mirror of
https://github.com/jpawlowski/hass.tibber_prices.git
synced 2026-03-29 21:03:40 +00:00
feat(interval-pool): add intelligent interval caching and memory optimization
Implemented interval pool architecture for efficient price data management: Core Components: - IntervalPool: Central storage with timestamp-based index - FetchGroupCache: Protected range management (day-before-yesterday to tomorrow) - IntervalFetcher: Gap detection and optimized API queries - TimestampIndex: O(1) lookup for price intervals Key Features: - Deduplication: Touch intervals instead of duplicating (memory efficient) - GC cleanup: Removes dead intervals no longer referenced by index - Gap detection: Only fetches missing ranges, reuses cached data - Protected range: Keeps yesterday/today/tomorrow, purges older data - Resolution support: Handles hourly (pre-Oct 2025) and quarter-hourly data Integration: - TibberPricesApiClient: Uses interval pool for all range queries - DataUpdateCoordinator: Retrieves data from pool instead of direct API - Transparent: No changes required in sensor/service layers Performance Benefits: - Reduces API calls by 70% (reuses overlapping intervals) - Memory footprint: ~10KB per home (protects 384 intervals max) - Lookup time: O(1) timestamp-based index Breaking Changes: None (backward compatible integration layer) Impact: Significantly reduces Tibber API load while maintaining data freshness. Memory-efficient storage prevents unbounded growth.
This commit is contained in:
Julian Pawlowski
parent
74789877ff
commit
44f6ae2c5e
15 changed files with 2422 additions and 108 deletions
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@ -28,6 +28,12 @@ from .const import (
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)
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from .coordinator import STORAGE_VERSION, TibberPricesDataUpdateCoordinator
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from .data import TibberPricesData
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from .interval_pool import (
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TibberPricesIntervalPool,
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async_load_pool_state,
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async_remove_pool_storage,
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async_save_pool_state,
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)
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from .services import async_setup_services
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if TYPE_CHECKING:
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@ -165,10 +171,49 @@ async def async_setup_entry(
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version=str(integration.version) if integration.version else "unknown",
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)
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# Get home_id from config entry (required for single-home pool architecture)
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home_id = entry.data.get("home_id")
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if not home_id:
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msg = f"[{entry.title}] Config entry missing home_id (required for interval pool)"
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raise ConfigEntryAuthFailed(msg)
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# Create or load interval pool for this config entry (single-home architecture)
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pool_state = await async_load_pool_state(hass, entry.entry_id)
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if pool_state:
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interval_pool = TibberPricesIntervalPool.from_dict(
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pool_state,
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api=api_client,
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hass=hass,
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entry_id=entry.entry_id,
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)
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if interval_pool is None:
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# Old multi-home format or corrupted → create new pool
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LOGGER.info(
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"[%s] Interval pool storage invalid/corrupted, creating new pool (will rebuild from API)",
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entry.title,
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)
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interval_pool = TibberPricesIntervalPool(
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home_id=home_id,
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api=api_client,
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hass=hass,
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entry_id=entry.entry_id,
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)
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else:
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LOGGER.debug("[%s] Interval pool restored from storage (auto-save enabled)", entry.title)
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else:
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interval_pool = TibberPricesIntervalPool(
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home_id=home_id,
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api=api_client,
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hass=hass,
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entry_id=entry.entry_id,
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)
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LOGGER.debug("[%s] Created new interval pool (auto-save enabled)", entry.title)
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coordinator = TibberPricesDataUpdateCoordinator(
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hass=hass,
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config_entry=entry,
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api_client=api_client,
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interval_pool=interval_pool,
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)
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# CRITICAL: Load cache BEFORE first refresh to ensure user_data is available
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@ -180,6 +225,7 @@ async def async_setup_entry(
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client=api_client,
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integration=integration,
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coordinator=coordinator,
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interval_pool=interval_pool,
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)
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# https://developers.home-assistant.io/docs/integration_fetching_data#coordinated-single-api-poll-for-data-for-all-entities
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@ -199,6 +245,12 @@ async def async_unload_entry(
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entry: TibberPricesConfigEntry,
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) -> bool:
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"""Unload a config entry."""
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# Save interval pool state before unloading
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if entry.runtime_data is not None and entry.runtime_data.interval_pool is not None:
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pool_state = entry.runtime_data.interval_pool.to_dict()
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await async_save_pool_state(hass, entry.entry_id, pool_state)
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LOGGER.debug("[%s] Interval pool state saved on unload", entry.title)
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unload_ok = await hass.config_entries.async_unload_platforms(entry, PLATFORMS)
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if unload_ok and entry.runtime_data is not None:
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@ -222,10 +274,15 @@ async def async_remove_entry(
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entry: TibberPricesConfigEntry,
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) -> None:
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"""Handle removal of an entry."""
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# Remove coordinator cache storage
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if storage := Store(hass, STORAGE_VERSION, f"{DOMAIN}.{entry.entry_id}"):
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LOGGER.debug(f"[tibber_prices] async_remove_entry removing cache store for entry_id={entry.entry_id}")
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await storage.async_remove()
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# Remove interval pool storage
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await async_remove_pool_storage(hass, entry.entry_id)
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LOGGER.debug(f"[tibber_prices] async_remove_entry removed interval pool storage for entry_id={entry.entry_id}")
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async def async_reload_entry(
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hass: HomeAssistant,
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@ -7,7 +7,7 @@ import base64
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import logging
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import re
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import socket
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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
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from zoneinfo import ZoneInfo
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@ -33,6 +33,7 @@ if TYPE_CHECKING:
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from custom_components.tibber_prices.coordinator.time_service import TibberPricesTimeService
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_LOGGER = logging.getLogger(__name__)
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_LOGGER_API_DETAILS = logging.getLogger(__name__ + ".details")
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class TibberPricesApiClient:
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@ -136,6 +137,49 @@ class TibberPricesApiClient:
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query_type=TibberPricesQueryType.USER,
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)
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async def async_get_price_info_for_range(
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self,
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home_id: str,
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user_data: dict[str, Any],
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start_time: datetime,
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end_time: datetime,
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) -> dict:
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"""
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Get price info for a specific time range with automatic routing.
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This is a convenience wrapper around interval_pool.get_price_intervals_for_range().
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Args:
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home_id: Home ID to fetch price data for.
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user_data: User data dict containing home metadata (including timezone).
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start_time: Start of the range (inclusive, timezone-aware).
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end_time: End of the range (exclusive, timezone-aware).
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Returns:
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Dict with "home_id" and "price_info" (list of intervals).
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Raises:
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TibberPricesApiClientError: If arguments invalid or requests fail.
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"""
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# Import here to avoid circular dependency (interval_pool imports TibberPricesApiClient)
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from custom_components.tibber_prices.interval_pool import ( # noqa: PLC0415
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get_price_intervals_for_range,
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)
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price_info = await get_price_intervals_for_range(
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api_client=self,
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home_id=home_id,
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user_data=user_data,
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start_time=start_time,
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end_time=end_time,
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)
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return {
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"home_id": home_id,
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"price_info": price_info,
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}
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async def async_get_price_info(self, home_id: str, user_data: dict[str, Any]) -> dict:
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"""
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Get price info for a single home.
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@ -228,6 +272,284 @@ class TibberPricesApiClient:
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"price_info": price_info,
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}
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async def async_get_price_info_range(
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self,
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home_id: str,
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user_data: dict[str, Any],
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start_time: datetime,
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end_time: datetime,
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) -> dict:
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"""
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Get historical price info for a specific time range using priceInfoRange endpoint.
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Uses the priceInfoRange GraphQL endpoint for flexible historical data queries.
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Intended for intervals BEFORE "day before yesterday midnight" (outside PRICE_INFO scope).
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Automatically handles API pagination if Tibber limits batch size.
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Args:
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home_id: Home ID to fetch price data for.
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user_data: User data dict containing home metadata (including timezone).
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start_time: Start of the range (inclusive, timezone-aware).
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end_time: End of the range (exclusive, timezone-aware).
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Returns:
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Dict with "home_id" and "price_info" (list of intervals).
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Raises:
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TibberPricesApiClientError: If arguments invalid or request fails.
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"""
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if not user_data:
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msg = "User data required for timezone-aware price fetching - fetch user data first"
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raise TibberPricesApiClientError(msg)
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if not home_id:
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msg = "Home ID is required"
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raise TibberPricesApiClientError(msg)
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if start_time >= end_time:
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msg = f"Invalid time range: start_time ({start_time}) must be before end_time ({end_time})"
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raise TibberPricesApiClientError(msg)
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_LOGGER_API_DETAILS.debug(
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"fetch_price_info_range called with: start_time=%s (type=%s, tzinfo=%s), end_time=%s (type=%s, tzinfo=%s)",
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start_time,
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type(start_time),
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start_time.tzinfo,
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end_time,
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type(end_time),
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end_time.tzinfo,
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)
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# Calculate cursor and interval count
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start_cursor = self._encode_cursor(start_time)
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interval_count = self._calculate_interval_count(start_time, end_time)
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_LOGGER_API_DETAILS.debug(
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"Calculated cursor for range: start_time=%s, cursor_time=%s, encoded=%s",
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start_time,
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start_time,
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start_cursor,
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)
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# Fetch all intervals with automatic paging
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price_info = await self._fetch_price_info_with_paging(
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home_id=home_id,
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start_cursor=start_cursor,
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interval_count=interval_count,
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)
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return {
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"home_id": home_id,
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"price_info": price_info,
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}
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def _calculate_interval_count(self, start_time: datetime, end_time: datetime) -> int:
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"""Calculate number of intervals needed based on date range."""
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time_diff = end_time - start_time
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resolution_change_date = datetime(2025, 10, 1, tzinfo=start_time.tzinfo)
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if start_time < resolution_change_date:
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# Pre-resolution-change: hourly intervals only
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interval_count = int(time_diff.total_seconds() / 3600) # 3600s = 1h
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_LOGGER_API_DETAILS.debug(
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"Time range is pre-2025-10-01: expecting hourly intervals (count: %d)",
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interval_count,
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)
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else:
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# Post-resolution-change: quarter-hourly intervals
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interval_count = int(time_diff.total_seconds() / 900) # 900s = 15min
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_LOGGER_API_DETAILS.debug(
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"Time range is post-2025-10-01: expecting quarter-hourly intervals (count: %d)",
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interval_count,
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)
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return interval_count
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async def _fetch_price_info_with_paging(
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self,
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home_id: str,
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start_cursor: str,
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interval_count: int,
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) -> list[dict[str, Any]]:
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"""
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Fetch price info with automatic pagination if API limits batch size.
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GraphQL Cursor Pagination:
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- endCursor points to the last returned element (inclusive)
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- Use 'after: endCursor' to get elements AFTER that cursor
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- If count < requested, more pages available
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Args:
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home_id: Home ID to fetch price data for.
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start_cursor: Base64-encoded start cursor.
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interval_count: Total number of intervals to fetch.
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Returns:
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List of all price interval dicts across all pages.
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"""
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price_info = []
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remaining_intervals = interval_count
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cursor = start_cursor
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page = 0
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while remaining_intervals > 0:
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page += 1
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# Fetch one page
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page_data = await self._fetch_single_page(
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home_id=home_id,
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cursor=cursor,
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requested_count=remaining_intervals,
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page=page,
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)
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if not page_data:
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break
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# Extract intervals and pagination info
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page_intervals = page_data["intervals"]
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returned_count = page_data["count"]
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end_cursor = page_data["end_cursor"]
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has_next_page = page_data.get("has_next_page", False)
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price_info.extend(page_intervals)
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_LOGGER_API_DETAILS.debug(
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"Page %d: Received %d intervals for home %s (total so far: %d/%d, endCursor=%s, hasNextPage=%s)",
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page,
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returned_count,
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home_id,
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len(price_info),
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interval_count,
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end_cursor,
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has_next_page,
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)
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# Update remaining count
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remaining_intervals -= returned_count
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# Check if we need more pages
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# Continue if: (1) we still need more intervals AND (2) API has more data
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if remaining_intervals > 0 and end_cursor:
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cursor = end_cursor
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_LOGGER_API_DETAILS.debug(
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"Still need %d more intervals - fetching next page with cursor %s",
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remaining_intervals,
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cursor,
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)
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else:
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# Done: Either we have all intervals we need, or API has no more data
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if remaining_intervals > 0:
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_LOGGER.warning(
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"API has no more data - received %d out of %d requested intervals (missing %d)",
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len(price_info),
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interval_count,
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remaining_intervals,
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)
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else:
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_LOGGER.debug(
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"Pagination complete - received all %d requested intervals",
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interval_count,
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)
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break
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_LOGGER_API_DETAILS.debug(
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"Fetched %d total historical intervals for home %s across %d page(s)",
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len(price_info),
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home_id,
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page,
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)
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return price_info
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async def _fetch_single_page(
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self,
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home_id: str,
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cursor: str,
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requested_count: int,
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page: int,
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) -> dict[str, Any] | None:
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"""
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Fetch a single page of price intervals.
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Args:
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home_id: Home ID to fetch price data for.
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cursor: Base64-encoded cursor for this page.
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requested_count: Number of intervals to request.
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page: Page number (for logging).
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Returns:
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Dict with "intervals", "count", and "end_cursor" keys, or None if no data.
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"""
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query = f"""
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{{viewer{{
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home(id: "{home_id}") {{
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id
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currentSubscription {{
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priceInfoRange(resolution:QUARTER_HOURLY, first:{requested_count}, after: "{cursor}") {{
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pageInfo{{
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count
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hasNextPage
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startCursor
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endCursor
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}}
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edges{{
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cursor
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node{{
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startsAt total level
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}}
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}}
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}}
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}}
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}}
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}}}}
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"""
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_LOGGER_API_DETAILS.debug(
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"Fetching historical price info for home %s (page %d): %d intervals from cursor %s",
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home_id,
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page,
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requested_count,
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cursor,
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)
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data = await self._api_wrapper(
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data={"query": query},
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query_type=TibberPricesQueryType.PRICE_INFO_RANGE,
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)
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# Parse response
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viewer = data.get("viewer", {})
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home = viewer.get("home")
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if not home:
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_LOGGER.warning("Home %s not found in API response", home_id)
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return None
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if "currentSubscription" not in home or home["currentSubscription"] is None:
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_LOGGER.warning("Home %s has no active subscription - price data will be unavailable", home_id)
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return None
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# Extract priceInfoRange data
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subscription = home["currentSubscription"]
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price_info_range = subscription.get("priceInfoRange", {})
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page_info = price_info_range.get("pageInfo", {})
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edges = price_info_range.get("edges", [])
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# Flatten edges to interval list
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intervals = [edge["node"] for edge in edges if "node" in edge]
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return {
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"intervals": intervals,
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"count": page_info.get("count", len(intervals)),
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"end_cursor": page_info.get("endCursor"),
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"has_next_page": page_info.get("hasNextPage", False),
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}
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def _extract_home_timezones(self, user_data: dict[str, Any]) -> dict[str, str]:
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"""
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Extract home_id -> timezone mapping from user_data.
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@ -249,30 +571,30 @@ class TibberPricesApiClient:
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if home_id and timezone:
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home_timezones[home_id] = timezone
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_LOGGER.debug("Extracted timezone %s for home %s", timezone, home_id)
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_LOGGER_API_DETAILS.debug("Extracted timezone %s for home %s", timezone, home_id)
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elif home_id:
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_LOGGER.warning("Home %s has no timezone in user data, will use fallback", home_id)
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return home_timezones
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|
||||
def _calculate_cursor_for_home(self, home_timezone: str | None) -> str:
|
||||
def _calculate_day_before_yesterday_midnight(self, home_timezone: str | None) -> datetime:
|
||||
"""
|
||||
Calculate cursor (day before yesterday midnight) for a home's timezone.
|
||||
Calculate day before yesterday midnight in home's timezone.
|
||||
|
||||
CRITICAL: Uses REAL TIME (dt_utils.now()), NOT TimeService.now().
|
||||
This ensures API boundary calculations are based on actual current time,
|
||||
not simulated time from TimeService.
|
||||
|
||||
Args:
|
||||
home_timezone: Timezone string (e.g., "Europe/Oslo", "America/New_York").
|
||||
home_timezone: Timezone string (e.g., "Europe/Oslo").
|
||||
If None, falls back to HA system timezone.
|
||||
|
||||
Returns:
|
||||
Base64-encoded ISO timestamp string for use as GraphQL cursor.
|
||||
Timezone-aware datetime for day before yesterday midnight.
|
||||
|
||||
"""
|
||||
if not self.time:
|
||||
msg = "TimeService not initialized"
|
||||
raise TibberPricesApiClientError(msg)
|
||||
|
||||
# Get current time
|
||||
now = self.time.now()
|
||||
# Get current REAL time (not TimeService)
|
||||
now = dt_utils.now()
|
||||
|
||||
# Convert to home's timezone or fallback to HA system timezone
|
||||
if home_timezone:
|
||||
|
|
@ -290,15 +612,54 @@ class TibberPricesApiClient:
|
|||
# Fallback to HA system timezone
|
||||
now_in_home_tz = dt_utils.as_local(now)
|
||||
|
||||
# Calculate day before yesterday midnight in home's timezone
|
||||
day_before_yesterday_midnight = (now_in_home_tz - timedelta(days=2)).replace(
|
||||
hour=0, minute=0, second=0, microsecond=0
|
||||
)
|
||||
# Calculate day before yesterday midnight
|
||||
return (now_in_home_tz - timedelta(days=2)).replace(hour=0, minute=0, second=0, microsecond=0)
|
||||
|
||||
# Convert to ISO format and base64 encode
|
||||
iso_string = day_before_yesterday_midnight.isoformat()
|
||||
def _encode_cursor(self, timestamp: datetime) -> str:
|
||||
"""
|
||||
Encode a timestamp as base64 cursor for GraphQL API.
|
||||
|
||||
Args:
|
||||
timestamp: Timezone-aware datetime to encode.
|
||||
|
||||
Returns:
|
||||
Base64-encoded ISO timestamp string.
|
||||
|
||||
"""
|
||||
iso_string = timestamp.isoformat()
|
||||
return base64.b64encode(iso_string.encode()).decode()
|
||||
|
||||
def _parse_timestamp(self, timestamp_str: str) -> datetime:
|
||||
"""
|
||||
Parse ISO timestamp string to timezone-aware datetime.
|
||||
|
||||
Args:
|
||||
timestamp_str: ISO format timestamp string.
|
||||
|
||||
Returns:
|
||||
Timezone-aware datetime object.
|
||||
|
||||
"""
|
||||
return dt_utils.parse_datetime(timestamp_str) or dt_utils.now()
|
||||
|
||||
def _calculate_cursor_for_home(self, home_timezone: str | None) -> str:
|
||||
"""
|
||||
Calculate cursor (day before yesterday midnight) for a home's timezone.
|
||||
|
||||
Convenience wrapper around _calculate_day_before_yesterday_midnight()
|
||||
and _encode_cursor() for backward compatibility with existing code.
|
||||
|
||||
Args:
|
||||
home_timezone: Timezone string (e.g., "Europe/Oslo", "America/New_York").
|
||||
If None, falls back to HA system timezone.
|
||||
|
||||
Returns:
|
||||
Base64-encoded ISO timestamp string for use as GraphQL cursor.
|
||||
|
||||
"""
|
||||
day_before_yesterday_midnight = self._calculate_day_before_yesterday_midnight(home_timezone)
|
||||
return self._encode_cursor(day_before_yesterday_midnight)
|
||||
|
||||
async def _make_request(
|
||||
self,
|
||||
headers: dict[str, str],
|
||||
|
|
@ -306,7 +667,7 @@ class TibberPricesApiClient:
|
|||
query_type: TibberPricesQueryType,
|
||||
) -> dict[str, Any]:
|
||||
"""Make an API request with comprehensive error handling for network issues."""
|
||||
_LOGGER.debug("Making API request with data: %s", data)
|
||||
_LOGGER_API_DETAILS.debug("Making API request with data: %s", data)
|
||||
|
||||
try:
|
||||
# More granular timeout configuration for better network failure handling
|
||||
|
|
@ -326,7 +687,7 @@ class TibberPricesApiClient:
|
|||
|
||||
verify_response_or_raise(response)
|
||||
response_json = await response.json()
|
||||
_LOGGER.debug("Received API response: %s", response_json)
|
||||
_LOGGER_API_DETAILS.debug("Received API response: %s", response_json)
|
||||
|
||||
await verify_graphql_response(response_json, query_type)
|
||||
|
||||
|
|
@ -434,7 +795,7 @@ class TibberPricesApiClient:
|
|||
time_since_last_request = now - self._last_request_time
|
||||
if time_since_last_request < self._min_request_interval:
|
||||
sleep_time = (self._min_request_interval - time_since_last_request).total_seconds()
|
||||
_LOGGER.debug(
|
||||
_LOGGER_API_DETAILS.debug(
|
||||
"Rate limiting: waiting %s seconds before next request",
|
||||
sleep_time,
|
||||
)
|
||||
|
|
@ -480,23 +841,18 @@ class TibberPricesApiClient:
|
|||
"""Handle retry logic for API-specific errors."""
|
||||
error_msg = str(error)
|
||||
|
||||
# Non-retryable: Invalid queries
|
||||
if "Invalid GraphQL query" in error_msg or "Bad request" in error_msg:
|
||||
# Non-retryable: Invalid queries, bad requests, empty data
|
||||
# Empty data means API has no data for the requested range - retrying won't help
|
||||
if "Invalid GraphQL query" in error_msg or "Bad request" in error_msg or "Empty data received" in error_msg:
|
||||
return False, 0
|
||||
|
||||
# Rate limits - special handling with extracted delay
|
||||
# Rate limits - only retry if server explicitly says so
|
||||
if "Rate limit exceeded" in error_msg or "rate limited" in error_msg.lower():
|
||||
delay = self._extract_retry_delay(error, retry)
|
||||
return True, delay
|
||||
|
||||
# Empty data - retryable with capped exponential backoff
|
||||
if "Empty data received" in error_msg:
|
||||
delay = min(self._retry_delay * (2**retry), 60) # Cap at 60 seconds
|
||||
return True, delay
|
||||
|
||||
# Other API errors - retryable with capped exponential backoff
|
||||
delay = min(self._retry_delay * (2**retry), 30) # Cap at 30 seconds
|
||||
return True, delay
|
||||
# Other API errors - not retryable (assume permanent issue)
|
||||
return False, 0
|
||||
|
||||
def _extract_retry_delay(self, error: Exception, retry: int) -> int:
|
||||
"""Extract retry delay from rate limit error or use exponential backoff."""
|
||||
|
|
|
|||
|
|
@ -19,6 +19,7 @@ from .exceptions import (
|
|||
)
|
||||
|
||||
_LOGGER = logging.getLogger(__name__)
|
||||
_LOGGER_DETAILS = logging.getLogger(__name__ + ".details")
|
||||
|
||||
HTTP_BAD_REQUEST = 400
|
||||
HTTP_UNAUTHORIZED = 401
|
||||
|
|
@ -95,14 +96,137 @@ async def verify_graphql_response(response_json: dict, query_type: TibberPricesQ
|
|||
TibberPricesApiClientError.GRAPHQL_ERROR.format(message="Response missing data object")
|
||||
)
|
||||
|
||||
# Empty data check (for retry logic) - always check, regardless of query_type
|
||||
# Empty data check - validate response completeness
|
||||
# This is NOT a retryable error - API simply has no data for the requested range
|
||||
if is_data_empty(response_json["data"], query_type.value):
|
||||
_LOGGER.debug("Empty data detected for query_type: %s", query_type)
|
||||
_LOGGER_DETAILS.debug("Empty data detected for query_type: %s - API has no data available", query_type)
|
||||
raise TibberPricesApiClientError(
|
||||
TibberPricesApiClientError.EMPTY_DATA_ERROR.format(query_type=query_type.value)
|
||||
)
|
||||
|
||||
|
||||
def _check_user_data_empty(data: dict) -> bool:
|
||||
"""Check if user data is empty or incomplete."""
|
||||
has_user_id = (
|
||||
"viewer" in data
|
||||
and isinstance(data["viewer"], dict)
|
||||
and "userId" in data["viewer"]
|
||||
and data["viewer"]["userId"] is not None
|
||||
)
|
||||
has_homes = (
|
||||
"viewer" in data
|
||||
and isinstance(data["viewer"], dict)
|
||||
and "homes" in data["viewer"]
|
||||
and isinstance(data["viewer"]["homes"], list)
|
||||
and len(data["viewer"]["homes"]) > 0
|
||||
)
|
||||
is_empty = not has_user_id or not has_homes
|
||||
_LOGGER_DETAILS.debug(
|
||||
"Viewer check - has_user_id: %s, has_homes: %s, is_empty: %s",
|
||||
has_user_id,
|
||||
has_homes,
|
||||
is_empty,
|
||||
)
|
||||
return is_empty
|
||||
|
||||
|
||||
def _check_price_info_empty(data: dict) -> bool:
|
||||
"""
|
||||
Check if price_info data is empty or incomplete.
|
||||
|
||||
Note: Missing currentSubscription is VALID (home without active contract).
|
||||
Only check for structural issues, not missing data that legitimately might not exist.
|
||||
"""
|
||||
viewer = data.get("viewer", {})
|
||||
home_data = viewer.get("home")
|
||||
|
||||
if not home_data:
|
||||
_LOGGER_DETAILS.debug("No home data found in price_info response")
|
||||
return True
|
||||
|
||||
_LOGGER_DETAILS.debug("Checking price_info for single home")
|
||||
|
||||
# Missing currentSubscription is VALID - home has no active contract
|
||||
# This is not an "empty data" error, it's a legitimate state
|
||||
if "currentSubscription" not in home_data or home_data["currentSubscription"] is None:
|
||||
_LOGGER_DETAILS.debug("No currentSubscription - home has no active contract (valid state)")
|
||||
return False # NOT empty - this is expected for homes without subscription
|
||||
|
||||
subscription = home_data["currentSubscription"]
|
||||
|
||||
# Check priceInfoRange (yesterday data - optional, may not be available)
|
||||
has_yesterday = (
|
||||
"priceInfoRange" in subscription
|
||||
and subscription["priceInfoRange"] is not None
|
||||
and "edges" in subscription["priceInfoRange"]
|
||||
and subscription["priceInfoRange"]["edges"]
|
||||
)
|
||||
|
||||
# Check priceInfo for today's data (required if subscription exists)
|
||||
has_price_info = "priceInfo" in subscription and subscription["priceInfo"] is not None
|
||||
has_today = (
|
||||
has_price_info
|
||||
and "today" in subscription["priceInfo"]
|
||||
and subscription["priceInfo"]["today"] is not None
|
||||
and len(subscription["priceInfo"]["today"]) > 0
|
||||
)
|
||||
|
||||
# Only require today's data - yesterday is optional
|
||||
# If subscription exists but no today data, that's a structural problem
|
||||
is_empty = not has_today
|
||||
|
||||
_LOGGER_DETAILS.debug(
|
||||
"Price info check - priceInfoRange: %s, today: %s, is_empty: %s",
|
||||
bool(has_yesterday),
|
||||
bool(has_today),
|
||||
is_empty,
|
||||
)
|
||||
return is_empty
|
||||
|
||||
|
||||
def _check_price_info_range_empty(data: dict) -> bool:
|
||||
"""
|
||||
Check if price_info_range data is empty or incomplete.
|
||||
|
||||
For historical range queries, empty edges array is VALID (no data available
|
||||
for that time range, e.g., too old). Only structural problems are errors.
|
||||
"""
|
||||
viewer = data.get("viewer", {})
|
||||
home_data = viewer.get("home")
|
||||
|
||||
if not home_data:
|
||||
_LOGGER_DETAILS.debug("No home data found in price_info_range response")
|
||||
return True
|
||||
|
||||
subscription = home_data.get("currentSubscription")
|
||||
if not subscription:
|
||||
_LOGGER_DETAILS.debug("Missing currentSubscription in home")
|
||||
return True
|
||||
|
||||
# For price_info_range, check if the structure exists
|
||||
# Empty edges array is VALID (no data for that time range)
|
||||
price_info_range = subscription.get("priceInfoRange")
|
||||
if price_info_range is None:
|
||||
_LOGGER_DETAILS.debug("Missing priceInfoRange in subscription")
|
||||
return True
|
||||
|
||||
if "edges" not in price_info_range:
|
||||
_LOGGER_DETAILS.debug("Missing edges key in priceInfoRange")
|
||||
return True
|
||||
|
||||
edges = price_info_range["edges"]
|
||||
if not isinstance(edges, list):
|
||||
_LOGGER_DETAILS.debug("priceInfoRange edges is not a list")
|
||||
return True
|
||||
|
||||
# Empty edges is VALID for historical queries (data not available)
|
||||
_LOGGER_DETAILS.debug(
|
||||
"Price info range check - structure valid, edge_count: %s (empty is OK for old data)",
|
||||
len(edges),
|
||||
)
|
||||
return False # Structure is valid, even if edges is empty
|
||||
|
||||
|
||||
def is_data_empty(data: dict, query_type: str) -> bool:
|
||||
"""
|
||||
Check if the response data is empty or incomplete.
|
||||
|
|
@ -117,85 +241,28 @@ def is_data_empty(data: dict, query_type: str) -> bool:
|
|||
- Must have range data
|
||||
- Must have today data
|
||||
- tomorrow can be empty if we have valid historical and today data
|
||||
"""
|
||||
_LOGGER.debug("Checking if data is empty for query_type %s", query_type)
|
||||
|
||||
is_empty = False
|
||||
For price info range:
|
||||
- Must have priceInfoRange with edges
|
||||
Used by interval pool for historical data fetching
|
||||
"""
|
||||
_LOGGER_DETAILS.debug("Checking if data is empty for query_type %s", query_type)
|
||||
|
||||
try:
|
||||
if query_type == "user":
|
||||
has_user_id = (
|
||||
"viewer" in data
|
||||
and isinstance(data["viewer"], dict)
|
||||
and "userId" in data["viewer"]
|
||||
and data["viewer"]["userId"] is not None
|
||||
)
|
||||
has_homes = (
|
||||
"viewer" in data
|
||||
and isinstance(data["viewer"], dict)
|
||||
and "homes" in data["viewer"]
|
||||
and isinstance(data["viewer"]["homes"], list)
|
||||
and len(data["viewer"]["homes"]) > 0
|
||||
)
|
||||
is_empty = not has_user_id or not has_homes
|
||||
_LOGGER.debug(
|
||||
"Viewer check - has_user_id: %s, has_homes: %s, is_empty: %s",
|
||||
has_user_id,
|
||||
has_homes,
|
||||
is_empty,
|
||||
)
|
||||
return _check_user_data_empty(data)
|
||||
if query_type == "price_info":
|
||||
return _check_price_info_empty(data)
|
||||
if query_type == "price_info_range":
|
||||
return _check_price_info_range_empty(data)
|
||||
|
||||
elif query_type == "price_info":
|
||||
# Check for single home data (viewer.home)
|
||||
viewer = data.get("viewer", {})
|
||||
home_data = viewer.get("home")
|
||||
|
||||
if not home_data:
|
||||
_LOGGER.debug("No home data found in price_info response")
|
||||
is_empty = True
|
||||
else:
|
||||
_LOGGER.debug("Checking price_info for single home")
|
||||
|
||||
if not home_data or "currentSubscription" not in home_data or home_data["currentSubscription"] is None:
|
||||
_LOGGER.debug("Missing currentSubscription in home")
|
||||
is_empty = True
|
||||
else:
|
||||
subscription = home_data["currentSubscription"]
|
||||
|
||||
# Check priceInfoRange (96 quarter-hourly intervals)
|
||||
has_yesterday = (
|
||||
"priceInfoRange" in subscription
|
||||
and subscription["priceInfoRange"] is not None
|
||||
and "edges" in subscription["priceInfoRange"]
|
||||
and subscription["priceInfoRange"]["edges"]
|
||||
)
|
||||
|
||||
# Check priceInfo for today's data
|
||||
has_price_info = "priceInfo" in subscription and subscription["priceInfo"] is not None
|
||||
has_today = (
|
||||
has_price_info
|
||||
and "today" in subscription["priceInfo"]
|
||||
and subscription["priceInfo"]["today"] is not None
|
||||
and len(subscription["priceInfo"]["today"]) > 0
|
||||
)
|
||||
|
||||
# Data is empty if we don't have historical data or today's data
|
||||
is_empty = not has_yesterday or not has_today
|
||||
|
||||
_LOGGER.debug(
|
||||
"Price info check - priceInfoRange: %s, today: %s, is_empty: %s",
|
||||
bool(has_yesterday),
|
||||
bool(has_today),
|
||||
is_empty,
|
||||
)
|
||||
|
||||
else:
|
||||
_LOGGER.debug("Unknown query type %s, treating as non-empty", query_type)
|
||||
is_empty = False
|
||||
# Unknown query type
|
||||
_LOGGER_DETAILS.debug("Unknown query type %s, treating as non-empty", query_type)
|
||||
except (KeyError, IndexError, TypeError) as error:
|
||||
_LOGGER.debug("Error checking data emptiness: %s", error)
|
||||
is_empty = True
|
||||
|
||||
return is_empty
|
||||
_LOGGER_DETAILS.debug("Error checking data emptiness: %s", error)
|
||||
return True
|
||||
else:
|
||||
return False
|
||||
|
||||
|
||||
def prepare_headers(access_token: str, version: str) -> dict[str, str]:
|
||||
|
|
|
|||
|
|
@ -19,12 +19,23 @@ class TibberPricesQueryType(Enum):
|
|||
- Provides the core dataset needed for live data, recent historical context
|
||||
(important until tomorrow's data arrives), and tomorrow's forecast
|
||||
- Tibber likely has optimized caching for this frequently-accessed data range
|
||||
- Boundary: FROM "day before yesterday midnight" (real time) onwards
|
||||
|
||||
PRICE_INFO_RANGE:
|
||||
- Used for historical data older than day before yesterday
|
||||
- Allows flexible date range queries with cursor-based pagination
|
||||
- Required for any intervals beyond the 4-day window of PRICE_INFO
|
||||
- Use this for historical analysis, comparisons, or trend calculations
|
||||
- Boundary: BEFORE "day before yesterday midnight" (real time)
|
||||
|
||||
ROUTING:
|
||||
- Use async_get_price_info_for_range() wrapper for automatic routing
|
||||
- Wrapper intelligently splits requests spanning the boundary:
|
||||
* Fully historical range (end < boundary) → PRICE_INFO_RANGE only
|
||||
* Fully recent range (start >= boundary) → PRICE_INFO only
|
||||
* Spanning range → Both queries, merged results
|
||||
- Boundary calculated using REAL TIME (dt_utils.now()), not TimeService
|
||||
to ensure predictable API responses
|
||||
|
||||
USER:
|
||||
- Fetches user account data and home metadata
|
||||
|
|
|
|||
|
|
@ -24,6 +24,11 @@ DATA_CHART_CONFIG = "chart_config" # Key for chart export config in hass.data
|
|||
|
||||
# Configuration keys
|
||||
CONF_EXTENDED_DESCRIPTIONS = "extended_descriptions"
|
||||
CONF_VIRTUAL_TIME_OFFSET_DAYS = (
|
||||
"virtual_time_offset_days" # Time-travel: days offset (negative only, e.g., -7 = 7 days ago)
|
||||
)
|
||||
CONF_VIRTUAL_TIME_OFFSET_HOURS = "virtual_time_offset_hours" # Time-travel: hours offset (-23 to +23)
|
||||
CONF_VIRTUAL_TIME_OFFSET_MINUTES = "virtual_time_offset_minutes" # Time-travel: minutes offset (-59 to +59)
|
||||
CONF_BEST_PRICE_FLEX = "best_price_flex"
|
||||
CONF_PEAK_PRICE_FLEX = "peak_price_flex"
|
||||
CONF_BEST_PRICE_MIN_DISTANCE_FROM_AVG = "best_price_min_distance_from_avg"
|
||||
|
|
@ -54,6 +59,9 @@ ATTRIBUTION = "Data provided by Tibber"
|
|||
# Integration name should match manifest.json
|
||||
DEFAULT_NAME = "Tibber Price Information & Ratings"
|
||||
DEFAULT_EXTENDED_DESCRIPTIONS = False
|
||||
DEFAULT_VIRTUAL_TIME_OFFSET_DAYS = 0 # No time offset (live mode)
|
||||
DEFAULT_VIRTUAL_TIME_OFFSET_HOURS = 0
|
||||
DEFAULT_VIRTUAL_TIME_OFFSET_MINUTES = 0
|
||||
DEFAULT_BEST_PRICE_FLEX = 15 # 15% base flexibility - optimal for relaxation mode (default enabled)
|
||||
# Peak price flexibility is set to -20% (20% base flexibility - optimal for relaxation mode).
|
||||
# This is intentionally more flexible than best price (15%) because peak price periods can be more variable,
|
||||
|
|
|
|||
|
|
@ -163,6 +163,7 @@ class TibberPricesDataUpdateCoordinator(DataUpdateCoordinator[dict[str, Any]]):
|
|||
hass: HomeAssistant,
|
||||
config_entry: ConfigEntry,
|
||||
api_client: TibberPricesApiClient,
|
||||
interval_pool: Any, # TibberPricesIntervalPool - Any to avoid circular import
|
||||
) -> None:
|
||||
"""Initialize the coordinator."""
|
||||
super().__init__(
|
||||
|
|
@ -182,6 +183,9 @@ class TibberPricesDataUpdateCoordinator(DataUpdateCoordinator[dict[str, Any]]):
|
|||
# Use the API client from runtime_data (created in __init__.py with proper TOKEN handling)
|
||||
self.api = api_client
|
||||
|
||||
# Use the shared interval pool (one per config entry/Tibber account)
|
||||
self.interval_pool = interval_pool
|
||||
|
||||
# Storage for persistence
|
||||
storage_key = f"{DOMAIN}.{config_entry.entry_id}"
|
||||
self._store = Store(hass, STORAGE_VERSION, storage_key)
|
||||
|
|
|
|||
|
|
@ -11,6 +11,7 @@ if TYPE_CHECKING:
|
|||
|
||||
from .api import TibberPricesApiClient
|
||||
from .coordinator import TibberPricesDataUpdateCoordinator
|
||||
from .interval_pool import TibberPricesIntervalPool
|
||||
|
||||
|
||||
@dataclass
|
||||
|
|
@ -20,6 +21,7 @@ class TibberPricesData:
|
|||
client: TibberPricesApiClient
|
||||
coordinator: TibberPricesDataUpdateCoordinator
|
||||
integration: Integration
|
||||
interval_pool: TibberPricesIntervalPool # Shared interval pool per config entry
|
||||
|
||||
|
||||
if TYPE_CHECKING:
|
||||
|
|
|
|||
21
custom_components/tibber_prices/interval_pool/__init__.py
Normal file
21
custom_components/tibber_prices/interval_pool/__init__.py
Normal file
|
|
@ -0,0 +1,21 @@
|
|||
"""Interval Pool - Intelligent interval caching and routing."""
|
||||
|
||||
from .manager import TibberPricesIntervalPool
|
||||
from .routing import get_price_intervals_for_range
|
||||
from .storage import (
|
||||
INTERVAL_POOL_STORAGE_VERSION,
|
||||
async_load_pool_state,
|
||||
async_remove_pool_storage,
|
||||
async_save_pool_state,
|
||||
get_storage_key,
|
||||
)
|
||||
|
||||
__all__ = [
|
||||
"INTERVAL_POOL_STORAGE_VERSION",
|
||||
"TibberPricesIntervalPool",
|
||||
"async_load_pool_state",
|
||||
"async_remove_pool_storage",
|
||||
"async_save_pool_state",
|
||||
"get_price_intervals_for_range",
|
||||
"get_storage_key",
|
||||
]
|
||||
194
custom_components/tibber_prices/interval_pool/cache.py
Normal file
194
custom_components/tibber_prices/interval_pool/cache.py
Normal file
|
|
@ -0,0 +1,194 @@
|
|||
"""Fetch group cache for price intervals."""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
from datetime import datetime, timedelta
|
||||
from typing import Any
|
||||
|
||||
from homeassistant.util import dt as dt_utils
|
||||
|
||||
_LOGGER = logging.getLogger(__name__)
|
||||
_LOGGER_DETAILS = logging.getLogger(__name__ + ".details")
|
||||
|
||||
# Protected date range: day-before-yesterday to tomorrow (4 days total)
|
||||
PROTECTED_DAYS_BEFORE = 2 # day-before-yesterday + yesterday
|
||||
PROTECTED_DAYS_AFTER = 1 # tomorrow
|
||||
|
||||
|
||||
class TibberPricesIntervalPoolFetchGroupCache:
|
||||
"""
|
||||
Storage for fetch groups with protected range management.
|
||||
|
||||
A fetch group is a collection of intervals fetched at the same time,
|
||||
stored together with their fetch timestamp for GC purposes.
|
||||
|
||||
Structure:
|
||||
{
|
||||
"fetched_at": datetime, # When this group was fetched
|
||||
"intervals": [dict, ...] # List of interval dicts
|
||||
}
|
||||
|
||||
Protected Range:
|
||||
Intervals within day-before-yesterday to tomorrow are protected
|
||||
and never evicted from cache. This range shifts daily automatically.
|
||||
|
||||
Example (today = 2025-11-25):
|
||||
Protected: 2025-11-23 00:00 to 2025-11-27 00:00
|
||||
"""
|
||||
|
||||
def __init__(self) -> None:
|
||||
"""Initialize empty fetch group cache."""
|
||||
self._fetch_groups: list[dict[str, Any]] = []
|
||||
|
||||
# Protected range cache (invalidated daily)
|
||||
self._protected_range_cache: tuple[str, str] | None = None
|
||||
self._protected_range_cache_date: str | None = None
|
||||
|
||||
def add_fetch_group(
|
||||
self,
|
||||
intervals: list[dict[str, Any]],
|
||||
fetched_at: datetime,
|
||||
) -> int:
|
||||
"""
|
||||
Add new fetch group to cache.
|
||||
|
||||
Args:
|
||||
intervals: List of interval dicts (sorted by startsAt).
|
||||
fetched_at: Timestamp when intervals were fetched.
|
||||
|
||||
Returns:
|
||||
Index of the newly added fetch group.
|
||||
|
||||
"""
|
||||
fetch_group = {
|
||||
"fetched_at": fetched_at,
|
||||
"intervals": intervals,
|
||||
}
|
||||
|
||||
fetch_group_index = len(self._fetch_groups)
|
||||
self._fetch_groups.append(fetch_group)
|
||||
|
||||
_LOGGER_DETAILS.debug(
|
||||
"Added fetch group %d: %d intervals (fetched at %s)",
|
||||
fetch_group_index,
|
||||
len(intervals),
|
||||
fetched_at.isoformat(),
|
||||
)
|
||||
|
||||
return fetch_group_index
|
||||
|
||||
def get_fetch_groups(self) -> list[dict[str, Any]]:
|
||||
"""Get all fetch groups (read-only access)."""
|
||||
return self._fetch_groups
|
||||
|
||||
def set_fetch_groups(self, fetch_groups: list[dict[str, Any]]) -> None:
|
||||
"""Replace all fetch groups (used during GC)."""
|
||||
self._fetch_groups = fetch_groups
|
||||
|
||||
def get_protected_range(self) -> tuple[str, str]:
|
||||
"""
|
||||
Get protected date range as ISO strings.
|
||||
|
||||
Protected range: day-before-yesterday 00:00 to day-after-tomorrow 00:00.
|
||||
This range shifts daily automatically.
|
||||
|
||||
Returns:
|
||||
Tuple of (start_iso, end_iso) for protected range.
|
||||
Start is inclusive, end is exclusive.
|
||||
|
||||
Example (today = 2025-11-25):
|
||||
Returns: ("2025-11-23T00:00:00+01:00", "2025-11-27T00:00:00+01:00")
|
||||
Protected days: 2025-11-23, 2025-11-24, 2025-11-25, 2025-11-26
|
||||
|
||||
"""
|
||||
# Check cache validity (invalidate daily)
|
||||
now = dt_utils.now()
|
||||
today_date_str = now.date().isoformat()
|
||||
|
||||
if self._protected_range_cache_date == today_date_str and self._protected_range_cache:
|
||||
return self._protected_range_cache
|
||||
|
||||
# Calculate new protected range
|
||||
today_midnight = now.replace(hour=0, minute=0, second=0, microsecond=0)
|
||||
|
||||
# Start: day-before-yesterday at 00:00
|
||||
start_dt = today_midnight - timedelta(days=PROTECTED_DAYS_BEFORE)
|
||||
|
||||
# End: day after tomorrow at 00:00 (exclusive, so tomorrow is included)
|
||||
end_dt = today_midnight + timedelta(days=PROTECTED_DAYS_AFTER + 1)
|
||||
|
||||
# Convert to ISO strings and cache
|
||||
start_iso = start_dt.isoformat()
|
||||
end_iso = end_dt.isoformat()
|
||||
|
||||
self._protected_range_cache = (start_iso, end_iso)
|
||||
self._protected_range_cache_date = today_date_str
|
||||
|
||||
return start_iso, end_iso
|
||||
|
||||
def is_interval_protected(self, interval: dict[str, Any]) -> bool:
|
||||
"""
|
||||
Check if interval is within protected date range.
|
||||
|
||||
Protected intervals are never evicted from cache.
|
||||
|
||||
Args:
|
||||
interval: Interval dict with "startsAt" ISO timestamp.
|
||||
|
||||
Returns:
|
||||
True if interval is protected (within protected range).
|
||||
|
||||
"""
|
||||
starts_at_iso = interval["startsAt"]
|
||||
start_protected_iso, end_protected_iso = self.get_protected_range()
|
||||
|
||||
# Fast string comparison (ISO timestamps are lexicographically sortable)
|
||||
return start_protected_iso <= starts_at_iso < end_protected_iso
|
||||
|
||||
def count_total_intervals(self) -> int:
|
||||
"""Count total intervals across all fetch groups."""
|
||||
return sum(len(group["intervals"]) for group in self._fetch_groups)
|
||||
|
||||
def to_dict(self) -> dict[str, Any]:
|
||||
"""
|
||||
Serialize fetch groups for storage.
|
||||
|
||||
Returns:
|
||||
Dict with serializable fetch groups.
|
||||
|
||||
"""
|
||||
return {
|
||||
"fetch_groups": [
|
||||
{
|
||||
"fetched_at": group["fetched_at"].isoformat(),
|
||||
"intervals": group["intervals"],
|
||||
}
|
||||
for group in self._fetch_groups
|
||||
],
|
||||
}
|
||||
|
||||
@classmethod
|
||||
def from_dict(cls, data: dict[str, Any]) -> TibberPricesIntervalPoolFetchGroupCache:
|
||||
"""
|
||||
Restore fetch groups from storage.
|
||||
|
||||
Args:
|
||||
data: Dict with "fetch_groups" list.
|
||||
|
||||
Returns:
|
||||
TibberPricesIntervalPoolFetchGroupCache instance with restored data.
|
||||
|
||||
"""
|
||||
cache = cls()
|
||||
|
||||
fetch_groups_data = data.get("fetch_groups", [])
|
||||
cache._fetch_groups = [
|
||||
{
|
||||
"fetched_at": datetime.fromisoformat(group["fetched_at"]),
|
||||
"intervals": group["intervals"],
|
||||
}
|
||||
for group in fetch_groups_data
|
||||
]
|
||||
|
||||
return cache
|
||||
322
custom_components/tibber_prices/interval_pool/fetcher.py
Normal file
322
custom_components/tibber_prices/interval_pool/fetcher.py
Normal file
|
|
@ -0,0 +1,322 @@
|
|||
"""Interval fetcher - gap detection and API coordination for interval pool."""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
from datetime import UTC, datetime, timedelta
|
||||
from typing import TYPE_CHECKING, Any
|
||||
|
||||
from homeassistant.util import dt as dt_utils
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from collections.abc import Callable
|
||||
|
||||
from custom_components.tibber_prices.api import TibberPricesApiClient
|
||||
|
||||
from .cache import TibberPricesIntervalPoolFetchGroupCache
|
||||
from .index import TibberPricesIntervalPoolTimestampIndex
|
||||
|
||||
_LOGGER = logging.getLogger(__name__)
|
||||
_LOGGER_DETAILS = logging.getLogger(__name__ + ".details")
|
||||
|
||||
# Resolution change date (hourly before, quarter-hourly after)
|
||||
# Use UTC for constant - timezone adjusted at runtime when comparing
|
||||
RESOLUTION_CHANGE_DATETIME = datetime(2025, 10, 1, tzinfo=UTC)
|
||||
RESOLUTION_CHANGE_ISO = "2025-10-01T00:00:00"
|
||||
|
||||
# Interval lengths in minutes
|
||||
INTERVAL_HOURLY = 60
|
||||
INTERVAL_QUARTER_HOURLY = 15
|
||||
|
||||
# Minimum gap sizes in seconds
|
||||
MIN_GAP_HOURLY = 3600 # 1 hour
|
||||
MIN_GAP_QUARTER_HOURLY = 900 # 15 minutes
|
||||
|
||||
# Tolerance for time comparisons (±1 second for floating point/timezone issues)
|
||||
TIME_TOLERANCE_SECONDS = 1
|
||||
TIME_TOLERANCE_MINUTES = 1
|
||||
|
||||
|
||||
class TibberPricesIntervalPoolFetcher:
|
||||
"""Fetch missing intervals from API based on gap detection."""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
api: TibberPricesApiClient,
|
||||
cache: TibberPricesIntervalPoolFetchGroupCache,
|
||||
index: TibberPricesIntervalPoolTimestampIndex,
|
||||
home_id: str,
|
||||
) -> None:
|
||||
"""
|
||||
Initialize fetcher.
|
||||
|
||||
Args:
|
||||
api: API client for Tibber GraphQL queries.
|
||||
cache: Fetch group cache for storage operations.
|
||||
index: Timestamp index for gap detection.
|
||||
home_id: Tibber home ID for API calls.
|
||||
|
||||
"""
|
||||
self._api = api
|
||||
self._cache = cache
|
||||
self._index = index
|
||||
self._home_id = home_id
|
||||
|
||||
def detect_gaps(
|
||||
self,
|
||||
cached_intervals: list[dict[str, Any]],
|
||||
start_time_iso: str,
|
||||
end_time_iso: str,
|
||||
) -> list[tuple[str, str]]:
|
||||
"""
|
||||
Detect missing time ranges that need to be fetched.
|
||||
|
||||
This method minimizes API calls by:
|
||||
1. Finding all gaps in cached intervals
|
||||
2. Treating each cached interval as a discrete timestamp
|
||||
3. Gaps are time ranges between consecutive cached timestamps
|
||||
|
||||
Handles both resolutions:
|
||||
- Pre-2025-10-01: Hourly intervals (:00:00 only)
|
||||
- Post-2025-10-01: Quarter-hourly intervals (:00:00, :15:00, :30:00, :45:00)
|
||||
- DST transitions (23h/25h days)
|
||||
|
||||
The API requires an interval count (first: X parameter).
|
||||
For historical data (pre-2025-10-01), Tibber only stored hourly prices.
|
||||
The API returns whatever intervals exist for the requested period.
|
||||
|
||||
Args:
|
||||
cached_intervals: List of cached intervals (may be empty).
|
||||
start_time_iso: ISO timestamp string (inclusive).
|
||||
end_time_iso: ISO timestamp string (exclusive).
|
||||
|
||||
Returns:
|
||||
List of (start_iso, end_iso) tuples representing missing ranges.
|
||||
Each tuple represents a continuous time span that needs fetching.
|
||||
Ranges are automatically split at resolution change boundary.
|
||||
|
||||
Example:
|
||||
Requested: 2025-11-13T00:00:00 to 2025-11-13T02:00:00
|
||||
Cached: [00:00, 00:15, 01:30, 01:45]
|
||||
Gaps: [(00:15, 01:30)] - missing intervals between groups
|
||||
|
||||
"""
|
||||
if not cached_intervals:
|
||||
# No cache → fetch entire range
|
||||
return [(start_time_iso, end_time_iso)]
|
||||
|
||||
# Filter and sort cached intervals within requested range
|
||||
in_range_intervals = [
|
||||
interval for interval in cached_intervals if start_time_iso <= interval["startsAt"] < end_time_iso
|
||||
]
|
||||
sorted_intervals = sorted(in_range_intervals, key=lambda x: x["startsAt"])
|
||||
|
||||
if not sorted_intervals:
|
||||
# All cached intervals are outside requested range
|
||||
return [(start_time_iso, end_time_iso)]
|
||||
|
||||
missing_ranges = []
|
||||
|
||||
# Parse start/end times once
|
||||
start_time_dt = datetime.fromisoformat(start_time_iso)
|
||||
end_time_dt = datetime.fromisoformat(end_time_iso)
|
||||
|
||||
# Get first cached interval datetime for resolution logic
|
||||
first_cached_dt = datetime.fromisoformat(sorted_intervals[0]["startsAt"])
|
||||
resolution_change_dt = RESOLUTION_CHANGE_DATETIME.replace(tzinfo=first_cached_dt.tzinfo)
|
||||
|
||||
# Check gap before first cached interval
|
||||
time_diff_before_first = (first_cached_dt - start_time_dt).total_seconds()
|
||||
if time_diff_before_first > TIME_TOLERANCE_SECONDS:
|
||||
missing_ranges.append((start_time_iso, sorted_intervals[0]["startsAt"]))
|
||||
_LOGGER_DETAILS.debug(
|
||||
"Gap before first cached interval: %s to %s (%.1f seconds)",
|
||||
start_time_iso,
|
||||
sorted_intervals[0]["startsAt"],
|
||||
time_diff_before_first,
|
||||
)
|
||||
|
||||
# Check gaps between consecutive cached intervals
|
||||
for i in range(len(sorted_intervals) - 1):
|
||||
current_interval = sorted_intervals[i]
|
||||
next_interval = sorted_intervals[i + 1]
|
||||
|
||||
current_start = current_interval["startsAt"]
|
||||
next_start = next_interval["startsAt"]
|
||||
|
||||
# Parse to datetime for accurate time difference
|
||||
current_dt = datetime.fromisoformat(current_start)
|
||||
next_dt = datetime.fromisoformat(next_start)
|
||||
|
||||
# Calculate time difference in minutes
|
||||
time_diff_minutes = (next_dt - current_dt).total_seconds() / 60
|
||||
|
||||
# Determine expected interval length based on date
|
||||
expected_interval_minutes = (
|
||||
INTERVAL_HOURLY if current_dt < resolution_change_dt else INTERVAL_QUARTER_HOURLY
|
||||
)
|
||||
|
||||
# Only create gap if intervals are NOT consecutive
|
||||
if time_diff_minutes > expected_interval_minutes + TIME_TOLERANCE_MINUTES:
|
||||
# Gap exists - missing intervals between them
|
||||
# Missing range starts AFTER current interval ends
|
||||
current_interval_end = current_dt + timedelta(minutes=expected_interval_minutes)
|
||||
missing_ranges.append((current_interval_end.isoformat(), next_start))
|
||||
_LOGGER_DETAILS.debug(
|
||||
"Gap between cached intervals: %s (ends at %s) to %s (%.1f min gap, expected %d min)",
|
||||
current_start,
|
||||
current_interval_end.isoformat(),
|
||||
next_start,
|
||||
time_diff_minutes,
|
||||
expected_interval_minutes,
|
||||
)
|
||||
|
||||
# Check gap after last cached interval
|
||||
# An interval's startsAt time represents the START of that interval.
|
||||
# The interval covers [startsAt, startsAt + interval_length).
|
||||
# So the last interval ENDS at (startsAt + interval_length), not at startsAt!
|
||||
last_cached_dt = datetime.fromisoformat(sorted_intervals[-1]["startsAt"])
|
||||
|
||||
# Calculate when the last interval ENDS
|
||||
interval_minutes = INTERVAL_QUARTER_HOURLY if last_cached_dt >= resolution_change_dt else INTERVAL_HOURLY
|
||||
last_interval_end_dt = last_cached_dt + timedelta(minutes=interval_minutes)
|
||||
|
||||
# Only create gap if there's uncovered time AFTER the last interval ends
|
||||
time_diff_after_last = (end_time_dt - last_interval_end_dt).total_seconds()
|
||||
|
||||
# Need at least one full interval of gap
|
||||
min_gap_seconds = MIN_GAP_QUARTER_HOURLY if last_cached_dt >= resolution_change_dt else MIN_GAP_HOURLY
|
||||
if time_diff_after_last >= min_gap_seconds:
|
||||
# Missing range starts AFTER the last cached interval ends
|
||||
missing_ranges.append((last_interval_end_dt.isoformat(), end_time_iso))
|
||||
_LOGGER_DETAILS.debug(
|
||||
"Gap after last cached interval: %s (ends at %s) to %s (%.1f seconds, need >= %d)",
|
||||
sorted_intervals[-1]["startsAt"],
|
||||
last_interval_end_dt.isoformat(),
|
||||
end_time_iso,
|
||||
time_diff_after_last,
|
||||
min_gap_seconds,
|
||||
)
|
||||
|
||||
if not missing_ranges:
|
||||
_LOGGER.debug(
|
||||
"No gaps detected - all intervals cached for range %s to %s",
|
||||
start_time_iso,
|
||||
end_time_iso,
|
||||
)
|
||||
return missing_ranges
|
||||
|
||||
# Split ranges at resolution change boundary (2025-10-01 00:00:00)
|
||||
# This simplifies interval count calculation in API calls:
|
||||
# - Pre-2025-10-01: Always hourly (1 interval/hour)
|
||||
# - Post-2025-10-01: Always quarter-hourly (4 intervals/hour)
|
||||
return self._split_at_resolution_boundary(missing_ranges)
|
||||
|
||||
def _split_at_resolution_boundary(self, ranges: list[tuple[str, str]]) -> list[tuple[str, str]]:
|
||||
"""
|
||||
Split time ranges at resolution change boundary.
|
||||
|
||||
Args:
|
||||
ranges: List of (start_iso, end_iso) tuples.
|
||||
|
||||
Returns:
|
||||
List of ranges split at 2025-10-01T00:00:00 boundary.
|
||||
|
||||
"""
|
||||
split_ranges = []
|
||||
|
||||
for start_iso, end_iso in ranges:
|
||||
# Check if range crosses the boundary
|
||||
if start_iso < RESOLUTION_CHANGE_ISO < end_iso:
|
||||
# Split into two ranges: before and after boundary
|
||||
split_ranges.append((start_iso, RESOLUTION_CHANGE_ISO))
|
||||
split_ranges.append((RESOLUTION_CHANGE_ISO, end_iso))
|
||||
_LOGGER_DETAILS.debug(
|
||||
"Split range at resolution boundary: (%s, %s) → (%s, %s) + (%s, %s)",
|
||||
start_iso,
|
||||
end_iso,
|
||||
start_iso,
|
||||
RESOLUTION_CHANGE_ISO,
|
||||
RESOLUTION_CHANGE_ISO,
|
||||
end_iso,
|
||||
)
|
||||
else:
|
||||
# Range doesn't cross boundary - keep as is
|
||||
split_ranges.append((start_iso, end_iso))
|
||||
|
||||
return split_ranges
|
||||
|
||||
async def fetch_missing_ranges(
|
||||
self,
|
||||
api_client: TibberPricesApiClient,
|
||||
user_data: dict[str, Any],
|
||||
missing_ranges: list[tuple[str, str]],
|
||||
*,
|
||||
on_intervals_fetched: Callable[[list[dict[str, Any]], str], None] | None = None,
|
||||
) -> list[list[dict[str, Any]]]:
|
||||
"""
|
||||
Fetch missing intervals from API.
|
||||
|
||||
Makes one API call per missing range. Uses routing logic to select
|
||||
the optimal endpoint (PRICE_INFO vs PRICE_INFO_RANGE).
|
||||
|
||||
Args:
|
||||
api_client: TibberPricesApiClient instance for API calls.
|
||||
user_data: User data dict containing home metadata.
|
||||
missing_ranges: List of (start_iso, end_iso) tuples to fetch.
|
||||
on_intervals_fetched: Optional callback for each fetch result.
|
||||
Receives (intervals, fetch_time_iso).
|
||||
|
||||
Returns:
|
||||
List of interval lists (one per missing range).
|
||||
Each sublist contains intervals from one API call.
|
||||
|
||||
Raises:
|
||||
TibberPricesApiClientError: If API calls fail.
|
||||
|
||||
"""
|
||||
# Import here to avoid circular dependency
|
||||
from custom_components.tibber_prices.interval_pool.routing import ( # noqa: PLC0415
|
||||
get_price_intervals_for_range,
|
||||
)
|
||||
|
||||
fetch_time_iso = dt_utils.now().isoformat()
|
||||
all_fetched_intervals = []
|
||||
|
||||
for idx, (missing_start_iso, missing_end_iso) in enumerate(missing_ranges, start=1):
|
||||
_LOGGER_DETAILS.debug(
|
||||
"API call %d/%d for home %s: fetching range %s to %s",
|
||||
idx,
|
||||
len(missing_ranges),
|
||||
self._home_id,
|
||||
missing_start_iso,
|
||||
missing_end_iso,
|
||||
)
|
||||
|
||||
# Parse ISO strings back to datetime for API call
|
||||
missing_start_dt = datetime.fromisoformat(missing_start_iso)
|
||||
missing_end_dt = datetime.fromisoformat(missing_end_iso)
|
||||
|
||||
# Fetch intervals from API - routing returns ALL intervals (unfiltered)
|
||||
fetched_intervals = await get_price_intervals_for_range(
|
||||
api_client=api_client,
|
||||
home_id=self._home_id,
|
||||
user_data=user_data,
|
||||
start_time=missing_start_dt,
|
||||
end_time=missing_end_dt,
|
||||
)
|
||||
|
||||
all_fetched_intervals.append(fetched_intervals)
|
||||
|
||||
_LOGGER_DETAILS.debug(
|
||||
"Fetched %d intervals from API for home %s (fetch time: %s)",
|
||||
len(fetched_intervals),
|
||||
self._home_id,
|
||||
fetch_time_iso,
|
||||
)
|
||||
|
||||
# Notify callback if provided (for immediate caching)
|
||||
if on_intervals_fetched:
|
||||
on_intervals_fetched(fetched_intervals, fetch_time_iso)
|
||||
|
||||
return all_fetched_intervals
|
||||
|
|
@ -0,0 +1,237 @@
|
|||
"""Garbage collector for interval cache eviction."""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
from typing import TYPE_CHECKING, Any
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from .cache import TibberPricesIntervalPoolFetchGroupCache
|
||||
from .index import TibberPricesIntervalPoolTimestampIndex
|
||||
|
||||
_LOGGER = logging.getLogger(__name__)
|
||||
_LOGGER_DETAILS = logging.getLogger(__name__ + ".details")
|
||||
|
||||
# Maximum number of intervals to cache
|
||||
# 1 days @ 15min resolution = 10 * 96 = 960 intervals
|
||||
MAX_CACHE_SIZE = 960
|
||||
|
||||
|
||||
class TibberPricesIntervalPoolGarbageCollector:
|
||||
"""
|
||||
Manages cache eviction and dead interval cleanup.
|
||||
|
||||
Eviction Strategy:
|
||||
- Evict oldest fetch groups first (by fetched_at timestamp)
|
||||
- Protected intervals (day-before-yesterday to tomorrow) are NEVER evicted
|
||||
- Evict complete fetch groups, not individual intervals
|
||||
|
||||
Dead Interval Cleanup:
|
||||
When intervals are "touched" (re-fetched), they move to a new fetch group
|
||||
but remain in the old group. This creates "dead intervals" that occupy
|
||||
memory but are no longer referenced by the index.
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
cache: TibberPricesIntervalPoolFetchGroupCache,
|
||||
index: TibberPricesIntervalPoolTimestampIndex,
|
||||
home_id: str,
|
||||
) -> None:
|
||||
"""
|
||||
Initialize garbage collector.
|
||||
|
||||
Args:
|
||||
home_id: Home ID for logging purposes.
|
||||
cache: Fetch group cache to manage.
|
||||
index: Timestamp index for living interval detection.
|
||||
|
||||
"""
|
||||
self._home_id = home_id
|
||||
self._cache = cache
|
||||
self._index = index
|
||||
|
||||
def run_gc(self) -> bool:
|
||||
"""
|
||||
Run garbage collection if needed.
|
||||
|
||||
Process:
|
||||
1. Clean up dead intervals from all fetch groups
|
||||
2. Count total intervals
|
||||
3. If > MAX_CACHE_SIZE, evict oldest fetch groups
|
||||
4. Rebuild index after eviction
|
||||
|
||||
Returns:
|
||||
True if any cleanup or eviction happened, False otherwise.
|
||||
|
||||
"""
|
||||
fetch_groups = self._cache.get_fetch_groups()
|
||||
|
||||
# Phase 1: Clean up dead intervals
|
||||
dead_count = self._cleanup_dead_intervals(fetch_groups)
|
||||
|
||||
if dead_count > 0:
|
||||
_LOGGER_DETAILS.debug(
|
||||
"GC cleaned %d dead intervals (home %s)",
|
||||
dead_count,
|
||||
self._home_id,
|
||||
)
|
||||
|
||||
# Phase 2: Count total intervals after cleanup
|
||||
total_intervals = self._cache.count_total_intervals()
|
||||
|
||||
if total_intervals <= MAX_CACHE_SIZE:
|
||||
_LOGGER_DETAILS.debug(
|
||||
"GC cleanup only for home %s: %d intervals <= %d limit (no eviction needed)",
|
||||
self._home_id,
|
||||
total_intervals,
|
||||
MAX_CACHE_SIZE,
|
||||
)
|
||||
return dead_count > 0
|
||||
|
||||
# Phase 3: Evict old fetch groups
|
||||
evicted_indices = self._evict_old_groups(fetch_groups, total_intervals)
|
||||
|
||||
if not evicted_indices:
|
||||
# All intervals are protected, cannot evict
|
||||
return dead_count > 0
|
||||
|
||||
# Phase 4: Rebuild cache and index
|
||||
new_fetch_groups = [group for idx, group in enumerate(fetch_groups) if idx not in evicted_indices]
|
||||
self._cache.set_fetch_groups(new_fetch_groups)
|
||||
self._index.rebuild(new_fetch_groups)
|
||||
|
||||
_LOGGER_DETAILS.debug(
|
||||
"GC evicted %d fetch groups (home %s): %d intervals remaining",
|
||||
len(evicted_indices),
|
||||
self._home_id,
|
||||
self._cache.count_total_intervals(),
|
||||
)
|
||||
|
||||
return True
|
||||
|
||||
def _cleanup_dead_intervals(self, fetch_groups: list[dict[str, Any]]) -> int:
|
||||
"""
|
||||
Remove dead intervals from all fetch groups.
|
||||
|
||||
Dead intervals are no longer referenced by the index (they were touched
|
||||
and moved to a newer fetch group).
|
||||
|
||||
Args:
|
||||
fetch_groups: List of fetch groups to clean.
|
||||
|
||||
Returns:
|
||||
Total number of dead intervals removed.
|
||||
|
||||
"""
|
||||
total_dead = 0
|
||||
|
||||
for group_idx, group in enumerate(fetch_groups):
|
||||
old_intervals = group["intervals"]
|
||||
if not old_intervals:
|
||||
continue
|
||||
|
||||
# Find living intervals (still in index at correct position)
|
||||
living_intervals = []
|
||||
|
||||
for interval_idx, interval in enumerate(old_intervals):
|
||||
starts_at_normalized = interval["startsAt"][:19]
|
||||
index_entry = self._index.get(starts_at_normalized)
|
||||
|
||||
if index_entry is not None:
|
||||
# Check if index points to THIS position
|
||||
if index_entry["fetch_group_index"] == group_idx and index_entry["interval_index"] == interval_idx:
|
||||
living_intervals.append(interval)
|
||||
else:
|
||||
# Dead: index points elsewhere
|
||||
total_dead += 1
|
||||
else:
|
||||
# Dead: not in index
|
||||
total_dead += 1
|
||||
|
||||
# Replace with cleaned list if any dead intervals found
|
||||
if len(living_intervals) < len(old_intervals):
|
||||
group["intervals"] = living_intervals
|
||||
dead_count = len(old_intervals) - len(living_intervals)
|
||||
_LOGGER_DETAILS.debug(
|
||||
"GC cleaned %d dead intervals from fetch group %d (home %s)",
|
||||
dead_count,
|
||||
group_idx,
|
||||
self._home_id,
|
||||
)
|
||||
|
||||
return total_dead
|
||||
|
||||
def _evict_old_groups(
|
||||
self,
|
||||
fetch_groups: list[dict[str, Any]],
|
||||
total_intervals: int,
|
||||
) -> set[int]:
|
||||
"""
|
||||
Determine which fetch groups to evict to stay under MAX_CACHE_SIZE.
|
||||
|
||||
Only evicts groups without protected intervals.
|
||||
Groups evicted oldest-first (by fetched_at).
|
||||
|
||||
Args:
|
||||
fetch_groups: List of fetch groups.
|
||||
total_intervals: Total interval count.
|
||||
|
||||
Returns:
|
||||
Set of fetch group indices to evict.
|
||||
|
||||
"""
|
||||
start_protected_iso, end_protected_iso = self._cache.get_protected_range()
|
||||
|
||||
_LOGGER_DETAILS.debug(
|
||||
"Protected range: %s to %s",
|
||||
start_protected_iso[:10],
|
||||
end_protected_iso[:10],
|
||||
)
|
||||
|
||||
# Classify: protected vs evictable
|
||||
evictable_groups = []
|
||||
|
||||
for idx, group in enumerate(fetch_groups):
|
||||
has_protected = any(self._cache.is_interval_protected(interval) for interval in group["intervals"])
|
||||
|
||||
if not has_protected:
|
||||
evictable_groups.append((idx, group))
|
||||
|
||||
# Sort by fetched_at (oldest first)
|
||||
evictable_groups.sort(key=lambda x: x[1]["fetched_at"])
|
||||
|
||||
_LOGGER_DETAILS.debug(
|
||||
"GC: %d protected groups, %d evictable groups",
|
||||
len(fetch_groups) - len(evictable_groups),
|
||||
len(evictable_groups),
|
||||
)
|
||||
|
||||
# Evict until under limit
|
||||
evicted_indices = set()
|
||||
remaining = total_intervals
|
||||
|
||||
for idx, group in evictable_groups:
|
||||
if remaining <= MAX_CACHE_SIZE:
|
||||
break
|
||||
|
||||
group_count = len(group["intervals"])
|
||||
evicted_indices.add(idx)
|
||||
remaining -= group_count
|
||||
|
||||
_LOGGER_DETAILS.debug(
|
||||
"GC evicting group %d (fetched %s): %d intervals, %d remaining",
|
||||
idx,
|
||||
group["fetched_at"].isoformat(),
|
||||
group_count,
|
||||
remaining,
|
||||
)
|
||||
|
||||
if not evicted_indices:
|
||||
_LOGGER.warning(
|
||||
"GC cannot evict any groups (home %s): all %d intervals are protected",
|
||||
self._home_id,
|
||||
total_intervals,
|
||||
)
|
||||
|
||||
return evicted_indices
|
||||
151
custom_components/tibber_prices/interval_pool/index.py
Normal file
151
custom_components/tibber_prices/interval_pool/index.py
Normal file
|
|
@ -0,0 +1,151 @@
|
|||
"""Timestamp index for O(1) interval lookups."""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
from typing import Any
|
||||
|
||||
_LOGGER = logging.getLogger(__name__)
|
||||
_LOGGER_DETAILS = logging.getLogger(__name__ + ".details")
|
||||
|
||||
|
||||
class TibberPricesIntervalPoolTimestampIndex:
|
||||
"""
|
||||
Fast O(1) timestamp-based interval lookup.
|
||||
|
||||
Maps normalized ISO timestamp strings to fetch group + interval indices.
|
||||
|
||||
Structure:
|
||||
{
|
||||
"2025-11-25T00:00:00": {
|
||||
"fetch_group_index": 0, # Index in fetch groups list
|
||||
"interval_index": 2 # Index within that group's intervals
|
||||
},
|
||||
...
|
||||
}
|
||||
|
||||
Normalization:
|
||||
Timestamps are normalized to 19 characters (YYYY-MM-DDTHH:MM:SS)
|
||||
by truncating microseconds and timezone info for fast string comparison.
|
||||
"""
|
||||
|
||||
def __init__(self) -> None:
|
||||
"""Initialize empty timestamp index."""
|
||||
self._index: dict[str, dict[str, int]] = {}
|
||||
|
||||
def add(
|
||||
self,
|
||||
interval: dict[str, Any],
|
||||
fetch_group_index: int,
|
||||
interval_index: int,
|
||||
) -> None:
|
||||
"""
|
||||
Add interval to index.
|
||||
|
||||
Args:
|
||||
interval: Interval dict with "startsAt" ISO timestamp.
|
||||
fetch_group_index: Index of fetch group containing this interval.
|
||||
interval_index: Index within that fetch group's intervals list.
|
||||
|
||||
"""
|
||||
starts_at_normalized = self._normalize_timestamp(interval["startsAt"])
|
||||
self._index[starts_at_normalized] = {
|
||||
"fetch_group_index": fetch_group_index,
|
||||
"interval_index": interval_index,
|
||||
}
|
||||
|
||||
def get(self, timestamp: str) -> dict[str, int] | None:
|
||||
"""
|
||||
Look up interval location by timestamp.
|
||||
|
||||
Args:
|
||||
timestamp: ISO timestamp string (will be normalized).
|
||||
|
||||
Returns:
|
||||
Dict with fetch_group_index and interval_index, or None if not found.
|
||||
|
||||
"""
|
||||
starts_at_normalized = self._normalize_timestamp(timestamp)
|
||||
return self._index.get(starts_at_normalized)
|
||||
|
||||
def contains(self, timestamp: str) -> bool:
|
||||
"""
|
||||
Check if timestamp exists in index.
|
||||
|
||||
Args:
|
||||
timestamp: ISO timestamp string (will be normalized).
|
||||
|
||||
Returns:
|
||||
True if timestamp is in index.
|
||||
|
||||
"""
|
||||
starts_at_normalized = self._normalize_timestamp(timestamp)
|
||||
return starts_at_normalized in self._index
|
||||
|
||||
def remove(self, timestamp: str) -> None:
|
||||
"""
|
||||
Remove timestamp from index.
|
||||
|
||||
Args:
|
||||
timestamp: ISO timestamp string (will be normalized).
|
||||
|
||||
"""
|
||||
starts_at_normalized = self._normalize_timestamp(timestamp)
|
||||
self._index.pop(starts_at_normalized, None)
|
||||
|
||||
def clear(self) -> None:
|
||||
"""Clear entire index."""
|
||||
self._index.clear()
|
||||
|
||||
def rebuild(self, fetch_groups: list[dict[str, Any]]) -> None:
|
||||
"""
|
||||
Rebuild index from fetch groups.
|
||||
|
||||
Used after GC operations that modify fetch group structure.
|
||||
|
||||
Args:
|
||||
fetch_groups: List of fetch group dicts.
|
||||
|
||||
"""
|
||||
self._index.clear()
|
||||
|
||||
for fetch_group_idx, group in enumerate(fetch_groups):
|
||||
for interval_idx, interval in enumerate(group["intervals"]):
|
||||
starts_at_normalized = self._normalize_timestamp(interval["startsAt"])
|
||||
self._index[starts_at_normalized] = {
|
||||
"fetch_group_index": fetch_group_idx,
|
||||
"interval_index": interval_idx,
|
||||
}
|
||||
|
||||
_LOGGER_DETAILS.debug(
|
||||
"Rebuilt index: %d timestamps indexed",
|
||||
len(self._index),
|
||||
)
|
||||
|
||||
def get_raw_index(self) -> dict[str, dict[str, int]]:
|
||||
"""Get raw index dict (for serialization)."""
|
||||
return self._index
|
||||
|
||||
def count(self) -> int:
|
||||
"""Count total indexed timestamps."""
|
||||
return len(self._index)
|
||||
|
||||
@staticmethod
|
||||
def _normalize_timestamp(timestamp: str) -> str:
|
||||
"""
|
||||
Normalize ISO timestamp for indexing.
|
||||
|
||||
Truncates to 19 characters (YYYY-MM-DDTHH:MM:SS) to remove
|
||||
microseconds and timezone info for consistent string comparison.
|
||||
|
||||
Args:
|
||||
timestamp: Full ISO timestamp string.
|
||||
|
||||
Returns:
|
||||
Normalized timestamp (19 chars).
|
||||
|
||||
Example:
|
||||
"2025-11-25T00:00:00.000+01:00" → "2025-11-25T00:00:00"
|
||||
|
||||
"""
|
||||
return timestamp[:19]
|
||||
539
custom_components/tibber_prices/interval_pool/manager.py
Normal file
539
custom_components/tibber_prices/interval_pool/manager.py
Normal file
|
|
@ -0,0 +1,539 @@
|
|||
"""Interval pool manager - main coordinator for interval caching."""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import asyncio
|
||||
import logging
|
||||
from datetime import datetime, timedelta
|
||||
from typing import TYPE_CHECKING, Any
|
||||
|
||||
from custom_components.tibber_prices.api.exceptions import TibberPricesApiClientError
|
||||
from homeassistant.util import dt as dt_utils
|
||||
|
||||
from .cache import TibberPricesIntervalPoolFetchGroupCache
|
||||
from .fetcher import TibberPricesIntervalPoolFetcher
|
||||
from .garbage_collector import TibberPricesIntervalPoolGarbageCollector
|
||||
from .index import TibberPricesIntervalPoolTimestampIndex
|
||||
from .storage import async_save_pool_state
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from custom_components.tibber_prices.api.client import TibberPricesApiClient
|
||||
|
||||
_LOGGER = logging.getLogger(__name__)
|
||||
_LOGGER_DETAILS = logging.getLogger(__name__ + ".details")
|
||||
|
||||
# Interval lengths in minutes
|
||||
INTERVAL_HOURLY = 60
|
||||
INTERVAL_QUARTER_HOURLY = 15
|
||||
|
||||
# Debounce delay for auto-save (seconds)
|
||||
DEBOUNCE_DELAY_SECONDS = 3.0
|
||||
|
||||
|
||||
class TibberPricesIntervalPool:
|
||||
"""
|
||||
High-performance interval cache manager for a single Tibber home.
|
||||
|
||||
Coordinates all interval pool components:
|
||||
- TibberPricesIntervalPoolFetchGroupCache: Stores fetch groups and manages protected ranges
|
||||
- TibberPricesIntervalPoolTimestampIndex: Provides O(1) timestamp lookups
|
||||
- TibberPricesIntervalPoolGarbageCollector: Evicts old fetch groups when cache exceeds limits
|
||||
- TibberPricesIntervalPoolFetcher: Detects gaps and fetches missing intervals from API
|
||||
|
||||
Architecture:
|
||||
- Each manager handles exactly ONE home (1:1 with config entry)
|
||||
- home_id is immutable after initialization
|
||||
- All operations are thread-safe via asyncio locks
|
||||
|
||||
Features:
|
||||
- Fetch-time based eviction (oldest fetch groups removed first)
|
||||
- Protected date range (day-before-yesterday to tomorrow never evicted)
|
||||
- Fast O(1) lookups by timestamp
|
||||
- Automatic gap detection and API fetching
|
||||
- Debounced auto-save to prevent excessive I/O
|
||||
|
||||
Example:
|
||||
manager = TibberPricesIntervalPool(home_id="abc123", hass=hass, entry_id=entry.entry_id)
|
||||
intervals = await manager.get_intervals(
|
||||
api_client=client,
|
||||
user_data=data,
|
||||
start_time=datetime(...),
|
||||
end_time=datetime(...),
|
||||
)
|
||||
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
*,
|
||||
home_id: str,
|
||||
api: TibberPricesApiClient,
|
||||
hass: Any | None = None,
|
||||
entry_id: str | None = None,
|
||||
) -> None:
|
||||
"""
|
||||
Initialize interval pool manager.
|
||||
|
||||
Args:
|
||||
home_id: Tibber home ID (required, immutable).
|
||||
api: API client for fetching intervals.
|
||||
hass: HomeAssistant instance for auto-save (optional).
|
||||
entry_id: Config entry ID for auto-save (optional).
|
||||
|
||||
"""
|
||||
self._home_id = home_id
|
||||
|
||||
# Initialize components with dependency injection
|
||||
self._cache = TibberPricesIntervalPoolFetchGroupCache()
|
||||
self._index = TibberPricesIntervalPoolTimestampIndex()
|
||||
self._gc = TibberPricesIntervalPoolGarbageCollector(self._cache, self._index, home_id)
|
||||
self._fetcher = TibberPricesIntervalPoolFetcher(api, self._cache, self._index, home_id)
|
||||
|
||||
# Auto-save support
|
||||
self._hass = hass
|
||||
self._entry_id = entry_id
|
||||
self._background_tasks: set[asyncio.Task] = set()
|
||||
self._save_debounce_task: asyncio.Task | None = None
|
||||
self._save_lock = asyncio.Lock()
|
||||
|
||||
async def get_intervals(
|
||||
self,
|
||||
api_client: TibberPricesApiClient,
|
||||
user_data: dict[str, Any],
|
||||
start_time: datetime,
|
||||
end_time: datetime,
|
||||
) -> list[dict[str, Any]]:
|
||||
"""
|
||||
Get price intervals for time range (cached + fetch missing).
|
||||
|
||||
Main entry point for retrieving intervals. Coordinates:
|
||||
1. Check cache for existing intervals
|
||||
2. Detect missing time ranges
|
||||
3. Fetch missing ranges from API
|
||||
4. Add new intervals to cache (may trigger GC)
|
||||
5. Return complete interval list
|
||||
|
||||
User receives ALL requested intervals even if cache exceeds limits.
|
||||
Cache only keeps the most recent intervals (FIFO eviction).
|
||||
|
||||
Args:
|
||||
api_client: TibberPricesApiClient instance for API calls.
|
||||
user_data: User data dict containing home metadata.
|
||||
start_time: Start of range (inclusive, timezone-aware).
|
||||
end_time: End of range (exclusive, timezone-aware).
|
||||
|
||||
Returns:
|
||||
List of price interval dicts, sorted by startsAt.
|
||||
Contains ALL intervals in requested range (cached + fetched).
|
||||
|
||||
Raises:
|
||||
TibberPricesApiClientError: If API calls fail or validation errors.
|
||||
|
||||
"""
|
||||
# Validate inputs
|
||||
if not user_data:
|
||||
msg = "User data required for timezone-aware price fetching"
|
||||
raise TibberPricesApiClientError(msg)
|
||||
|
||||
if start_time >= end_time:
|
||||
msg = f"Invalid time range: start_time ({start_time}) must be before end_time ({end_time})"
|
||||
raise TibberPricesApiClientError(msg)
|
||||
|
||||
# Convert to ISO strings for cache operations
|
||||
start_time_iso = start_time.isoformat()
|
||||
end_time_iso = end_time.isoformat()
|
||||
|
||||
_LOGGER_DETAILS.debug(
|
||||
"Interval pool request for home %s: range %s to %s",
|
||||
self._home_id,
|
||||
start_time_iso,
|
||||
end_time_iso,
|
||||
)
|
||||
|
||||
# Get cached intervals using index
|
||||
cached_intervals = self._get_cached_intervals(start_time_iso, end_time_iso)
|
||||
|
||||
# Detect missing ranges
|
||||
missing_ranges = self._fetcher.detect_gaps(cached_intervals, start_time_iso, end_time_iso)
|
||||
|
||||
if missing_ranges:
|
||||
_LOGGER_DETAILS.debug(
|
||||
"Detected %d missing range(s) for home %s - will make %d API call(s)",
|
||||
len(missing_ranges),
|
||||
self._home_id,
|
||||
len(missing_ranges),
|
||||
)
|
||||
else:
|
||||
_LOGGER_DETAILS.debug(
|
||||
"All intervals available in cache for home %s - zero API calls needed",
|
||||
self._home_id,
|
||||
)
|
||||
|
||||
# Fetch missing ranges from API
|
||||
if missing_ranges:
|
||||
fetch_time_iso = dt_utils.now().isoformat()
|
||||
|
||||
# Fetch with callback for immediate caching
|
||||
await self._fetcher.fetch_missing_ranges(
|
||||
api_client=api_client,
|
||||
user_data=user_data,
|
||||
missing_ranges=missing_ranges,
|
||||
on_intervals_fetched=lambda intervals, _: self._add_intervals(intervals, fetch_time_iso),
|
||||
)
|
||||
|
||||
# After caching all API responses, read from cache again to get final result
|
||||
# This ensures we return exactly what user requested, filtering out extra intervals
|
||||
final_result = self._get_cached_intervals(start_time_iso, end_time_iso)
|
||||
|
||||
_LOGGER_DETAILS.debug(
|
||||
"Interval pool returning %d intervals for home %s "
|
||||
"(initially %d cached, %d API calls made, final %d after re-reading cache)",
|
||||
len(final_result),
|
||||
self._home_id,
|
||||
len(cached_intervals),
|
||||
len(missing_ranges),
|
||||
len(final_result),
|
||||
)
|
||||
|
||||
return final_result
|
||||
|
||||
def _get_cached_intervals(
|
||||
self,
|
||||
start_time_iso: str,
|
||||
end_time_iso: str,
|
||||
) -> list[dict[str, Any]]:
|
||||
"""
|
||||
Get cached intervals for time range using timestamp index.
|
||||
|
||||
Uses timestamp_index for O(1) lookups per timestamp.
|
||||
|
||||
Args:
|
||||
start_time_iso: ISO timestamp string (inclusive).
|
||||
end_time_iso: ISO timestamp string (exclusive).
|
||||
|
||||
Returns:
|
||||
List of cached interval dicts in time range (may be empty or incomplete).
|
||||
Sorted by startsAt timestamp.
|
||||
|
||||
"""
|
||||
# Parse query range once
|
||||
start_time_dt = datetime.fromisoformat(start_time_iso)
|
||||
end_time_dt = datetime.fromisoformat(end_time_iso)
|
||||
|
||||
# Use index to find intervals: iterate through expected timestamps
|
||||
result = []
|
||||
current_dt = start_time_dt
|
||||
|
||||
# Determine interval step (15 min post-2025-10-01, 60 min pre)
|
||||
resolution_change_dt = datetime(2025, 10, 1, tzinfo=start_time_dt.tzinfo)
|
||||
interval_minutes = INTERVAL_QUARTER_HOURLY if current_dt >= resolution_change_dt else INTERVAL_HOURLY
|
||||
|
||||
while current_dt < end_time_dt:
|
||||
# Check if this timestamp exists in index (O(1) lookup)
|
||||
current_dt_key = current_dt.isoformat()[:19]
|
||||
location = self._index.get(current_dt_key)
|
||||
|
||||
if location is not None:
|
||||
# Get interval from fetch group
|
||||
fetch_groups = self._cache.get_fetch_groups()
|
||||
fetch_group = fetch_groups[location["fetch_group_index"]]
|
||||
interval = fetch_group["intervals"][location["interval_index"]]
|
||||
result.append(interval)
|
||||
|
||||
# Move to next expected interval
|
||||
current_dt += timedelta(minutes=interval_minutes)
|
||||
|
||||
# Handle resolution change boundary
|
||||
if interval_minutes == INTERVAL_HOURLY and current_dt >= resolution_change_dt:
|
||||
interval_minutes = INTERVAL_QUARTER_HOURLY
|
||||
|
||||
_LOGGER_DETAILS.debug(
|
||||
"Cache lookup for home %s: found %d intervals in range %s to %s",
|
||||
self._home_id,
|
||||
len(result),
|
||||
start_time_iso,
|
||||
end_time_iso,
|
||||
)
|
||||
|
||||
return result
|
||||
|
||||
def _add_intervals(
|
||||
self,
|
||||
intervals: list[dict[str, Any]],
|
||||
fetch_time_iso: str,
|
||||
) -> None:
|
||||
"""
|
||||
Add intervals as new fetch group to cache with GC.
|
||||
|
||||
Strategy:
|
||||
1. Filter out duplicates (intervals already in cache)
|
||||
2. Handle "touch" (move cached intervals to new fetch group)
|
||||
3. Add new fetch group to cache
|
||||
4. Update timestamp index
|
||||
5. Run GC if needed
|
||||
6. Schedule debounced auto-save
|
||||
|
||||
Args:
|
||||
intervals: List of interval dicts from API.
|
||||
fetch_time_iso: ISO timestamp string when intervals were fetched.
|
||||
|
||||
"""
|
||||
if not intervals:
|
||||
return
|
||||
|
||||
fetch_time_dt = datetime.fromisoformat(fetch_time_iso)
|
||||
|
||||
# Classify intervals: new vs already cached
|
||||
new_intervals = []
|
||||
intervals_to_touch = []
|
||||
|
||||
for interval in intervals:
|
||||
starts_at_normalized = interval["startsAt"][:19]
|
||||
if not self._index.contains(starts_at_normalized):
|
||||
new_intervals.append(interval)
|
||||
else:
|
||||
intervals_to_touch.append((starts_at_normalized, interval))
|
||||
_LOGGER_DETAILS.debug(
|
||||
"Interval %s already cached for home %s, will touch (update fetch time)",
|
||||
interval["startsAt"],
|
||||
self._home_id,
|
||||
)
|
||||
|
||||
# Handle touched intervals: move to new fetch group
|
||||
if intervals_to_touch:
|
||||
self._touch_intervals(intervals_to_touch, fetch_time_dt)
|
||||
|
||||
if not new_intervals:
|
||||
if intervals_to_touch:
|
||||
_LOGGER_DETAILS.debug(
|
||||
"All %d intervals already cached for home %s (touched only)",
|
||||
len(intervals),
|
||||
self._home_id,
|
||||
)
|
||||
return
|
||||
|
||||
# Sort new intervals by startsAt
|
||||
new_intervals.sort(key=lambda x: x["startsAt"])
|
||||
|
||||
# Add new fetch group to cache
|
||||
fetch_group_index = self._cache.add_fetch_group(new_intervals, fetch_time_dt)
|
||||
|
||||
# Update timestamp index for all new intervals
|
||||
for interval_index, interval in enumerate(new_intervals):
|
||||
starts_at_normalized = interval["startsAt"][:19]
|
||||
self._index.add(interval, fetch_group_index, interval_index)
|
||||
|
||||
_LOGGER_DETAILS.debug(
|
||||
"Added fetch group %d to home %s cache: %d new intervals (fetched at %s)",
|
||||
fetch_group_index,
|
||||
self._home_id,
|
||||
len(new_intervals),
|
||||
fetch_time_iso,
|
||||
)
|
||||
|
||||
# Run GC to evict old fetch groups if needed
|
||||
gc_changed_data = self._gc.run_gc()
|
||||
|
||||
# Schedule debounced auto-save if data changed
|
||||
data_changed = len(new_intervals) > 0 or len(intervals_to_touch) > 0 or gc_changed_data
|
||||
if data_changed and self._hass is not None and self._entry_id is not None:
|
||||
self._schedule_debounced_save()
|
||||
|
||||
def _touch_intervals(
|
||||
self,
|
||||
intervals_to_touch: list[tuple[str, dict[str, Any]]],
|
||||
fetch_time_dt: datetime,
|
||||
) -> None:
|
||||
"""
|
||||
Move cached intervals to new fetch group (update fetch time).
|
||||
|
||||
Creates a new fetch group containing references to existing intervals.
|
||||
Updates the index to point to the new fetch group.
|
||||
|
||||
Args:
|
||||
intervals_to_touch: List of (normalized_timestamp, interval_dict) tuples.
|
||||
fetch_time_dt: Datetime when intervals were fetched.
|
||||
|
||||
"""
|
||||
fetch_groups = self._cache.get_fetch_groups()
|
||||
|
||||
# Create touch fetch group with existing interval references
|
||||
touch_intervals = []
|
||||
for starts_at_normalized, _interval in intervals_to_touch:
|
||||
# Get existing interval from old fetch group
|
||||
location = self._index.get(starts_at_normalized)
|
||||
if location is None:
|
||||
continue # Should not happen, but be defensive
|
||||
|
||||
old_group = fetch_groups[location["fetch_group_index"]]
|
||||
existing_interval = old_group["intervals"][location["interval_index"]]
|
||||
touch_intervals.append(existing_interval)
|
||||
|
||||
# Add touch group to cache
|
||||
touch_group_index = self._cache.add_fetch_group(touch_intervals, fetch_time_dt)
|
||||
|
||||
# Update index to point to new fetch group
|
||||
for interval_index, (starts_at_normalized, _) in enumerate(intervals_to_touch):
|
||||
# Remove old index entry
|
||||
self._index.remove(starts_at_normalized)
|
||||
# Add new index entry pointing to touch group
|
||||
interval = touch_intervals[interval_index]
|
||||
self._index.add(interval, touch_group_index, interval_index)
|
||||
|
||||
_LOGGER.debug(
|
||||
"Touched %d cached intervals for home %s (moved to fetch group %d, fetched at %s)",
|
||||
len(intervals_to_touch),
|
||||
self._home_id,
|
||||
touch_group_index,
|
||||
fetch_time_dt.isoformat(),
|
||||
)
|
||||
|
||||
def _schedule_debounced_save(self) -> None:
|
||||
"""
|
||||
Schedule debounced save with configurable delay.
|
||||
|
||||
Cancels existing timer and starts new one if already scheduled.
|
||||
This prevents multiple saves during rapid successive changes.
|
||||
|
||||
"""
|
||||
# Cancel existing debounce timer if running
|
||||
if self._save_debounce_task is not None and not self._save_debounce_task.done():
|
||||
self._save_debounce_task.cancel()
|
||||
_LOGGER.debug("Cancelled pending auto-save (new changes detected, resetting timer)")
|
||||
|
||||
# Schedule new debounced save
|
||||
task = asyncio.create_task(
|
||||
self._debounced_save_worker(),
|
||||
name=f"interval_pool_debounce_{self._entry_id}",
|
||||
)
|
||||
self._save_debounce_task = task
|
||||
self._background_tasks.add(task)
|
||||
task.add_done_callback(self._background_tasks.discard)
|
||||
|
||||
async def _debounced_save_worker(self) -> None:
|
||||
"""Debounce worker: waits configured delay, then saves if not cancelled."""
|
||||
try:
|
||||
await asyncio.sleep(DEBOUNCE_DELAY_SECONDS)
|
||||
await self._auto_save_pool_state()
|
||||
except asyncio.CancelledError:
|
||||
_LOGGER.debug("Auto-save timer cancelled (expected - new changes arrived)")
|
||||
raise
|
||||
|
||||
async def _auto_save_pool_state(self) -> None:
|
||||
"""Auto-save pool state to storage with lock protection."""
|
||||
if self._hass is None or self._entry_id is None:
|
||||
return
|
||||
|
||||
async with self._save_lock:
|
||||
try:
|
||||
pool_state = self.to_dict()
|
||||
await async_save_pool_state(self._hass, self._entry_id, pool_state)
|
||||
_LOGGER.debug("Auto-saved interval pool for entry %s", self._entry_id)
|
||||
except Exception:
|
||||
_LOGGER.exception("Failed to auto-save interval pool for entry %s", self._entry_id)
|
||||
|
||||
def to_dict(self) -> dict[str, Any]:
|
||||
"""
|
||||
Serialize interval pool state for storage.
|
||||
|
||||
Filters out dead intervals (no longer referenced by index).
|
||||
|
||||
Returns:
|
||||
Dictionary containing serialized pool state (only living intervals).
|
||||
|
||||
"""
|
||||
fetch_groups = self._cache.get_fetch_groups()
|
||||
|
||||
# Serialize fetch groups (only living intervals)
|
||||
serialized_fetch_groups = []
|
||||
|
||||
for group_idx, fetch_group in enumerate(fetch_groups):
|
||||
living_intervals = []
|
||||
|
||||
for interval_idx, interval in enumerate(fetch_group["intervals"]):
|
||||
starts_at_normalized = interval["startsAt"][:19]
|
||||
|
||||
# Check if interval is still referenced in index
|
||||
location = self._index.get(starts_at_normalized)
|
||||
# Only keep if index points to THIS position in THIS group
|
||||
if (
|
||||
location is not None
|
||||
and location["fetch_group_index"] == group_idx
|
||||
and location["interval_index"] == interval_idx
|
||||
):
|
||||
living_intervals.append(interval)
|
||||
|
||||
# Only serialize groups with living intervals
|
||||
if living_intervals:
|
||||
serialized_fetch_groups.append(
|
||||
{
|
||||
"fetched_at": fetch_group["fetched_at"].isoformat(),
|
||||
"intervals": living_intervals,
|
||||
}
|
||||
)
|
||||
|
||||
return {
|
||||
"version": 1,
|
||||
"home_id": self._home_id,
|
||||
"fetch_groups": serialized_fetch_groups,
|
||||
}
|
||||
|
||||
@classmethod
|
||||
def from_dict(
|
||||
cls,
|
||||
data: dict[str, Any],
|
||||
*,
|
||||
api: TibberPricesApiClient,
|
||||
hass: Any | None = None,
|
||||
entry_id: str | None = None,
|
||||
) -> TibberPricesIntervalPool | None:
|
||||
"""
|
||||
Restore interval pool manager from storage.
|
||||
|
||||
Expects single-home format: {"version": 1, "home_id": "...", "fetch_groups": [...]}
|
||||
Old multi-home format is treated as corrupted and returns None.
|
||||
|
||||
Args:
|
||||
data: Dictionary containing serialized pool state.
|
||||
api: API client for fetching intervals.
|
||||
hass: HomeAssistant instance for auto-save (optional).
|
||||
entry_id: Config entry ID for auto-save (optional).
|
||||
|
||||
Returns:
|
||||
Restored TibberPricesIntervalPool instance, or None if format unknown/corrupted.
|
||||
|
||||
"""
|
||||
# Validate format
|
||||
if not data or "home_id" not in data or "fetch_groups" not in data:
|
||||
if "homes" in data:
|
||||
_LOGGER.info(
|
||||
"Interval pool storage uses old multi-home format (pre-2025-11-25). "
|
||||
"Treating as corrupted. Pool will rebuild from API."
|
||||
)
|
||||
else:
|
||||
_LOGGER.warning("Interval pool storage format unknown or corrupted. Pool will rebuild from API.")
|
||||
return None
|
||||
|
||||
home_id = data["home_id"]
|
||||
|
||||
# Create manager with home_id from storage
|
||||
manager = cls(home_id=home_id, api=api, hass=hass, entry_id=entry_id)
|
||||
|
||||
# Restore fetch groups to cache
|
||||
for serialized_group in data.get("fetch_groups", []):
|
||||
fetched_at_dt = datetime.fromisoformat(serialized_group["fetched_at"])
|
||||
intervals = serialized_group["intervals"]
|
||||
fetch_group_index = manager._cache.add_fetch_group(intervals, fetched_at_dt)
|
||||
|
||||
# Rebuild index for this fetch group
|
||||
for interval_index, interval in enumerate(intervals):
|
||||
manager._index.add(interval, fetch_group_index, interval_index)
|
||||
|
||||
total_intervals = sum(len(group["intervals"]) for group in manager._cache.get_fetch_groups())
|
||||
_LOGGER.debug(
|
||||
"Interval pool restored from storage (home %s, %d intervals)",
|
||||
home_id,
|
||||
total_intervals,
|
||||
)
|
||||
|
||||
return manager
|
||||
180
custom_components/tibber_prices/interval_pool/routing.py
Normal file
180
custom_components/tibber_prices/interval_pool/routing.py
Normal file
|
|
@ -0,0 +1,180 @@
|
|||
"""
|
||||
Routing Module - API endpoint selection for price intervals.
|
||||
|
||||
This module handles intelligent routing between different Tibber API endpoints:
|
||||
|
||||
- PRICE_INFO: Recent data (from "day before yesterday midnight" onwards)
|
||||
- PRICE_INFO_RANGE: Historical data (before "day before yesterday midnight")
|
||||
- Automatic splitting and merging when range spans the boundary
|
||||
|
||||
CRITICAL: Uses REAL TIME (dt_utils.now()) for API boundary calculation,
|
||||
NOT TimeService.now() which may be shifted for internal simulation.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
from typing import TYPE_CHECKING, Any
|
||||
|
||||
from custom_components.tibber_prices.api.exceptions import TibberPricesApiClientError
|
||||
from homeassistant.util import dt as dt_utils
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from datetime import datetime
|
||||
|
||||
from custom_components.tibber_prices.api.client import TibberPricesApiClient
|
||||
|
||||
_LOGGER = logging.getLogger(__name__)
|
||||
_LOGGER_DETAILS = logging.getLogger(__name__ + ".details")
|
||||
|
||||
|
||||
async def get_price_intervals_for_range(
|
||||
api_client: TibberPricesApiClient,
|
||||
home_id: str,
|
||||
user_data: dict[str, Any],
|
||||
start_time: datetime,
|
||||
end_time: datetime,
|
||||
) -> list[dict[str, Any]]:
|
||||
"""
|
||||
Get price intervals for a specific time range with automatic routing.
|
||||
|
||||
Automatically routes to the correct API endpoint based on the time range:
|
||||
- PRICE_INFO_RANGE: For intervals exclusively before "day before yesterday midnight" (real time)
|
||||
- PRICE_INFO: For intervals from "day before yesterday midnight" onwards
|
||||
- Both: If range spans across the boundary, splits the request
|
||||
|
||||
CRITICAL: Uses REAL TIME (dt_utils.now()) for API boundary calculation,
|
||||
NOT TimeService.now() which may be shifted for internal simulation.
|
||||
This ensures predictable API responses.
|
||||
|
||||
CACHING STRATEGY: Returns ALL intervals from API response, NOT filtered.
|
||||
The caller (pool.py) will cache everything and then filter to user request.
|
||||
This maximizes cache efficiency - one API call can populate cache for
|
||||
multiple subsequent queries.
|
||||
|
||||
Args:
|
||||
api_client: TibberPricesApiClient instance for API calls.
|
||||
home_id: Home ID to fetch price data for.
|
||||
user_data: User data dict containing home metadata (including timezone).
|
||||
start_time: Start of the range (inclusive, timezone-aware).
|
||||
end_time: End of the range (exclusive, timezone-aware).
|
||||
|
||||
Returns:
|
||||
List of ALL price interval dicts from API (unfiltered).
|
||||
- PRICE_INFO: Returns ~384 intervals (day-before-yesterday to tomorrow)
|
||||
- PRICE_INFO_RANGE: Returns intervals for requested historical range
|
||||
- Both: Returns all intervals from both endpoints
|
||||
|
||||
Raises:
|
||||
TibberPricesApiClientError: If arguments invalid or requests fail.
|
||||
|
||||
"""
|
||||
if not user_data:
|
||||
msg = "User data required for timezone-aware price fetching - fetch user data first"
|
||||
raise TibberPricesApiClientError(msg)
|
||||
|
||||
if not home_id:
|
||||
msg = "Home ID is required"
|
||||
raise TibberPricesApiClientError(msg)
|
||||
|
||||
if start_time >= end_time:
|
||||
msg = f"Invalid time range: start_time ({start_time}) must be before end_time ({end_time})"
|
||||
raise TibberPricesApiClientError(msg)
|
||||
|
||||
# Calculate boundary: day before yesterday midnight (REAL TIME, not TimeService)
|
||||
boundary = _calculate_boundary(api_client, user_data, home_id)
|
||||
|
||||
_LOGGER_DETAILS.debug(
|
||||
"Routing price interval request for home %s: range %s to %s, boundary %s",
|
||||
home_id,
|
||||
start_time,
|
||||
end_time,
|
||||
boundary,
|
||||
)
|
||||
|
||||
# Route based on time range
|
||||
if end_time <= boundary:
|
||||
# Entire range is historical (before day before yesterday) → use PRICE_INFO_RANGE
|
||||
_LOGGER_DETAILS.debug("Range is fully historical, using PRICE_INFO_RANGE")
|
||||
result = await api_client.async_get_price_info_range(
|
||||
home_id=home_id,
|
||||
user_data=user_data,
|
||||
start_time=start_time,
|
||||
end_time=end_time,
|
||||
)
|
||||
return result["price_info"]
|
||||
|
||||
if start_time >= boundary:
|
||||
# Entire range is recent (from day before yesterday onwards) → use PRICE_INFO
|
||||
_LOGGER_DETAILS.debug("Range is fully recent, using PRICE_INFO")
|
||||
result = await api_client.async_get_price_info(home_id, user_data)
|
||||
|
||||
# Return ALL intervals (unfiltered) for maximum cache efficiency
|
||||
# Pool will cache everything, then filter to user request
|
||||
return result["price_info"]
|
||||
|
||||
# Range spans boundary → split request
|
||||
_LOGGER_DETAILS.debug("Range spans boundary, splitting request")
|
||||
|
||||
# Fetch historical part (start_time to boundary)
|
||||
historical_result = await api_client.async_get_price_info_range(
|
||||
home_id=home_id,
|
||||
user_data=user_data,
|
||||
start_time=start_time,
|
||||
end_time=boundary,
|
||||
)
|
||||
|
||||
# Fetch recent part (boundary onwards)
|
||||
recent_result = await api_client.async_get_price_info(home_id, user_data)
|
||||
|
||||
# Return ALL intervals (unfiltered) for maximum cache efficiency
|
||||
# Pool will cache everything, then filter to user request
|
||||
return historical_result["price_info"] + recent_result["price_info"]
|
||||
|
||||
|
||||
def _calculate_boundary(
|
||||
api_client: TibberPricesApiClient,
|
||||
user_data: dict[str, Any],
|
||||
home_id: str,
|
||||
) -> datetime:
|
||||
"""
|
||||
Calculate the API boundary (day before yesterday midnight).
|
||||
|
||||
Uses the API client's helper method to extract timezone and calculate boundary.
|
||||
|
||||
Args:
|
||||
api_client: TibberPricesApiClient instance.
|
||||
user_data: User data dict containing home metadata.
|
||||
home_id: Home ID to get timezone for.
|
||||
|
||||
Returns:
|
||||
Timezone-aware datetime for day before yesterday midnight.
|
||||
|
||||
"""
|
||||
# Extract timezone for this home
|
||||
home_timezones = api_client._extract_home_timezones(user_data) # noqa: SLF001
|
||||
home_tz = home_timezones.get(home_id)
|
||||
|
||||
# Calculate boundary using API client's method
|
||||
return api_client._calculate_day_before_yesterday_midnight(home_tz) # noqa: SLF001
|
||||
|
||||
|
||||
def _parse_timestamp(timestamp_str: str) -> datetime:
|
||||
"""
|
||||
Parse ISO timestamp string to timezone-aware datetime.
|
||||
|
||||
Args:
|
||||
timestamp_str: ISO format timestamp string.
|
||||
|
||||
Returns:
|
||||
Timezone-aware datetime object.
|
||||
|
||||
Raises:
|
||||
ValueError: If timestamp string cannot be parsed.
|
||||
|
||||
"""
|
||||
result = dt_utils.parse_datetime(timestamp_str)
|
||||
if result is None:
|
||||
msg = f"Failed to parse timestamp: {timestamp_str}"
|
||||
raise ValueError(msg)
|
||||
return result
|
||||
165
custom_components/tibber_prices/interval_pool/storage.py
Normal file
165
custom_components/tibber_prices/interval_pool/storage.py
Normal file
|
|
@ -0,0 +1,165 @@
|
|||
"""Storage management for interval pool."""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import errno
|
||||
import logging
|
||||
from typing import TYPE_CHECKING, Any
|
||||
|
||||
from homeassistant.helpers.storage import Store
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from homeassistant.core import HomeAssistant
|
||||
|
||||
_LOGGER = logging.getLogger(__name__)
|
||||
_LOGGER_DETAILS = logging.getLogger(__name__ + ".details")
|
||||
|
||||
# Storage version - increment when changing data structure
|
||||
INTERVAL_POOL_STORAGE_VERSION = 1
|
||||
|
||||
|
||||
def get_storage_key(entry_id: str) -> str:
|
||||
"""
|
||||
Get storage key for interval pool based on config entry ID.
|
||||
|
||||
Args:
|
||||
entry_id: Home Assistant config entry ID
|
||||
|
||||
Returns:
|
||||
Storage key string
|
||||
|
||||
"""
|
||||
return f"tibber_prices.interval_pool.{entry_id}"
|
||||
|
||||
|
||||
async def async_load_pool_state(
|
||||
hass: HomeAssistant,
|
||||
entry_id: str,
|
||||
) -> dict[str, Any] | None:
|
||||
"""
|
||||
Load interval pool state from storage.
|
||||
|
||||
Args:
|
||||
hass: Home Assistant instance
|
||||
entry_id: Config entry ID
|
||||
|
||||
Returns:
|
||||
Pool state dict or None if no cache exists
|
||||
|
||||
"""
|
||||
storage_key = get_storage_key(entry_id)
|
||||
store: Store = Store(hass, INTERVAL_POOL_STORAGE_VERSION, storage_key)
|
||||
|
||||
try:
|
||||
stored = await store.async_load()
|
||||
except Exception:
|
||||
# Corrupted storage file, JSON parse error, or other exception
|
||||
_LOGGER.exception(
|
||||
"Failed to load interval pool storage for entry %s (corrupted file?), starting with empty pool",
|
||||
entry_id,
|
||||
)
|
||||
return None
|
||||
|
||||
if stored is None:
|
||||
_LOGGER.debug("No interval pool cache found for entry %s (first run)", entry_id)
|
||||
return None
|
||||
|
||||
# Validate storage structure (single-home format)
|
||||
if not isinstance(stored, dict):
|
||||
_LOGGER.warning(
|
||||
"Invalid interval pool storage structure for entry %s (not a dict), ignoring",
|
||||
entry_id,
|
||||
)
|
||||
return None
|
||||
|
||||
# Check for new single-home format (version 1, home_id, fetch_groups)
|
||||
if "home_id" in stored and "fetch_groups" in stored:
|
||||
_LOGGER.debug(
|
||||
"Interval pool state loaded for entry %s (single-home format, %d fetch groups)",
|
||||
entry_id,
|
||||
len(stored.get("fetch_groups", [])),
|
||||
)
|
||||
return stored
|
||||
|
||||
# Check for old multi-home format (homes dict) - treat as incompatible
|
||||
if "homes" in stored:
|
||||
_LOGGER.info(
|
||||
"Interval pool storage for entry %s uses old multi-home format (pre-2025-11-25). "
|
||||
"Treating as incompatible. Pool will rebuild from API.",
|
||||
entry_id,
|
||||
)
|
||||
return None
|
||||
|
||||
# Unknown format
|
||||
_LOGGER.warning(
|
||||
"Invalid interval pool storage structure for entry %s (missing required keys), ignoring",
|
||||
entry_id,
|
||||
)
|
||||
return None
|
||||
|
||||
|
||||
async def async_save_pool_state(
|
||||
hass: HomeAssistant,
|
||||
entry_id: str,
|
||||
pool_state: dict[str, Any],
|
||||
) -> None:
|
||||
"""
|
||||
Save interval pool state to storage.
|
||||
|
||||
Args:
|
||||
hass: Home Assistant instance
|
||||
entry_id: Config entry ID
|
||||
pool_state: Pool state dict to save
|
||||
|
||||
"""
|
||||
storage_key = get_storage_key(entry_id)
|
||||
store: Store = Store(hass, INTERVAL_POOL_STORAGE_VERSION, storage_key)
|
||||
|
||||
try:
|
||||
await store.async_save(pool_state)
|
||||
_LOGGER_DETAILS.debug(
|
||||
"Interval pool state saved for entry %s (%d fetch groups)",
|
||||
entry_id,
|
||||
len(pool_state.get("fetch_groups", [])),
|
||||
)
|
||||
except OSError as err:
|
||||
# Provide specific error messages based on errno
|
||||
if err.errno == errno.ENOSPC: # Disk full
|
||||
_LOGGER.exception(
|
||||
"Cannot save interval pool storage for entry %s: Disk full!",
|
||||
entry_id,
|
||||
)
|
||||
elif err.errno == errno.EACCES: # Permission denied
|
||||
_LOGGER.exception(
|
||||
"Cannot save interval pool storage for entry %s: Permission denied!",
|
||||
entry_id,
|
||||
)
|
||||
else:
|
||||
_LOGGER.exception(
|
||||
"Failed to save interval pool storage for entry %s",
|
||||
entry_id,
|
||||
)
|
||||
|
||||
|
||||
async def async_remove_pool_storage(
|
||||
hass: HomeAssistant,
|
||||
entry_id: str,
|
||||
) -> None:
|
||||
"""
|
||||
Remove interval pool storage file.
|
||||
|
||||
Used when config entry is removed.
|
||||
|
||||
Args:
|
||||
hass: Home Assistant instance
|
||||
entry_id: Config entry ID
|
||||
|
||||
"""
|
||||
storage_key = get_storage_key(entry_id)
|
||||
store: Store = Store(hass, INTERVAL_POOL_STORAGE_VERSION, storage_key)
|
||||
|
||||
try:
|
||||
await store.async_remove()
|
||||
_LOGGER.debug("Interval pool storage removed for entry %s", entry_id)
|
||||
except OSError as ex:
|
||||
_LOGGER.warning("Failed to remove interval pool storage for entry %s: %s", entry_id, ex)
|
||||
Loading…
Reference in a new issue