DataChannel

Python pydantic class corresponding to json type data.channel, version 000.

class gwproto.types.DataChannel(*, DisplayName, AboutName, CapturedByName, TelemetryName, TypeName='data.channel', Version='000')

Data Channel.

A data channel is a concept of some collection of readings that share all characteristics other than time.

Parameters:

  • DisplayName (str)

  • AboutName (str)

  • CapturedByName (str)

  • TelemetryName (TelemetryName)

  • TypeName (Literal['data.channel'])

  • Version (Literal['000'])

as_dict()

Translate the object into a dictionary representation that can be serialized into a data.channel.000 object.

This method prepares the object for serialization by the as_type method, creating a dictionary with key-value pairs that follow the requirements for an instance of the data.channel.000 type. Unlike the standard python dict method, it makes the following substantive changes: - Enum Values: Translates between the values used locally by the actor to the symbol sent in messages. - Removes any key-value pairs where the value is None for a clearer message, especially in cases with many optional attributes.

It also applies these changes recursively to sub-types.

Return type:

Dict[str, Any]

as_type()

Serialize to the data.channel.000 representation.

Instances in the class are python-native representations of data.channel.000 objects, while the actual data.channel.000 object is the serialized UTF-8 byte string designed for sending in a message.

This method calls the as_dict() method, which differs from the native python dict() in the following key ways: - Enum Values: Translates between the values used locally by the actor to the symbol sent in messages. - - Removes any key-value pairs where the value is None for a clearer message, especially in cases with many optional attributes.

It also applies these changes recursively to sub-types.

Its near-inverse is DataChannel.type_to_tuple(). If the type (or any sub-types) includes an enum, then the type_to_tuple will map an unrecognized symbol to the default enum value. This is why these two methods are only ‘near’ inverses.

Return type:

bytes

DisplayName:

  • Description: Display Name. This display name is the handle for the data channel. It is meant to be set by the person/people who will be analyzing time series data. It is only expected to be unique within the data channels associated to a specific Terminal Asset.

AboutName:

  • Description: About Name. The name of the SpaceheatNode whose physical quantities are getting captured.

  • Format: SpaceheatName

CapturedByName:

  • Description: The name of the SpaceheatNode that is capturing the physical quantities (which can be AboutName but does not have to be).

  • Format: SpaceheatName

TelemetryName:

  • Description: The name of the physical quantity getting measured.

TypeName:

  • Description: All GridWorks Versioned Types have a fixed TypeName, which is a string of lowercase alphanumeric words separated by periods, most significant word (on the left) starting with an alphabet character, and final word NOT all Hindu-Arabic numerals.

Version:

  • Description: All GridWorks Versioned Types have a fixed version, which is a string of three Hindu-Arabic numerals.

class gwproto.types.data_channel.check_is_spaceheat_name(v)

Check SpaceheatName Format.

Validates if the provided string adheres to the SpaceheatName format: Lowercase words separated by periods, where word characters can be alphanumeric or a hyphen, and the first word starts with an alphabet character.

Parameters:

v (str) – The string to be validated.

Raises:

ValueError – If the provided string is not in SpaceheatName format.

class gwproto.types.DataChannel_Maker(display_name, about_name, captured_by_name, telemetry_name)
Parameters:

  • display_name (str)

  • about_name (str)

  • captured_by_name (str)

  • telemetry_name (TelemetryName)

classmethod dict_to_tuple(d)

Deserialize a dictionary representation of a data.channel.000 message object into a DataChannel python object for internal use.

This is the near-inverse of the DataChannel.as_dict() method:

  • Enums: translates between the symbols sent in messages between actors and

the values used by the actors internally once they’ve deserialized the messages.

  • Types: recursively validates and deserializes sub-types.

Note that if a required attribute with a default value is missing in a dict, this method will raise a SchemaError. This differs from the pydantic BaseModel practice of auto-completing missing attributes with default values when they exist.

Parameters:

d (dict) – the dictionary resulting from json.loads(t) for a serialized JSON type object t.

Raises:

SchemaError – if the dict cannot be turned into a DataChannel object.

Returns:

DataChannel

Return type:

DataChannel

classmethod tuple_to_type(tpl)

Given a Python class object, returns the serialized JSON type object.

Parameters:

tpl (DataChannel)

Return type:

bytes

classmethod type_to_tuple(t)

Given a serialized JSON type object, returns the Python class object.

Parameters:

t (bytes)

Return type:

DataChannel