Object Categories

ObjectCategories(baze)

Class used for handling object categories.

Source code in echo_baze/baze_root.py

def __init__(self, baze: e_bz.Baze) -> None:
    """Base class that all subclasses should inherit from.

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

    """
    # check inputs
    if not isinstance(baze, e_bz.Baze):
        raise ValueError(f"baze must be of type Baze, not {type(baze)}")

    self.baze: e_bz.Baze = baze

get(output_type='dict')

Gets all object categories with detailed information.

The most useful keys/columns returned are: - categoryId - acronym

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_categories.py

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

    The most useful keys/columns returned are:
    - categoryId
    - acronym

    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, ...]
    """
    endpoint = "objectCategory"

    # 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 category names and ids.

Returns:

• dict[str, int]: –

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

Source code in echo_baze/object_categories.py

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

    Returns
    -------
    dict[str, int]:
        Dictionary with all object categories in the format {name: id, ...}
    """
    endpoint = "objectCategory"

    # 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["categoryId"] for entry in result}