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mwings.parsers.app_cue_pal_event Module

Parsers for packets sent from TWELITE CUE in PAL event mode (Dice/Move mode) and data structures to store their contents.

src/mwings/parsers/app_cue_pal_event.py

`PacketParser`

Static class parser that interprets packets representing data sent from the CUE app (operation PAL mode: Dice/Move mode).

Inherits from: common.PacketParserBase

Members inherited from the base class are listed.

`is_valid()`

is_valid(bare_packet)

Checks whether the given raw packet is valid.

Arguments

Name	Type	Description
`bare_packet`	`common.BarePacket`	Raw packet data

Returns

Type	Value	Description
`bool`	`True`	Valid, parsable
	`False`	Invalid, not parsable

`parse()`

parse(bare_packet)

Parses the given raw packet.

Arguments

Name	Type	Description
`bare_packet`	`common.BarePacket`	Raw packet data

Returns

Type	Value	Description
`optional ParsedPacket`	Data of type `ParsedPacket`	Parsed data
	`None`	Parsing failed

`ParsedPacket`

Data structure to store the result of parsing packets representing data sent from the CUE app (operation PAL mode: Dice/Move mode).

Inherits from: common.ParsedPacketBase

Members inherited from the base class are also listed.

`ParsedPacket()`

ParsedPacket(*, time_parsed=None, packet_type=PacketType.BARE, sequence_number=None, source_serial_id=0, source_logical_id=0, lqi=None, supply_voltage=None, ai1_voltage=0, accel_event=AccelEvent.NONE)

Arguments

Includes inherited properties as well.

Name	Type	Description
`time_parsed`	`optional AwareDatetime`	Parsing timestamp
`packet_type`	`common.PacketType`	Packet type
`sequence_number`	`optional common.UInt16`	Sequence number
`source_serial_id`	`common.UInt32`	Source serial ID
`source_logical_id`	`common.UInt8`	Source logical device ID
`lqi`	`optional common.UInt8`	Radio communication quality
`supply_voltage`	`optional common.UInt16`	Supply voltage (mV)
`router_serial_id`	`common.UInt32`	Serial ID of the first relay device (no relay is `0x80000000`) `v1.0.13+`
`ai1_voltage`	`common.UInt16`	Voltage of `AI1` (mV)
`accel_event`	`common.AccelEvent`	Acceleration event

You can also pass a dictionary unpacked with **.

In addition to the variables specified as constructor arguments, the following @computed_field are available.

Name	Type	Description
`mwings_implementation`	`str`	MWings implementation (only `"python"`)
`mwings_version`	`str`	MWings version (PEP440 format)
`hostname`	`str`	Host machine name
`system_type`	`str`	System type (e.g., `"Linux"`)

Applicable field_validator

source_logical_id: Automatically validates the value range
- check_source_logical_id(lid)
time_parsed: Automatically validates that timezone is attached
- datetime_must_be_clear(dt)

Applicable field_serializer

packet_type: Serializes enum name as-is for JSON etc.
- serialize_packet_type(packet_type)
source_serial_id: Serializes as hexadecimal string for JSON etc.
- serialize_source_serial_id(source_serial_id)
time_parsed: Serializes as ISO 8601 string for JSON etc.
- serialize_time_parsed(dt)
accel_event: Serializes enum name as-is for JSON etc.
- serialize_accel_event(accel_event)

`to_df()`

to_df(include=None, exclude=None, verbose=True)

Converts the parsed data into a pandas DataFrame format.

Arguments

Name	Type	Description
`include`	`optional set[str]`	Set of columns (members) to include in the DataFrame
`exclude`	`optional set[str]`	Set of columns (members) to exclude from the DataFrame
`verbose`	`bool`	Include system information (only if other arguments are `None`)

Returns

Type	Value	Description
`pd.DataFrame`	-	Converted DataFrame

Exceptions

EnvironmentError if pandas is not installed

`to_dict()`

to_dict(include=None, exclude=None, verbose=True, spread=False, sort_keys=False)

Converts the parsed data into dictionary format.

Arguments

Name	Type	Description
`include`	`optional set[str]`	Set of keys (members) to include in the dictionary
`exclude`	`optional set[str]`	Set of keys (members) to exclude from the dictionary
`verbose`	`bool`	Include system information (only if other arguments are `None`)
`spread`	`bool`	Whether to split non-time-series list-like data
`sort_keys`	`bool`	Whether to sort keys

If spread is set, data of type common.CrossSectional[T] will be split. Time-series data of type common.TimeSeries[T] will not be split.

Returns

Type	Value	Description
`dict[str, Any]`	-	Converted dictionary

`to_json()`

to_json(include=None, exclude=None, verbose=True, spread=False, indent=2, sort_keys=False)

Converts the parsed data into JSON format.

Arguments

Name	Type	Description
`include`	`optional set[str]`	Set of keys (members) to include in the JSON
`exclude`	`optional set[str]`	Set of keys (members) to exclude from the JSON
`verbose`	`bool`	Include system information (only if other arguments are `None`)
`spread`	`bool`	Whether to split non-time-series list-like data
`indent`	`optional int`	Number of spaces for indentation (`None` means no line breaks)
`sort_keys`	`bool`	Whether to sort keys

If spread is set, data of type common.CrossSectional[T] will be split. Time-series data of type common.TimeSeries[T] will not be split.

Returns

Type	Value	Description
`str`	-	Converted JSON string

`model_*()`

In addition, you can use the various methods of pydantic.BaseModel.