# coding: utf-8

"""
    SmartyMeet Dev03 API REST

    No description provided (generated by Openapi Generator https://github.com/openapitools/openapi-generator)

    The version of the OpenAPI document: 1.0.1
    Contact: developer@smartymeet.com
    Generated by OpenAPI Generator (https://openapi-generator.tech)

    Do not edit the class manually.
"""  # noqa: E501


from __future__ import annotations
import pprint
import re  # noqa: F401
import json

from pydantic import BaseModel, ConfigDict, Field, StrictBool, StrictFloat, StrictInt, StrictStr, field_validator
from typing import Any, ClassVar, Dict, List, Optional, Union
from typing import Optional, Set
from typing_extensions import Self
from pydantic_core import to_jsonable_python

class CandidateCriteriaSchema(BaseModel):
    """
    Comparison criteria object for candidate evaluation. Contains expected values from the job, received values from the talent, and comparison metadata.
    """ # noqa: E501
    name: Optional[StrictStr] = Field(default=None, description="Display name of the criteria")
    description: Optional[StrictStr] = Field(default=None, description="Description of what this criteria evaluates")
    priority: Optional[StrictStr] = Field(default=None, description="Priority level of this criteria")
    priority_confidence: Optional[StrictStr] = Field(default=None, description="Confidence level of the priority assignment", alias="priorityConfidence")
    priority_reasoning: Optional[StrictStr] = Field(default=None, description="Explanation for the assigned priority level", alias="priorityReasoning")
    expected: Optional[List[Dict[str, Any]]] = None
    received: Optional[List[Dict[str, Any]]] = None
    weight: Optional[StrictStr] = Field(default=None, description="Weight factor for this criteria in overall scoring")
    rating: Optional[Union[StrictFloat, StrictInt]] = Field(default=None, description="Match rating for this criteria (0-5)")
    prev_rating: Optional[Union[StrictFloat, StrictInt]] = Field(default=None, description="Previous rating before recalculation", alias="prevRating")
    data_available: Optional[StrictBool] = Field(default=None, description="Whether data was available to perform the comparison", alias="dataAvailable")
    comparison_confidence: Optional[StrictStr] = Field(default=None, description="Confidence level of the comparison result", alias="comparisonConfidence")
    comparison_reasoning: Optional[StrictStr] = Field(default=None, description="Explanation of the comparison result", alias="comparisonReasoning")
    is_comparison_assumed: Optional[StrictBool] = Field(default=None, description="Whether the comparison was assumed rather than directly derived", alias="isComparisonAssumed")
    __properties: ClassVar[List[str]] = ["name", "description", "priority", "priorityConfidence", "priorityReasoning", "expected", "received", "weight", "rating", "prevRating", "dataAvailable", "comparisonConfidence", "comparisonReasoning", "isComparisonAssumed"]

    @field_validator('priority')
    def priority_validate_enum(cls, value):
        """Validates the enum"""
        if value is None:
            return value

        if value not in set(['low', 'medium', 'high', 'must']):
            raise ValueError("must be one of enum values ('low', 'medium', 'high', 'must')")
        return value

    @field_validator('priority_confidence')
    def priority_confidence_validate_enum(cls, value):
        """Validates the enum"""
        if value is None:
            return value

        if value not in set(['low', 'medium', 'high']):
            raise ValueError("must be one of enum values ('low', 'medium', 'high')")
        return value

    model_config = ConfigDict(
        validate_by_name=True,
        validate_by_alias=True,
        validate_assignment=True,
        protected_namespaces=(),
    )


    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"""
        return json.dumps(to_jsonable_python(self.to_dict()))

    @classmethod
    def from_json(cls, json_str: str) -> Optional[Self]:
        """Create an instance of CandidateCriteriaSchema 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,
        )
        # set to None if expected (nullable) is None
        # and model_fields_set contains the field
        if self.expected is None and "expected" in self.model_fields_set:
            _dict['expected'] = None

        # set to None if received (nullable) is None
        # and model_fields_set contains the field
        if self.received is None and "received" in self.model_fields_set:
            _dict['received'] = None

        # set to None if rating (nullable) is None
        # and model_fields_set contains the field
        if self.rating is None and "rating" in self.model_fields_set:
            _dict['rating'] = None

        # set to None if prev_rating (nullable) is None
        # and model_fields_set contains the field
        if self.prev_rating is None and "prev_rating" in self.model_fields_set:
            _dict['prevRating'] = None

        # set to None if comparison_confidence (nullable) is None
        # and model_fields_set contains the field
        if self.comparison_confidence is None and "comparison_confidence" in self.model_fields_set:
            _dict['comparisonConfidence'] = None

        return _dict

    @classmethod
    def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
        """Create an instance of CandidateCriteriaSchema from a dict"""
        if obj is None:
            return None

        if not isinstance(obj, dict):
            return cls.model_validate(obj)

        _obj = cls.model_validate({
            "name": obj.get("name"),
            "description": obj.get("description"),
            "priority": obj.get("priority"),
            "priorityConfidence": obj.get("priorityConfidence"),
            "priorityReasoning": obj.get("priorityReasoning"),
            "expected": obj.get("expected"),
            "received": obj.get("received"),
            "weight": obj.get("weight"),
            "rating": obj.get("rating"),
            "prevRating": obj.get("prevRating"),
            "dataAvailable": obj.get("dataAvailable"),
            "comparisonConfidence": obj.get("comparisonConfidence"),
            "comparisonReasoning": obj.get("comparisonReasoning"),
            "isComparisonAssumed": obj.get("isComparisonAssumed")
        })
        return _obj


