from pathlib import Path
import json
import os
import sys

from sqlalchemy.exc import SQLAlchemyError

ROOT = Path(__file__).resolve().parents[1]
if str(ROOT) not in sys.path:
    sys.path.insert(0, str(ROOT))

from src.services.bias import BiasService
from src.services.signals import MINIMAL_SIGNAL_EVIDENCE_KEYS, STRICT_SIGNAL_EVIDENCE_KEYS, SignalService


def build_signal_evidence_keys_from_env(env=None) -> tuple[str, ...]:
    env = os.environ if env is None else env
    mode = str(env.get("SIGNAL_EVIDENCE_MODE") or "strict").strip().lower()
    if mode == "minimal":
        return MINIMAL_SIGNAL_EVIDENCE_KEYS
    if mode == "strict":
        return STRICT_SIGNAL_EVIDENCE_KEYS
    raise ValueError(f"unsupported_signal_evidence_mode:{mode}")


def build_signal_timeframe_set_from_env(env=None) -> dict:
    env = os.environ if env is None else env
    bias_tf = str(env.get("AI_ICT_BIAS_TIMEFRAME") or env.get("SIGNAL_BIAS_TIMEFRAME") or "1m")
    setup_tf = str(env.get("AI_ICT_SETUP_TIMEFRAME") or env.get("SIGNAL_SETUP_TIMEFRAME") or bias_tf)
    trigger_tf = str(env.get("AI_ICT_TRIGGER_TIMEFRAME") or env.get("SIGNAL_TRIGGER_TIMEFRAME") or setup_tf)
    return {
        "bias_tf": bias_tf,
        "setup_tf": setup_tf,
        "trigger_tf": trigger_tf,
    }


def main(env=None) -> int:
    env = os.environ if env is None else env
    output_json = _get_bool(env, "SIGNALS_OUTPUT_JSON", False)
    instrument_id = 1
    timeframe_set = build_signal_timeframe_set_from_env(env=env)
    bias_service = BiasService()
    signal_service = SignalService(required_evidence_keys=build_signal_evidence_keys_from_env(env=env))

    try:
        bias = bias_service.build_bias(
            instrument_id=instrument_id,
            bias_tf=timeframe_set["bias_tf"],
            setup_tf=timeframe_set["setup_tf"],
            trigger_tf=timeframe_set["trigger_tf"],
        )
        bias_id = bias_service.persist_bias(
            instrument_id=instrument_id,
            bias_tf=timeframe_set["bias_tf"],
            setup_tf=timeframe_set["setup_tf"],
            trigger_tf=timeframe_set["trigger_tf"],
            candidate=bias,
        )
        signal = signal_service.build_signal(
            instrument_id=instrument_id,
            setup_tf=timeframe_set["setup_tf"],
            trigger_tf=timeframe_set["trigger_tf"],
        )
        written = signal_service.persist_signal(
            instrument_id=instrument_id,
            setup_tf=timeframe_set["setup_tf"],
            trigger_tf=timeframe_set["trigger_tf"],
            candidate=signal,
        )
    except SQLAlchemyError as exc:
        payload = {
            "passed": False,
            "instrument_id": instrument_id,
            "timeframe": timeframe_set["trigger_tf"],
            "timeframe_set": timeframe_set,
            "error_type": exc.__class__.__name__,
            "error": str(exc),
        }
        if output_json:
            print(json.dumps(payload, default=str, ensure_ascii=False, sort_keys=True))
        else:
            print(f"Database unavailable for signal sample: {exc.__class__.__name__}")
        return 2
    payload = {
        "passed": True,
        "instrument_id": instrument_id,
        "timeframe": timeframe_set["trigger_tf"],
        "timeframe_set": timeframe_set,
        "bias_snapshot_id": bias_id,
        "signal_rows_written": written,
    }
    if output_json:
        print(json.dumps(payload, default=str, ensure_ascii=False, sort_keys=True))
    else:
        print(f'Bias snapshot id: {bias_id}; signal rows written: {written}')
    return 0


def _get_bool(env, key: str, default: bool) -> bool:
    value = env.get(key)
    if value is None or value == "":
        return default
    return str(value).strip().lower() in {"1", "true", "yes", "on"}


if __name__ == '__main__':
    raise SystemExit(main())