#!/usr/bin/env python3
from __future__ import annotations

import json
from pathlib import Path
from typing import Any


ROOT = Path(__file__).resolve().parents[1]
TEMP = ROOT / "Temp"
OUTPUT = TEMP / "wbs_4_1_7_1_status_v1.json"


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


def _pick_top_candidates(priority: dict[str, Any], limit: int = 5) -> list[dict[str, Any]]:
    rows = priority.get("priority_list") if isinstance(priority.get("priority_list"), list) else []
    out: list[dict[str, Any]] = []
    for row in rows[:limit]:
        if isinstance(row, dict):
            out.append(
                {
                    "calibration_id": row.get("calibration_id"),
                    "source": row.get("source"),
                    "sample_n": row.get("sample_n"),
                    "urgency_score": row.get("urgency_score"),
                    "current_value": row.get("current_value"),
                    "owner_formula": row.get("owner_formula"),
                }
            )
    return out


def main() -> int:
    live_gate = _load_json(TEMP / "live_data_activation_gate_v1.json")
    op_queue = _load_json(TEMP / "operational_eval_queue_v1.json")
    calib_reg = _load_json(TEMP / "calibration_registry_v1.json")
    calib_priority = _load_json(TEMP / "calibration_priority_v1.json")
    pred_acc = _load_json(TEMP / "prediction_accuracy_harness_v2.json")

    live_t20_count = int(live_gate.get("live_t20_count") or 0)
    live_t20_threshold = int(live_gate.get("live_t20_threshold") or 30)
    live_progress_pct = float(live_gate.get("progress_pct") or 0.0)
    live_gate_state = str(live_gate.get("gate") or "PENDING")

    eval_metrics = op_queue.get("metrics") if isinstance(op_queue.get("metrics"), dict) else {}
    records_total = int(eval_metrics.get("records_total") or 0)
    t20_evaluated_count = int(eval_metrics.get("t20_evaluated_count") or 0)
    t20_due_capture_count = int(eval_metrics.get("t20_due_capture_count") or 0)

    reg_counts = {
        "total_thresholds": int(calib_reg.get("total_thresholds") or 0),
        "calibrated_count": int(calib_reg.get("calibrated_count") or 0),
        "provisional_count": int(calib_reg.get("provisional_count") or 0),
        "expert_prior_count": int(calib_reg.get("expert_prior_count") or 0),
        "spec_derived_count": int(calib_reg.get("spec_derived_count") or 0),
        "unregistered_threshold_count": int(calib_reg.get("unregistered_threshold_count") or 0),
        "overclaimed_count": int(calib_reg.get("overclaimed_count") or 0),
    }

    pred_t5_sample = int(pred_acc.get("t5_sample") or 0)
    pred_t5_rate = pred_acc.get("t5_op_rate")
    pred_t5_state = "DATA_GATED" if pred_t5_sample == 0 else "OK"

    status = {
        "formula_id": "WBS_4_1_7_1_STATUS_V1",
        "wbs_4_1": {
            "live_t20_count": live_t20_count,
            "live_t20_threshold": live_t20_threshold,
            "live_progress_pct": live_progress_pct,
            "live_gate": live_gate_state,
            "records_total": records_total,
            "t20_evaluated_count": t20_evaluated_count,
            "t20_due_capture_count": t20_due_capture_count,
            "operational_queue_state": "EMPTY" if records_total == 0 else "POPULATED",
        },
        "wbs_7_1": {
            "registry_counts": reg_counts,
            "prediction_accuracy_state": pred_t5_state,
            "prediction_t5_sample": pred_t5_sample,
            "prediction_t5_rate_pct": pred_t5_rate,
            "top_priority_candidates": _pick_top_candidates(calib_priority, 5),
        },
        "summary": {
            "wbs_4_1_remaining_to_threshold": max(0, live_t20_threshold - live_t20_count),
            "wbs_7_1_calibrated_pct": round(100.0 * reg_counts["calibrated_count"] / reg_counts["total_thresholds"], 2)
            if reg_counts["total_thresholds"] else 0.0,
            "wbs_7_1_unvalidated_pct": round(100.0 * (reg_counts["spec_derived_count"] + reg_counts["expert_prior_count"]) / reg_counts["total_thresholds"], 2)
            if reg_counts["total_thresholds"] else 0.0,
        },
    }

    OUTPUT.write_text(json.dumps(status, ensure_ascii=False, indent=2), encoding="utf-8")
    print(json.dumps(status, ensure_ascii=False, indent=2))
    return 0


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