Object Types

ObjectTypes(baze)

Class used for handling object types.

Parameters:

• baze

  (Baze) –

  Top level object carrying all functionality and the connection handler.

Source code in echo_baze/object_types.py

def __init__(self, baze: e_bz.Baze) -> None:
    """Class used for handling object types.

    Parameters
    ----------
    baze : Baze
        Top level object carrying all functionality and the connection handler.

    """
    super().__init__(baze)

    # * subclasses

    from .object_type_attributes import ObjectTypeAttributes

    self.attributes = ObjectTypeAttributes(baze)

get(output_type='dict')

Gets all object types with detailed information.

The most useful keys/columns returned are: - itemTypeId - acronym - type

Parameters:

• output_type

  (Literal['dict', 'DataFrame'], default: 'dict' ) –

  Output type of the data. Can be one of ["dict", "DataFrame"] By default "dict"

Returns:

• dict[str, dict[str, Any]] –

  In case output_type == "dict" it will return a dict with the following format: {name: {attribute: value, ...}, ...}

• DataFrame –

  In case output_type == "DataFrame" it will return a DataFrame with the following format: index = name, columns = [attribute, ...]

Source code in echo_baze/object_types.py

@validate_call
def get(self, output_type: Literal["dict", "DataFrame"] = "dict") -> dict[str, dict[str, Any]] | DataFrame:
    """Gets all object types with detailed information.

    The most useful keys/columns returned are:
    - itemTypeId
    - acronym
    - type

    Parameters
    ----------
    output_type : Literal["dict", "DataFrame"], optional
        Output type of the data. Can be one of ["dict", "DataFrame"]
        By default "dict"

    Returns
    -------
    dict[str, dict[str, Any]]
        In case output_type == "dict" it will return a dict with the following format: {name: {attribute: value, ...}, ...}
    DataFrame
        In case output_type == "DataFrame" it will return a DataFrame with the following format: index = name, columns = [attribute, ...]

    """
    # checking input

    endpoint = "objectTypes"

    # getting the data
    result = self.baze.conn.get(endpoint)
    self._handle_http_errors(result)

    # converting to dict
    result: list[dict[str, Any]] = result.json()

    # returning on the desired format
    match output_type:
        case "dict":
            # defining the name as the key for the dict
            result_dict = {entry["name"]: entry for entry in result}
            # removing the name from the dict values
            for entry in result_dict.values():
                del entry["name"]
            return result_dict
        case "DataFrame":
            df = json_normalize(result, max_level=1)
            df = df.convert_dtypes(dtype_backend="pyarrow")
            df = df.set_index("name")
            return df
        case _:
            raise ValueError(f"Invalid output_type: {output_type}")

get_ids()

Gets a dictionary with all object type names and ids.

Returns:

• dict[str, int]: –

  Dictionary with all object types in the format {name: id, ...}

Source code in echo_baze/object_types.py

def get_ids(self) -> dict[str, int]:
    """Gets a dictionary with all object type names and ids.

    Returns
    -------
    dict[str, int]:
        Dictionary with all object types in the format {name: id, ...}

    """
    endpoint = "objectTypes"

    # getting the data
    result = self.baze.conn.get(endpoint)
    self._handle_http_errors(result)

    # converting to dict
    result: list[dict[str, Any]] = result.json()

    return {entry["name"]: entry["type"]["typeId"] for entry in result}