# coding: utf-8

"""
    ME TT DataPortal Data Portal API

    ME TT DataPortal Data Portal APIs to fetch Gut Microbes Genomes / Genes information.

    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 pprint
import re  # noqa: F401
import json

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

class FitnessSearchQuerySchema(BaseModel):
    """
    Schema for fitness search endpoint query parameters.
    """ # noqa: E501
    locus_tags: Optional[StrictStr] = None
    uniprot_ids: Optional[StrictStr] = None
    contrast: Optional[StrictStr] = None
    min_lfc: Optional[Union[StrictFloat, StrictInt]] = None
    max_fdr: Optional[Union[Annotated[float, Field(le=1, strict=True, ge=0)], Annotated[int, Field(le=1, strict=True, ge=0)]]] = None
    min_barcodes: Optional[Annotated[int, Field(strict=True, ge=0)]] = None
    __properties: ClassVar[List[str]] = ["locus_tags", "uniprot_ids", "contrast", "min_lfc", "max_fdr", "min_barcodes"]

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

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

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

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

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

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

        return _dict

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

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

        _obj = cls.model_validate({
            "locus_tags": obj.get("locus_tags"),
            "uniprot_ids": obj.get("uniprot_ids"),
            "contrast": obj.get("contrast"),
            "min_lfc": obj.get("min_lfc"),
            "max_fdr": obj.get("max_fdr"),
            "min_barcodes": obj.get("min_barcodes")
        })
        return _obj


