"""
TA-Lib CDL pattern detection module.

Extracted from generate_talib_annotations.py for use in the FastAPI service.
Provides detect_patterns() for use in pattern detection endpoints.
"""

from typing import List, Dict, Any, Optional
import logging

import numpy as np

try:
    import talib
except ImportError:
    talib = None

logger = logging.getLogger(__name__)

TALIB_PATTERNS: Dict[str, str] = {
    'CDLENGULFING': 'Engulfing',
    'CDLHAMMER': 'Hammer',
    'CDLINVERTEDHAMMER': 'Inverted Hammer',
    'CDLSHOOTINGSTAR': 'Shooting Star',
    'CDLDOJI': 'Doji',
    'CDLDOJISTAR': 'Doji Star',
    'CDLMORNINGSTAR': 'Morning Star',
    'CDLEVENINGSTAR': 'Evening Star',
    'CDLHARAMI': 'Harami',
    'CDLHARAMICROSS': 'Harami Cross',
    'CDLPIERCING': 'Piercing',
    'CDLDARKCLOUDCOVER': 'Dark Cloud Cover',
    'CDLMARUBOZU': 'Marubozu',
    'CDLSPINNINGTOP': 'Spinning Top',
    'CDL3WHITESOLDIERS': 'Three White Soldiers',
    'CDL3BLACKCROWS': 'Three Black Crows',
    'CDLABANDONEDBABY': 'Abandoned Baby',
    'CDLADVANCEBLOCK': 'Advance Block',
    'CDLBELTHOLD': 'Belt Hold',
    'CDLBREAKAWAY': 'Breakaway',
    'CDLCLOSINGMARUBOZU': 'Closing Marubozu',
    'CDLCONCEALBABYSWALL': 'Concealing Baby Swallow',
    'CDLCOUNTERATTACK': 'Counterattack',
    'CDLDRAGONFLYDOJI': 'Dragonfly Doji',
    'CDLGAPSIDESIDEWHITE': 'Up/Down Gap Side-by-Side White Lines',
    'CDLGRAVESTONEDOJI': 'Gravestone Doji',
    'CDLHANGINGMAN': 'Hanging Man',
    'CDLHIGHWAVE': 'High Wave',
    'CDLHIKKAKE': 'Hikkake',
    'CDLHIKKAKEMOD': 'Modified Hikkake',
    'CDLHOMINGPIGEON': 'Homing Pigeon',
    'CDLIDENTICAL3CROWS': 'Identical Three Crows',
    'CDLINNECK': 'In-Neck',
    'CDLKICKING': 'Kicking',
    'CDLKICKINGBYLENGTH': 'Kicking by Length',
    'CDLLADDERBOTTOM': 'Ladder Bottom',
    'CDLLONGLEGGEDDOJI': 'Long-Legged Doji',
    'CDLLONGLINE': 'Long Line',
    'CDLMATCHINGLOW': 'Matching Low',
    'CDLMATHOLD': 'Mat Hold',
    'CDLMORNINGDOJISTAR': 'Morning Doji Star',
    'CDLONNECK': 'On-Neck',
    'CDLRISEFALL3METHODS': 'Rising/Falling Three Methods',
    'CDLSEPARATINGLINES': 'Separating Lines',
    'CDLSHORTLINE': 'Short Line',
    'CDLSTALLEDPATTERN': 'Stalled Pattern',
    'CDLSTICKSANDWICH': 'Stick Sandwich',
    'CDLTAKURI': 'Takuri',
    'CDLTASUKIGAP': 'Tasuki Gap',
    'CDLTHRUSTING': 'Thrusting',
    'CDLTRISTAR': 'Tristar',
    'CDLUNIQUE3RIVER': 'Unique Three River',
    'CDLUPSIDEGAP2CROWS': 'Upside Gap Two Crows',
    'CDLXSIDEGAP3METHODS': 'Upside/Downside Gap Three Methods',
}


def get_available_patterns() -> List[Dict[str, str]]:
    """
    Return all supported CDL pattern names with display names.

    Returns:
        List of dicts with function_name and display_name keys.
    """
    return [
        {"function_name": fn, "display_name": display}
        for fn, display in TALIB_PATTERNS.items()
    ]


def validate_pattern_names(pattern_names: List[str]) -> List[str]:
    """
    Validate a list of pattern names against the supported set.

    Args:
        pattern_names: List of CDL function names to validate.

    Returns:
        List of invalid pattern names (empty if all valid).
    """
    return [name for name in pattern_names if name not in TALIB_PATTERNS]


def detect_patterns(
    candles: List[Dict[str, Any]],
    pattern_names: Optional[List[str]] = None,
) -> List[Dict[str, Any]]:
    """
    Run TA-Lib CDL pattern functions on candle data and return span annotations.

    Args:
        candles: List of candle dicts with keys time, open, high, low, close.
        pattern_names: CDL function names to run. None or empty list means run all.

    Returns:
        List of span annotation dicts with keys:
            start_time, end_time, label, confidence, source, notes.
    """
    if talib is None:
        raise RuntimeError("TA-Lib is not installed")

    if not candles:
        return []

    if not pattern_names:
        pattern_names = list(TALIB_PATTERNS.keys())

    times = np.array([c["time"] for c in candles], dtype=np.float64)
    open_prices = np.array([c["open"] for c in candles], dtype=np.float64)
    high_prices = np.array([c["high"] for c in candles], dtype=np.float64)
    low_prices = np.array([c["low"] for c in candles], dtype=np.float64)
    close_prices = np.array([c["close"] for c in candles], dtype=np.float64)

    n = len(candles)
    annotations = []

    for pattern_func in pattern_names:
        if not hasattr(talib, pattern_func):
            logger.warning("Unknown TA-Lib function: %s", pattern_func)
            continue

        try:
            func = getattr(talib, pattern_func)
            values = func(open_prices, high_prices, low_prices, close_prices)
        except Exception as exc:
            logger.error("Error running %s: %s", pattern_func, exc)
            continue

        friendly_name = TALIB_PATTERNS.get(pattern_func, pattern_func)

        for idx, value in enumerate(values):
            if value == 0:
                continue

            if value > 0:
                label = f"Bullish {friendly_name}"
            else:
                label = f"Bearish {friendly_name}"

            start_idx = max(0, idx - 1)
            end_idx = min(n - 1, idx + 1)

            annotations.append({
                "start_time": int(times[start_idx]),
                "end_time": int(times[end_idx]),
                "label": label,
                "confidence": abs(int(value)) / 100.0,
                "source": "talib",
                "notes": f"TA-Lib {pattern_func} detection",
            })

    logger.info("Detected %d pattern annotations", len(annotations))
    return annotations