# core/external_score.py
from __future__ import annotations
from typing import Dict, Any, List, Tuple
import pandas as pd

__all__ = [
    "get_external_template_df",
    "fill_missing_with_external",
    "score_external_from_df",
    "apply_llm_signals_to_df",
]

_TEMPLATE_ROWS: List[Tuple[str, str]] = [
    # 成長性をより定量化
    ("成長率","市場CAGR(%)"),
    ("成長率","売上_期3(最新期)"),
    ("成長率","売上_期2"),
    ("成長率","売上_期1(最古期)"),
    ("成長率","営業利益_期3(最新期)"),
    ("成長率","営業利益_期2"),
    ("成長率","営業利益_期1(最古期)"),
    ("成長率","主力商品数"),
    ("成長率","成長中主力商品数"),

    # 経営者能力
    ("経営者能力","予実達成率_3年平均(%)"),
    ("経営者能力","監査・内部統制の重大な不備 件数(過去3年)"),
    ("経営者能力","重大コンプライアンス件数(過去3年)"),
    ("経営者能力","社外取締役比率(%)"),
    ("経営者能力","代表者の業界経験年数"),
    ("経営者能力","現預金(円)"),
    ("経営者能力","月商(円)"),
    ("経営者能力","担保余力評価額(円)"),
    ("経営者能力","倒産歴の有無(TRUE/FALSE)"),
    ("経営者能力","倒産からの経過年数"),
    ("経営者能力","重大事件・事故件数(過去10年)"),

    # 安定性
    ("安定性","自己資本比率(%)"),
    ("安定性","利益剰余金(円)"),
    ("安定性","支払遅延件数(直近12ヶ月)"),
    ("安定性","不渡り件数(直近12ヶ月)"),
    ("安定性","平均支払遅延日数"),
    ("安定性","メインバンク明確か(TRUE/FALSE)"),
    ("安定性","借入先数"),
    ("安定性","メインバンク借入シェア(%)"),
    ("安定性","コミットメントライン等の長期与信枠あり(TRUE/FALSE)"),
    ("安定性","担保余力評価額(円)"),
    ("安定性","月商(円)_再掲"),
    ("安定性","主要顧客上位1社売上比率(%)"),
    ("安定性","主要顧客上位3社売上比率(%)"),
    ("安定性","主要顧客の平均信用スコア(0-100)"),
    ("安定性","不良債権件数(直近12ヶ月)"),
    ("安定性","業歴(年)"),

    # 公平性
    ("公平性・総合世評","有価証券報告書提出企業か(TRUE/FALSE)"),
    ("公平性・総合世評","決算公告や官報での公開あり(TRUE/FALSE)"),
    ("公平性・総合世評","HP/IRサイトで財務資料公開あり(TRUE/FALSE)"),
    ("公平性・総合世評","直近更新が定め通りか(TRUE/FALSE)"),
]

def get_external_template_df() -> pd.DataFrame:
    return pd.DataFrame([(c,i,"") for c,i in _TEMPLATE_ROWS], columns=["カテゴリー","入力項目","値"])

def fill_missing_with_external(df: pd.DataFrame, company: str = "", country: str = "") -> pd.DataFrame:
    return df.copy()

# === LLMの抽出結果をテンプレに反映 ===
def apply_llm_signals_to_df(df: pd.DataFrame, signals: Dict[str, Any]) -> pd.DataFrame:
    df2 = df.copy()
    def setv(field: str, val):
        m = df2["入力項目"].eq(field)
        if m.any():
            df2.loc[m, "値"] = "" if val is None else val
    if signals:
        mkt = signals.get("market", {})
        prod = signals.get("products", {})
        setv("市場CAGR(%)", mkt.get("cagr_pct"))
        setv("主力商品数", prod.get("count"))
        setv("成長中主力商品数", prod.get("growing_count"))
    return df2

# ===== スコア計算 =====
_WEIGHTS = {
    # 成長の定量性を強化
    ("成長率","市場成長率"): 12,
    ("成長率","売上高伸長性"): 10,
    ("成長率","利益伸長性"): 10,
    ("成長率","商品"): 6,

    ("経営者能力","経営姿勢"): 8,
    ("経営者能力","事業経験"): 5,
    ("経営者能力","資産担保力"): 6,
    ("経営者能力","減点事項"): 7,

    ("安定性","自己資本"): 8,
    ("安定性","決済振り"): 10,
    ("安定性","金融取引"): 6,
    ("安定性","資産担保余力"): 6,
    ("安定性","取引先"): 6,
    ("安定性","業歴"): 4,

    ("公平性・総合世評","ディスクロージャー"): 8,
}
_WEIGHT_NORM = 100.0 / float(sum(_WEIGHTS.values()))

def _clamp(v, a, b): return max(a, min(b, v))

def _add(items, cat, name, raw, weight, reason):
    if raw is None: raw = 5.0
    items.append({
        "category": cat, "name": name, "raw": round(raw,2),
        "weight": round(weight*_WEIGHT_NORM,2),
        "score": round((raw/10.0)*weight*_WEIGHT_NORM,2),
        "reason": reason
    })

def _to_float(x):
    if x is None: return None
    try: return float(str(x).replace(",","").replace("▲","-").replace("△","-"))
    except Exception: return None

def _to_bool(x):
    if x is None: return None
    s = str(x).strip().lower()
    if s in ("true","t","1","yes","y","有","あり"): return True
    if s in ("false","f","0","no","n","無","なし"): return False
    return None

def _ratio(a,b):
    if a is None or b is None or b == 0: return None
    return a/b

def _ramp(x, good, bad, lo=0.0, hi=10.0, neutral=None):
    if x is None:
        return neutral if neutral is not None else (lo+hi)/2.0
    if good > bad:
        if x <= bad: return lo
        if x >= good: return hi
        return lo + (hi-lo) * (x-bad)/(good-bad)
    else:
        if x >= bad: return lo
        if x <= good: return hi
        return lo + (hi-lo) * (x-good)/(bad-good)

def score_external_from_df(df: pd.DataFrame) -> Dict[str, Any]:
    def ref(label: str):
        m = df["入力項目"].eq(label)
        return df.loc[m, "値"].values[0] if m.any() else None

    items = []

    # ---- 成長率（定量） ----
    market_cagr=_to_float(ref("市場CAGR(%)"))
    s1=_to_float(ref("売上_期1(最古期)")); s2=_to_float(ref("売上_期2")); s3=_to_float(ref("売上_期3(最新期)"))
    p1=_to_float(ref("営業利益_期1(最古期)")); p2=_to_float(ref("営業利益_期2")); p3=_to_float(ref("営業利益_期3(最新期)"))
    prod_n=_to_float(ref("主力商品数")); prod_g=_to_float(ref("成長中主力商品数"))

    def cagr(v1, v3):
        if v1 is None or v3 is None or v1 <= 0: return None
        try: return (v3/v1)**(1/2) - 1.0
        except Exception: return None

    s_cagr = cagr(s1, s3); p_cagr = cagr(p1, p3)
    # 市場CAGR 12%で満点、-3%で0点（景気循環を意識しやや厳しめ）
    _add(items,"成長率","市場成長率", _ramp(market_cagr,12,-3), _WEIGHTS[("成長率","市場成長率")],
         f"市場CAGR {market_cagr if market_cagr is not None else '—'}%")
    _add(items,"成長率","売上高伸長性", _ramp(s_cagr,0.10,-0.05), _WEIGHTS[("成長率","売上高伸長性")],
         f"CAGR売上{round((s_cagr or 0)*100,1) if s_cagr is not None else '—'}%")
    _add(items,"成長率","利益伸長性", _ramp(p_cagr,0.10,-0.05), _WEIGHTS[("成長率","利益伸長性")],
         f"CAGR営業{round((p_cagr or 0)*100,1) if p_cagr is not None else '—'}%")
    # 製品ポートフォリオの定量化（成長中比率）
    grow_ratio = _ratio(prod_g, prod_n)
    _add(items,"成長率","商品", _ramp(grow_ratio,0.6,0.1), _WEIGHTS[("成長率","商品")],
         f"成長中比率{round((grow_ratio or 0)*100,1) if grow_ratio is not None else '—'}%")

    # ---- 経営者能力 ----
    yoy3=_to_float(ref("予実達成率_3年平均(%)"))
    audit_bad=_to_float(ref("監査・内部統制の重大な不備 件数(過去3年)"))
    comp_bad=_to_float(ref("重大コンプライアンス件数(過去3年)"))
    indep=_to_float(ref("社外取締役比率(%)"))
    exp_years=_to_float(ref("代表者の業界経験年数"))
    cash=_to_float(ref("現預金(円)"))
    sales_m=_to_float(ref("月商(円)"))
    collat=_to_float(ref("担保余力評価額(円)"))
    has_bk=_to_bool(ref("倒産歴の有無(TRUE/FALSE)"))
    bk_years=_to_float(ref("倒産からの経過年数"))
    incidents=_to_float(ref("重大事件・事故件数(過去10年)"))

    cash_to_ms=_ratio(cash, sales_m)

    mg_att = (_ramp(yoy3, 90,50)+_ramp(0 if not audit_bad else -audit_bad,0,-3)+_ramp(0 if not comp_bad else -comp_bad,0,-2)+_ramp(indep,33,0))/4
    _add(items,"経営者能力","経営姿勢",mg_att,_WEIGHTS[("経営者能力","経営姿勢")],f"予実{yoy3 or '—'}%/監査{audit_bad or 0}/違反{comp_bad or 0}/社外{indep or '—'}%")

    mg_exp = _ramp(exp_years if exp_years is not None else 5.0, 15, 0)
    _add(items,"経営者能力","事業経験",mg_exp,_WEIGHTS[("経営者能力","事業経験")],f"経験{exp_years if exp_years is not None else '不明→中立'}年")

    mg_asset = _ramp(cash_to_ms, 1.5, 0.2)
    _add(items,"経営者能力","資産担保力",mg_asset,_WEIGHTS[("経営者能力","資産担保力")],f"現預金/月商≈{round(cash_to_ms,2) if cash_to_ms else '—'}")

    if incidents and incidents>0:
        pen=0.0; rs=f"重大事故{int(incidents)}件→大幅減点"
    elif has_bk:
        pen=6.0 if (bk_years and bk_years>=10) else 3.0; rs=f"倒産歴あり（{bk_years or '不明'}年）"
    else:
        pen=10.0; rs="事故/倒産なし"
    _add(items,"経営者能力","減点事項",pen,_WEIGHTS[("経営者能力","減点事項")],rs)

    # ---- 安定性 ----
    equity=_to_float(ref("自己資本比率(%)"))
    delay_cnt=_to_float(ref("支払遅延件数(直近12ヶ月)"))
    boun_cnt=_to_float(ref("不渡り件数(直近12ヶ月)"))
    delay_days=_to_float(ref("平均支払遅延日数"))
    mainbank=_to_bool(ref("メインバンク明確か(TRUE/FALSE)"))
    main_share=_to_float(ref("メインバンク借入シェア(%)"))
    has_line=_to_bool(ref("コミットメントライン等の長期与信枠あり(TRUE/FALSE)"))
    coll_to_ms=_ratio(_to_float(ref("担保余力評価額(円)")), _to_float(ref("月商(円)_再掲")) or sales_m)

    _add(items,"安定性","自己資本", _ramp(equity,40,5), _WEIGHTS[("安定性","自己資本")], f"自己資本比率{equity or '—'}%")

    if (delay_cnt is not None) or (boun_cnt is not None) or (delay_days is not None):
        sc=( _ramp(- (delay_cnt or 0),0,-6) + _ramp(- (boun_cnt or 0),0,-1) + _ramp(- (delay_days or 0),0,-30) )/3
        rs=f"遅延{int(delay_cnt or 0)}/不渡{int(boun_cnt or 0)}/平均{int(delay_days or 0)}日"
    else:
        sc=_ramp(cash_to_ms,1.0,0.2); rs=f"代理：現預金/月商≈{round(cash_to_ms,2) if cash_to_ms else '—'}"
    _add(items,"安定性","決済振り", sc, _WEIGHTS[("安定性","決済振り")], rs)

    sc_mb = 5.0
    sc_mb += 2.0 if mainbank else (-0.5 if mainbank is False else 0)
    sc_mb += 1.0 if has_line else 0
    sc_mb = _clamp(sc_mb,0,10)
    _add(items,"安定性","金融取引", sc_mb, _WEIGHTS[("安定性","金融取引")],
         f"ﾒｲﾝ{'有' if mainbank else '無' if mainbank is False else '—'}/与信枠{'有' if has_line else '無' if has_line is False else '—'}")

    _add(items,"安定性","資産担保余力", _ramp(coll_to_ms,4.0,0.0), _WEIGHTS[("安定性","資産担保余力")],
         f"担保/月商≈{round(coll_to_ms,2) if coll_to_ms else '—'}")

    top1=_to_float(ref("主要顧客上位1社売上比率(%)"))
    cust_score=_to_float(ref("主要顧客の平均信用スコア(0-100)"))
    npl_cnt=_to_float(ref("不良債権件数(直近12ヶ月)"))
    _add(items,"安定性","取引先", ( _ramp(- (top1 or 50),0,-80) + _ramp(cust_score,80,50) + _ramp(- (npl_cnt or 1),0,-3) )/3,
         _WEIGHTS[("安定性","取引先")], f"上位1社{top1 or '—'}%/信用{cust_score or '—'}/不良{int(npl_cnt or 0)}")

    years=_to_float(ref("業歴(年)"))
    _add(items,"安定性","業歴", _ramp(years,20,1), _WEIGHTS[("安定性","業歴")], f"{years or '—'}年")

    # ---- 公平性 ----
    has_sec=_to_bool(ref("有価証券報告書提出企業か(TRUE/FALSE)"))
    pub_off=_to_bool(ref("決算公告や官報での公開あり(TRUE/FALSE)"))
    pub_web=_to_bool(ref("HP/IRサイトで財務資料公開あり(TRUE/FALSE)"))
    upd_on=_to_bool(ref("直近更新が定め通りか(TRUE/FALSE)"))
    sc_dis = 0.0
    sc_dis += 10.0 if has_sec else (7.0 if (pub_off or pub_web) else 4.0)
    sc_dis += 1.0 if upd_on else 0.0
    sc_dis = _clamp(sc_dis,0,10)
    _add(items,"公平性・総合世評","ディスクロージャー", sc_dis, _WEIGHTS[("公平性・総合世評","ディスクロージャー")],
         f"{'有報' if has_sec else '公開あり' if (pub_off or pub_web) else '公開乏しい'} / 更新{'◯' if upd_on else '—'}")

    total = round(sum(x["score"] for x in items),1)
    return {"name":"企業評価（外部）","external_total": total, "items": items, "notes":"欠損は中立、連続スコア×重み（自動正規化）"}