# coding: utf-8

"""
    Neurograph Core

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

    The version of the OpenAPI document: 1.0
    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, StrictStr
from typing import Any, ClassVar, Dict, List, Optional
from typing import Optional, Set
from typing_extensions import Self

class ReportingClearCacheRequest(BaseModel):
    """
    ReportingClearCacheRequest
    """ # noqa: E501
    client_partition_key: Optional[StrictStr] = Field(default=None, description="ClientPartitionKey: org_uid + client_uid + domain")
    persona_id: Optional[StrictStr] = Field(default=None, description="PersonaId: the persona seed ID (per_...) to clear caches for")
    query_type: Optional[StrictStr] = Field(default=None, description="QueryType: specific cache to clear (only used when scope=query) Options: persona-affinity, persona-demographics, buyer-scenarios, customer-insights,          product-affinity, enrichment-coverage, model-insights, model-job-detail,          prediction-detail, client-activity, daily-rollup, portfolio-activity, all")
    scope: Optional[StrictStr] = Field(default=None, description="Scope: \"persona\" clears all caches for a persona, \"query\" clears a specific query type")
    __properties: ClassVar[List[str]] = ["client_partition_key", "persona_id", "query_type", "scope"]

    model_config = ConfigDict(
        populate_by_name=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"""
        # 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 ReportingClearCacheRequest 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,
        )
        return _dict

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

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

        _obj = cls.model_validate({
            "client_partition_key": obj.get("client_partition_key"),
            "persona_id": obj.get("persona_id"),
            "query_type": obj.get("query_type"),
            "scope": obj.get("scope")
        })
        return _obj


