"""
Swing Quant Engine — Central Configuration
All tunable parameters, universe definitions, and thresholds.
"""
import os
from pathlib import Path

from dotenv import load_dotenv

# ── Paths ──
BASE_DIR = Path(__file__).parent
DATA_DIR = BASE_DIR / "data"
PARQUET_DIR = DATA_DIR / "parquet"
DB_PATH = DATA_DIR / "quant.db"

# Ensure dirs exist
DATA_DIR.mkdir(exist_ok=True)
PARQUET_DIR.mkdir(exist_ok=True)

# Load env from portfolio_website if local .env doesn't exist
_local_env = BASE_DIR / ".env"
_portfolio_env = BASE_DIR.parent / "portfolio_website" / ".env"
if _local_env.exists():
    load_dotenv(_local_env)
elif _portfolio_env.exists():
    load_dotenv(_portfolio_env)

# ── API Keys ──
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY", "")
OPENAI_MODEL = os.getenv("OPENAI_MODEL", "gpt-4o-mini")
PERPLEXITY_API_KEY = os.getenv("PERPLEXITY_API_KEY", "")
FINNHUB_API_KEY = os.getenv("FINNHUB_API_KEY", "")

# ── Stock Universe ──
# Indian blue-chips (NSE) — top Nifty 50 + select mid-caps
INDIA_UNIVERSE = [
    "RELIANCE.NS", "TCS.NS", "HDFCBANK.NS", "INFY.NS", "ICICIBANK.NS",
    "HINDUNILVR.NS", "BHARTIARTL.NS", "SBIN.NS", "ITC.NS", "KOTAKBANK.NS",
    "LT.NS", "AXISBANK.NS", "BAJFINANCE.NS", "ASIANPAINT.NS", "MARUTI.NS",
    "HCLTECH.NS", "WIPRO.NS", "SUNPHARMA.NS", "TITAN.NS", "ULTRACEMCO.NS",
    "ONGC.NS", "NTPC.NS", "POWERGRID.NS", "TATAMOTORS.NS", "TATASTEEL.NS",
    "ADANIENT.NS", "ADANIPORTS.NS", "COALINDIA.NS", "JSWSTEEL.NS", "M&M.NS",
    "BAJAJ-AUTO.NS", "TECHM.NS", "HEROMOTOCO.NS", "DRREDDY.NS", "CIPLA.NS",
    "DIVISLAB.NS", "APOLLOHOSP.NS", "EICHERMOT.NS", "BPCL.NS", "GRASIM.NS",
    "TATACONSUM.NS", "NESTLEIND.NS", "BRITANNIA.NS", "INDUSINDBK.NS",
    "HINDALCO.NS", "SBILIFE.NS", "HDFCLIFE.NS", "BAJAJFINSV.NS",
    "SHREECEM.NS", "PIDILITIND.NS",
]

# US blue-chips — S&P 100 subset
US_UNIVERSE = [
    "AAPL", "MSFT", "GOOGL", "AMZN", "NVDA", "META", "TSLA", "BRK-B",
    "UNH", "JNJ", "V", "XOM", "JPM", "PG", "MA", "HD", "CVX", "MRK",
    "ABBV", "LLY", "PEP", "KO", "COST", "AVGO", "WMT", "MCD", "CSCO",
    "ACN", "TMO", "ABT", "DHR", "NEE", "LIN", "PM", "TXN", "UNP",
    "RTX", "HON", "LOW", "AMGN", "COP", "QCOM", "ORCL", "GS", "BAC",
    "CAT", "SBUX", "AXP", "PFE", "AMD",
]

# Combined default universe
DEFAULT_UNIVERSE = INDIA_UNIVERSE + US_UNIVERSE

# ── Technical Signal Thresholds ──
SIGNAL_PARAMS = {
    # RSI
    "rsi_oversold": 30,
    "rsi_overbought": 75,
    "rsi_bullish_zone": (45, 76),  # Tightened momentum sweet spot

    # MACD
    "macd_fast": 12,
    "macd_slow": 26,
    "macd_signal": 9,

    # Bollinger Bands
    "bb_period": 20,
    "bb_std": 2.0,

    # Moving Averages
    "sma_short": 20,
    "sma_medium": 50,
    "sma_long": 200,
    "ema_fast": 9,
    "ema_slow": 21,

    # Volume
    "volume_spike_threshold": 2.0,  # Increased to 2.0x avg volume for higher conviction
    "volume_sma_period": 20,

    # ADX (trend strength)
    "adx_trending": 25,  # ADX > 25 = trending market

    # ATR
    "atr_period": 14,

    # Breakout
    "breakout_lookback": 20,  # days to look for resistance
    "breakout_volume_confirm": 1.3,  # min volume multiplier for confirmation
}

# ── Risk Parameters ──
RISK_PARAMS = {
    "max_position_pct": 5.0,       # Max 5% of portfolio in one position
    "max_sector_pct": 15.0,        # Reduced to 15% for better diversification
    "max_drawdown_pct": 15.0,      # Kill switch at 15% portfolio drawdown
    "min_liquidity_inr": 5_00_00_000,  # ₹5Cr daily volume for India
    "min_liquidity_usd": 10_000_000,   # $10M daily volume for US
    "max_atr_pct": 5.0,            # Skip stocks with ATR% > 5%
    "max_correlation": 0.85,       # Reject if corr > 0.85 with existing
    "kelly_fraction": 0.25,        # Use 25% of Kelly optimal (conservative)
}

# ── Alpha Scoring Weights ──
ALPHA_WEIGHTS = {
    "momentum": 0.35,
    "volume_breakout": 0.20,
    "sentiment": 0.20,
    "regime_fit": 0.15,
    "fundamental": 0.10,
}

# ── Scan Schedule ──
SCAN_INTERVAL_HOURS = 4  # Re-scan every 4 hours during market hours

# ── Market Hours (for scheduling) ──
MARKET_HOURS = {
    "india": {"open": "09:15", "close": "15:30", "tz": "Asia/Kolkata"},
    "us": {"open": "09:30", "close": "16:00", "tz": "America/New_York"},
}

# ── Backtest Defaults ──
BACKTEST_PARAMS = {
    "in_sample_months": 12,#6
    "out_sample_months": 3,#1
    "commission_india_pct": 0.1,
    "commission_us_pct": 0.05,
    "slippage_pct": 0.05,
    "initial_capital": 10_00_000,  # ₹10L or $10K equivalent
}

# ── Logging ──
import logging

LOG_FORMAT = "%(asctime)s [%(levelname)s] %(name)s: %(message)s"
logging.basicConfig(level=logging.INFO, format=LOG_FORMAT)