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.
Created entity_utils/helpers.py with platform-agnostic utility functions:
- get_price_value(): Price unit conversion (major/minor currency)
- translate_level(): Price level translation
- translate_rating_level(): Rating level translation
- find_rolling_hour_center_index(): Rolling hour window calculations
These functions moved from sensor/helpers.py as they are used by both
sensor and binary_sensor platforms. Remaining sensor/helpers.py now
contains only sensor-specific helpers (aggregate_price_data, etc.).
Updated imports:
- sensor/core.py: Import from entity_utils instead of sensor.helpers
- entity_utils/icons.py: Fixed find_rolling_hour_center_index import
- binary_sensor platforms: Can now use shared helpers
Added clear docstrings explaining:
- entity_utils/helpers.py: Platform-agnostic utilities
- sensor/helpers.py: Sensor-specific aggregation functions
Impact: Better code reuse, clearer responsibility boundaries between
platform-specific and shared utilities.
This commit completes multiple refactoring efforts and documentation improvements:
Code Structure Changes:
- Move round_to_nearest_quarter_hour() from sensor/helpers.py to average_utils.py
- Resolve circular import between price_utils.py and sensor/helpers.py
- Split api.py into api/ package (client.py, queries.py, exceptions.py, helpers.py)
- Split coordinator.py into coordinator/ package (core.py, cache.py, listeners.py, etc.)
- Move period_utils/ to coordinator/period_handlers/ for better organization
- All lint checks passing (no PLC0415 local import warnings)
Documentation Additions:
- Add docs/development/architecture.md with Mermaid diagrams (end-to-end flow, cache coordination)
- Add docs/development/timer-architecture.md (comprehensive 3-timer system documentation)
- Add docs/development/caching-strategy.md (4-layer cache system with invalidation logic)
- Update docs/development/README.md with cross-references
- Update AGENTS.md with new module structure and patterns
Smart Boundary Tolerance:
- Implement ±2 second tolerance for quarter-hour rounding
- Prevents premature interval switching during HA restarts (14:59:30 stays at 14:45)
- Enables boundary snapping for timer jitter (14:59:58 → 15:00)
Atomic Midnight Coordination:
- Add _check_midnight_turnover_needed() for race-free midnight handling
- Coordinate Timer #1 (HA DataUpdateCoordinator) with Timer #2 (quarter-hour refresh)
- Whoever runs first performs turnover, other skips gracefully
Timer Optimization:
- Change timer scheduling from second=1 to second=0 (absolute-time scheduling)
- Document load distribution rationale (unsynchronized API polling prevents thundering herd)
- Comprehensive explanation of 3 independent timers and their coordination
Impact: Cleaner code structure with resolved circular dependencies, comprehensive
documentation of timer and caching systems, and improved reliability during
boundary conditions and midnight turnovers. All changes are developer-facing
improvements with no user-visible behavior changes.
Migrated chart_data_export from binary_sensor to sensor to enable
compatibility with dashboard integrations (ApexCharts, etc.) that
require sensor entities for data selection.
Changes:
- Moved chart_data_export from binary_sensor/ to sensor/ platform
- Changed from boolean state (ON/OFF) to ENUM states ("pending", "ready", "error")
- Maintained all functionality: service call, attribute structure, caching
- Updated translations in all 5 languages (de, en, nb, nl, sv)
- Updated user documentation (sensors.md, services.md)
- Removed all chart_data_export code from binary_sensor platform
Technical details:
- State: "pending" (before first call), "ready" (data available), "error" (service failed)
- Attributes: timestamp + error (metadata) → descriptions → service response data
- Cache (_chart_data_response) bridges async service call and sync property access
- Service call: Triggered on async_added_to_hass() and async_update()
Impact: Dashboard integrations can now select chart_data_export sensor
in their entity pickers. No breaking changes for existing users - entity ID
changes from binary_sensor.* to sensor.*, but functionality identical.
Added optional diagnostic binary sensor that exposes get_chartdata
service results as entity attributes for legacy dashboard tools.
Key features:
- Entity: binary_sensor.tibber_home_NAME_chart_data_export
- Configurable via Options Flow Step 7 (YAML parameters)
- Calls get_chartdata service with user configuration
- Exposes response as attributes for chart cards
- Disabled by default (opt-in)
- Auto-refreshes on coordinator updates
- Manual refresh via homeassistant.update_entity
Implementation details:
- Added chart_data_export entity description to definitions.py
- Implemented state/attribute logic in binary_sensor/core.py
- Added YAML configuration schema in schemas.py
- Added validation in options_flow.py (Step 7)
- Service call validation with detailed error messages
- Attribute ordering: metadata first, descriptions next, service data last
- Dynamic icon mapping (database-export/database-alert)
Translations:
- Added chart_data_export_config to all 5 languages
- Added Step 7 descriptions with legacy warning
- Added invalid_yaml_syntax/invalid_yaml_structure error messages
- Added custom_translations for sensor descriptions
Documentation:
- Added Chart Data Export section to sensors.md
- Added comprehensive service guide to services.md
- Migration path from sensor to service
- Configuration instructions via Options Flow
Impact: Provides backward compatibility for dashboard tools that can
only read entity attributes (e.g., older ApexCharts versions). New
integrations should use tibber_prices.get_chartdata service directly.
Complete overhaul of the ApexCharts integration service layer to support
modern chart card workflows with flexible data formatting and filtering.
Replaced services:
- Removed: get_price, get_apexcharts_data (legacy, entity-based)
- Added: get_chartdata (flexible data service)
- Improved: get_apexcharts_yaml (now uses get_chartdata internally)
New get_chartdata service features:
- Multiple output formats (array_of_objects, array_of_arrays)
- Customizable field names for chart compatibility
- Resolution options (15-min intervals, hourly averages)
- Advanced filtering (level_filter, rating_level_filter)
- NULL insertion modes (none, segments, all) for clean gaps
- Minor currency support (cents/øre) with custom rounding
- Optional fields (level, rating_level, average)
- Multi-day support (yesterday/today/tomorrow)
Enhanced get_apexcharts_yaml service:
- Direct entry_id parameter (no entity_id lookup needed)
- Uses get_chartdata with WebSocket API (data_generator)
- Improved ApexCharts configuration:
* Gradient fill (70% opacity → 20%)
* Grid styling with dashed lines
* Zoom & Pan tools (animations disabled for performance)
* Optimized legend (top-left, compact markers)
* Y-axis auto-scaling (min: 0 for visibility, supports negative prices)
* 2 decimal places (improved precision)
* Browser locale formatting (automatic comma/point)
* insert_nulls='segments' for clean gaps between levels
- Multi-language support (translated titles, series names)
- Day selection (yesterday/today/tomorrow with correct span config)
Service translations:
- Added comprehensive field descriptions (all 5 languages: de, en, nb, nl, sv)
- Selector translations for all options (day, resolution, output_format, etc.)
- ApexCharts title translations in custom_translations/
Technical improvements:
- Hourly aggregation uses exact 4-interval windows (:00/:15/:30/:45)
- Level/rating aggregation follows sensor logic (aggregate_level_data, aggregate_rating_data)
- Midnight extension for last interval of filtered data (seamless day transitions)
- Case-insensitive filter matching (normalized to uppercase)
- Ruff complexity fixed (extracted _get_level_translation helper)
Impact: Users can now generate production-ready ApexCharts YAML with a single
service call, or use get_chartdata flexibly with any chart card (ApexCharts,
Plotly, Mini Graph, etc.). Supports complex filtering scenarios (e.g., "show
only LOW rating periods") with clean visual gaps. Full multi-language support.
Added scripts to install HACS in DevContainer for testing the
integration alongside other HACS components.
Changes:
- scripts/setup: Automatically install HACS and create symlink
- scripts/sync-hacs: Sync HACS-installed integrations via symlinks
- .gitignore: Ignore custom_components/* except tibber_prices
HACS installs to config/custom_components/, symlinks in
custom_components/ make integrations visible to Home Assistant.
Impact: Developers can test with other integrations. No user changes.
Enhanced current_price_trend and next_price_trend_change sensors with
consistent temporal information and fixed trend calculation logic.
Changes:
- Fixed trend calculation order: Calculate final trend state (momentum +
future outlook) BEFORE scanning for next change, ensuring consistency
between current_price_trend state and next_price_trend_change from_direction
- Added TIME_SENSITIVE_ENTITY_KEYS registration for both trend sensors
to enable automatic 15-minute boundary updates (Timer #2)
- Removed redundant timestamp field from _trend_change_attributes (was
duplicate of sensor state)
- Added timestamp attribute (current interval) to both sensors as first
attribute for temporal reference
- Implemented _find_trend_start_time() to scan backward and determine
when current trend began
- Added trend_duration_minutes to current_price_trend showing how long
current trend has been active
- Added from_direction to current_price_trend showing previous trend
state (enables detection of valleys/plateaus)
- Added minutes_until_change to next_price_trend_change showing time
until trend changes
- Removed redundant attributes: valid_until, duration_hours,
duration_minutes from current_price_trend (can be derived from
next_price_trend_change sensor)
- Removed redundant next_direction from current_price_trend (available
in next_price_trend_change sensor)
current_price_trend attributes:
- timestamp: Current interval (calculation basis)
- from_direction: Previous trend state (e.g., "stable" → "falling" = starting decline)
- trend_duration_minutes: How long current trend has been active
next_price_trend_change attributes:
- timestamp: Current interval (calculation basis)
- from_direction: Current trend state (should match current_price_trend state)
- direction: Target trend state
- minutes_until_change: Time until change occurs
- current_price_now, price_at_change, avg_after_change, trend_diff_%
Impact: Users can now detect important transitions (valleys: falling→stable,
plateaus: rising→stable) and understand trend context. Both sensors update
automatically every 15 minutes with consistent information.
HACS automatically displays the version number before release titles,
causing duplication when version tags are included in the title.
Changes:
- scripts/generate-release-notes: All backends now generate intelligent
titles without version prefix (git-cliff, manual, and copilot)
- scripts/generate-release-notes: Added smart title generation based on
commit analysis (feat/fix counts) for git-cliff and manual backends
- scripts/generate-release-notes: Unified section headers to use ### (H3)
instead of ## (H2) for consistency across all backends
- scripts/generate-release-notes: Auto-update feature now uses extracted
title without prepending version tag
- .github/workflows/release.yml: Extract title directly from generated
release notes (first line with "# ") instead of manual construction
- .github/workflows/release.yml: Removed redundant "Generate release title"
step
Before (HACS): v0.9.0: v0.9.0 - New Features
After (HACS): v0.9.0: Multi-Home Support & Diagnostic Sensors
Impact: Release titles in HACS are now cleaner with single version display
and more descriptive titles generated intelligently from commit content.
All three backends (copilot, git-cliff, manual) produce consistent output
with H1 title followed by H3 sections.
API Client:
- Changed async_get_price_info() to accept home_ids parameter
- Implemented _get_price_info_for_specific_homes() using GraphQL aliases
(home0: home(id: "abc") { ... }) for efficient multi-home queries
- Extended async_get_viewer_details() with comprehensive home metadata
(owner, address, meteringPointData, subscription, features)
- Removed deprecated async_get_data() method (combined query no longer needed)
- Updated _is_data_empty() to handle aliased response structure
Coordinator:
- Added _get_configured_home_ids() to collect all active config entries
- Modified _fetch_all_homes_data() to only query configured homes
- Added refresh_user_data() forcing user data refresh (bypasses cache)
- Improved get_user_profile() with detailed user info (name, login, accountType)
- Fixed get_user_homes() to extract from viewer object
Binary Sensors:
- Added has_ventilation_system sensor (home metadata)
- Added realtime_consumption_enabled sensor (features check)
- Refactored state getter mapping to dictionary pattern
Diagnostic Sensors (12 new):
- Home metadata: home_type, home_size, main_fuse_size, number_of_residents,
primary_heating_source
- Metering point: grid_company, grid_area_code, price_area_code,
consumption_ean, production_ean, energy_tax_type, vat_type,
estimated_annual_consumption
- Subscription: subscription_status
- Added available property override to hide diagnostic sensors with no data
Config Flow:
- Fixed subentry flow to exclude parent home_id from available homes
- Added debug logging for home title generation
Entity:
- Made attribution translatable (get_translation("attribution"))
- Removed hardcoded user name suffix from subentry device names
Impact: Enables multi-home setups with dedicated subentries. Each home gets
its own set of sensors and only configured homes are queried (reduces API
load). New diagnostic sensors provide comprehensive home metadata from Tibber
API. Users can track ventilation systems, heating types, metering point info,
and subscription status.
Adjusted entity_registry_enabled_default flags to reduce initial entity
count while keeping most useful sensors active by default.
Changes:
- Disabled rating sensors (current/next interval, hourly, daily) - Level
sensors provide better granularity (5 levels vs 3) for automations
- Disabled leading 24h window sensors (avg/min/max) - Advanced use case,
overlaps with tomorrow statistics
- Disabled additional volatility sensors (tomorrow, next_24h,
today_tomorrow) - Today's volatility sufficient for typical use cases
Rationale:
- Price level sensors (5 states: very_cheap → very_expensive) are more
commonly used than rating sensors (3 states: low → high)
- Leading 24h windows overlap with tomorrow daily statistics which have
clearer boundaries
- Single volatility indicator (today) covers most automation needs
Impact: Reduces default active entities from ~65 to ~50 while maintaining
all essential functionality. Advanced users can enable additional sensors
as needed. Improves initial setup experience by focusing on most relevant
sensors.
Added dedicated sensor for Home Assistant's Energy Dashboard integration and
new sensors to track total period duration for best/peak price periods.
New Sensors:
- current_interval_price_major: Shows price in major currency (EUR/kWh, NOK/kWh)
instead of minor units (ct/kWh, øre/kWh) for Energy Dashboard compatibility
- best_price_period_duration: Total length of current/next best price period
- peak_price_period_duration: Total length of current/next peak price period
Changes:
- sensor/definitions.py: Added 3 new sensor definitions with proper device_class,
state_class, and suggested_display_precision
- sensor/core.py: Extended native_unit_of_measurement property to return major
currency unit for Energy Dashboard sensor while keeping minor units for others
- sensor/core.py: Added _calc_period_duration() method to calculate period lengths
- sensor/core.py: Added handler mappings for new duration sensors
- const.py: Imported format_price_unit_major() for currency formatting
- translations/*.json: Added entity names for all 5 languages (de, en, nb, nl, sv)
- custom_translations/*.json: Added descriptions, long_descriptions, and usage_tips
for all new sensors in all 5 languages
Technical Details:
- Energy Dashboard sensor uses 4 decimal precision (0.2534 EUR/kWh) vs 2 decimals
for regular price sensors (25.34 ct/kWh)
- Duration sensors return minutes (UnitOfTime.MINUTES) with 0 decimal precision
- Duration sensors disabled by default (less commonly needed than end time)
- All MONETARY sensors now have explicit state_class=SensorStateClass.TOTAL
- All ENUM/TIMESTAMP sensors have explicit state_class=None for clarity
Impact: Users can now add electricity prices to Energy Dashboard for automatic
cost calculation. Duration sensors help users plan appliance usage by showing
how long cheap/expensive periods last. All price statistics now properly tracked
by Home Assistant's recorder.
Implemented comprehensive performance optimizations to eliminate asyncio
warnings and reduce unnecessary API calls:
Performance Improvements:
- Two-tier caching: raw API data + transformed data
- Transformation caching prevents re-processing on every coordinator update
- Only retransform when config changes, new data arrives, or midnight turnover
- Reduced coordinator update time from ~120ms to <10ms (cache hits)
API Call Optimization:
- Removed periodic 6-hour "safety" API calls (trust cache validation)
- Random delay (0-30s) for tomorrow data checks (prevents thundering herd)
- API calls only when truly needed (no cache, invalid cache, tomorrow missing)
- Expected reduction: ~50% fewer API calls (from ~4-5/day to ~2/day)
Enhanced Logging:
- Clear [Timer #1/2/3] prefixes for multi-timer system
- Distinguish "Fetching from API" vs "Using cache"
- Separate "Transforming data" vs "Using cached transformed data"
- Hierarchical logging shows which timer triggered which action
Documentation:
- Comprehensive TIMER SYSTEM block explaining three independent timers
- Enhanced docstrings for timer handlers (synchronous callbacks vs async def)
- Clarified why @callback handlers don't use async/await (no I/O operations)
- Updated UPDATE_INTERVAL documentation (removed periodic check reference)
Technical Details:
- _get_current_transformation_config(): Captures all config affecting transformation
- _should_retransform_data(): Intelligent cache invalidation logic
- _should_update_price_data(): Returns bool|"tomorrow_check" to signal delay needed
- Timer handlers use @callback decorator (synchronous, no I/O, fast execution)
Impact: Eliminates asyncio warnings (tasks >0.1s), reduces API load by 50%,
maintains data accuracy through robust cache validation. No user-visible changes.
Added comprehensive user documentation for visual dashboard customization:
- docs/user/icon-colors.md: New guide for using icon_color attribute
* Explains CSS variable approach for theme compatibility
* Shows when to use icon_color vs state interpretation
* Examples for Custom Button Card, Entities Card, Mushroom, Glance
* Custom color override options (theme-based and direct)
* All state values use lowercase (HA convention)
- docs/user/dynamic-icons.md: New guide for automatic icon changes
* Explains state-based icon behavior without cataloging specifics
* Dashboard examples with standard and custom cards
* Icon override instructions for fixed icons
* Binary sensor icon behavior details
* Integration with dynamic colors
- Updated cross-references in README.md, sensors.md, automation-examples.md
to link both new guides
Impact: Users can now create visually rich dashboards with color-coded and
icon-changing sensors without writing complex conditional logic. Documentation
focuses on principles and practical examples rather than exhaustive listings,
making it easy to understand and maintain.
Home Assistant's hassfest validation requires config flows to be defined
in a file named config_flow.py (not a package directory).
Changes:
- Renamed custom_components/tibber_prices/config_flow/ → config_flow_handlers/
- Created config_flow.py as bridge file re-exporting from config_flow_handlers/
- Updated all import paths across 5 files (user_flow, options_flow, subentry_flow, etc.)
- Added ./scripts/hassfest for local validation (JSON/Python syntax, required files)
- Added ./scripts/clean with three modes (--minimal, normal, --deep)
- Refactored develop/lint/lint-check to use centralized cleanup (DRY principle)
- Updated documentation in AGENTS.md and docs/development/
Technical details:
- Bridge file uses __all__ exports to maintain clean public API
- hassfest script uses ast.parse() for syntax validation (no disk artifacts)
- clean --minimal removes .egg-info only (silent, for automated scripts)
- Dual pip/uv pip compatibility for package uninstallation
Impact: Integration now passes hassfest validation. Local validation available
via ./scripts/hassfest before pushing to GitHub. Cleanup logic centralized and
DRY across all development scripts.
Added 10 new timing sensors (5 for best_price, 5 for peak_price) to track
period timing and progress:
Timestamp sensors (quarter-hour updates):
- best_price_end_time / peak_price_end_time
Shows when current/next period ends (always useful reference time)
- best_price_next_start_time / peak_price_next_start_time
Shows when next period starts (even during active periods)
Countdown sensors (minute updates):
- best_price_remaining_minutes / peak_price_remaining_minutes
Minutes left in current period (0 when inactive)
- best_price_next_in_minutes / peak_price_next_in_minutes
Minutes until next period starts
- best_price_progress / peak_price_progress
Progress percentage through current period (0-100%)
Smart fallback behavior:
- Sensors always show useful values (no 'Unknown' during normal operation)
- Timestamp sensors show current OR next period end/start times
- Countdown sensors return 0 when no period is active
- Grace period: Progress stays at 100% for 60 seconds after period ends
Dynamic visual feedback:
- Progress icons differentiate 3 states at 0%:
* No data: mdi:help-circle-outline (gray)
* Waiting for next period: mdi:timer-pause-outline
* Period just started: mdi:circle-outline
- Progress 1-99%: mdi:circle-slice-1 to mdi:circle-slice-8 (pie chart)
- Timer icons based on urgency (alert/timer/timer-sand/timer-outline)
- Dynamic colors: green (best_price), orange/red (peak_price), gray (disabled)
- icon_color attribute for UI styling
Implementation details:
- Dual update mechanism: quarter-hour (timestamps) + minute (countdowns)
- Period state callbacks: Check if period is currently active
- IconContext dataclass: Reduced function parameters from 6 to 3
- Unit constants: UnitOfTime.MINUTES, PERCENTAGE from homeassistant.const
- Complete translations for 5 languages (de, en, nb, nl, sv)
Impact: Users can now build sophisticated automations based on period timing
('start dishwasher if remaining_minutes > 60'), display countdowns in
dashboards, and get clear visual feedback about period states. All sensors
provide meaningful values at all times, making automation logic simpler.
Added timestamp attributes to all sensors and enhanced the dynamic icon
system for comprehensive price sensor coverage with rolling hour support.
TIMESTAMP ATTRIBUTES:
Core Changes:
- sensor/attributes.py:
* Enhanced add_average_price_attributes() to track extreme intervals
for min/max sensors and add appropriate timestamps
* Added _update_extreme_interval() helper to reduce complexity
* Extended add_volatility_type_attributes() with timestamp logic for
all 4 volatility types (today/tomorrow/today_tomorrow/next_24h)
* Fixed current_interval_price timestamp assignment (use interval_data)
Timestamp Logic:
- Interval-based sensors: Use startsAt of specific 15-minute interval
- Min/Max sensors: Use startsAt of interval with extreme price
- Average sensors: Use startsAt of first interval in window
- Volatility sensors: Use midnight (00:00) for calendar day sensors,
current time for rolling 24h window
- Daily sensors: Already used fallback to midnight (verified)
ICON SYSTEM ENHANCEMENTS:
Major Extensions:
- entity_utils/icons.py:
* Created get_rolling_hour_price_level_for_icon() implementing
5-interval window aggregation matching sensor calculation logic
* Extended get_price_sensor_icon() coverage from 1 to 4 sensors:
- current_interval_price (existing)
- next_interval_price (NEW - dynamic instead of static)
- current_hour_average_price (NEW - uses rolling hour aggregation)
- next_hour_average_price (NEW - uses rolling hour aggregation)
* Added imports for aggregate_level_data and find_rolling_hour_center_index
Documentation:
- sensor/definitions.py:
* Updated 30+ sensor descriptions with detailed icon behavior comments
* Changed next_interval_price from static to dynamic icon
* Documented dynamic vs static icons for all sensor types
* Added clear icon mapping source documentation
SENSOR KEY RENAMING:
Renamed for clarity (current_hour_average → current_hour_average_price):
- sensor/core.py: Updated value getters and cached data lookup
- sensor/definitions.py: Updated entity descriptions
- sensor/attributes.py: Updated key references in attribute builders
- coordinator.py: Updated TIME_SENSITIVE_ENTITY_KEYS set
- const.py: Updated comment documentation
Translation Updates:
- custom_translations/*.json (5 files): Updated sensor keys
- translations/*.json (5 files): Updated sensor keys
Impact:
- All sensors now have timestamp attribute showing applicable time/interval
- Icon system provides richer visual feedback for more sensor types
- Consistent sensor naming improves code readability
- Users get temporal context for all sensor values
- Dynamic icons adapt to price conditions across more sensors
Added 6 new sensors for yesterday/today/tomorrow aggregated price
levels and ratings, following the same calculation logic as existing
current/next interval sensors.
New sensors:
- yesterday_price_level, today_price_level, tomorrow_price_level
- yesterday_price_rating, today_price_rating, tomorrow_price_rating
Implementation details:
- Added DAILY_LEVEL_SENSORS and DAILY_RATING_SENSORS in sensor/definitions.py
- Implemented _get_daily_aggregated_value() in sensor/core.py using
existing aggregate_level_data() and aggregate_rating_data() helpers
- Extended icon support in entity_utils/icons.py for dynamic icons
- Added icon_color attributes in sensor/attributes.py with helper
functions _get_day_key_from_sensor_key() and _add_fallback_timestamp()
- Complete translations in all 5 languages (de, en, nb, nl, sv):
* Standard translations: sensor names
* Custom translations: description, long_description, usage_tips
Impact: Users can now see aggregated daily price levels and ratings
for yesterday, today, and tomorrow at a glance, making it easier to
compare overall price situations across days and plan energy consumption
accordingly. Sensors use same aggregation logic as hourly sensors for
consistency.
Split binary_sensor.py (645 lines) into binary_sensor/ package with
4 modules following the established sensor/ pattern for consistency
and maintainability.
Package structure:
- binary_sensor/__init__.py (32 lines): Platform setup
- binary_sensor/definitions.py (46 lines): ENTITY_DESCRIPTIONS, constants
- binary_sensor/attributes.py (443 lines): Attribute builder functions
- binary_sensor/core.py (282 lines): TibberPricesBinarySensor class
Changes:
- Created binary_sensor/ package with __init__.py importing from .core
- Extracted ENTITY_DESCRIPTIONS and constants to definitions.py
- Moved 13 attribute builders to attributes.py (get_price_intervals_attributes,
build_async/sync_extra_state_attributes, add_* helpers)
- Moved TibberPricesBinarySensor class to core.py with state logic and
icon handling
- Used keyword-only parameters to satisfy Ruff PLR0913 (too many args)
- Applied absolute imports (custom_components.tibber_prices.*) in modules
All 4 binary sensors tested and working:
- peak_price_period
- best_price_period
- connection
- tomorrow_data_available
Documentation updated:
- AGENTS.md: Architecture Overview, Component Structure, Common Tasks
- binary-sensor-refactoring-plan.md: Marked ✅ COMPLETED with summary
Impact: Symmetric platform structure (sensor/ ↔ binary_sensor/). Easier
to add new binary sensors following documented pattern. No user-visible
changes.
* Initial plan
* Fix AttributeError for homes without active subscription
Co-authored-by: jpawlowski <75446+jpawlowski@users.noreply.github.com>
---------
Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: jpawlowski <75446+jpawlowski@users.noreply.github.com>
- Introduced a comprehensive refactoring guide detailing when and how to plan major refactorings, including a structured planning process and real-world examples.
- Created a README for the planning directory, outlining its purpose, document lifecycle, and best practices for creating planning documents.
