"""
Fundamentals — Fetch key fundamental data from yfinance.
Provides value, growth, and quality metrics for alpha scoring.
"""
import logging

import yfinance as yf

logger = logging.getLogger(__name__)


def fetch_fundamentals(ticker: str) -> dict:
    """
    Fetch key fundamental metrics for a ticker.
    Returns a dict with value, growth, and quality indicators.
    """
    try:
        stock = yf.Ticker(ticker)
        info = stock.info or {}

        fundamentals = {
            "ticker": ticker,
            # Valuation
            "pe_ratio": info.get("trailingPE") or info.get("forwardPE"),
            "pb_ratio": info.get("priceToBook"),
            "ps_ratio": info.get("priceToSalesTrailing12Months"),
            "ev_ebitda": info.get("enterpriseToEbitda"),
            "peg_ratio": info.get("pegRatio"),
            # Growth
            "revenue_growth": info.get("revenueGrowth"),
            "earnings_growth": info.get("earningsGrowth"),
            "earnings_quarterly_growth": info.get("earningsQuarterlyGrowth"),
            # Profitability
            "profit_margin": info.get("profitMargins"),
            "operating_margin": info.get("operatingMargins"),
            "roe": info.get("returnOnEquity"),
            "roa": info.get("returnOnAssets"),
            # Dividend
            "dividend_yield": info.get("dividendYield"),
            # Size & Liquidity
            "market_cap": info.get("marketCap"),
            "avg_volume": info.get("averageVolume"),
            "avg_volume_10d": info.get("averageDailyVolume10Day"),
            # Analyst
            "target_mean": info.get("targetMeanPrice"),
            "target_low": info.get("targetLowPrice"),
            "target_high": info.get("targetHighPrice"),
            "recommendation": info.get("recommendationKey"),
            "num_analysts": info.get("numberOfAnalystOpinions"),
            # Info
            "sector": info.get("sector", "Unknown"),
            "industry": info.get("industry", "Unknown"),
            "name": info.get("shortName", ticker),
            "currency": info.get("currency", "USD"),
        }

        logger.info(f"{ticker}: Fetched fundamentals (PE={fundamentals['pe_ratio']}, sector={fundamentals['sector']})")
        return fundamentals

    except Exception as e:
        logger.error(f"{ticker}: Failed to fetch fundamentals: {e}")
        return {"ticker": ticker, "error": str(e)}


def compute_fundamental_score(fundamentals: dict) -> float:
    """
    Compute a composite fundamental quality score (0-100).
    Blends value, growth, and quality.
    """
    score = 50.0  # Start neutral

    # Value component (lower PE = more value, capped)
    pe = fundamentals.get("pe_ratio")
    if pe and pe > 0:
        if pe < 15:
            score += 10
        elif pe < 25:
            score += 5
        elif pe > 50:
            score -= 10

    # Growth component
    rev_growth = fundamentals.get("revenue_growth")
    if rev_growth:
        if rev_growth > 0.20:
            score += 15
        elif rev_growth > 0.10:
            score += 8
        elif rev_growth < 0:
            score -= 10

    earn_growth = fundamentals.get("earnings_growth")
    if earn_growth:
        if earn_growth > 0.20:
            score += 10
        elif earn_growth > 0.10:
            score += 5
        elif earn_growth < -0.10:
            score -= 10

    # Profitability
    roe = fundamentals.get("roe")
    if roe:
        if roe > 0.20:
            score += 10
        elif roe > 0.15:
            score += 5
        elif roe < 0:
            score -= 15

    margin = fundamentals.get("profit_margin")
    if margin:
        if margin > 0.20:
            score += 5
        elif margin < 0:
            score -= 10

    # Analyst sentiment
    rec = fundamentals.get("recommendation")
    if rec:
        rec_scores = {"strongBuy": 10, "buy": 5, "hold": 0, "sell": -10, "strongSell": -15}
        score += rec_scores.get(rec, 0)

    return max(0.0, min(100.0, score))