#!/bin/bash
# update.sh - 自动从 Google Sheet 拉取 EG Nagwa 当月数据并生成 data.json
# 数据源：公开导出的 Google Sheet CSV
# 每天由服务器自动执行一次（见 schedule.conf）
set -euo pipefail

SHEET_ID="11Npr4IpXT8jtgUnrkrjITJ8s1fHNYTwRRwSGIvcfeIs"
GID="699511110"
CSV_URL="https://docs.google.com/spreadsheets/d/${SHEET_ID}/export?format=csv&gid=${GID}"

OUT="data.json"
TMP_CSV="$(mktemp)"
trap 'rm -f "$TMP_CSV"' EXIT

# 当月，格式如 September-2026
MONTH_TAG="$(date +%B-%Y)"

echo "Fetching CSV for month: $MONTH_TAG"
curl -fsSL "$CSV_URL" -o "$TMP_CSV"

# 用 python 解析 CSV 生成 data.json（python3 处理带引号/逗号的字段更稳妥）
python3 - "$TMP_CSV" "$OUT" "$MONTH_TAG" <<'PY'
import csv, json, sys, re
from datetime import datetime

csv_path, out_path, month_tag = sys.argv[1], sys.argv[2], sys.argv[3]

def num(s):
    if s is None: return None
    s = s.strip().replace(',', '').replace('$', '').replace('%', '')
    if s == '': return None
    try:
        f = float(s)
        return int(f) if f.is_integer() else f
    except ValueError:
        return None

rows = list(csv.reader(open(csv_path, newline='', encoding='utf-8')))

# 列索引（0-based），依据表头布局：
# Month=7, DT=8, Geo=9, Install=10, Price=11, MidasSpend=12,
# PayableSpend=13, Enroll_Session=14, Enroll_Session%=15, Remark=16,
# meta-key=17, meta-value=18
COL_MONTH, COL_DT, COL_INSTALL = 7, 8, 10
COL_PAYABLE, COL_ENROLL, COL_ENROLLPCT = 13, 14, 15
COL_METAK, COL_METAV = 16, 17

daily = []
meta = {"geo": "EG", "product": "Nagwa"}

# 从 month_tag 解析目标年月，用于把 DT（如 2026/9/1 或 20260901）标准化成 YYYY-MM-DD
target_month = datetime.strptime(month_tag, "%B-%Y")
ty, tm = target_month.year, target_month.month

def parse_dt(dt):
    dt = dt.strip()
    if not dt: return None
    # 形如 2026/9/1
    m = re.match(r'^(\d{4})/(\d{1,2})/(\d{1,2})$', dt)
    if m:
        y, mo, d = map(int, m.groups())
        return f"{y:04d}-{mo:02d}-{d:02d}"
    # 形如 20260901
    m = re.match(r'^(\d{4})(\d{2})(\d{2})$', dt)
    if m:
        y, mo, d = map(int, m.groups())
        return f"{y:04d}-{mo:02d}-{d:02d}"
    return None

price_seen = None
for r in rows:
    if len(r) <= COL_ENROLLPCT:
        continue
    if r[COL_MONTH].strip() != month_tag:
        continue
    date = parse_dt(r[COL_DT])
    if not date:
        continue
    install = num(r[COL_INSTALL]) or 0
    spend = num(r[COL_PAYABLE]) or 0.0
    enroll = num(r[COL_ENROLL]) or 0
    pct = num(r[COL_ENROLLPCT]) or 0.0
    daily.append({
        "date": date,
        "install": int(install),
        "payable_spend": round(float(spend), 2),
        "enroll_session": int(enroll),
        "enroll_session_pct": round(float(pct), 2),
    })
    # 记录价格（取当月出现的最新价）
    p = num(r[11])
    if p is not None:
        price_seen = p
    # 抓取 meta（Remark 区块的 key/value）
    k = r[COL_METAK].strip() if len(r) > COL_METAK else ""
    v = r[COL_METAV].strip() if len(r) > COL_METAV else ""
    if k and v:
        kl = k.lower()
        if "budget" in kl:
            meta["sep_budget"] = num(v)
        elif kl == "spend":
            meta["spend"] = num(v)
        elif kl == "left":
            meta["left"] = num(v)
        elif kl == "%":
            meta["spend_pct"] = v if v.endswith('%') else (v + '%')
        elif "daily install" in kl:
            meta["rec_daily_install"] = num(v)

if price_seen is not None:
    meta["price"] = price_seen

data = {"meta": meta, "daily": daily}
with open(out_path, "w", encoding="utf-8") as f:
    json.dump(data, f, ensure_ascii=False, indent=2)

print(f"Wrote {len(daily)} days to {out_path}")
PY

echo "Done. Last run: $(date)"