Replaced incorrect day_volatility_% on binary sensor with actual coefficient_of_variation attribute from sensor.tibber_home_volatility_today
Co-authored-by: jpawlowski <75446+jpawlowski@users.noreply.github.com>
Changed from numeric_state with enum sensor to template using day_volatility_% attribute from binary sensor
Co-authored-by: jpawlowski <75446+jpawlowski@users.noreply.github.com>
Changed all documentation links from version-specific tags (v0.20.0) to
main branch references. This makes documentation maintenance-free - links
stay current as code evolves.
Updated 38 files across:
- docs/developer/docs/ (7 files)
- docs/developer/versioned_docs/version-v0.21.0/ (8 files)
- docs/developer/versioned_docs/version-v0.22.0/ (8 files)
Impact: Documentation links no longer break when new versions are released.
Links always point to current code implementation.
Expanded user documentation with detailed guidance on average sensors:
1. sensors.md (+182 lines):
- New 'Average Price Sensors' section with mean vs median explanation
- 3 real-world automation examples (heat pump, dishwasher, EV charging)
- Display configuration guide with use-case recommendations
2. configuration.md (+75 lines):
- New 'Average Sensor Display Settings' section
- Comparison table of display modes (mean/median/both)
- Attribute availability details and recorder implications
3. Minor updates to installation.md and versioned docs
Impact: Users can now understand when to use mean vs median and how to
configure display format for their specific automation needs.
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.
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
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.
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.
Add dynamic rolling window mode to get_chartdata and get_apexcharts_yaml
services that automatically adapts to data availability.
When 'day' parameter is omitted, services return 48-hour window:
- With tomorrow data (after ~13:00): today + tomorrow
- Without tomorrow data: yesterday + today
Changes:
- Implement rolling window logic in get_chartdata using has_tomorrow_data()
- Generate config-template-card wrapper in get_apexcharts_yaml for dynamic
ApexCharts span.offset based on tomorrow_data_available binary sensor
- Update service descriptions in services.yaml
- Add rolling window descriptions to all translations (de, en, nb, nl, sv)
- Document rolling window mode in docs/user/services.md
- Add ApexCharts examples with prerequisites in docs/user/automation-examples.md
BREAKING CHANGE: get_apexcharts_yaml rolling window mode requires
config-template-card in addition to apexcharts-card for dynamic offset
calculation.
Impact: Users can create auto-adapting 48h price charts without manual day
selection. Fixed day views (day: today/yesterday/tomorrow) still work with
apexcharts-card only.
Major restructuring of the scripts/ directory with consistent output
formatting, improved organization, and stricter error handling.
Breaking Changes:
- Updated development environment to Home Assistant 2025.7+
- Removed Python 3.12 compatibility (HA 2025.7+ requires Python 3.13)
- Updated all HA core requirements from 2025.7 requirement files
- Added new dependencies: python-multipart, uv (for faster package management)
- Updated GitHub Actions workflows to use Python 3.13
Changes:
- Created centralized output library (scripts/.lib/output.sh)
- Unified color codes and Unicode symbols
- Consistent formatting functions (log_header, log_success, log_error, etc.)
- Support for embedded formatting codes (${BOLD}, ${GREEN}, etc.)
- Reorganized into logical subdirectories:
- scripts/setup/ - Setup and maintenance scripts
- bootstrap: Install/update dependencies (used in CI/CD)
- setup: Full DevContainer setup (pyright, copilot, HACS)
- reset: Reset config/ directory to fresh state (NEW)
- sync-hacs: Sync HACS integrations
- scripts/release/ - Release management scripts
- prepare: Version bump and tagging
- suggest-version: Semantic version suggestion
- generate-notes: Release notes generation
- check-if-released: Check release status
- hassfest: Local integration validation
- Updated all scripts with:
- set -euo pipefail for stricter error handling
- Consistent SCRIPT_DIR pattern for reliable sourcing
- Professional output with colors and emojis
- Unified styling across all 17 scripts
- Removed redundant scripts:
- scripts/update (was just wrapper around bootstrap)
- scripts/json_schemas/ (moved to schemas/json/)
- Enhanced clean script:
- Improved artifact cleanup
- Better handling of accidental package installations
- Hints for reset and deep clean options
- New reset script features:
- Standard mode: Keep configuration.yaml
- Full mode (--full): Reset configuration.yaml from git
- Automatic re-setup after reset
- Updated documentation:
- AGENTS.md: Updated script references and workflow guidance
- docs/development/: Updated all references to new script structure
Impact: Development environment now requires Python 3.13 and Home Assistant
2025.7+. Developers get consistent, professional script output with better
error handling and logical organization. Single source of truth for styling
makes future updates trivial.
- Introduced `get_intervals_for_day_offsets` helper to streamline access to price intervals for yesterday, today, and tomorrow.
- Updated various components to replace direct access to `priceInfo` with the new helper, ensuring a flat structure for price intervals.
- Adjusted calculations and data processing methods to accommodate the new data structure.
- Enhanced documentation to reflect changes in caching strategy and data structure.
Introduced TibberPricesMidnightHandler to prevent duplicate midnight
turnover when multiple timers fire simultaneously.
Problem: Timer #1 (API poll) and Timer #2 (quarter-hour refresh) both
wake at midnight, each detecting day change and triggering cache clear.
Race condition caused duplicate turnover operations.
Solution:
- Atomic flag coordination: First timer sets flag, subsequent timers skip
- Persistent state survives HA restart (cache stores last_turnover_time)
- Day-boundary detection: Compares current.date() vs last_check.date()
- 13 comprehensive tests covering race conditions and HA restart scenarios
Architecture:
- coordinator/midnight_handler.py: 165 lines, atomic coordination logic
- coordinator/core.py: Integrated handler in coordinator initialization
- coordinator/listeners.py: Delegate midnight check to handler
Impact: Eliminates duplicate cache clears at midnight. Single atomic
turnover operation regardless of how many timers fire simultaneously.
Periods can now naturally cross midnight boundaries, and new diagnostic
attributes help users understand price classification changes at midnight.
**New Features:**
1. Midnight-Crossing Period Support (relaxation.py):
- group_periods_by_day() assigns periods to ALL spanned days
- Periods crossing midnight appear in both yesterday and today
- Enables period formation across calendar day boundaries
- Ensures min_periods checking works correctly at midnight
2. Extended Price Data Window (relaxation.py):
- Period calculation now uses full 3-day data (yesterday+today+tomorrow)
- Enables natural period formation without artificial midnight cutoff
- Removed date filter that excluded yesterday's prices
3. Day Volatility Diagnostic Attributes (period_statistics.py, core.py):
- day_volatility_%: Daily price spread as percentage (span/avg × 100)
- day_price_min/max/span: Daily price range in minor currency (ct/øre)
- Helps detect when midnight classification changes are economically significant
- Uses period start day's reference prices for consistency
**Documentation:**
4. Design Principles (period-calculation-theory.md):
- Clarified per-day evaluation principle (always was the design)
- Added comprehensive section on midnight boundary handling
- Documented volatility threshold separation (sensor vs period filters)
- Explained market context for midnight price jumps (EPEX SPOT timing)
5. User Guides (period-calculation.md, automation-examples.md):
- Added \"Midnight Price Classification Changes\" troubleshooting section
- Provided automation examples using volatility attributes
- Explained why Best→Peak classification can change at midnight
- Documented level filter volatility threshold behavior
**Architecture:**
- Per-day evaluation: Each interval evaluated against its OWN day's min/max/avg
(not period start day) ensures mathematical correctness across midnight
- Period boundaries: Periods can naturally cross midnight but may split when
consecutive days differ significantly (intentional, mathematically correct)
- Volatility thresholds: Sensor thresholds (user-configurable) remain separate
from period filter thresholds (fixed internal) to prevent unexpected behavior
Impact: Periods crossing midnight are now consistently visible before and
after midnight turnover. Users can understand and handle edge cases where
price classification changes at midnight on low-volatility days.
BREAKING CHANGE: Period overlap resolution now merges adjacent/overlapping periods
instead of marking them as extensions. This simplifies automation logic and provides
clearer period boundaries for users.
Previous Behavior:
- Adjacent periods created by relaxation were marked with is_extension=true
- Multiple short periods instead of one continuous period
- Complex logic needed to determine actual period length in automations
New Behavior:
- Adjacent/overlapping periods are merged into single continuous periods
- Newer period's relaxation attributes override older period's
- Simpler automation: one period = one continuous time window
Changes:
- Period Overlap Resolution (new file: period_overlap.py):
* Added merge_adjacent_periods() to combine periods and preserve attributes
* Rewrote resolve_period_overlaps() with simplified merge logic
* Removed split_period_by_overlaps() (no longer needed)
* Removed is_extension marking logic
* Removed unused parameters: min_period_length, baseline_periods
- Relaxation Strategy (relaxation.py):
* Removed all is_extension filtering from period counting
* Simplified standalone counting to just len(periods)
* Changed from period_merging import to period_overlap import
* Added MAX_FLEX_HARD_LIMIT constant (0.50)
* Improved debug logging for merged periods
- Code Quality:
* Fixed all remaining linter errors (N806, PLR2004, PLR0912)
* Extracted magic values to module-level constants:
- FLEX_SCALING_THRESHOLD = 0.20
- SCALE_FACTOR_WARNING_THRESHOLD = 0.8
- MAX_FLEX_HARD_LIMIT = 0.50
* Added appropriate noqa comments for unavoidable patterns
- Configuration (from previous work in this session):
* Removed CONF_RELAXATION_STEP_BEST, CONF_RELAXATION_STEP_PEAK
* Hard-coded 3% relaxation increment for reliability
* Optimized defaults: RELAXATION_ATTEMPTS 8→11, ENABLE_MIN_PERIODS False→True,
MIN_PERIODS undefined→2
* Removed relaxation_step UI fields from config flow
* Updated all 5 translation files
- Documentation:
* Updated period_handlers/__init__.py: period_merging → period_overlap
* No user-facing docs changes needed (already described continuous periods)
Rationale - Period Merging:
User experience was complicated by fragmented periods:
- Automations had to check multiple adjacent periods
- Binary sensors showed ON/OFF transitions within same cheap time
- No clear way to determine actual continuous period length
With merging:
- One continuous cheap time = one period
- Binary sensor clearly ON during entire period
- Attributes show merge history via merged_from dict
- Relaxation info preserved from newest/highest flex period
Rationale - Hard-Coded Relaxation Increment:
The configurable relaxation_step parameter proved problematic:
- High base flex + high step → rapid explosion (40% base + 10% step → 100% in 6 steps)
- Users don't understand the multiplicative nature
- 3% increment provides optimal balance: 11 attempts to reach 50% hard cap
Impact:
- Existing installations: Periods may appear longer (merged instead of split)
- Automations benefit from simpler logic (no is_extension checks needed)
- Custom relaxation_step values will use new 3% increment
- Users may need to adjust relaxation_attempts if they relied on high step sizes
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.
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.
