item[price_field] for item in chart_data if item.get(price_field) is not None]
|
||||
|
||||
if not prices:
|
||||
return {}
|
||||
|
||||
# Parse timestamps to determine day boundaries
|
||||
# Group by date (midnight-to-midnight)
|
||||
dates_seen = set()
|
||||
for item in chart_data:
|
||||
timestamp_str = item.get(start_time_field)
|
||||
if timestamp_str and item.get(price_field) is not None:
|
||||
# Parse ISO timestamp
|
||||
dt = datetime.fromisoformat(timestamp_str) if isinstance(timestamp_str, str) else timestamp_str
|
||||
date = dt.date()
|
||||
dates_seen.add(date)
|
||||
|
||||
# Sort dates to ensure consistent day numbering
|
||||
sorted_dates = sorted(dates_seen)
|
||||
|
||||
# Split data by day - dynamically handle any number of days
|
||||
days_data: dict[str, list[float]] = {}
|
||||
for i, _date in enumerate(sorted_dates, start=1):
|
||||
day_key = f"day{i}"
|
||||
days_data[day_key] = []
|
||||
|
||||
# Assign prices to their respective days
|
||||
for item in chart_data:
|
||||
timestamp_str = item.get(start_time_field)
|
||||
price = item.get(price_field)
|
||||
if timestamp_str and price is not None:
|
||||
dt = datetime.fromisoformat(timestamp_str) if isinstance(timestamp_str, str) else timestamp_str
|
||||
date = dt.date()
|
||||
# Find which day this date corresponds to
|
||||
day_index = sorted_dates.index(date) + 1
|
||||
day_key = f"day{day_index}"
|
||||
days_data[day_key].append(price)
|
||||
|
||||
def calc_stats(data: list[float]) -> dict[str, float]:
|
||||
"""Calculate comprehensive statistics for a dataset."""
|
||||
if not data:
|
||||
return {}
|
||||
min_val = min(data)
|
||||
max_val = max(data)
|
||||
avg_val = sum(data) / len(data)
|
||||
median_val = sorted(data)[len(data) // 2]
|
||||
|
||||
# Calculate avg_position and median_position (0-1 scale)
|
||||
price_range = max_val - min_val
|
||||
avg_position = (avg_val - min_val) / price_range if price_range > 0 else 0.5
|
||||
median_position = (median_val - min_val) / price_range if price_range > 0 else 0.5
|
||||
|
||||
# Position precision: 2 decimals for minor currency, 4 for major currency
|
||||
position_decimals = 2 if minor_currency else 4
|
||||
|
||||
return {
|
||||
"min": round(min_val, 2),
|
||||
"max": round(max_val, 2),
|
||||
"avg": round(avg_val, 2),
|
||||
"avg_position": round(avg_position, position_decimals),
|
||||
"median": round(median_val, 2),
|
||||
"median_position": round(median_position, position_decimals),
|
||||
}
|
||||
|
||||
# Calculate stats for combined and per-day data
|
||||
combined_stats = calc_stats(prices)
|
||||
|
||||
# Calculate stats for each day dynamically
|
||||
per_day_stats: dict[str, dict[str, float]] = {}
|
||||
for day_key, day_data in days_data.items():
|
||||
if day_data:
|
||||
per_day_stats[day_key] = calc_stats(day_data)
|
||||
|
||||
# Calculate suggested yaxis bounds (floor(min) - 1 and ceil(max) + 1)
|
||||
yaxis_min = math.floor(combined_stats["min"]) - 1 if combined_stats else 0
|
||||
yaxis_max = math.ceil(combined_stats["max"]) + 1 if combined_stats else 100
|
||||
|
||||
# Get time range from chart data
|
||||
timestamps = [item[start_time_field] for item in chart_data if item.get(start_time_field)]
|
||||
time_range = {}
|
||||
|
||||
if timestamps:
|
||||
time_range = {
|
||||
"start": timestamps[0],
|
||||
"end": timestamps[-1],
|
||||
"days_included": list(days_data.keys()),
|
||||
}
|
||||
|
||||
# Determine interval duration in minutes based on resolution
|
||||
interval_duration_minutes = 15 if resolution == "interval" else 60
|
||||
|
||||
# Calculate suggested yaxis bounds
|
||||
# For minor currency (ct, øre): integer values (floor/ceil)
|
||||
# For major currency (€, kr): 2 decimal places precision
|
||||
if minor_currency:
|
||||
yaxis_min = math.floor(combined_stats["min"]) - 1 if combined_stats else 0
|
||||
yaxis_max = math.ceil(combined_stats["max"]) + 1 if combined_stats else 100
|
||||
else:
|
||||
# Major currency: round to 2 decimal places with padding
|
||||
yaxis_min = round(math.floor(combined_stats["min"] * 100) / 100 - 0.01, 2) if combined_stats else 0
|
||||
yaxis_max = round(math.ceil(combined_stats["max"] * 100) / 100 + 0.01, 2) if combined_stats else 1.0
|
||||
|
||||
return {
|
||||
"currency": currency_obj,
|
||||
"resolution": interval_duration_minutes,
|
||||
"data_count": len(chart_data),
|
||||
"price_stats": {"combined": combined_stats, **per_day_stats},
|
||||
"yaxis_suggested": {"min": yaxis_min, "max": yaxis_max},
|
||||
"time_range": time_range,
|
||||
}
|
||||
|
||||
|
||||
# Service constants
|
||||
CHARTDATA_SERVICE_NAME: Final = "get_chartdata"
|
||||
ATTR_DAY: Final = "day"
|
||||
|
|
@ -102,6 +261,7 @@ CHARTDATA_SERVICE_SCHEMA: Final = vol.Schema(
|
|||
vol.Optional("rating_level_field", default="rating_level"): str,
|
||||
vol.Optional("average_field", default="average"): str,
|
||||
vol.Optional("data_key", default="data"): str,
|
||||
vol.Optional("metadata", default="include"): vol.In(["include", "only", "none"]),
|
||||
}
|
||||
)
|
||||
|
||||
|
|
@ -162,6 +322,7 @@ async def handle_chartdata(call: ServiceCall) -> dict[str, Any]: # noqa: PLR091
|
|||
resolution = call.data.get("resolution", "interval")
|
||||
output_format = call.data.get("output_format", "array_of_objects")
|
||||
minor_currency = call.data.get("minor_currency", False)
|
||||
metadata = call.data.get("metadata", "include")
|
||||
round_decimals = call.data.get("round_decimals")
|
||||
include_level = call.data.get("include_level", False)
|
||||
include_rating_level = call.data.get("include_rating_level", False)
|
||||
|
|
@ -174,6 +335,44 @@ async def handle_chartdata(call: ServiceCall) -> dict[str, Any]: # noqa: PLR091
|
|||
level_filter = call.data.get("level_filter")
|
||||
rating_level_filter = call.data.get("rating_level_filter")
|
||||
|
||||
# === METADATA-ONLY MODE ===
|
||||
# Early return: calculate and return only metadata, skip all data processing
|
||||
if metadata == "only":
|
||||
# Get minimal data to calculate metadata (just timestamps and prices)
|
||||
# Use helper to get intervals for requested days
|
||||
day_offset_map = {"yesterday": -1, "today": 0, "tomorrow": 1}
|
||||
offsets = [day_offset_map[day] for day in days]
|
||||
all_intervals = get_intervals_for_day_offsets(coordinator.data, offsets)
|
||||
|
||||
# Build minimal chart_data for metadata calculation
|
||||
chart_data_for_meta = []
|
||||
for interval in all_intervals:
|
||||
start_time = interval.get("startsAt")
|
||||
price = interval.get("total")
|
||||
if start_time is not None and price is not None:
|
||||
# Convert price to requested currency
|
||||
converted_price = round(price * 100, 2) if minor_currency else round(price, 4)
|
||||
chart_data_for_meta.append(
|
||||
{
|
||||
start_time_field: start_time.isoformat() if hasattr(start_time, "isoformat") else start_time,
|
||||
price_field: converted_price,
|
||||
}
|
||||
)
|
||||
|
||||
# Calculate metadata
|
||||
metadata = _calculate_metadata(
|
||||
chart_data=chart_data_for_meta,
|
||||
price_field=price_field,
|
||||
start_time_field=start_time_field,
|
||||
currency=coordinator.data.get("currency", "EUR"),
|
||||
resolution=resolution,
|
||||
minor_currency=minor_currency,
|
||||
)
|
||||
|
||||
return {"metadata": metadata}
|
||||
|
||||
# Filter values are already normalized to uppercase by schema validators
|
||||
|
||||
# If array_fields is specified, implicitly enable fields that are used
|
||||
array_fields_template = call.data.get("array_fields")
|
||||
if array_fields_template and output_format == "array_of_arrays":
|
||||
|
|
@ -620,7 +819,34 @@ async def handle_chartdata(call: ServiceCall) -> dict[str, Any]: # noqa: PLR091
|
|||
null_row = [points[-1][0]] + [None] * (len(field_names) - 1)
|
||||
points.append(null_row)
|
||||
|
||||
return {data_key: points}
|
||||
# Calculate metadata (before adding trailing null to chart_data)
|
||||
result = {data_key: points}
|
||||
if metadata in ("include", "only"):
|
||||
metadata_obj = _calculate_metadata(
|
||||
chart_data=chart_data,
|
||||
price_field=price_field,
|
||||
start_time_field=start_time_field,
|
||||
currency=coordinator.data.get("currency", "EUR"),
|
||||
resolution=resolution,
|
||||
minor_currency=minor_currency,
|
||||
)
|
||||
if metadata_obj:
|
||||
result["metadata"] = metadata_obj # type: ignore[index]
|
||||
return result
|
||||
|
||||
# Calculate metadata (before adding trailing null)
|
||||
result = {data_key: chart_data}
|
||||
if metadata in ("include", "only"):
|
||||
metadata_obj = _calculate_metadata(
|
||||
chart_data=chart_data,
|
||||
price_field=price_field,
|
||||
start_time_field=start_time_field,
|
||||
currency=coordinator.data.get("currency", "EUR"),
|
||||
resolution=resolution,
|
||||
minor_currency=minor_currency,
|
||||
)
|
||||
if metadata_obj:
|
||||
result["metadata"] = metadata_obj # type: ignore[index]
|
||||
|
||||
# Add trailing null point for array_of_objects format if requested
|
||||
if add_trailing_null and chart_data:
|
||||
|
|
@ -633,4 +859,4 @@ async def handle_chartdata(call: ServiceCall) -> dict[str, Any]: # noqa: PLR091
|
|||
null_point[field] = None
|
||||
chart_data.append(null_point)
|
||||
|
||||
return {data_key: chart_data}
|
||||
return result
|
||||
|
|
|
|||
|
|
@ -995,9 +995,13 @@
|
|||
"name": "Durchschnitts-Feldname",
|
||||
"description": "Benutzerdefinierter Name für das Durchschnitts-Feld in der Ausgabe. Standard ist 'average', falls nicht angegeben. Wird nur verwendet, wenn include_average aktiviert ist."
|
||||
},
|
||||
"metadata": {
|
||||
"name": "Metadaten",
|
||||
"description": "Steuerung der Metadaten-Einbindung in der Antwort. 'include' (Standard): Gibt Chart-Daten und Metadaten mit Preisstatistiken, Währungsinformationen, Y-Achsen-Vorschlägen und Zeitbereich zurück. 'only': Gibt nur Metadaten zurück ohne Chart-Daten zu verarbeiten (schnell, nützlich für dynamische Y-Achsen-Konfiguration). 'none': Gibt nur Chart-Daten ohne Metadaten zurück."
|
||||
},
|
||||
"data_key": {
|
||||
"name": "Daten-Schlüssel",
|
||||
"description": "Benutzerdefinierter Name für den obersten Datenschlüssel in der Antwort. Standard ist 'data', falls nicht angegeben. Für ApexCharts-Kompatibilität mit Array von Arrays verwende 'points'."
|
||||
"description": "Benutzerdefinierter Name für den obersten Datenschlüssel in der Antwort. Standard ist 'data', falls nicht angegeben."
|
||||
}
|
||||
}
|
||||
},
|
||||
|
|
@ -1074,6 +1078,13 @@
|
|||
"peak_price": "Spitzenpreis-Zeiträume"
|
||||
}
|
||||
},
|
||||
"metadata": {
|
||||
"options": {
|
||||
"include": "Einbeziehen (Daten + Metadaten)",
|
||||
"only": "Nur Metadaten",
|
||||
"none": "Keine (nur Daten)"
|
||||
}
|
||||
},
|
||||
"volatility": {
|
||||
"options": {
|
||||
"low": "Niedrig",
|
||||
|
|
|
|||
|
|
@ -933,7 +933,7 @@
|
|||
},
|
||||
"data_key": {
|
||||
"name": "Data Key",
|
||||
"description": "Custom name for the top-level data key in the response. Defaults to 'data' if not specified. For ApexCharts compatibility with Array of Arrays, use 'points'."
|
||||
"description": "Custom name for the top-level data key in the response. Defaults to 'data' if not specified."
|
||||
},
|
||||
"include_level": {
|
||||
"name": "Include Level",
|
||||
|
|
@ -994,6 +994,10 @@
|
|||
"average_field": {
|
||||
"name": "Average Field Name",
|
||||
"description": "Custom name for the average field in the output. Defaults to 'average' if not specified. Only used when include_average is enabled."
|
||||
},
|
||||
"metadata": {
|
||||
"name": "Metadata",
|
||||
"description": "Control metadata inclusion in the response. 'include' (default): Returns both chart data and metadata with price statistics, currency info, Y-axis suggestions, and time range. 'only': Returns only metadata without processing chart data (fast, useful for dynamic Y-axis configuration). 'none': Returns only chart data without metadata."
|
||||
}
|
||||
}
|
||||
},
|
||||
|
|
@ -1070,6 +1074,13 @@
|
|||
"peak_price": "Peak Price Periods"
|
||||
}
|
||||
},
|
||||
"metadata": {
|
||||
"options": {
|
||||
"include": "Include (data + metadata)",
|
||||
"only": "Only metadata",
|
||||
"none": "None (data only)"
|
||||
}
|
||||
},
|
||||
"volatility": {
|
||||
"options": {
|
||||
"low": "Low",
|
||||
|
|
|
|||
|
|
@ -991,9 +991,13 @@
|
|||
"name": "Gjennomsnittsfelt-navn",
|
||||
"description": "Tilpasset navn for gjennomsnittsfeltet i utdata. Standard er 'average'. Brukes bare når include_average er aktivert."
|
||||
},
|
||||
"metadata": {
|
||||
"name": "Metadata",
|
||||
"description": "Kontroller metadata-inkludering i svaret. 'include' (standard): Returnerer både diagramdata og metadata med prisstatistikk, valutainformasjon, Y-akse forslag og tidsperiode. 'only': Returnerer bare metadata uten å behandle diagramdata (raskt, nyttig for dynamisk Y-akse konfigurasjon). 'none': Returnerer bare diagramdata uten metadata."
|
||||
},
|
||||
"data_key": {
|
||||
"name": "Datanøkkel",
|
||||
"description": "Tilpasset navn for datanøkkelen på toppnivå i svaret. Standard er 'data' hvis ikke angitt. For ApexCharts-kompatibilitet med Array av arrays, bruk 'points'."
|
||||
"description": "Tilpasset navn for datanøkkelen på toppnivå i svaret. Standard er 'data' hvis ikke angitt."
|
||||
}
|
||||
}
|
||||
},
|
||||
|
|
@ -1070,6 +1074,13 @@
|
|||
"peak_price": "Topp prisperioder"
|
||||
}
|
||||
},
|
||||
"metadata": {
|
||||
"options": {
|
||||
"include": "Inkluder (data + metadata)",
|
||||
"only": "Kun metadata",
|
||||
"none": "Ingen (kun data)"
|
||||
}
|
||||
},
|
||||
"volatility": {
|
||||
"options": {
|
||||
"low": "Lav",
|
||||
|
|
|
|||
|
|
@ -991,9 +991,13 @@
|
|||
"name": "Gemiddelde veld-naam",
|
||||
"description": "Aangepaste naam voor het gemiddelde veld in de uitvoer. Standaard is 'average'. Alleen gebruikt wanneer include_average is ingeschakeld."
|
||||
},
|
||||
"metadata": {
|
||||
"name": "Metadata",
|
||||
"description": "Beheer metadata-opname in het antwoord. 'include' (standaard): Retourneert zowel grafiekdata als metadata met prijsstatistieken, valuta-info, Y-as suggesties en tijdsbereik. 'only': Retourneert alleen metadata zonder grafiekdata te verwerken (snel, handig voor dynamische Y-as configuratie). 'none': Retourneert alleen grafiekdata zonder metadata."
|
||||
},
|
||||
"data_key": {
|
||||
"name": "Gegevenssleutel",
|
||||
"description": "Aangepaste naam voor de gegevenssleutel op het hoogste niveau in het antwoord. Standaard is 'data' als niet opgegeven. Voor ApexCharts-compatibiliteit met Array van arrays, gebruik 'points'."
|
||||
"description": "Aangepaste naam voor de gegevenssleutel op het hoogste niveau in het antwoord. Standaard is 'data' als niet opgegeven."
|
||||
}
|
||||
}
|
||||
},
|
||||
|
|
@ -1070,6 +1074,13 @@
|
|||
"peak_price": "Piek prijsperioden"
|
||||
}
|
||||
},
|
||||
"metadata": {
|
||||
"options": {
|
||||
"include": "Opnemen (data + metadata)",
|
||||
"only": "Alleen metadata",
|
||||
"none": "Geen (alleen data)"
|
||||
}
|
||||
},
|
||||
"volatility": {
|
||||
"options": {
|
||||
"low": "Laag",
|
||||
|
|
|
|||
|
|
@ -991,9 +991,13 @@
|
|||
"name": "Genomsnittsfältsnamn",
|
||||
"description": "Anpassat namn för genomsnittsfältet i utdata. Standard är 'average'. Används endast när include_average är aktiverad."
|
||||
},
|
||||
"metadata": {
|
||||
"name": "Metadata",
|
||||
"description": "Styr metadata-inkludering i svaret. 'include' (standard): Returnerar både diagramdata och metadata med prisstatistik, valutainformation, Y-axelförslag och tidsperiod. 'only': Returnerar endast metadata utan att bearbeta diagramdata (snabbt, användbart för dynamisk Y-axel konfiguration). 'none': Returnerar endast diagramdata utan metadata."
|
||||
},
|
||||
"data_key": {
|
||||
"name": "Datanyckel",
|
||||
"description": "Anpassat namn för datanyckeln på toppnivå i svaret. Standard är 'data' om inte angivet. För ApexCharts-kompatibilitet med Array av arrayer, använd 'points'."
|
||||
"description": "Anpassat namn för datanyckeln på toppnivå i svaret. Standard är 'data' om inte angivet."
|
||||
}
|
||||
}
|
||||
},
|
||||
|
|
@ -1070,6 +1074,13 @@
|
|||
"peak_price": "Topp prisperioder"
|
||||
}
|
||||
},
|
||||
"metadata": {
|
||||
"options": {
|
||||
"include": "Inkludera (data + metadata)",
|
||||
"only": "Endast metadata",
|
||||
"none": "Ingen (endast data)"
|
||||
}
|
||||
},
|
||||
"volatility": {
|
||||
"options": {
|
||||
"low": "Låg",
|
||||
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|||
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Reference in a new issue