QuantEngineByItz/tools/build_unified_route_packet_v1.py

from __future__ import annotations

import argparse
import json
from pathlib import Path
from typing import Any


ROOT = Path(__file__).resolve().parents[1]
TEMP = ROOT / "Temp"
DEFAULT_CAPITAL = TEMP / "capital_style_allocation_v1.json"
DEFAULT_HORIZON = TEMP / "horizon_classification_v1.json"
DEFAULT_FUND = TEMP / "fundamental_multifactor_v3.json"
DEFAULT_OUT = TEMP / "unified_route_packet_v1.json"
FORMULA_ID = "UNIFIED_ROUTE_PACKET_V1"
VALID_STYLES = ("SCALP", "SWING", "MOMENTUM", "POSITION")


def _load(path: Path) -> dict[str, Any]:
    if not path.exists():
        return {}
    try:
        obj = json.loads(path.read_text(encoding="utf-8"))
    except Exception:
        return {}
    return obj if isinstance(obj, dict) else {}


def _f(v: Any, default: float = 0.0) -> float:
    try:
        return float(v)
    except Exception:
        return default


def _best_style(row: dict[str, Any]) -> dict[str, Any]:
    styles = row.get("styles") or []
    best = max(
        [s for s in styles if isinstance(s, dict)],
        key=lambda s: _f(s.get("conviction_score")),
        default={},
    )
    return best if isinstance(best, dict) else {}


def main() -> int:
    ap = argparse.ArgumentParser()
    ap.add_argument("--capital", default=str(DEFAULT_CAPITAL))
    ap.add_argument("--horizon", default=str(DEFAULT_HORIZON))
    ap.add_argument("--fund", default=str(DEFAULT_FUND))
    ap.add_argument("--out", default=str(DEFAULT_OUT))
    args = ap.parse_args()

    capital_path = Path(args.capital)
    horizon_path = Path(args.horizon)
    fund_path = Path(args.fund)
    out_path = Path(args.out)
    if not capital_path.is_absolute():
        capital_path = ROOT / capital_path
    if not horizon_path.is_absolute():
        horizon_path = ROOT / horizon_path
    if not fund_path.is_absolute():
        fund_path = ROOT / fund_path
    if not out_path.is_absolute():
        out_path = ROOT / out_path

    capital = _load(capital_path)
    horizon = _load(horizon_path)
    fund = _load(fund_path)

    fund_rows = {str(r.get("ticker") or ""): r for r in (fund.get("rows") or []) if isinstance(r, dict)}
    hz_rows = {str(r.get("ticker") or ""): r for r in (horizon.get("rows") or []) if isinstance(r, dict)}

    rows_out: list[dict[str, Any]] = []
    blocked_count = 0
    style_score_range_violations = 0
    every_ticker_has_one_best_style = True
    blocked_reason_codes_non_empty_when_blocked = True

    for row in capital.get("rows") or []:
        if not isinstance(row, dict):
            continue
        ticker = str(row.get("ticker") or "")
        name = str(row.get("name") or "")
        sb = row.get("signal_breakdown") or {}
        best = _best_style(row)
        best_style = str(best.get("style") or "UNKNOWN")
        conviction = _f(best.get("conviction_score"))
        recommended_pct = _f(best.get("recommended_pct"))
        actual_horizon = str(hz_rows.get(ticker, {}).get("horizon") or "UNKNOWN")
        expected_horizon = {"SCALP": "SHORT", "SWING": "SHORT", "MOMENTUM": "MID", "POSITION": "LONG"}.get(best_style, "UNKNOWN")
        buy_allowed = bool((fund_rows.get(ticker) or {}).get("buy_allowed"))
        liquidity_label = str(sb.get("liquidity_label") or "UNKNOWN")
        macro_gate = str(sb.get("macro_gate") or "UNKNOWN")
        blocked_reason_codes: list[str] = []

        if not best_style or best_style not in VALID_STYLES:
            every_ticker_has_one_best_style = False
            blocked_reason_codes.append("BEST_STYLE_MISSING")
        if not (0.0 <= conviction <= 100.0):
            style_score_range_violations += 1
            blocked_reason_codes.append("CONVICTION_RANGE")
        if liquidity_label == "FROZEN":
            blocked_reason_codes.append("LIQUIDITY_FROZEN")
        if macro_gate == "AVOID_NEW_BUY":
            blocked_reason_codes.append("MACRO_AVOID_NEW_BUY")
        if not buy_allowed:
            blocked_reason_codes.append("FUNDAMENTAL_BUY_BLOCK")
        if expected_horizon != "UNKNOWN" and actual_horizon not in ("UNKNOWN", "ETF") and expected_horizon != actual_horizon:
            blocked_reason_codes.append("STYLE_HORIZON_MISMATCH")
        if conviction < 35.0:
            blocked_reason_codes.append("CONVICTION_LT_35")

        blocked = len(blocked_reason_codes) > 0
        if blocked:
            blocked_count += 1
            if not blocked_reason_codes:
                blocked_reason_codes_non_empty_when_blocked = False

        rows_out.append({
            "ticker": ticker,
            "name": name,
            "best_style": best_style,
            "best_style_conviction_score": round(conviction, 2),
            "recommended_pct": recommended_pct,
            "expected_horizon": expected_horizon,
            "actual_horizon": actual_horizon,
            "blocked": blocked,
            "blocked_reason_codes": blocked_reason_codes,
            "signal_breakdown": sb,
            "formula_id": FORMULA_ID,
        })

    result = {
        "formula_id": FORMULA_ID,
        "gate": "PASS" if every_ticker_has_one_best_style and style_score_range_violations == 0 and blocked_reason_codes_non_empty_when_blocked else "FAIL",
        "ticker_count": len(rows_out),
        "blocked_count": blocked_count,
        "every_ticker_has_one_best_style": every_ticker_has_one_best_style,
        "every_style_score_range_0_100": style_score_range_violations == 0,
        "blocked_reason_codes_non_empty_when_blocked": blocked_reason_codes_non_empty_when_blocked,
        "rows": rows_out,
        "source": {
            "capital_style_allocation_v1_json": str(capital_path),
            "horizon_classification_v1_json": str(horizon_path),
            "fundamental_multifactor_v3_json": str(fund_path),
        },
    }

    out_path.parent.mkdir(parents=True, exist_ok=True)
    out_path.write_text(json.dumps(result, ensure_ascii=False, indent=2), encoding="utf-8")
    print(json.dumps({k: v for k, v in result.items() if k != "rows"}, ensure_ascii=False, indent=2))
    return 0


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