"""
Quant strategy related Pydantic schemas.
"""
from datetime import date
from decimal import Decimal
from typing import Optional, List, Dict

from pydantic import BaseModel, Field

from app.schemas.portfolio import FloatDecimal


class FactorWeights(BaseModel):
    """Factor weights for multi-factor strategy."""
    value: FloatDecimal = Field(default=Decimal("0.25"), ge=0, le=1)
    quality: FloatDecimal = Field(default=Decimal("0.25"), ge=0, le=1)
    momentum: FloatDecimal = Field(default=Decimal("0.25"), ge=0, le=1)
    low_vol: FloatDecimal = Field(default=Decimal("0.25"), ge=0, le=1)


class UniverseFilter(BaseModel):
    """Stock universe filtering criteria."""
    markets: List[str] = ["KOSPI", "KOSDAQ"]
    min_market_cap: Optional[int] = None  # in 억원
    max_market_cap: Optional[int] = None
    exclude_stock_types: List[str] = ["spac", "preferred", "reit"]
    exclude_sectors: List[str] = []


class StrategyRequest(BaseModel):
    """Base request for running a strategy."""
    universe: UniverseFilter = UniverseFilter()
    top_n: int = Field(default=30, ge=1, le=100)
    base_date: Optional[date] = None
    dc_only: bool = False


class MultiFactorRequest(StrategyRequest):
    """Multi-factor strategy request."""
    weights: FactorWeights = FactorWeights()


class QualityRequest(StrategyRequest):
    """Super Quality strategy request."""
    min_fscore: int = Field(default=7, ge=0, le=9)


class ValueMomentumRequest(StrategyRequest):
    """Value-Momentum strategy request."""
    value_weight: FloatDecimal = Field(default=Decimal("0.5"), ge=0, le=1)
    momentum_weight: FloatDecimal = Field(default=Decimal("0.5"), ge=0, le=1)


class KJBRequest(StrategyRequest):
    """KJB strategy request."""
    pass


class StockFactor(BaseModel):
    """Factor scores for a single stock."""
    ticker: str
    name: str
    market: str
    sector_name: Optional[str] = None
    market_cap: Optional[int] = None
    close_price: Optional[FloatDecimal] = None

    # Raw metrics
    per: Optional[FloatDecimal] = None
    pbr: Optional[FloatDecimal] = None
    psr: Optional[FloatDecimal] = None
    pcr: Optional[FloatDecimal] = None
    dividend_yield: Optional[FloatDecimal] = None
    roe: Optional[FloatDecimal] = None

    # Factor scores (z-scores)
    value_score: Optional[FloatDecimal] = None
    quality_score: Optional[FloatDecimal] = None
    momentum_score: Optional[FloatDecimal] = None

    # Composite
    total_score: Optional[FloatDecimal] = None
    rank: Optional[int] = None
    fscore: Optional[int] = None


class StrategyResult(BaseModel):
    """Result from running a strategy."""
    strategy_name: str
    base_date: date
    universe_count: int
    result_count: int
    stocks: List[StockFactor]


class StockInfo(BaseModel):
    """Detailed stock information."""
    ticker: str
    name: str
    market: str
    sector_name: Optional[str] = None
    stock_type: str
    close_price: Optional[FloatDecimal] = None
    market_cap: Optional[int] = None

    # Valuation
    per: Optional[FloatDecimal] = None
    pbr: Optional[FloatDecimal] = None
    psr: Optional[FloatDecimal] = None
    pcr: Optional[FloatDecimal] = None
    dividend_yield: Optional[FloatDecimal] = None

    # Per-share data
    eps: Optional[FloatDecimal] = None
    bps: Optional[FloatDecimal] = None

    base_date: Optional[date] = None

    class Config:
        from_attributes = True


class StockSearchResult(BaseModel):
    """Stock search result."""
    ticker: str
    name: str
    market: str


class PriceData(BaseModel):
    """Price data point."""
    date: date
    open: FloatDecimal
    high: FloatDecimal
    low: FloatDecimal
    close: FloatDecimal
    volume: int

    class Config:
        from_attributes = True