"""
Risk manager — lot sizing, hold time calculation, gap strategy.
Central trade decision layer.
"""

import logging
from config import TRADE_MODE, MIN_CONFIDENCE
from agents.aggregator import get_lot_size, get_hold_time, determine_strategy
from data.price_data import detect_gap

logger = logging.getLogger("gap_system.execution.risk_manager")


async def evaluate_trade(
    asset: str,
    direction: str,
    confidence: float,
) -> dict:
    """
    Evaluate whether to trade and with what parameters.
    Returns trade parameters or skip signal.
    """
    # Confidence threshold
    if confidence < MIN_CONFIDENCE:
        logger.info("Skipping %s: confidence %.1f%% below threshold %.1f%%",
                     asset, confidence * 100, MIN_CONFIDENCE * 100)
        return {"action": "SKIP", "reason": "below_confidence_threshold"}

    # Lot size
    lot_size = get_lot_size(confidence)
    if lot_size is None:
        return {"action": "SKIP", "reason": "no_lot_for_confidence"}

    # Hold time
    hold_seconds = get_hold_time(confidence)
    if hold_seconds is None:
        return {"action": "SKIP", "reason": "no_hold_time_for_confidence"}

    # Detect gap
    gap_info = await detect_gap(asset)
    if gap_info is None:
        gap_direction = "NONE"
    else:
        gap_direction = gap_info.get("gap_direction", "NONE")

    # No gap = no trade
    if gap_direction == "NONE":
        logger.info("No gap detected for %s — skipping", asset)
        return {"action": "SKIP", "reason": "no_gap_detected"}

    # Strategy
    strategy = determine_strategy(gap_direction, direction, confidence)
    if strategy == "SKIP":
        logger.info("Strategy SKIP for %s (conflict, low confidence)", asset)
        return {"action": "SKIP", "reason": "conflicting_signals"}

    return {
        "action": "TRADE",
        "asset": asset,
        "direction": direction,
        "confidence": confidence,
        "lot_size": lot_size,
        "hold_seconds": hold_seconds,
        "strategy": strategy,
        "gap_direction": gap_direction,
        "gap_info": gap_info,
    }


async def execute(trade_params: dict) -> dict:
    """Execute a trade using the configured mode."""
    if trade_params.get("action") != "TRADE":
        return trade_params

    asset = trade_params["asset"]
    direction = trade_params["direction"]
    lot_size = trade_params["lot_size"]
    hold_seconds = trade_params["hold_seconds"]

    logger.info(
        "Executing: %s %s %.2f lots, hold %ds, strategy=%s",
        asset, direction, lot_size, hold_seconds,
        trade_params.get("strategy", "?"),
    )

    if TRADE_MODE == "darwinex":
        from execution.darwinex_executor import execute_trade
    else:
        from execution.mt5_executor import execute_trade

    result = await execute_trade(asset, direction, lot_size, hold_seconds)
    result["strategy"] = trade_params.get("strategy", "")
    return result