Object Model Attributes¶

`ObjectModelAttributeDefinitions(baze)` ¶

Class used for handling object model attribute definitions.

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(object_models, output_type='dict')` ¶

Gets the attribute definitions for specific object models.

These can be viewed in the portal in Object Types > Model Attribute Definition. Most of the attributes will have the following properties:

attributeId
categoryId
displayId
groupId
isBuiltIn
isMandatory
isVisible
name
valueType

Parameters:

object_models ¶
(list[str]) –

List of object models to get the attributes from.
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_model_attribute_definitions.py

@validate_call
def get(self, object_models: list[str], output_type: Literal["dict", "DataFrame"] = "dict") -> dict[str, dict[str, Any]] | DataFrame:
    """Gets the attribute definitions for specific object models.

    These can be viewed in the portal in `Object Types > Model Attribute Definition`.
    Most of the attributes will have the following properties:

    - attributeId
    - categoryId
    - displayId
    - groupId
    - isBuiltIn
    - isMandatory
    - isVisible
    - name
    - valueType

    Parameters
    ----------
    object_models : list[str]
        List of object models to get the attributes from.
    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, ...]
    """
    # getting object type
    object_models_types = self.baze.objects.models.get()
    object_models_types = {k: v["itemTypeName"] for k, v in object_models_types.items() if k in object_models}
    if not object_models_types:
        raise ValueError("No valid object models were given.")

    # getting object type and category ids
    object_types = self.baze.objects.types.get()
    object_types = {k: {"typeId": v["type"]["typeId"], "categoryId": v["type"]["categoryId"]} for k, v in object_types.items()}

    attributes_def = []

    # getting attribute definitions
    for object_model_name, object_model_type in object_models_types.items():
        # getting the data
        endpoint = f"configuration/objecttype/{object_types[object_model_type]['typeId']}/category/{object_types[object_model_type]['categoryId']}/attributes/model"
        result = self.baze.conn.get(endpoint)
        self._handle_http_errors(result)
        # converting to dict
        result: dict[str, Any] = result.json()
        # converting to a better format
        # {attribute_key: {name: name, value: value, valueType: valueType}, ...}
        result = {entry["key"]: entry for entry in result}
        # removing key
        for attribute in result.values():
            del attribute["key"]
        # adding to root list
        attributes_def.append({"name": object_model_name} | result)

    # 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 attributes_def}
            # removing the name from the dict values
            for entry in result_dict.values():
                del entry["name"]
            return result_dict
        case "DataFrame":
            df = json_normalize(attributes_def, 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}")

`ObjectModelAttributeValues(baze)` ¶

Class used for handling object model attribute values.

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(object_models, output_type='dict')` ¶

Gets the attribute values for specific object models.

These can be viewed and set in the Object Models section of the portal.

Parameters:

object_models ¶
(list[str]) –

List of object models to get the attributes from.
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_model_attribute_values.py

@validate_call
def get(self, object_models: list[str], output_type: Literal["dict", "DataFrame"] = "dict") -> dict[str, dict[str, Any]] | DataFrame:
    """Gets the attribute values for specific object models.

    These can be viewed and set in the Object Models section of the portal.

    Parameters
    ----------
    object_models : list[str]
        List of object models to get the attributes from.
    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, ...]

    """
    # getting ids of the object models
    object_models_ids = self.baze.objects.models.get_ids()

    for object_model in object_models:
        if object_model not in object_models_ids:
            raise ValueError(f"Invalid object model: {object_model}")

    attribute_values = []
    for object_model in object_models:
        endpoint = f"configuration/domains/{object_models_ids[object_model]}"
        # getting the data
        result = self.baze.conn.get(endpoint)
        self._handle_http_errors(result)
        # converting to dict
        result: dict[str, Any] = result.json()
        # casting data types
        result = self.baze.objects.instances._cast_attributes([result])[0]  # pylint: disable=protected-access # noqa
        # converting to a better format
        # {attribute_key: value, ...}
        result = result["attributes"]
        # adding to root list
        attribute_values.append({"model_name": object_model} | result)

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

`update(object_model, attributes)` ¶

Updates attribute values for a specific object model.

This action can be done in the Object Models section of the portal.

Parameters:

object_model ¶
(str) –

Name of the desired object model.
attributes ¶
(dict[str, Any]) –

Dict with the attributes to be updated. It must be in the format {key: value, ...}

Source code in echo_baze/object_model_attribute_values.py

@validate_call
def update(self, object_model: str, attributes: dict[str, Any]) -> None:
    """Updates attribute values for a specific object model.

    This action can be done in the Object Models section of the portal.

    Parameters
    ----------
    object_model : str
        Name of the desired object model.
    attributes : dict[str, Any]
        Dict with the attributes to be updated. It must be in the format {key: value, ...}

    """
    # getting ids of the object models
    object_models_ids = self.baze.objects.models.get_ids()

    # getting the model definition
    endpoint = f"configuration/domains/{object_models_ids[object_model]}"
    # getting the data
    result = self.baze.conn.get(endpoint)
    self._handle_http_errors(result)
    # converting to dict
    model_def: dict[str, Any] = result.json()

    # changing attributes
    for attribute_key, attribute_value in attributes.items():
        if attribute_key not in model_def["attributes"]:
            raise ValueError(f"Attribute key {attribute_key} is not valid for object model {object_model}.")
        model_def["attributes"][attribute_key] = attribute_value

    # updating
    endpoint = "configuration/domains"

    payload = deepcopy(model_def)

    result = self.baze.conn.post(endpoint, json=payload)
    self._handle_http_errors(result)
    # converting to dict
    result: dict[str, Any] = result.json()

    # checking if the update was successful
    for attribute_name, attribute_value in result["attributes"].items():
        if attribute_value != str(payload["attributes"][attribute_name]):
            raise ValueError(f"Updating attribute {attribute_name} failed.")

Object Model Attributes¶

`ObjectModelAttributeDefinitions(baze)` ¶

`get(object_models, output_type='dict')` ¶

`object_models` ¶

`output_type` ¶

`ObjectModelAttributeValues(baze)` ¶

`get(object_models, output_type='dict')` ¶

`object_models` ¶

`output_type` ¶

`update(object_model, attributes)` ¶

`object_model` ¶

`attributes` ¶

Object Model Attributes¶

ObjectModelAttributeDefinitions(baze) ¶

get(object_models, output_type='dict') ¶

object_models ¶

output_type ¶

ObjectModelAttributeValues(baze) ¶

get(object_models, output_type='dict') ¶

object_models ¶

output_type ¶

update(object_model, attributes) ¶

object_model ¶

attributes ¶

`ObjectModelAttributeDefinitions(baze)` ¶

`get(object_models, output_type='dict')` ¶

`object_models` ¶

`output_type` ¶

`ObjectModelAttributeValues(baze)` ¶

`get(object_models, output_type='dict')` ¶

`object_models` ¶

`output_type` ¶

`update(object_model, attributes)` ¶

`object_model` ¶

`attributes` ¶