# coding: utf-8

"""
    qoery's API

    Every number on the internet, queryable. Instant access to millions of trusted statistics through a single natural language query or API call.  # Installation  ### Python SDK  Install from PyPI:  ```bash pip install qoery ```  PyPI: [qoery](https://pypi.org/project/qoery/)  ### JavaScript SDK  Install from npm:  ```bash npm install qoery ```  npm: [qoery](https://www.npmjs.com/package/qoery) 

    The version of the OpenAPI document: 0.4.0
    Contact: samuel.tinnerholm@gmail.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, StrictStr
from typing import Any, ClassVar, Dict, List, Optional
from typing_extensions import Annotated
from typing import Optional, Set
from typing_extensions import Self

class NLQueryRequest(BaseModel):
    """
    NLQueryRequest
    """ # noqa: E501
    query: StrictStr = Field(description="Natural language query")
    num_results: Optional[Annotated[int, Field(le=100, strict=True, ge=1)]] = Field(default=10, description="Number of search results to process")
    paragraph_extraction: Optional[StrictBool] = Field(default=False, description="Enable paragraph-based time-series extraction")
    plot2table: Optional[Annotated[int, Field(strict=True, ge=0)]] = Field(default=0, description="Number of charts/images to process with plot2table")
    __properties: ClassVar[List[str]] = ["query", "num_results", "paragraph_extraction", "plot2table"]

    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 NLQueryRequest 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 NLQueryRequest from a dict"""
        if obj is None:
            return None

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

        _obj = cls.model_validate({
            "query": obj.get("query"),
            "num_results": obj.get("num_results") if obj.get("num_results") is not None else 10,
            "paragraph_extraction": obj.get("paragraph_extraction") if obj.get("paragraph_extraction") is not None else False,
            "plot2table": obj.get("plot2table") if obj.get("plot2table") is not None else 0
        })
        return _obj


