Source code for pydelfini.delfini_core.models.metrics_categorical
from typing import Any
from typing import Dict
from typing import List
from typing import Type
from typing import TypeVar
from attrs import define as _attrs_define
from ..models.metrics_categorical_value import MetricsCategoricalValue
T = TypeVar("T", bound="MetricsCategorical")
[docs]
@_attrs_define
class MetricsCategorical:
"""MetricsCategorical model
Attributes:
low_cardinality_threshold (int):
unique_values_sorted (List['MetricsCategoricalValue']):
"""
low_cardinality_threshold: int
unique_values_sorted: List["MetricsCategoricalValue"]
[docs]
def to_dict(self) -> Dict[str, Any]:
"""Convert to a dict"""
low_cardinality_threshold = self.low_cardinality_threshold
unique_values_sorted = []
for unique_values_sorted_item_data in self.unique_values_sorted:
unique_values_sorted_item = unique_values_sorted_item_data.to_dict()
unique_values_sorted.append(unique_values_sorted_item)
field_dict: Dict[str, Any] = {}
field_dict.update(
{
"lowCardinalityThreshold": low_cardinality_threshold,
"uniqueValuesSorted": unique_values_sorted,
}
)
return field_dict
[docs]
@classmethod
def from_dict(cls: Type[T], src_dict: Dict[str, Any]) -> T:
"""Create an instance of :py:class:`MetricsCategorical` from a dict"""
d = src_dict.copy()
low_cardinality_threshold = d.pop("lowCardinalityThreshold")
unique_values_sorted = []
_unique_values_sorted = d.pop("uniqueValuesSorted")
for unique_values_sorted_item_data in _unique_values_sorted:
unique_values_sorted_item = MetricsCategoricalValue.from_dict(
unique_values_sorted_item_data
)
unique_values_sorted.append(unique_values_sorted_item)
metrics_categorical = cls(
low_cardinality_threshold=low_cardinality_threshold,
unique_values_sorted=unique_values_sorted,
)
return metrics_categorical