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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.
173 lines
5.5 KiB
Markdown
173 lines
5.5 KiB
Markdown
# Services
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This integration provides several services for advanced price data access and manipulation.
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## Available Services
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### tibber_prices.get_chartdata
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**Purpose:** Returns electricity price data in chart-friendly formats for visualization and analysis.
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**Key Features:**
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- **Flexible Output Formats**: Array of objects or array of arrays
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- **Time Range Selection**: Filter by day (yesterday, today, tomorrow)
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- **Price Filtering**: Filter by price level or rating
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- **Period Support**: Return best/peak price period summaries instead of intervals
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- **Resolution Control**: Interval (15-minute) or hourly aggregation
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- **Customizable Field Names**: Rename output fields to match your chart library
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- **Currency Control**: Major (EUR/NOK) or minor (ct/øre) units
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**Basic Example:**
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```yaml
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service: tibber_prices.get_chartdata
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data:
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entry_id: YOUR_ENTRY_ID
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day: ["today", "tomorrow"]
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output_format: array_of_objects
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response_variable: chart_data
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```
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**Response Format:**
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```json
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{
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"data": [
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{
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"start_time": "2025-11-17T00:00:00+01:00",
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"price_per_kwh": 0.2534
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},
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{
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"start_time": "2025-11-17T00:15:00+01:00",
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"price_per_kwh": 0.2498
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}
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]
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}
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```
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**Common Parameters:**
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| Parameter | Description | Default |
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| ---------------- | ------------------------------------------- | ----------------------- |
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| `entry_id` | Integration entry ID (required) | - |
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| `day` | Days to include: yesterday, today, tomorrow | `["today", "tomorrow"]` |
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| `output_format` | `array_of_objects` or `array_of_arrays` | `array_of_objects` |
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| `resolution` | `interval` (15-min) or `hourly` | `interval` |
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| `minor_currency` | Return prices in ct/øre instead of EUR/NOK | `false` |
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| `round_decimals` | Decimal places (0-10) | 4 (major) or 2 (minor) |
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**Rolling Window Mode:**
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Omit the `day` parameter to get a dynamic 48-hour rolling window that automatically adapts to data availability:
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```yaml
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service: tibber_prices.get_chartdata
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data:
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entry_id: YOUR_ENTRY_ID
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# Omit 'day' for rolling window
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output_format: array_of_objects
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response_variable: chart_data
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```
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**Behavior:**
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- **When tomorrow data available** (typically after ~13:00): Returns today + tomorrow
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- **When tomorrow data not available**: Returns yesterday + today
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This is useful for charts that should always show a 48-hour window without manual day selection.
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**Period Filter Example:**
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Get best price periods as summaries instead of intervals:
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```yaml
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service: tibber_prices.get_chartdata
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data:
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entry_id: YOUR_ENTRY_ID
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period_filter: best_price # or peak_price
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day: ["today", "tomorrow"]
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include_level: true
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include_rating_level: true
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response_variable: periods
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```
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**Advanced Filtering:**
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```yaml
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service: tibber_prices.get_chartdata
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data:
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entry_id: YOUR_ENTRY_ID
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level_filter: ["VERY_CHEAP", "CHEAP"] # Only cheap periods
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rating_level_filter: ["LOW"] # Only low-rated prices
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insert_nulls: segments # Add nulls at segment boundaries
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```
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**Complete Documentation:**
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For detailed parameter descriptions, see the service definition in **Developer Tools → Services → tibber_prices.get_chartdata** or check the inline documentation in the integration's `services.yaml` file.
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---
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### tibber_prices.get_apexcharts_yaml
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**Purpose:** Generates complete ApexCharts card YAML configuration for visualizing electricity prices.
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**Prerequisites:**
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- [ApexCharts Card](https://github.com/RomRider/apexcharts-card) (required for all configurations)
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- [Config Template Card](https://github.com/iantrich/config-template-card) (required only for rolling window mode without `day` parameter)
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**Quick Example:**
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```yaml
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service: tibber_prices.get_apexcharts_yaml
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data:
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entry_id: YOUR_ENTRY_ID
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day: today # Optional: omit for rolling 48h window (requires config-template-card)
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response_variable: apexcharts_config
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```
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**Rolling Window Mode:** When omitting the `day` parameter, the service generates a dynamic 48-hour rolling window that automatically shows:
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- Today + Tomorrow (when tomorrow data is available)
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- Yesterday + Today (when tomorrow data is not yet available)
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This mode requires the Config Template Card to dynamically adjust the time window based on data availability.
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Use the response in Lovelace dashboards by copying the generated YAML.
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**Documentation:** See Developer Tools → Services for parameter details.
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---
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### tibber_prices.refresh_user_data
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**Purpose:** Forces an immediate refresh of user data (homes, subscriptions) from the Tibber API.
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**Example:**
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```yaml
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service: tibber_prices.refresh_user_data
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data:
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entry_id: YOUR_ENTRY_ID
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```
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**Note:** User data is cached for 24 hours. Use this service only when you need immediate updates (e.g., after changing Tibber subscriptions).
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---
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## Migration from Chart Data Export Sensor
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If you're currently using the `sensor.tibber_home_chart_data_export` sensor, consider migrating to `tibber_prices.get_chartdata`:
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**Benefits:**
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- No HA restart required for configuration changes
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- More flexible filtering and formatting options
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- Better performance (on-demand instead of polling)
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- Future-proof (active development)
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**Migration Steps:**
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1. Note your current sensor configuration (Step 7 in Options Flow)
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2. Create automation/script using `tibber_prices.get_chartdata` with same parameters
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3. Test the new approach
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4. Disable the old sensor when satisfied
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