ForexBot2/config.py

"""
ForexBot2 — Configuration (XAU/USD focused)
==========================================
"""

from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List


class Timeframe(Enum):
    M1 = "1min"
    M5 = "5min"
    M15 = "15min"
    M30 = "30min"
    H1 = "1h"
    H4 = "4h"
    D1 = "1d"
    W1 = "1wk"


class SignalStrength(Enum):
    STRONG_BUY = 2
    BUY = 1
    NEUTRAL = 0
    SELL = -1
    STRONG_SELL = -2


class MarketSession(Enum):
    SYDNEY = "sydney"
    TOKYO = "tokyo"
    LONDON = "london"
    NEW_YORK = "new_york"
    OVERLAP_LONDON_NY = "london_ny_overlap"


# ── Supported pairs ──────────────────────────────────────────────
XAUUSD = "XAU/USD"

PAIR_INFO = {
    XAUUSD: {"display": "XAU/USD", "pip_value": 0.10, "is_jpy_pair": False},
}


@dataclass
class TechnicalConfig:
    """Technical indicator parameters."""
    ema_fast: int = 9
    ema_medium: int = 21
    ema_slow: int = 50
    ema_trend: int = 200

    rsi_period: int = 14
    rsi_overbought: float = 70.0
    rsi_oversold: float = 30.0
    rsi_neutral_upper: float = 60.0
    rsi_neutral_lower: float = 40.0

    macd_fast: int = 12
    macd_slow: int = 26
    macd_signal: int = 9

    bb_period: int = 20
    bb_std: float = 2.0

    atr_period: int = 14

    adx_period: int = 14
    adx_strong_trend: float = 25.0
    adx_very_strong: float = 50.0

    divergence_lookback: int = 40
    swing_sr_lookback: int = 50

    disabled_indicators: List[str] = field(default_factory=list)

    ema_mode: str = "4ema"          # "4ema" (9/21/50/200) or "2ema" (50/200)
    rsi_mode: str = "regime_aware"  # "classic" or "regime_aware"
    macd_as_pillar: bool = True     # MACD histogram is a scored signal

    # ROC (Rate of Change)
    roc_period: int = 10
    roc_threshold: float = 1.0     # % threshold for strong signal

    # Keltner Channels
    kc_period: int = 20
    kc_atr_period: int = 10
    kc_multiplier: float = 1.5

    # ADX slope (trend acceleration detection)
    adx_slope_lookback: int = 5
    adx_slope_emerging_threshold: float = 3.0

    regime_weights_override: Dict[str, Dict[str, float]] = field(default_factory=dict)


@dataclass
class SignalConfig:
    """Signal scoring & filtering."""
    min_confidence: float = 55.0

    weights: Dict[str, float] = field(default_factory=lambda: {
        "ema_trend": 1.0,
        "rsi": 1.5,
        "bollinger": 1.5,
        "macd": 1.5,
        "keltner": 1.5,
        "roc": 1.5,
        "candlestick": 1.0,
        "divergence": 1.5,
    })

    mtf_agreement_threshold: int = 2  # of 3 timeframes
    cooldown_bars: int = 5

    default_risk_pct: float = 1.0
    default_rr_ratio: float = 2.0
    atr_sl_multiplier: float = 1.5
    min_rr_ratio: float = 0.5
    # TP tightening (May 2026) was tuned on the pre-spread backtester.
    # Re-tested 2026-07-08 with $0.30 spread + gap fills: 0.8 nearly
    # halves total R (+36.1R vs +66.8R, worse in both train/val halves)
    # — smaller wins make the fixed spread a larger share of every TP.
    tp_tightening_factor: float = 1.0


@dataclass
class NewsConfig:
    """Economic calendar & sentiment."""
    tracked_currencies: List[str] = field(default_factory=lambda: ["USD", "XAU"])
    min_impact: str = "medium"
    pre_event_buffer_minutes: int = 30
    post_event_buffer_minutes: int = 15

    rss_feeds: List[str] = field(default_factory=lambda: [
        "https://investinglive.com/feed/",
        "https://www.fxstreet.com/rss",
    ])


@dataclass
class XauStrategyConfig:
    """XAU/USD strategy config.
    Legacy gates (H4 RSI, H1 MACD, M15 score) removed in favor of
    new momentum indicators (ROC, Keltner squeeze, ADX slope).
    """
    enabled: bool = True
    rsi_entry_threshold: float = 45.0
    tp_atr_multiplier: float = 1.0
    sl_atr_multiplier: float = 2.0
    min_ema200_tfs: int = 2
    allow_generic_trades: bool = True
    blocked_hours_utc: List[int] = field(default_factory=lambda: [0, 1, 2, 10, 11, 13, 16, 21])
    weekend_filter: bool = True
    min_atr_threshold: float = 1.0
    v2_sl_atr_multiplier: float = 2.0
    buy_threshold_boost: int = 0
    m5_confirmation_bars: int = 0
    h4_rsi_gate: bool = False
    h1_macd_gate: bool = False
    rsi_zone: tuple = (40.0, 65.0)
    allowed_weekdays: List[int] = field(default_factory=lambda: [0, 1, 2, 3, 4, 6])  # Mon-Fri + Sun (Sydney open)
    sell_min_quality: List[str] = field(default_factory=lambda: ["A+", "A", "B"])
    # Volatility regimes in which SELL setups are allowed (low/normal-vol
    # shorts lose consistently against gold's macro uptrend).
    sell_vol_regimes: List[str] = field(default_factory=lambda: ["high", "extreme"])


@dataclass
class FilterConfig:
    """Regime and session filters for live signals."""
    regime_filter: bool = False
    regime_filter_timeframe: Timeframe = Timeframe.H4
    regime_filter_min_adx: float = 25.0

    session_filter: bool = True
    session_start_hour: int = 3
    session_end_hour: int = 23
    blocked_hours_utc: List[int] = field(default_factory=lambda: [0, 1, 2, 10, 11, 13, 16, 21])

    allowed_weekdays: List[int] = field(default_factory=lambda: [0, 1, 2, 3, 4, 6])  # Mon-Fri + Sun (Sydney open)


@dataclass
class PlatformConfig:
    """Top-level configuration."""
    technical: TechnicalConfig = field(default_factory=TechnicalConfig)
    signals: SignalConfig = field(default_factory=SignalConfig)
    news: NewsConfig = field(default_factory=NewsConfig)
    backtest: FilterConfig = field(default_factory=FilterConfig)
    xau_strategy: XauStrategyConfig = field(default_factory=XauStrategyConfig)

    symbol: str = XAUUSD
    display_name: str = "XAU/USD"
    pip_value: float = 0.10

    primary_timeframe: Timeframe = Timeframe.H1
    confirmation_timeframes: List[Timeframe] = field(
        default_factory=lambda: [Timeframe.M15, Timeframe.H4]
    )

    data_lookback_days: int = 60

    twelve_data_api_key: str = "f563b22ffdfd4924955decbe1a8c8701"

    refresh_interval: int = 300

    scan_pairs: List[str] = field(
        default_factory=lambda: [XAUUSD]
    )
    scan_timeframes: List[Timeframe] = field(
        default_factory=lambda: [Timeframe.M5, Timeframe.M15, Timeframe.H1, Timeframe.H4]
    )
    candle_buffer_seconds: int = 10
    ws_cooldown_seconds: int = 300

    log_level: str = "INFO"