Messages - `standard`#

This package contains standard messages.

Header#

This message represents a standard message header used by all messages.

pydantic model duckietown_messages.standard.header.Header#

Show JSON schema

{
   "title": "Header",
   "type": "object",
   "properties": {
      "version": {
         "title": "Version",
         "description": "Version of the message this header is attached to",
         "default": "1.0",
         "pattern": "^[0-9]+\\.[0-9]+(\\.[0-9]+)?$",
         "example": "0.1.3",
         "type": "string"
      },
      "frame": {
         "title": "Frame",
         "description": "Reference frame this data is captured in",
         "type": "string"
      },
      "txt": {
         "title": "Txt",
         "description": "Auxiliary data attached to the message",
         "type": "object"
      }
   }
}

Fields

frame (Optional[str])
txt (Optional[dict])
version (str)

field version: str = '1.0'#

Version of the message this header is attached to

Constraints

pattern = ^[0-9]+.[0-9]+(.[0-9]+)?$

field frame: Optional[str] = None#: Reference frame this data is captured in

field txt: Optional[dict] = None#: Auxiliary data attached to the message

classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model#: Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values

copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model#

Duplicate a model, optionally choose which fields to include, exclude and change.

Parameters

include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model

Returns

new model instance

dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) → DictStrAny#: Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

classmethod from_orm(obj: Any) → Model#

classmethod from_rawdata(rd: dtps_http.structures.RawData) → duckietown_messages.base.BaseMessage#

json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) → unicode#

Generate a JSON representation of the model, include and exclude arguments as per dict().

encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().

classmethod parse_file(path: Union[str, pathlib.Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: pydantic.parse.Protocol = None, allow_pickle: bool = False) → Model#

classmethod parse_obj(obj: Any) → Model#

classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: pydantic.parse.Protocol = None, allow_pickle: bool = False) → Model#

classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny#

classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode#

to_rawdata() → dtps_http.structures.RawData#

classmethod update_forward_refs(**localns: Any) → None#: Try to update ForwardRefs on fields based on this Model, globalns and localns.

classmethod validate(value: Any) → Model#

Boolean#

This message represents a boolean value.

pydantic model duckietown_messages.standard.boolean.Boolean#

Show JSON schema

{
   "title": "Boolean",
   "type": "object",
   "properties": {
      "header": {
         "title": "Header",
         "description": "Auto-generated header",
         "allOf": [
            {
               "$ref": "#/definitions/Header"
            }
         ]
      },
      "data": {
         "title": "Data",
         "description": "Boolean value payload",
         "type": "boolean"
      }
   },
   "required": [
      "data"
   ],
   "definitions": {
      "Header": {
         "title": "Header",
         "type": "object",
         "properties": {
            "version": {
               "title": "Version",
               "description": "Version of the message this header is attached to",
               "default": "1.0",
               "pattern": "^[0-9]+\\.[0-9]+(\\.[0-9]+)?$",
               "example": "0.1.3",
               "type": "string"
            },
            "frame": {
               "title": "Frame",
               "description": "Reference frame this data is captured in",
               "type": "string"
            },
            "txt": {
               "title": "Txt",
               "description": "Auxiliary data attached to the message",
               "type": "object"
            }
         }
      }
   }
}

Fields

data (bool)
header (duckietown_messages.standard.header.Header)

field header: duckietown_messages.standard.header.Header [Optional]#: Auto-generated header

field data: bool [Required]#: Boolean value payload

classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model#: Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values

Duplicate a model, optionally choose which fields to include, exclude and change.

Parameters

include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model

Returns

new model instance

dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) → DictStrAny#: Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

classmethod from_orm(obj: Any) → Model#

classmethod from_rawdata(rd: dtps_http.structures.RawData) → duckietown_messages.base.BaseMessage#

Generate a JSON representation of the model, include and exclude arguments as per dict().

encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().

classmethod parse_file(path: Union[str, pathlib.Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: pydantic.parse.Protocol = None, allow_pickle: bool = False) → Model#

classmethod parse_obj(obj: Any) → Model#

classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: pydantic.parse.Protocol = None, allow_pickle: bool = False) → Model#

classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny#

classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode#

to_rawdata() → dtps_http.structures.RawData#

classmethod update_forward_refs(**localns: Any) → None#: Try to update ForwardRefs on fields based on this Model, globalns and localns.

classmethod validate(value: Any) → Model#

Integer#

This message represents an integer value.

pydantic model duckietown_messages.standard.integer.Integer#

Show JSON schema

{
   "title": "Integer",
   "type": "object",
   "properties": {
      "header": {
         "title": "Header",
         "description": "Auto-generated header",
         "allOf": [
            {
               "$ref": "#/definitions/Header"
            }
         ]
      },
      "data": {
         "title": "Data",
         "description": "Integer value payload",
         "type": "integer"
      }
   },
   "required": [
      "data"
   ],
   "definitions": {
      "Header": {
         "title": "Header",
         "type": "object",
         "properties": {
            "version": {
               "title": "Version",
               "description": "Version of the message this header is attached to",
               "default": "1.0",
               "pattern": "^[0-9]+\\.[0-9]+(\\.[0-9]+)?$",
               "example": "0.1.3",
               "type": "string"
            },
            "frame": {
               "title": "Frame",
               "description": "Reference frame this data is captured in",
               "type": "string"
            },
            "txt": {
               "title": "Txt",
               "description": "Auxiliary data attached to the message",
               "type": "object"
            }
         }
      }
   }
}

Fields

data (int)
header (duckietown_messages.standard.header.Header)

field header: duckietown_messages.standard.header.Header [Optional]#: Auto-generated header

field data: int [Required]#: Integer value payload

classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model#: Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values

Duplicate a model, optionally choose which fields to include, exclude and change.

Parameters

include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model

Returns

new model instance

dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) → DictStrAny#: Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

classmethod from_orm(obj: Any) → Model#

classmethod from_rawdata(rd: dtps_http.structures.RawData) → duckietown_messages.base.BaseMessage#

Generate a JSON representation of the model, include and exclude arguments as per dict().

encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().

classmethod parse_file(path: Union[str, pathlib.Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: pydantic.parse.Protocol = None, allow_pickle: bool = False) → Model#

classmethod parse_obj(obj: Any) → Model#

classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: pydantic.parse.Protocol = None, allow_pickle: bool = False) → Model#

classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny#

classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode#

to_rawdata() → dtps_http.structures.RawData#

classmethod update_forward_refs(**localns: Any) → None#: Try to update ForwardRefs on fields based on this Model, globalns and localns.

classmethod validate(value: Any) → Model#

Float#

This message represents a floating point number.

pydantic model duckietown_messages.standard.float.Float#

Show JSON schema

{
   "title": "Float",
   "type": "object",
   "properties": {
      "header": {
         "title": "Header",
         "description": "Auto-generated header",
         "allOf": [
            {
               "$ref": "#/definitions/Header"
            }
         ]
      },
      "data": {
         "title": "Data",
         "description": "Floating point number payload",
         "type": "number"
      }
   },
   "required": [
      "data"
   ],
   "definitions": {
      "Header": {
         "title": "Header",
         "type": "object",
         "properties": {
            "version": {
               "title": "Version",
               "description": "Version of the message this header is attached to",
               "default": "1.0",
               "pattern": "^[0-9]+\\.[0-9]+(\\.[0-9]+)?$",
               "example": "0.1.3",
               "type": "string"
            },
            "frame": {
               "title": "Frame",
               "description": "Reference frame this data is captured in",
               "type": "string"
            },
            "txt": {
               "title": "Txt",
               "description": "Auxiliary data attached to the message",
               "type": "object"
            }
         }
      }
   }
}

Fields

data (float)
header (duckietown_messages.standard.header.Header)

field header: duckietown_messages.standard.header.Header [Optional]#: Auto-generated header

field data: float [Required]#: Floating point number payload

classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model#: Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values

Duplicate a model, optionally choose which fields to include, exclude and change.

Parameters

include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model

Returns

new model instance

dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) → DictStrAny#: Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

classmethod from_orm(obj: Any) → Model#

classmethod from_rawdata(rd: dtps_http.structures.RawData) → duckietown_messages.base.BaseMessage#

Generate a JSON representation of the model, include and exclude arguments as per dict().

encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().

classmethod parse_file(path: Union[str, pathlib.Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: pydantic.parse.Protocol = None, allow_pickle: bool = False) → Model#

classmethod parse_obj(obj: Any) → Model#

classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: pydantic.parse.Protocol = None, allow_pickle: bool = False) → Model#

classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny#

classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode#

to_rawdata() → dtps_http.structures.RawData#

classmethod update_forward_refs(**localns: Any) → None#: Try to update ForwardRefs on fields based on this Model, globalns and localns.

classmethod validate(value: Any) → Model#

List#

This message represents a generic list.

pydantic model duckietown_messages.standard.list.List#

Show JSON schema

{
   "title": "List",
   "type": "object",
   "properties": {
      "header": {
         "title": "Header",
         "description": "Auto-generated header",
         "allOf": [
            {
               "$ref": "#/definitions/Header"
            }
         ]
      },
      "data": {
         "title": "Data",
         "description": "List payload",
         "type": "array",
         "items": {}
      }
   },
   "required": [
      "data"
   ],
   "definitions": {
      "Header": {
         "title": "Header",
         "type": "object",
         "properties": {
            "version": {
               "title": "Version",
               "description": "Version of the message this header is attached to",
               "default": "1.0",
               "pattern": "^[0-9]+\\.[0-9]+(\\.[0-9]+)?$",
               "example": "0.1.3",
               "type": "string"
            },
            "frame": {
               "title": "Frame",
               "description": "Reference frame this data is captured in",
               "type": "string"
            },
            "txt": {
               "title": "Txt",
               "description": "Auxiliary data attached to the message",
               "type": "object"
            }
         }
      }
   }
}

Fields

data (list)
header (duckietown_messages.standard.header.Header)

field header: duckietown_messages.standard.header.Header [Optional]#: Auto-generated header

field data: list [Required]#: List payload

classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model#: Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values

Duplicate a model, optionally choose which fields to include, exclude and change.

Parameters

include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model

Returns

new model instance

dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) → DictStrAny#: Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

classmethod from_orm(obj: Any) → Model#

classmethod from_rawdata(rd: dtps_http.structures.RawData) → duckietown_messages.base.BaseMessage#

Generate a JSON representation of the model, include and exclude arguments as per dict().

encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().

classmethod parse_file(path: Union[str, pathlib.Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: pydantic.parse.Protocol = None, allow_pickle: bool = False) → Model#

classmethod parse_obj(obj: Any) → Model#

classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: pydantic.parse.Protocol = None, allow_pickle: bool = False) → Model#

classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny#

classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode#

to_rawdata() → dtps_http.structures.RawData#

classmethod update_forward_refs(**localns: Any) → None#: Try to update ForwardRefs on fields based on this Model, globalns and localns.

classmethod validate(value: Any) → Model#

Dictionary#

This message represents a generic (key, value) mapping (i.e., dictionary).

pydantic model duckietown_messages.standard.dictionary.Dictionary#

Show JSON schema

{
   "title": "Dictionary",
   "type": "object",
   "properties": {
      "header": {
         "title": "Header",
         "description": "Auto-generated header",
         "allOf": [
            {
               "$ref": "#/definitions/Header"
            }
         ]
      },
      "data": {
         "title": "Data",
         "description": "Dictionary payload",
         "type": "object"
      }
   },
   "required": [
      "data"
   ],
   "definitions": {
      "Header": {
         "title": "Header",
         "type": "object",
         "properties": {
            "version": {
               "title": "Version",
               "description": "Version of the message this header is attached to",
               "default": "1.0",
               "pattern": "^[0-9]+\\.[0-9]+(\\.[0-9]+)?$",
               "example": "0.1.3",
               "type": "string"
            },
            "frame": {
               "title": "Frame",
               "description": "Reference frame this data is captured in",
               "type": "string"
            },
            "txt": {
               "title": "Txt",
               "description": "Auxiliary data attached to the message",
               "type": "object"
            }
         }
      }
   }
}

Fields

data (dict)
header (duckietown_messages.standard.header.Header)

field header: duckietown_messages.standard.header.Header [Optional]#: Auto-generated header

field data: dict [Required]#: Dictionary payload

classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model#: Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values

Duplicate a model, optionally choose which fields to include, exclude and change.

Parameters

include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model

Returns

new model instance

dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) → DictStrAny#: Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

classmethod from_orm(obj: Any) → Model#

classmethod from_rawdata(rd: dtps_http.structures.RawData) → duckietown_messages.base.BaseMessage#

Generate a JSON representation of the model, include and exclude arguments as per dict().

encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().

classmethod parse_file(path: Union[str, pathlib.Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: pydantic.parse.Protocol = None, allow_pickle: bool = False) → Model#

classmethod parse_obj(obj: Any) → Model#

classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: pydantic.parse.Protocol = None, allow_pickle: bool = False) → Model#

classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny#

classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode#

to_rawdata() → dtps_http.structures.RawData#

classmethod update_forward_refs(**localns: Any) → None#: Try to update ForwardRefs on fields based on this Model, globalns and localns.

classmethod validate(value: Any) → Model#

Pair#

This message represents a generic pair of values.

pydantic model duckietown_messages.standard.pair.Pair#

Show JSON schema

{
   "title": "Pair",
   "description": "Abstract base class for generic types.\n\nA generic type is typically declared by inheriting from\nthis class parameterized with one or more type variables.\nFor example, a generic mapping type might be defined as::\n\n  class Mapping(Generic[KT, VT]):\n      def __getitem__(self, key: KT) -> VT:\n          ...\n      # Etc.\n\nThis class can then be used as follows::\n\n  def lookup_name(mapping: Mapping[KT, VT], key: KT, default: VT) -> VT:\n      try:\n          return mapping[key]\n      except KeyError:\n          return default",
   "type": "object",
   "properties": {
      "header": {
         "title": "Header",
         "description": "Auto-generated header",
         "allOf": [
            {
               "$ref": "#/definitions/Header"
            }
         ]
      },
      "first": {
         "title": "First",
         "description": "First element of the pair"
      },
      "second": {
         "title": "Second",
         "description": "Second element of the pair"
      }
   },
   "definitions": {
      "Header": {
         "title": "Header",
         "type": "object",
         "properties": {
            "version": {
               "title": "Version",
               "description": "Version of the message this header is attached to",
               "default": "1.0",
               "pattern": "^[0-9]+\\.[0-9]+(\\.[0-9]+)?$",
               "example": "0.1.3",
               "type": "string"
            },
            "frame": {
               "title": "Frame",
               "description": "Reference frame this data is captured in",
               "type": "string"
            },
            "txt": {
               "title": "Txt",
               "description": "Auxiliary data attached to the message",
               "type": "object"
            }
         }
      }
   }
}

Fields

first (duckietown_messages.standard.pair.T1)
header (duckietown_messages.standard.header.Header)
second (duckietown_messages.standard.pair.T2)

field header: duckietown_messages.standard.header.Header [Optional]#: Auto-generated header

field first: duckietown_messages.standard.pair.T1 = None#: First element of the pair

field second: duckietown_messages.standard.pair.T2 = None#: Second element of the pair

classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model#: Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values

Duplicate a model, optionally choose which fields to include, exclude and change.

Parameters

include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data
deep – set to True to make a deep copy of the model

Returns

new model instance

dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) → DictStrAny#: Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

classmethod from_orm(obj: Any) → Model#

classmethod from_rawdata(rd: dtps_http.structures.RawData) → duckietown_messages.base.BaseMessage#

Generate a JSON representation of the model, include and exclude arguments as per dict().

encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().

classmethod parse_file(path: Union[str, pathlib.Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: pydantic.parse.Protocol = None, allow_pickle: bool = False) → Model#

classmethod parse_obj(obj: Any) → Model#

classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: pydantic.parse.Protocol = None, allow_pickle: bool = False) → Model#

classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny#

classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode#

to_rawdata() → dtps_http.structures.RawData#

classmethod update_forward_refs(**localns: Any) → None#: Try to update ForwardRefs on fields based on this Model, globalns and localns.

classmethod validate(value: Any) → Model#

The Duckietown Developer Manual - ente

Messages - standard

Contents

Messages - `standard`#

Header#

Boolean#

Integer#

Float#

List#

Dictionary#

Pair#

The Duckietown Developer Manual - ente

Messages - standard

Contents

Messages - standard#

Header#

Boolean#

Integer#

Float#

List#

Dictionary#

Pair#

Messages - `standard`#