Add user-configurable option to choose between median and arithmetic mean
as the displayed value for all 14 average price sensors, with the alternate
value exposed as attribute.
BREAKING CHANGE: Average sensor default changed from arithmetic mean to
median. Users who rely on arithmetic mean behavior may use the price_mean attribue now, or must manually reconfigure
via Settings → Devices & Services → Tibber Prices → Configure → General
Settings → "Average Sensor Display" → Select "Arithmetic Mean" to get this as sensor state.
Affected sensors (14 total):
- Daily averages: average_price_today, average_price_tomorrow
- 24h windows: trailing_price_average, leading_price_average
- Rolling hour: current_hour_average_price, next_hour_average_price
- Future forecasts: next_avg_3h, next_avg_6h, next_avg_9h, next_avg_12h
Implementation:
- All average calculators now return (mean, median) tuples
- User preference controls which value appears in sensor state
- Alternate value automatically added to attributes
- Period statistics (best_price/peak_price) extended with both values
Technical changes:
- New config option: CONF_AVERAGE_SENSOR_DISPLAY (default: "median")
- Calculator functions return tuples: (avg, median)
- Attribute builders: add_alternate_average_attribute() helper function
- Period statistics: price_avg → price_mean + price_median
- Translations: Updated all 5 languages (de, en, nb, nl, sv)
- Documentation: AGENTS.md, period-calculation.md, recorder-optimization.md
Migration path:
Users can switch back to arithmetic mean via:
Settings → Integrations → Tibber Prices → Configure
→ General Settings → "Average Sensor Display" → "Arithmetic Mean"
Impact: Median is more resistant to price spikes, providing more stable
automation triggers. Statistical analysis from coordinator still uses
arithmetic mean (e.g., trailing_avg_24h for rating calculations).
Co-developed-with: GitHub Copilot <copilot@github.com>
Add repair notification system with three auto-clearing repair types:
- Tomorrow data missing (after 18:00)
- API rate limit exceeded (3+ consecutive errors)
- Home not found in Tibber account
Includes:
- coordinator/repairs.py: Complete TibberPricesRepairManager implementation
- Enhanced API error handling with explicit 5xx handling
- Translations for 5 languages (EN, DE, NB, NL, SV)
- Developer documentation in docs/developer/docs/repairs-system.md
Impact: Users receive actionable notifications for important issues instead
of only seeing stale data in logs.
Implemented comprehensive entity lifecycle patterns following Home Assistant
best practices for proper state management and history tracking.
Changes:
- entity.py: Added available property to base class
- Returns False when coordinator has no data or last_update_success=False
- Prevents entities from showing stale data during errors
- Auth failures trigger reauth flow via ConfigEntryAuthFailed
- sensor/core.py: Added state restore and background task handling
- Changed inheritance: SensorEntity → RestoreSensor
- Restore native_value from SensorExtraStoredData in async_added_to_hass()
- Chart sensors restore response data from attributes
- Converted blocking service calls to background tasks using hass.async_create_task()
- Eliminates 194ms setup warning by making async_added_to_hass non-blocking
- binary_sensor/core.py: Added state restore and force_update
- Changed inheritance: BinarySensorEntity → RestoreEntity + BinarySensorEntity
- Restore is_on state in async_added_to_hass()
- Added available property override for connection sensor (always True)
- Added force_update property for connection sensor to track all state changes
- Other binary sensors use base available logic
- AGENTS.md: Documented entity lifecycle patterns in Common Pitfalls
- Added "Entity Lifecycle & State Management" section
- Documents available, state restore, and force_update patterns
- Explains why each pattern matters for proper HA integration
Impact: Entities no longer show stale data during errors, history has no gaps
after HA restart, connection state changes are properly tracked, and config
entry setup completes in <200ms (under HA threshold).
All patterns verified against HA developer documentation:
https://developers.home-assistant.io/docs/core/entity/
Update all references to reflect two separate Docusaurus instances
(user + developer) with proper file paths and navigation management.
Changes:
- AGENTS.md: Document Docusaurus structure and file organization
- CONTRIBUTING.md: Add Docusaurus workflow guidelines
- docs/developer/docs/period-calculation-theory.md: Fix cross-reference
- docs/developer/sidebars.ts: Add recorder-optimization to navigation
Documentation organized as:
- docs/user/docs/*.md (user guides, via sidebars.ts)
- docs/developer/docs/*.md (developer guides, via sidebars.ts)
- AGENTS.md (AI patterns, conventions)
Impact: AI and contributors know where to place new documentation.
Add comprehensive documentation for _unrecorded_attributes
implementation, categorizing all excluded attributes with reasoning,
expected database impact, and decision framework for future attributes.
Added to Developer Docs → Advanced Topics navigation.
Content includes:
- 7 exclusion categories with examples
- Space savings calculations (60-85% reduction)
- Decision framework for new attributes
- Testing and validation guidelines
- SQL queries for verification
Implement _unrecorded_attributes in both sensor and binary_sensor
entities to prevent Home Assistant Recorder database bloat.
Excluded attributes (60-85% size reduction per state):
- Descriptions/help text (static, large strings)
- Large nested structures (periods, trend_attributes, chart data)
- Frequently changing diagnostics (icon_color, cache_age)
- Static/rarely changing config (currency, resolution)
- Temporary/time-bound data (next_api_poll, last_*)
- Redundant/derived data (price_spread, diff_%)
Kept for history analysis:
- timestamp (always first), all price values
- Period timing (start, end, duration_minutes)
- Price statistics (avg, min, max)
- Boolean status flags, relaxation_active
Impact: Reduces attribute size from ~3-8 KB to ~0.5-1.5 KB per state
change. Expected savings: ~1 GB per month for typical installation.
See: https://developers.home-assistant.io/docs/core/entity/#excluding-state-attributes-from-recorder-history
Unified enum representation across all translation files and improved
consistency of localization patterns.
Key changes:
- Replaced uppercase enum constants (VERY_CHEAP, LOW, RISING) with
localized lowercase values (sehr günstig, niedrig, steigend) across
all languages in both translations/ and custom_translations/
- Removed **bold** markdown from sensor attributes (custom_translations/)
as it doesn't render in extra_state_attributes UI
- Preserved **bold** in Config Flow descriptions (translations/) where
markdown is properly rendered
- Corrected German formality: "Sie" → "du" throughout all descriptions
- Completed missing Config Flow translations in Dutch, Swedish, and
Norwegian (~45 fields: period_settings, flexibility_settings,
relaxation_and_target_periods sections)
- Fixed chart_data_export and chart_metadata sensor classification
(moved from binary_sensor to sensor as they are ENUM type)
- Corrected sensor placement in custom_translations/ (all 5 languages)
Files changed: 10 (5 translations/ + 5 custom_translations/)
Lines: +203, -222
Impact: All 5 languages now use consistent, properly formatted
localized enum values. Config Flow UI displays correctly formatted
examples with bold highlighting. Sensor attributes show clean text
without raw markdown syntax. German uses informal "du" tone throughout.
Change relative path ../development/ to absolute path /hass.tibber_prices/developer/
since user and developer docs are now separate Docusaurus instances.
Fixes broken link warning during build.
- Created a new documentation file `chart-examples.md` detailing various chart configurations available through the `tibber_prices.get_apexcharts_yaml` action.
- Included descriptions, dependencies, and YAML generation examples for four chart modes: Today's Prices, Rolling 48h Window, and Rolling Window Auto-Zoom.
- Added a section on dynamic Y-axis scaling and best price period highlights.
- Established prerequisites for using the charts, including required cards and customization tips.
- Introduced a new `README.md` in the images/charts directory to document available chart screenshots and guidelines for capturing them.
Implementation flaw discovered: gradient_stop calculated as
`(avg - min) / (max - min)` for combined data produces one value
applied to ALL series. Each series (VERY_CHEAP, NORMAL, VERY_EXPENSIVE)
has different min/max ranges, so the same gradient stop position
represents a different absolute price in each series.
Example failure case:
- VERY_CHEAP: 10-20 ct → 50% at 15 ct (below overall avg!)
- VERY_EXPENSIVE: 40-50 ct → 50% at 45 ct (above overall avg!)
Conclusion: Gradient shows middle of each series range, not average
price position.
Solution: Fixed 50% gradient purely for visual appeal. Semantic
information provided by:
- Series colors (CHEAP/NORMAL/EXPENSIVE)
- Grid lines (implicitly show average)
- Dynamic Y-axis bounds (optimal scaling via chart_metadata sensor)
Changes:
- sensor/chart_metadata.py: Remove gradient_stop extraction
- services/get_apexcharts_yaml.py: Fixed gradient at [50, 100]
- custom_translations/*.json: Remove gradient_stop references
Impact: Honest visualization with no false semantic signals. Feature
was never released, clean removal without migration.
Implemented new chart_metadata diagnostic sensor that provides essential
chart configuration values (yaxis_min, yaxis_max, gradient_stop) as
attributes, enabling dynamic chart configuration without requiring
async service calls in templates.
Sensor implementation:
- New chart_metadata.py module with metadata-only service calls
- Automatically calls get_chartdata with metadata="only" parameter
- Refreshes on coordinator updates (new price data or user data)
- State values: "pending", "ready", "error"
- Enabled by default (critical for chart features)
ApexCharts YAML generator integration:
- Checks for chart_metadata sensor availability before generation
- Uses template variables to read sensor attributes dynamically
- Fallback to fixed values (gradient_stop=50%) if sensor unavailable
- Creates separate notifications for two independent issues:
1. Chart metadata sensor disabled (reduced functionality warning)
2. Required custom cards missing (YAML won't work warning)
- Both notifications explain YAML generation context and provide
complete fix instructions with regeneration requirement
Configuration:
- Supports configuration.yaml: tibber_prices.chart_metadata_config
- Optional parameters: day, minor_currency, resolution
- Defaults to minor_currency=True for ApexCharts compatibility
Translation additions:
- Entity name and state translations (all 5 languages)
- Notification messages for sensor unavailable and missing cards
- best_price_period_name for tooltip formatter
Binary sensor improvements:
- tomorrow_data_available now enabled by default (critical for automations)
- data_lifecycle_status now enabled by default (critical for debugging)
Impact: Users get dynamic chart configuration with optimized Y-axis scaling
and gradient positioning without manual calculations. ApexCharts YAML
generation now provides clear, actionable notifications when issues occur,
ensuring users understand why functionality is limited and how to fix it.
Implemented comprehensive metadata calculation for chart data export service
with automatic Y-axis scaling and gradient positioning based on actual price
statistics.
Changes:
- Added 'metadata' parameter to get_chartdata service (include/only/none)
- Implemented _calculate_metadata() with per-day price statistics
* min/max/avg/median prices
* avg_position and median_position (0-1 scale for gradient stops)
* yaxis_suggested bounds (floor(min)-1, ceil(max)+1)
* time_range with day boundaries
* currency info with symbol and unit
- Integrated metadata into rolling_window modes via config-template-card
* Pre-calculated yaxis bounds (no async issues in templates)
* Dynamic gradient stops based on avg_position
* Server-side calculation ensures consistency
Visual refinements:
- Best price overlay opacity reduced to 0.05 (ultra-subtle green hint)
- Stroke width increased to 1.5 for better visibility
- Gradient opacity adjusted to 0.45 with "light" shade
- Marker configuration: size 0, hover size 2, strokeWidth 1
- Header display: Only show LOW/HIGH rating_levels (min/max prices)
* Conditional logic excludes NORMAL and level types
* Entity state shows meaningful extrema values
- NOW marker label removed for rolling_window_autozoom mode
* Static position at 120min lookback makes label misleading
Code cleanup:
- Removed redundant all_series_config (server-side data formatting)
- Currency names capitalized (Cents, Øre, Öre, Pence)
Translation updates:
- Added metadata selector translations (de, en, nb, nl, sv)
- Added metadata field description in services
- Synchronized all language files
Impact: Users get dynamic Y-axis scaling based on actual price data,
eliminating manual configuration. Rolling window charts automatically
adjust axis bounds and gradient positioning. Header shows only
meaningful extreme values (daily min/max). All data transformation
happens server-side for optimal performance and consistency.
Added two new rolling window options for get_apexcharts_yaml service to provide
flexible dynamic chart visualization:
- rolling_window: Fixed 48h window that automatically shifts between
yesterday+today and today+tomorrow based on data availability
- rolling_window_autozoom: Same as rolling_window but with progressive zoom-in
(2h lookback + remaining time until midnight, updates every 15min)
Implementation changes:
- Updated service schema validation to accept new day options
- Added entity mapping patterns for both rolling modes
- Implemented minute-based graph_span calculation with quarter-hour alignment
- Added config-template-card integration for dynamic span updates
- Used current_interval_price sensor as 15-minute update trigger
- Unified data loading: both rolling modes omit day parameter for dynamic selection
- Applied ternary operator pattern for cleaner day_param logic
- Made grid lines more subtle (borderColor #f5f5f5, strokeDashArray 0)
Translation updates:
- Added selector options in all 5 languages (de, en, nb, nl, sv)
- Updated field descriptions to include default behavior and new options
- Documented that rolling window is default when day parameter omitted
Documentation updates:
- Updated user docs (actions.md, automation-examples.md) with new options
- Added detailed explanation of day parameter options
- Included examples for both rolling_window and rolling_window_autozoom modes
Impact: Users can now create auto-adapting ApexCharts that show 48h rolling
windows with optional progressive zoom throughout the day. Requires
config-template-card for dynamic behavior.
Period data in array_of_arrays format now generates proper segment structure
for stepline charts. Each period produces 2-3 data points depending on
insert_nulls parameter:
1. Start time with price (begin period)
2. End time with price (hold price level)
3. End time with NULL (terminate segment, only if insert_nulls='segments'/'all')
This enables ApexCharts to correctly display periods as continuous blocks with
clean gaps between them. Previously only start point was generated, causing
periods to render as single points instead of continuous segments.
Changes:
- formatters.py: Updated get_period_data() to generate 2-3 points per period
- formatters.py: Added insert_nulls parameter to control NULL termination
- get_chartdata.py: Pass insert_nulls parameter to get_period_data()
- get_apexcharts_yaml.py: Set insert_nulls='segments' for period overlay
- get_apexcharts_yaml.py: Preserve NULL values in data_generator mapping
- get_apexcharts_yaml.py: Store original price for potential tooltip access
- tests: Added comprehensive period data format tests
Impact: Best price and peak price period overlays now display correctly as
continuous blocks with proper segment separation in ApexCharts cards.
Release workflow now automatically deletes tags when version number doesn't
match commit types (e.g., PATCH bump when MINOR needed for features).
Changes:
- New step 'Delete inappropriate version tag' runs after version_check
- Automatically deletes tag and exits with error if version inappropriate
- All subsequent steps conditional on successful version validation
- Improved warning message: removed confusing 'X.Y.Z' placeholder
- Added notice: 'This tag will be automatically deleted in the next step'
- Removed redundant 'Version Check Summary' step
Impact: Users get immediate, clear feedback when pushing wrong version tags.
Workflow fails fast with actionable error message instead of creating release
with embedded warning. No manual tag deletion needed.
Binary sensor _handle_coordinator_update() was empty, blocking all push updates
from coordinator. This prevented binary sensors from reflecting state changes
immediately after API fetch or error conditions.
Changes:
- Implement _handle_coordinator_update() to call async_write_ha_state()
- All binary sensors now receive push updates when coordinator has new data
Binary sensors affected:
- tomorrow_data_available: Now reflects data availability immediately after API fetch
- connection: Now shows disconnected state immediately on auth/API errors
- chart_data_export: Now updates chart data when price data changes
- peak_price_period, best_price_period: Get push updates when periods change
- data_lifecycle_status: Gets push updates on status changes
Impact: Binary sensors update in real-time instead of waiting for next timer
cycle or user interaction. Fixes stale state issue where tomorrow_data_available
remained off despite data being available, and connection sensor not reflecting
authentication failures immediately.
Restructured 5 options flow steps (current_interval_price_rating, best_price,
peak_price, price_trend, volatility) to use Home Assistant's sections feature
for better UI organization and logical grouping.
Changes:
- current_interval_price_rating: Single section "price_rating_thresholds"
- best_price: Three sections (period_settings, flexibility_settings,
relaxation_and_target_periods)
- peak_price: Three sections (period_settings, flexibility_settings,
relaxation_and_target_periods)
- price_trend: Single section "price_trend_thresholds"
- volatility: Single section "volatility_thresholds"
Each section includes name, description, data fields, and data_description
fields following HA translation schema requirements.
Updated all 5 language files (de, en, nb, nl, sv) with new section structure
while preserving existing field descriptions and translations.
Impact: Options flow now displays configuration fields in collapsible,
logically grouped sections with clear section headers, improving UX for
complex multi-parameter configuration steps. No functional changes to
configuration logic or validation.
