Source code for pydelfini.delfini_core.models.metrics_numeric
from typing import Any
from typing import Dict
from typing import Type
from typing import TypeVar
from typing import Union
from attrs import define as _attrs_define
from ..models.metrics_quantiles import MetricsQuantiles
from ..types import UNSET
from ..types import Unset
T = TypeVar("T", bound="MetricsNumeric")
[docs]
@_attrs_define
class MetricsNumeric:
"""MetricsNumeric model
Attributes:
max_ (float):
mean (float):
min_ (float):
std_dev (float):
quantiles (Union[Unset, MetricsQuantiles]):
"""
max_: float
mean: float
min_: float
std_dev: float
quantiles: Union[Unset, "MetricsQuantiles"] = UNSET
[docs]
def to_dict(self) -> Dict[str, Any]:
"""Convert to a dict"""
max_ = self.max_
mean = self.mean
min_ = self.min_
std_dev = self.std_dev
quantiles: Union[Unset, Dict[str, Any]] = UNSET
if not isinstance(self.quantiles, Unset):
quantiles = self.quantiles.to_dict()
field_dict: Dict[str, Any] = {}
field_dict.update(
{
"max": max_,
"mean": mean,
"min": min_,
"stdDev": std_dev,
}
)
if quantiles is not UNSET:
field_dict["quantiles"] = quantiles
return field_dict
[docs]
@classmethod
def from_dict(cls: Type[T], src_dict: Dict[str, Any]) -> T:
"""Create an instance of :py:class:`MetricsNumeric` from a dict"""
d = src_dict.copy()
max_ = d.pop("max")
mean = d.pop("mean")
min_ = d.pop("min")
std_dev = d.pop("stdDev")
_quantiles = d.pop("quantiles", UNSET)
quantiles: Union[Unset, MetricsQuantiles]
if isinstance(_quantiles, Unset):
quantiles = UNSET
else:
quantiles = MetricsQuantiles.from_dict(_quantiles)
metrics_numeric = cls(
max_=max_,
mean=mean,
min_=min_,
std_dev=std_dev,
quantiles=quantiles,
)
return metrics_numeric