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area_array.py
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102 lines (84 loc) · 3.67 KB
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# coding: utf-8
"""
Generated by: https://openapi-generator.tech
"""
from __future__ import annotations
import pprint
import re # noqa: F401
import json
from pydantic import BaseModel, ConfigDict, Field, StrictFloat, StrictInt
from typing import Any, ClassVar, Dict, List, Union
from regula.documentreader.webclient.gen.models.point_array import PointArray
from regula.documentreader.webclient.gen.models.rectangle_coordinates import RectangleCoordinates
from typing import Optional, Set
from typing_extensions import Self
from pydantic import SkipValidation, Field
class AreaArray(BaseModel):
"""
AreaArray
""" # noqa: E501
count: SkipValidation[float] = Field(alias="Count", description="Number of elements in List and Points")
list: SkipValidation[List[RectangleCoordinates]] = Field(alias="List")
points: SkipValidation[List[PointArray]] = Field(alias="Points")
__properties: ClassVar[List[str]] = ["Count", "List", "Points"]
model_config = ConfigDict(
populate_by_name=True,
validate_assignment=True,
protected_namespaces=(),
arbitrary_types_allowed=True,
use_enum_values=True
)
def to_str(self) -> str:
"""Returns the string representation of the model using alias"""
return pprint.pformat(self.model_dump(by_alias=True))
def to_json(self) -> str:
"""Returns the JSON representation of the model using alias"""
# TODO: pydantic v2: use .model_dump_json(by_alias=True, exclude_unset=True) instead
return json.dumps(self.to_dict())
@classmethod
def from_json(cls, json_str: str) -> Optional[Self]:
"""Create an instance of AreaArray from a JSON string"""
return cls.from_dict(json.loads(json_str))
def to_dict(self) -> Dict[str, Any]:
"""Return the dictionary representation of the model using alias.
This has the following differences from calling pydantic's
`self.model_dump(by_alias=True)`:
* `None` is only added to the output dict for nullable fields that
were set at model initialization. Other fields with value `None`
are ignored.
"""
excluded_fields: Set[str] = set([
])
_dict = self.model_dump(
by_alias=True,
exclude=excluded_fields,
exclude_none=True,
)
# override the default output from pydantic by calling `to_dict()` of each item in list (list)
_items = []
if self.list:
for _item_list in self.list:
if _item_list and hasattr(_item_list, "to_dict"):
_items.append(_item_list.to_dict())
_dict['List'] = _items
# override the default output from pydantic by calling `to_dict()` of each item in points (list)
_items = []
if self.points:
for _item_points in self.points:
if _item_points and hasattr(_item_points, "to_dict"):
_items.append(_item_points.to_dict())
_dict['Points'] = _items
return _dict
@classmethod
def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
"""Create an instance of AreaArray from a dict"""
if obj is None:
return None
if not isinstance(obj, dict):
return cls.model_validate(obj)
_obj = cls.model_validate({
"Count": obj.get("Count"),
"List": [RectangleCoordinates.from_dict(_item) for _item in obj.get("List", []) if RectangleCoordinates.from_dict(_item) is not None],
"Points": [PointArray.from_dict(_item) for _item in obj.get("Points", []) if PointArray.from_dict(_item) is not None]
})
return _obj