Source code for pydelfini.delfini_core.models.metrics_text

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 ..types import UNSET
from ..types import Unset


T = TypeVar("T", bound="MetricsText")




@_attrs_define
class MetricsText:
    """MetricsText model

    Attributes:
        avg_length (float):
        max_length (int):
        min_length (int):
        empty_string_count (Union[Unset, int]):  Default: 0.
    """

    avg_length: float
    max_length: int
    min_length: int
    empty_string_count: Union[Unset, int] = 0



    def to_dict(self) -> Dict[str, Any]:
        """Convert to a dict"""
        avg_length = self.avg_length
        max_length = self.max_length
        min_length = self.min_length
        empty_string_count = self.empty_string_count

        field_dict: Dict[str, Any] = {}
        field_dict.update(
            {
                "avgLength": avg_length,
                "maxLength": max_length,
                "minLength": min_length,
            }
        )
        if empty_string_count is not UNSET:
            field_dict["emptyStringCount"] = empty_string_count

        return field_dict




    @classmethod
    def from_dict(cls: Type[T], src_dict: Dict[str, Any]) -> T:
        """Create an instance of :py:class:`MetricsText` from a dict"""
        d = src_dict.copy()
        avg_length = d.pop("avgLength")

        max_length = d.pop("maxLength")

        min_length = d.pop("minLength")

        empty_string_count = d.pop("emptyStringCount", UNSET)

        metrics_text = cls(
            avg_length=avg_length,
            max_length=max_length,
            min_length=min_length,
            empty_string_count=empty_string_count,
        )

        return metrics_text