Remove the DATA_STATISTICS_REVIEW_REQUIRED flag and all associated
persistence logic. The flag approach was over-engineered: we cannot
detect whether the Recorder statistics have been fixed, and requiring
the user to re-save display settings as acknowledgement is bad UX.
New design: show the repair notice once when the mode changes.
The user dismisses it when done reviewing. The HA Recorder will
independently show its own unit-change dialog — that is sufficient.
Changes:
- Remove DATA_STATISTICS_REVIEW_REQUIRED constant from const.py
- Remove _check_statistics_review_repair() from __init__.py
- Remove ir import from __init__.py (no longer needed there)
- Remove flag set/clear logic from options_flow.py
- Change is_persistent=False (no restart persistence needed)
- Update all 5 translations: restore simple "Dismiss this notice" ending
We have no way to programmatically detect whether the Recorder statistics
have been fixed. Dismissing the Repairs notification does not mean the
problem is resolved, only that the user has seen it.
Revert to delete + create on every async_setup_entry when the flag is set.
This guarantees the issue is visible after every restart until the user
explicitly acknowledges completion by re-saving the display settings in
the options flow.
Remove the dismissed_version auto-clear logic that was treating dismissal
as acknowledgement (it was not).
Update all 5 translation files: replace "Dismiss this notice" with
instructions to re-save display settings as the only way to permanently
close the notification.
Released-Bug: no
async_create_issue preserves dismissed_version when called with the same
issue_id. This means that if a user had previously dismissed the repair
issue, changing the currency mode again would set the flag but the issue
would stay hidden (because it still has a dismissed_version).
Fix: use delete + create in the options flow when mode_changed=True.
This resets dismissed_version so the new instance is always visible.
The __init__.py path (HA restart with flag set) continues to use plain
async_create_issue so that a restart alone does not un-dismiss an issue
the user already acknowledged.
Released-Bug: no
The previous implementation used delete + create on every async_setup_entry,
which reset dismissed_version and forced the issue to reappear after every
HA restart regardless of whether the user had dismissed it.
Fix: use async_create_issue (internally get-or-create, preserves
dismissed_version when params are unchanged) instead of delete + create.
The options flow still uses delete + create when the mode changes again,
ensuring the issue is forced into view for any new change.
Also auto-clear the DATA_STATISTICS_REVIEW_REQUIRED flag from
config_entry.data when the issue is detected as dismissed on setup,
so the flag does not linger indefinitely after the user has acknowledged
the issue.
Released-Bug: no
Enhance the script to only check for existing releases if the specified tag exists locally. Added authentication check for the GitHub CLI before querying releases, with informative logging for users.
Impact: Users will receive clearer messages regarding the status of GitHub releases and authentication requirements.
Updated the sensor reference documentation to remove obsolete price phase sensors, ensuring clarity and relevance for users.
Impact: Users will see a cleaner and more accurate list of available sensors.
Introduced comprehensive documentation for price phase sensors, detailing their functionality and usage. Updated links in existing documentation for clarity.
Impact: Users can now understand and utilize price phase sensors effectively in their configurations.
Introduced new documentation files covering various configuration aspects such as chart data export, currency display, general settings, peak price periods, price levels, price ratings, price trends, and volatility. Each section provides detailed explanations of settings, their impacts, and migration guidance for legacy features.
Impact: Users gain clear guidance on configuring the Tibber Prices integration, enhancing usability and understanding of features.
### Notes
- New files include config-chart-export.md, config-currency.md, config-general.md, config-peak-price.md, config-price-level.md, config-price-rating.md, config-price-trend.md, config-runtime-overrides.md, and config-volatility.md.
- Updated sidebar for improved navigation within the documentation.
Updated the legacy migration section to specify that only changes released under a public version tag require migration code. Added clarifications regarding uncommitted changes and new features not needing migration.
Impact: Provides clearer guidance for developers on handling legacy migrations, reducing potential confusion.
_resolve_time_with_day_offset() was calling dt_util.now() internally
instead of using the injected now parameter. This caused incorrect date
calculations in tests and any caller that passes a specific reference time.
Also add missing price_rank_* sensor keys to TIME_SENSITIVE_ENTITY_KEYS
in coordinator/constants.py so quarter-hour refresh is registered for all
11 price rank sensors (current/next/previous interval and hour variants).
Rename dt as dt_utils → dt as dt_util (ICN001) across 11 files to follow
the project-wide import alias convention. Apply ruff auto-fixes for import
ordering and collapsing single-item imports throughout the codebase.
Released-Bug: no
Adjusted the required Python version in the project configuration to ensure compatibility with the latest features and improvements.
Impact: Users must have Python 3.14.2 or higher to run the project.
Restructure configuration.md: separate "stored precision" from "default display
precision" tables to avoid confusion between internal representation and what is
shown in dashboards. Add note that HA shows its own unit-change dialog (delayed);
our repair issue appears immediately as step 1. Recommend deleting old statistics
data rather than re-labeling, which would leave wrong values with the new unit.
Update faq.md examples to use display precision values for consistency with the
documentation.
Add DATA_STATISTICS_REVIEW_REQUIRED flag to config_entry.data. Set on
currency mode change, cleared on same-mode save. On every async_setup_entry
with flag set, delete and recreate the repair issue so it reappears after
HA restart even if previously dismissed.
Repair issue text explains that HA Recorder shows its own unit-change
dialog (delayed) and recommends deleting old statistic data rather than
re-labeling, which would leave wrong values with the new unit.
Impact: Users are notified to review statistics and automations after
switching between base/subunit currency mode. Notification persists across
HA restarts until acknowledged by saving display settings again.
Add get_display_precision() to const.py returning DISPLAY_PRECISION_SUBUNIT (2)
or DISPLAY_PRECISION_BASE (4) based on config. Replace hardcoded round(..., 2)
with get_display_precision() in all calculators and attribute builders.
Add _update_suggested_precision() to sensor core; syncs entity registry
suggested_display_precision on every coordinator update.
Interval price sensors get full precision (2 or 4 dp); other MONETARY sensors
get half precision (1 or 2 dp) as sensible default.
Impact: Price sensor states and attributes now correctly use 4 decimal places
in base-currency mode (was always 2). Display precision in dashboards updates
automatically when currency mode changes.
Enhance the documentation for volatility sensors by explaining that the maximum price rank will never reach 100% and providing a YAML automation example for managing device usage during peak pricing.
Impact: Users gain a clearer understanding of price rank behavior and practical automation guidance.
Refactor the contribution guidelines to enhance readability and consistency in formatting. Adjusted code blocks and list formatting for better visual structure.
Impact: Contributors will find it easier to follow the guidelines when contributing to the project.
---
docs(README): update automation examples for better readability
Reformatted YAML automation examples in the README to improve clarity and consistency. Indentation and structure were adjusted for better understanding.
Impact: Users will have clearer examples for setting up automations with the integration.
---
chore(manifest): streamline manifest file formatting
Consolidated formatting in the manifest file for consistency. Adjusted the codeowners and requirements sections for a cleaner look.
User-Impact: none
---
chore(pyproject): enhance project configuration for better linting and testing
Updated the pyproject.toml file to improve linting configurations and testing options. Added specific rules for ruff and pytest to align with project standards.
User-Impact: none
---
chore(manifest_schema): simplify JSON schema for integration manifest
Refined the manifest schema by consolidating enum definitions for better readability and maintenance.
User-Impact: none
---
chore(prettier): add Prettier configuration for consistent code formatting
Introduced a Prettier configuration file to standardize code formatting across the project, ensuring consistency in style.
User-Impact: none
Updated color and icon logic to include additional keys for price trends, outlooks, and trajectories. This improves the visual representation of price changes in the UI.
Impact: Users will see more accurate color coding and icons for price trends and forecasts.
Improve error handling for API fetch failures by implementing a fallback to cached intervals. This ensures the system can continue functioning during transient API issues.
Impact: Users experience fewer interruptions when the API is temporarily unavailable, as cached data will be used seamlessly.
Modified error messages in multiple language translation files to remove unnecessary curly braces around the template placeholder for improved clarity.
Impact: Users will see clearer error messages when invalid array_fields are provided.
Improved validation logic for service parameters in find_cheapest_hours, find_cheapest_schedule, and chartdata services. Added checks for unique task names, ensured that segment durations do not exceed total duration, and clarified error messages for better user understanding.
Impact: Users will receive clearer error messages and improved validation when using the services, leading to a more robust experience.
Updated the filter logic to include period_filter alongside level_filter and rating_level_filter for segment definitions. This change ensures that users can utilize period_filter effectively when defining segments.
Impact: Users can now use period_filter in addition to existing filters for more flexible segment definitions.
Updated sensor definitions to enhance clarity and maintain consistency by removing the diagnostic entity category from day pattern sensors.
Impact: No user-facing changes.
Revised the comment regarding explicitly skipped commits to enhance readability and maintain consistency in documentation style.
Impact: Improved clarity for developers reviewing the release notes generation script.
Updated the long descriptions and usage tips for the price trend change sensors in multiple languages (de, en, nb, nl, sv) to provide clearer guidance on detection mechanics and expected behavior during V-shaped price days.
Impact: Users will have a better understanding of how the sensors operate and can make more informed decisions regarding automation based on price trends.
Refactor the period extension logic to clarify the handling of primary and fallback price levels. Update the documentation to reflect the changes in how periods extend into adjacent intervals.
Impact: Users will benefit from clearer price extension behavior and improved performance in period calculations.
Implement an auto-assign workflow to automatically assign newly opened issues to the repository owner.
Impact: Streamlines issue management by ensuring the owner is automatically assigned to new issues.
Replace CV with IQR% as the primary indicator for flat-day detection
in _compute_day_effective_min(). CV is inflated by isolated price spikes
(a single spike at 2× the average pushes CV to 15-25% while the core
price band stays flat), causing the flat-day adaptation to be missed.
IQR% (spread of the central 50% of prices / median) is unaffected by
tail outliers and correctly identifies "flat core + spike" days.
Threshold: LOW_IQR_PCT_FLAT_DAY_THRESHOLD = 15.0%
- IQR% ≈ 1.35 × CV for symmetric data, so 15% ≈ old CV threshold of 10%
- Extra headroom catches flat days with a single outlier (IQR%~3%,
CV~20%) that were previously missed
CV retained as fallback for edge cases where iqr_pct is None
(near-zero or negative median prices).
Impact: Flat days with a single isolated price spike are now correctly
identified, reducing unnecessary relaxation iterations on those days.
Rename the three existing price rank sensors from price_rank_* to
current_interval_price_rank_* to clarify they rank the current
quarter-hour interval's price, not a daily aggregate — consistent with
current_interval_price_level / current_interval_price_rating naming.
Add 8 new rank sensors covering additional subjects and reference windows:
- next_interval_price_rank_{today,today_tomorrow}
- previous_interval_price_rank_{today,today_tomorrow}
- current_hour_price_rank_{today,today_tomorrow} (5-interval rolling avg)
- next_hour_price_rank_{today,today_tomorrow} (5-interval rolling avg)
All new sensors are disabled by default. The volatility calculator gains a
subject parameter (_get_subject_price / _get_subject_price_attr_key /
_get_rolling_hour_avg_price) to select which price to rank. Sensor key
routing in value_getters.py and attributes/__init__.py updated accordingly.
No migration entries needed — the original price_rank_* sensors were never
released to users.
All 5 translation files updated. sensor-reference.md regenerated (129 entities).
Impact: Users can now track price rank for the next interval (look-ahead),
the previous interval (logging), and rolling hourly averages — for both
same-day and two-day reference windows.
Updated the configuration files to improve development experience by explicitly loading useful integrations and adjusting logging levels. Added YAML schemas for configuration and services to ensure proper structure and validation.
Impact: Developers will have a more streamlined setup process and better logging during integration development.
Enhance the configuration for the HTTP component to support development in Codespaces and DevContainer. This includes settings for server host, IP banning, trusted proxies, and CORS.
Impact: Improved development experience by allowing easier access and configuration in development environments.
Convert four-space-indented list items (`- item`) to standard two-space
(`- item`) in AGENTS.md, CONTRIBUTING.md, README.md, and all Docusaurus
documentation pages (developer and user, including versioned snapshots).
No content changes.
Release-Notes: skip
Apply consistent 4-space indentation and trailing-operator style for line
continuations (&&, |) across all development and release scripts. No logic
changes.
Release-Notes: skip
Update sensors-volatility.md to cover the three new price rank sensors and the
IQR-based volatility attributes (typical price band / price spike count).
Section headers include technical terms in parentheses for experts:
"Typical Price Band Statistics (IQR)" and "Price Rank Sensors (Percentile Rank)".
Attribute tables list Tukey fence formulas and plain-language explanations
side-by-side.
Regenerate sensor-reference.md to include price_rank_today,
price_rank_tomorrow, and price_rank_today_tomorrow with translations for all
five supported languages.
Impact: Users have full documentation for the new sensors including examples,
formulas, and a multi-language lookup table.
Add entity descriptions, long descriptions, and usage tips for the three new
price_rank_* sensors and the updated volatility sensors with IQR attributes.
Plain-language terms are used as primary labels (e.g. "typical price band",
"price rank"); technical terms are included parenthetically for experts
(e.g. "IQR", "percentile rank", "Tukey fences") in all five languages.
Impact: Sensors show descriptive help text in the entity detail view, making it
easier for users to understand what each sensor measures without consulting
external documentation.
Add entity name translations for price_rank_today, price_rank_tomorrow, and
price_rank_today_tomorrow sensors in English, German, Norwegian, Dutch, and
Swedish.
Impact: Sensor display names appear correctly in the Home Assistant UI for all
supported languages.
Add three new price rank sensors that show where today's/tomorrow's/combined
average price falls relative to all intervals in the evaluated window:
- price_rank_today: today's average price percentile rank (0–100%)
- price_rank_tomorrow: tomorrow's average price percentile rank
- price_rank_today_tomorrow: combined today+tomorrow percentile rank
Extend all volatility sensors with IQR-based band statistics:
- price_typical_spread: interquartile range (IQR) in currency subunit
- price_typical_spread_%: IQR as percentage of daily average
- price_spike_count: number of intervals outside Tukey fences (outliers)
Add calculate_iqr_stats() utility function in utils/price.py that computes
the 25th/75th percentiles, IQR, outer fences (Q1 - 1.5×IQR / Q3 + 1.5×IQR),
and outlier count for any list of price values. Entity keys and attribute
names use plain language (`price_rank`, `price_typical_spread`) as primary
labels; technical terms (percentile rank, IQR) are included parenthetically
in descriptions and documentation.
Impact: Users can now see where current day prices rank compared to their window and how tightly clustered or spike-prone a day's prices are.
