"""Yahoo Finance Aggressive Small Caps Model."""

# pylint: disable=unused-argument

from typing import Any

from openbb_core.provider.abstract.fetcher import Fetcher
from openbb_core.provider.standard_models.equity_performance import (
    EquityPerformanceQueryParams,
)
from openbb_yfinance.utils.references import YFPredefinedScreenerData
from pydantic import Field


class YFAggressiveSmallCapsQueryParams(EquityPerformanceQueryParams):
    """Yahoo Finance Aggressive Small Caps Query.

    Source: https://finance.yahoo.com/screener/predefined/aggressive_small_caps
    """

    limit: int | None = Field(
        default=None,
        description="Limit the number of results. Default is all.",
    )


class YFAggressiveSmallCapsData(YFPredefinedScreenerData):
    """Yahoo Finance Aggressive Small Caps Data."""


class YFAggressiveSmallCapsFetcher(
    Fetcher[YFAggressiveSmallCapsQueryParams, list[YFAggressiveSmallCapsData]]
):
    """Transform the query, extract and transform the data from the Yahoo Finance endpoints."""

    @staticmethod
    def transform_query(params: dict[str, Any]) -> YFAggressiveSmallCapsQueryParams:
        """Transform query params."""
        return YFAggressiveSmallCapsQueryParams(**params)

    @staticmethod
    async def aextract_data(
        query: YFAggressiveSmallCapsQueryParams,
        credentials: dict[str, str] | None,
        **kwargs: Any,
    ) -> list[dict]:
        """Get data from YF."""
        # pylint: disable=import-outside-toplevel
        from openbb_yfinance.utils.helpers import get_custom_screener

        # The predefined screener doesn't match what yFinance has for the settings. We'll have to create our own.
        body = {
            "offset": 0,
            "size": 250,
            "sortField": "totalrevenues1yrgrowth.lasttwelvemonths",
            "sortType": "desc",
            "quoteType": "equity",
            "query": {
                "operator": "and",
                "operands": [
                    {"operator": "lt", "operands": ["intradaymarketcap", 2000000000]},
                    {
                        "operator": "or",
                        "operands": [
                            {"operator": "eq", "operands": ["exchange", "NMS"]},
                            {"operator": "eq", "operands": ["exchange", "NYQ"]},
                        ],
                    },
                    {"operator": "gt", "operands": ["epsgrowth.lasttwelvemonths", 25]},
                    {"operator": "gt", "operands": ["intradayprice", 5]},
                ],
            },
            "userId": "",
            "userIdType": "guid",
        }
        return await get_custom_screener(body=body, limit=query.limit)

    @staticmethod
    def transform_data(
        query: EquityPerformanceQueryParams,
        data: list[dict],
        **kwargs: Any,
    ) -> list[YFAggressiveSmallCapsData]:
        """Transform data."""
        return sorted(
            [YFAggressiveSmallCapsData.model_validate(d) for d in data],
            key=lambda x: x.percent_change,
            reverse=query.sort == "desc",
        )