# coding: utf-8

"""
    STACKIT File Storage (SFS)

    API used to create and manage NFS Shares.

    The version of the OpenAPI document: 1.0.0
    Generated by OpenAPI Generator (https://openapi-generator.tech)

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

from __future__ import annotations

import json
import pprint
from typing import Any, ClassVar, Dict, List, Optional, Set

from pydantic import BaseModel, ConfigDict, Field, StrictStr
from typing_extensions import Self

from stackit.sfs.models.validation_error_field import ValidationErrorField


class ValidationError(BaseModel):
    """
    ValidationError
    """  # noqa: E501

    error_description: Optional[Any] = Field(
        default=None, description="Human-readable string of the error that occured"
    )
    title: StrictStr = Field(description="Human-readable description of the error that occurred.")
    type: StrictStr = Field(
        description="URI Uniquely identifies the error type. It will be in the format of storage.stackit.cloud/<error-type> e.g. storage.stackit.cloud/validation-error"
    )
    fields: List[ValidationErrorField]
    __properties: ClassVar[List[str]] = ["error_description", "title", "type", "fields"]

    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 ValidationError 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 fields (list)
        _items = []
        if self.fields:
            for _item_fields in self.fields:
                if _item_fields:
                    _items.append(_item_fields.to_dict())
            _dict["fields"] = _items
        # set to None if error_description (nullable) is None
        # and model_fields_set contains the field
        if self.error_description is None and "error_description" in self.model_fields_set:
            _dict["error_description"] = None

        return _dict

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

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

        _obj = cls.model_validate(
            {
                "error_description": obj.get("error_description"),
                "title": obj.get("title"),
                "type": obj.get("type"),
                "fields": (
                    [ValidationErrorField.from_dict(_item) for _item in obj["fields"]]
                    if obj.get("fields") is not None
                    else None
                ),
            }
        )
        return _obj
