Topographically Structured Attribute Data #12575
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The existing format for how attribute reports were returned to callers of DeviceController.ReadAttribute() made it quite challenging for them to consume it in an easy enough manner. Instead of providing them with an effectively raw stream of attribute data, this commit organizes and structures that data into a series of nested dictionaries that mirror the topography and composition of the data in a given Matter device: Endpoints that contain Clusters that in turn contain Attributes. The Python data structure equivalent represents these as nested dictionaries: Dict[EndpointId, Dict[ClusterType, Dict[AttributeType, AttributeValue]]] Tests: - Updated the existing ReadAttribute and Subscription tests to utilize this new format. - Added new ones. - Validated using the REPL
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…k on to the REPL's main event loop for backgrounded work
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The existing format for how attribute reports were returned to callers of
DeviceController.ReadAttribute()made it quite challenging for them to consume it in an easy enough manner. Data was stored in an attribute cache, organized as a flatlist of elements containing an
AttributePath+ Data.This had two notable dis-advantages:
chip.clusters.Attribute.AttributePathfirst, understand its constructor, then correctly initialize it and use that as a key to the returned data stream.This PR organizes and structures that data into a series of nested dictionaries that mirror the topography and composition of the data in a given Matter device: Endpoints that contain Clusters that in
turn contain Attributes.
The Python data structure equivalent represents these as nested dictionaries:
It uses the cluster object types themselves as strongly typed keys into the composed data! It also embeds any exceptions/IM errors as the value for an attribute instead of the data itself.
It also creates a cluster-objectified version of the entire cluster as a whole, permitting a more natural 'object-model' representation of the state of a cluster.
Accessing the returned data is as easy as pie:
Example: Reading out
OnOffcluster on all endpointsOld:
New (attribute-view):
New (cluster-view):
In-band IM status:
Tests: