Data source

Data sources help group target timeframe sensors together to be fed from a central data source. These data sources take a specific shape, but can represent anything. To start configuring target timeframe sensors, you'll need to create an initial data source. This can be done via the integration UI.

Properties

Name

The name of the data source. This is for informative purposes.

Id

The unique identifier of the data source. This is used by internal events to ensure sensors use the correct data as well as part of the entity name of all related entities.

The data source will listen for the update data source event where the data source id matches this id. This event might be raised by other integrations. If this data source is being used for this purpose, then the id will need to be set to a certain value which should be highlighted in that integrations guide.

Alternatively, you can use the available service to configure the underlying data. There is a collection of blueprints available for loading data from popular data sources.

Entities

Once the data source has been created, you'll have the following entities created.

Data Source Last Updated

sensor.target_timeframes_{{DATA_SOURCE_ID}}_data_source_last_updated

This entity represents when the data source data was last updated via the associated service.

Attribute	Type	Description
data_source_id	string	The id of the underlying data source.
data	list	The current collection of data associated with the data source.

For each item within data, you get the following attributes

Attribute	Type	Description
start	datetime	The start datetime of the period the value is applicable for.
end	datetime	The end datetime of the period the value is applicable for.
value	float	The value associated with the time period. This is what drives the target timeframe sensors.
metadata	object	The optional metadata associated with the timeframe. This can be used to show how the value was calculated. This is up to the datasource to determine the shape and will vary.