2 commits

Author	SHA1	Message	Date
Julian Pawlowski	625bc222ca	refactor(coordinator): centralize time operations through TimeService ... Introduce TimeService as single source of truth for all datetime operations, replacing direct dt_util calls throughout the codebase. This establishes consistent time context across update cycles and enables future time-travel testing capability. Core changes: - NEW: coordinator/time_service.py with timezone-aware datetime API - Coordinator now creates TimeService per update cycle, passes to calculators - Timer callbacks (#2, #3) inject TimeService into entity update flow - All sensor calculators receive TimeService via coordinator reference - Attribute builders accept time parameter for timestamp calculations Key patterns replaced: - dt_util.now() → time.now() (single reference time per cycle) - dt_util.parse_datetime() + as_local() → time.get_interval_time() - Manual interval arithmetic → time.get_interval_offset_time() - Manual day boundaries → time.get_day_boundaries() - round_to_nearest_quarter_hour() → time.round_to_nearest_quarter() Import cleanup: - Removed dt_util imports from ~30 files (calculators, attributes, utils) - Restricted dt_util to 3 modules: time_service.py (operations), api/client.py (rate limiting), entity_utils/icons.py (cosmetic updates) - datetime/timedelta only for TYPE_CHECKING (type hints) or duration arithmetic Interval resolution abstraction: - Removed hardcoded MINUTES_PER_INTERVAL constant from 10+ files - New methods: time.minutes_to_intervals(), time.get_interval_duration() - Supports future 60-minute resolution (legacy data) via TimeService config Timezone correctness: - API timestamps (startsAt) already localized by data transformation - TimeService operations preserve HA user timezone throughout - DST transitions handled via get_expected_intervals_for_day() (future use) Timestamp ordering preserved: - Attribute builders generate default timestamp (rounded quarter) - Sensors override when needed (next interval, daily midnight, etc.) - Platform ensures timestamp stays FIRST in attribute dict Timer integration: - Timer #2 (quarter-hour): Creates TimeService, calls _handle_time_sensitive_update(time) - Timer #3 (30-second): Creates TimeService, calls _handle_minute_update(time) - Consistent time reference for all entities in same update batch Time-travel readiness: - TimeService.with_reference_time() enables time injection (not yet used) - All calculations use time.now() → easy to simulate past/future states - Foundation for debugging period calculations with historical data Impact: Eliminates timestamp drift within update cycles (previously 60+ independent dt_util.now() calls could differ by milliseconds). Establishes architecture for time-based testing and debugging features.	2025-11-19 18:36:12 +00:00
Julian Pawlowski	a962289682	refactor(sensor): implement Calculator Pattern with specialized modules ... Massive refactoring of sensor platform reducing core.py from 2,170 to 909 lines (58% reduction). Extracted business logic into specialized calculators and attribute builders following separation of concerns principles. Changes: - Created sensor/calculators/ package (8 specialized calculators, 1,838 lines): * base.py: Abstract BaseCalculator with coordinator access * interval.py: Single interval calculations (current/next/previous) * rolling_hour.py: 5-interval rolling windows * daily_stat.py: Calendar day min/max/avg statistics * window_24h.py: Trailing/leading 24h windows * volatility.py: Price volatility analysis * trend.py: Complex trend analysis with caching (640 lines) * timing.py: Best/peak price period timing * metadata.py: Home/metering metadata - Created sensor/attributes/ package (8 specialized modules, 1,209 lines): * Modules match calculator types for consistent organization * __init__.py: Routing logic + unified builders * Handles state presentation separately from business logic - Created sensor/chart_data.py (144 lines): * Extracted chart data export functionality from entity class * YAML parsing, service calls, metadata formatting - Created sensor/value_getters.py (276 lines): * Centralized handler mapping for all 80+ sensor types * Single source of truth for sensor routing - Extended sensor/helpers.py (+88 lines): * Added aggregate_window_data() unified aggregator * Added get_hourly_price_value() for backward compatibility * Consolidated sensor-specific helper functions - Refactored sensor/core.py (909 lines, was 2,170): * Instantiates all calculators in __init__ * Delegates value calculations to appropriate calculator * Uses unified handler methods via value_getters mapping * Minimal platform-specific logic remains (icon callbacks, entity lifecycle) - Deleted sensor/attributes.py (1,106 lines): * Functionality split into attributes/ package (8 modules) - Updated AGENTS.md: * Documented Calculator Pattern architecture * Added guidance for adding new sensors with calculation groups * Updated file organization with new package structure Architecture Benefits: - Clear separation: Calculators (business logic) vs Attributes (presentation) - Improved testability: Each calculator independently testable - Better maintainability: 21 focused modules vs monolithic file - Easy extensibility: Add sensors by choosing calculation pattern - Reusable components: Calculators and attribute builders shared across sensors Impact: Significantly improved code organization and maintainability while preserving all functionality. All 80+ sensor types continue working with cleaner, more modular architecture. Developer experience improved with logical file structure and clear separation of concerns.	2025-11-18 21:25:55 +00:00