Commit graph

8 commits

Author SHA1 Message Date
Copilot
49628f3394
Add connect_segments parameter and fix ApexCharts header N/A display (#46)
* Initial plan

* Add connect_segments parameter to get_chartdata service for visual segment connections

Co-authored-by: jpawlowski <75446+jpawlowski@users.noreply.github.com>

* Address code review feedback: fix test logic and correct misleading comment

Co-authored-by: jpawlowski <75446+jpawlowski@users.noreply.github.com>

* Integrate PR45: Remove trailing null values for proper ApexCharts header display

Co-authored-by: jpawlowski <75446+jpawlowski@users.noreply.github.com>

* Add connect_segments translations for de, nb, nl, sv languages

Co-authored-by: jpawlowski <75446+jpawlowski@users.noreply.github.com>

* Changes before error encountered

Co-authored-by: jpawlowski <75446+jpawlowski@users.noreply.github.com>

* Fix hassfest validation: Move time_units from translations to custom_translations

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>
2025-12-01 03:19:52 +01:00
Julian Pawlowski
6f93bb8288 refactor(formatters, get_chartdata): serialize datetime objects to ISO format in data points 2025-11-30 15:07:18 +00:00
Julian Pawlowski
6338f51527 refactor(services): rename service modules to match service names
Renamed service modules for consistency with service identifiers:
- apexcharts.py → get_apexcharts_yaml.py
- chartdata.py → get_chartdata.py
- Added: get_price.py (new service module)

Naming convention: Module names now match service names directly
(tibber_prices.get_apexcharts_yaml → get_apexcharts_yaml.py)

Impact: Improved code organization, easier to locate service implementations.
No functional changes.
2025-11-25 20:44:39 +00:00
Julian Pawlowski
b6f5f1678f feat(services): add fetch_price_info_range service and update schema
Added new service for fetching historical/future price data:
- fetch_price_info_range: Query prices for arbitrary date ranges
- Supports start_time and end_time parameters
- Returns structured price data via service response
- Uses interval pool for efficient data retrieval

Service definition:
- services.yaml: Added fetch_price_info_range with date selectors
- services/__init__.py: Implemented handler with validation
- Response format: {"priceInfo": [...], "currency": "..."}

Schema updates:
- config_flow_handlers/schemas.py: Convert days slider to IntSelector
  (was NumberSelector with float, caused "2.0 Tage" display issue)

Impact: Users can fetch price data for custom date ranges programmatically.
Config flow displays clean integer values for day offsets.
2025-11-25 20:44:39 +00:00
Julian Pawlowski
2de793cfda refactor: migrate from multi-home to single-home-per-coordinator architecture
Changed from centralized main+subentry coordinator pattern to independent
coordinators per home. Each config entry now manages its own home data
with its own API client and access token.

Architecture changes:
- API Client: async_get_price_info() changed from home_ids: set[str] to home_id: str
  * Removed GraphQL alias pattern (home0, home1, ...)
  * Single-home query structure without aliasing
  * Simplified response parsing (viewer.home instead of viewer.home0)

- Coordinator: Removed main/subentry distinction
  * Deleted is_main_entry() and _has_existing_main_coordinator()
  * Each coordinator fetches its own data independently
  * Removed _find_main_coordinator() and _get_configured_home_ids()
  * Simplified _async_update_data() - no subentry logic
  * Added _home_id instance variable from config_entry.data

- __init__.py: New _get_access_token() helper
  * Handles token retrieval for both parent and subentries
  * Subentries find parent entry to get shared access token
  * Creates single API client instance per coordinator

- Data structures: Flat single-home format
  * Old: {"homes": {home_id: {"price_info": [...]}}}
  * New: {"home_id": str, "price_info": [...], "currency": str}
  * Attribute name: "periods" → "pricePeriods" (consistent with priceInfo)

- helpers.py: Removed get_configured_home_ids() (no longer needed)
  * parse_all_timestamps() updated for single-home structure

Impact: Each home operates independently with its own lifecycle tracking,
caching, and period calculations. Simpler architecture, easier debugging,
better isolation between homes.
2025-11-24 16:24:37 +00:00
Julian Pawlowski
981fb08a69 refactor(price_info): price data handling to use unified interval retrieval
- 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.
2025-11-24 10:49:34 +00:00
Julian Pawlowski
625bc222ca refactor(coordinator): centralize time operations through TimeService
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.
2025-11-19 18:36:12 +00:00
Julian Pawlowski
ac24f6a8cb refactor(services): split monolithic services.py into package
Split services.py (1,097 lines) into modular package (6 files, ~200-600 lines each):

Structure:
- services/__init__.py: Service registration (70 lines)
- services/helpers.py: Entry validation (55 lines)
- services/formatters.py: Data transformation (380 lines)
- services/chartdata.py: Chart data export handler (600 lines)
- services/apexcharts.py: ApexCharts YAML generator (240 lines)
- services/refresh_user_data.py: User data refresh (110 lines)

Benefits:
- Clear separation of concerns (helpers, formatters, handlers)
- Each service isolated and independently testable
- Consistent handler naming (handle_* pattern)
- Better code reuse through formatters module

All services working identically (get_chartdata, get_apexcharts_yaml,
refresh_user_data). Updated __init__.py to import from services package.

Impact: Improved maintainability, reduced max file size from 1,097
to 600 lines. Architecture quality improved from 7.5/10 to ~8.5/10.
2025-11-18 20:07:05 +00:00