Bundle automation and script blueprints into the integration and
install them automatically at HA startup via _install_blueprints().
Remove them cleanly when the last config entry is removed.
Automation blueprints (standalone):
- dishwasher, washing_machine, dryer — smart plug and Home Connect
variants (HC: door/remote-start sensors; HC Alt: program selector)
Automation blueprints (pipeline):
- laundry_day_pipeline — chains washer → dryer for multiple loads,
HC and HC Alt variants
Other automation blueprints:
- ev_charging, heat_pump_price_level, heat_pump_smart_boost,
home_battery, water_heater, laundry_day_pipeline (smart plug)
Script blueprint:
- notify_residents — presence-aware dispatcher for up to 10 residents
with auto-discovered mobile_app notify services, iOS/Android push
settings, and per-resident notify overrides
Notification UX across all blueprints:
- Apple Watch-optimised titles (~25 chars) and messages (most
important info first, middle-dot separators, emoji anchors)
- Customisable notification titles via blueprint inputs (standalone)
- Comma-separated notify services for simple multi-target delivery
- Advanced script path for presence filtering and platform push data
Impact: Users get ready-to-use blueprints installed automatically
with the integration for scheduling appliances during cheap Tibber
price windows. No manual import required.
Read the version field from manifest.json at import time via a new
INTEGRATION_VERSION constant in const.py. Pass it as sw_version to
DeviceInfo in TibberPricesEntity so the current integration version
is visible in the HA device registry.
Impact: Device page in HA now shows the installed integration version
under firmware/software version.
Add entity_resolver module that lets all service parameters accept
HA entity references in place of literal values. The entity's current
state (or a specific attribute via the @attr syntax) is resolved at
call time and coerced to the expected Python type.
Syntax:
"sensor.washing_duration" → uses entity state
"sensor.washing_duration@run_minutes" → uses entity attribute
Apply or_entity_ref() and resolve_entity_references() to all five
service handlers (get_price, find_cheapest_block, find_cheapest_hours,
find_cheapest_schedule, get_chartdata) for every parameter where a
dynamic value from another entity is useful (duration, start/end times,
offsets, etc.).
Add five new translation keys for entity-resolution error messages
(invalid_entity_reference, entity_not_found, entity_attribute_not_found,
entity_state_unavailable, entity_value_conversion_failed) across all
five language files.
Fix pytest warning filter to suppress AsyncMock cleanup noise, and
update test_resource_cleanup to mock hass.config_entries.async_entries
so the blueprint-removal path in async_remove_entry does not raise.
Impact: Automations and scripts can pass sensor entity IDs as service
parameters (e.g. duration from a sensor) instead of having to use
template-based workarounds.
Replace workaround recommendations (2× find_cheapest_block) with the
new sequential: true parameter. Rewrite washer→dryer example as a single
find_cheapest_schedule call. Update quick reference tables.
Release-Notes: skip
When sequential: true, tasks are placed in declaration order instead of
being sorted by duration. Each task's search window starts after the
previous task ends (plus gap_minutes). If a task cannot be placed, all
subsequent tasks in the chain are also marked unscheduled.
Adds 12 tests covering ordering, chaining, gap enforcement, and
chain-breaking behavior.
Impact: Users can now schedule dependent appliances (e.g., washing
machine → dryer) in a single find_cheapest_schedule call with guaranteed
order, instead of chaining two find_cheapest_block calls.
Updated the dishwasher automation to include planning and execution steps using input_datetime helpers for better reliability across restarts. Clarified the use of find_cheapest_schedule for independent appliances and added caution regarding task order. Improved messaging in notifications for planned schedules.
Impact: Users can now schedule appliances more reliably, ensuring planned start times persist through Home Assistant restarts.
docs(sidebars): rename automation section for clarity
Changed the sidebar label from '🤖 Automations' to '🤖 Automations & Usage' to better reflect the content and improve user navigation.
Impact: Users will find it easier to locate automation-related documentation.
Removed unnecessary sections from the get_apexcharts_yaml service and added new fields for search tuning and cost estimation in chartdata services. This improves the clarity and usability of the service definitions.
Impact: Users will benefit from a more concise and organized service structure, enhancing the overall experience.
The old extension algorithm extended a single late-evening period forward
past midnight by appending qualifying intervals one-directionally. This
caused false extensions (e.g. peak 19:45–21:30 extended to 01:00 by
pulling in 14 declining-price intervals).
Replace with bidirectional bridging: two independently qualifying periods
on both sides of midnight are merged only when separated by a small gap
(≤4 intervals = 1 hour) and the combined period passes the CV quality
gate (≤25%). A period ending well before midnight is no longer touched.
User-Impact: none
Implement a new service that progressively relaxes user-defined filters to ensure a result is always returned when price data is available. This includes three phases: halving the minimum distance from average, expanding level filters, and reducing duration.
Impact: Users will receive results even when strict filters would otherwise yield no matches, improving the reliability of scheduling actions.
feat(pricing): enhance scheduling actions with new parameters
Introduce new parameters `smooth_outliers`, `min_distance_from_avg`, and `allow_relaxation` to scheduling actions, allowing for better control over price selection and ensuring results are meaningfully different from average prices.
Impact: Users can now fine-tune their scheduling actions to avoid marginal savings and ensure more uniform pricing within selected windows.
docs(scheduling): update documentation for new features
Revise the scheduling actions documentation to include new parameters and their effects, such as outlier smoothing and minimum distance from average, along with examples for better user understanding.
Impact: Users will have clearer guidance on how to utilize new features effectively in their automations.
test(scheduling): add tests for new relaxation logic
Implement unit tests to verify the behavior of the new relaxation logic in scheduling actions, ensuring that filters are correctly relaxed and results are returned as expected.
Impact: Increased test coverage and reliability of the scheduling features.
Improve the logic for trimming trailing gap-tolerance intervals in periods to prevent misleading period end shifts. Additionally, refine cross-day boundary validation for both best and peak periods to eliminate false extremes caused by inter-day reference shifts.
Impact: More accurate period calculations and reduced artifacts in reported price periods.
Improve the filtering of peak periods to eliminate cross-day artifacts and ensure that only genuine high-price windows are retained. This includes adjustments to the criteria for peak classification and the introduction of validation against previous day's prices for overnight intervals.
Impact: Users will experience more accurate peak pricing data, reducing misleading peak classifications on flat days.
Enhanced descriptions for V-shaped and U-shaped price days to include their characteristics and how they are classified as 'valley' by the Day Pattern sensor.
Impact: Users gain a clearer understanding of price patterns and their implications for automation.
docs(glossary): update V-Shaped Day definition for clarity
Revised the definition of V-Shaped Day to include U-Shaped Day as an informal term, emphasizing the classification as 'valley' by the Day Pattern sensor.
Impact: Users receive a more comprehensive explanation of price day classifications.
docs(period-calculation): improve algorithm overview and phase descriptions
Added detailed explanations for each phase of the period calculation algorithm, including visual aids and clarifications on the importance of each phase.
Impact: Users can better understand the underlying logic of price period calculations.
docs(sensors-price-phases): refine sensor descriptions for clarity
Updated descriptions of price phase sensors to clarify the shapes and conditions they represent, including distinctions between V-shaped and U-shaped curves.
Impact: Users benefit from improved clarity on sensor classifications and their applications in automations.
Include the MermaidChart extension to enhance diagramming capabilities within the development environment.
Impact: Users can now create and visualize diagrams directly in their code editor.
Updated pattern names for clarity and consistency in the codebase. The changes include renaming constants and updating related logic to reflect the new terminology.
Impact: Improved readability and understanding of day pattern classifications for developers.
Refactor the pattern classification logic to include start and end prices for better accuracy in identifying day patterns. This change improves the classification of price patterns, particularly for cases involving valleys and peaks.
Impact: Users will experience more accurate price pattern classifications, leading to better decision-making based on price trends.
The Copilot backend relies on the AI to reproduce the footer text exactly,
which leads to subtle differences (URL parameter order, whitespace, emoji
encoding) compared to the git-cliff template in cliff.toml.
Fix: define CANONICAL_FOOTER as a single bash constant and pipe all three
backends (copilot, git-cliff, manual) through ensure_canonical_footer(),
which strips any existing BMAC footer block and appends the canonical one.
Also tell the AI not to generate a footer at all, since it is now added
programmatically. The manual backend gains a footer it previously lacked.
User-Impact: none
The PRICE_INFO endpoint returns all available intervals (~384) regardless
of the requested range. When fetching multiple missing ranges, subsequent
calls are redundant if the first response already covers them.
After each fetch, track returned timestamps and skip ranges that are
already covered by previously fetched data.
Impact: Reduces redundant Tibber API calls, especially after restarts or
cache invalidation when multiple gaps exist in the interval pool.
Touch operations create dead intervals in old fetch groups, but GC only
ran when new intervals were added. Dead intervals accumulated until
the next fetch with genuinely new data.
Now run GC after touch-only paths and schedule a save if data changed.
Impact: Reduces memory usage by cleaning up stale fetch groups promptly
instead of letting dead intervals accumulate between API fetches.
Cherry-pick of v0.30.1 hotfix (ec3bc9f). When _cleanup_dead_intervals
compacted group lists but no groups became fully empty, the index retained
stale interval_index values pointing past compacted list ends, causing
IndexError in _get_cached_intervals.
Now rebuilds the index whenever dead intervals are removed, even if no
groups are deleted.
Includes regression test for Issue #118 and updated touch operation tests
to reflect that GC now runs immediately after touch-only paths.
Closes#118
Impact: Eliminates IndexError crash for users with brand-new Tibber accounts
that have limited price history, where partial group compaction was most likely.
git-cliff ≤2.12.0 --include-path ignores the commit range and generates
a full changelog. The commit_parsers in cliff.toml already filter
non-user-facing types/scopes, making path filtering redundant.
Changed RELEASE_NOTES_CLIFF_FILTER_PATHS default from true to false.
User-Impact: none
Introduce additional sensors for current price phase, phase duration, and upcoming phase timings to enhance user visibility of pricing dynamics.
Impact: Users can now monitor current price phases and their durations, improving decision-making based on real-time pricing information.
Consolidate logic for determining current price phase and associated attributes by introducing shared helper functions. This enhances code maintainability and reduces duplication across components.
Impact: Improved clarity and efficiency in price phase handling for users.
Modified the TypeScript configuration files to set the ignoreDeprecations option to "6.0" for improved compatibility with future TypeScript versions.
User-Impact: none
Revised the descriptions and names for the previous interval price rank entities across multiple language translation files to enhance clarity and consistency.
Impact: Users will see improved terminology in the interface, making it clearer that the ranks refer to the previous interval's prices.
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.
