Update Sep 2026 data; auto-fetch from Google Sheet; daily refresh
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@@ -1,6 +1,120 @@
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#!/bin/bash
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# update.sh - 数据来自手动更新的 data.json
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# 由于数据源是 Excel 表格(无公开 API),此脚本仅做占位
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# 每次有新数据时,直接更新 data.json 并 push 即可
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echo "data.json is manually maintained from Excel export."
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echo "Last check: $(date)"
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# update.sh - 自动从 Google Sheet 拉取 EG Nagwa 当月数据并生成 data.json
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# 数据源:公开导出的 Google Sheet CSV
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# 每天由服务器自动执行一次(见 schedule.conf)
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set -euo pipefail
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SHEET_ID="11Npr4IpXT8jtgUnrkrjITJ8s1fHNYTwRRwSGIvcfeIs"
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GID="699511110"
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CSV_URL="https://docs.google.com/spreadsheets/d/${SHEET_ID}/export?format=csv&gid=${GID}"
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OUT="data.json"
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TMP_CSV="$(mktemp)"
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trap 'rm -f "$TMP_CSV"' EXIT
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# 当月,格式如 September-2026
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MONTH_TAG="$(date +%B-%Y)"
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echo "Fetching CSV for month: $MONTH_TAG"
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curl -fsSL "$CSV_URL" -o "$TMP_CSV"
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# 用 python 解析 CSV 生成 data.json(python3 处理带引号/逗号的字段更稳妥)
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python3 - "$TMP_CSV" "$OUT" "$MONTH_TAG" <<'PY'
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import csv, json, sys, re
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from datetime import datetime
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csv_path, out_path, month_tag = sys.argv[1], sys.argv[2], sys.argv[3]
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def num(s):
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if s is None: return None
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s = s.strip().replace(',', '').replace('$', '').replace('%', '')
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if s == '': return None
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try:
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f = float(s)
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return int(f) if f.is_integer() else f
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except ValueError:
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return None
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rows = list(csv.reader(open(csv_path, newline='', encoding='utf-8')))
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# 列索引(0-based),依据表头布局:
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# Month=7, DT=8, Geo=9, Install=10, Price=11, MidasSpend=12,
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# PayableSpend=13, Enroll_Session=14, Enroll_Session%=15, Remark=16,
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# meta-key=17, meta-value=18
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COL_MONTH, COL_DT, COL_INSTALL = 7, 8, 10
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COL_PAYABLE, COL_ENROLL, COL_ENROLLPCT = 13, 14, 15
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COL_METAK, COL_METAV = 16, 17
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daily = []
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meta = {"geo": "EG", "product": "Nagwa"}
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# 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
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target_month = datetime.strptime(month_tag, "%B-%Y")
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ty, tm = target_month.year, target_month.month
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def parse_dt(dt):
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dt = dt.strip()
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if not dt: return None
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# 形如 2026/9/1
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m = re.match(r'^(\d{4})/(\d{1,2})/(\d{1,2})$', dt)
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if m:
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y, mo, d = map(int, m.groups())
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return f"{y:04d}-{mo:02d}-{d:02d}"
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# 形如 20260901
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m = re.match(r'^(\d{4})(\d{2})(\d{2})$', dt)
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if m:
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y, mo, d = map(int, m.groups())
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return f"{y:04d}-{mo:02d}-{d:02d}"
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return None
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price_seen = None
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for r in rows:
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if len(r) <= COL_ENROLLPCT:
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continue
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if r[COL_MONTH].strip() != month_tag:
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continue
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date = parse_dt(r[COL_DT])
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if not date:
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continue
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install = num(r[COL_INSTALL]) or 0
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spend = num(r[COL_PAYABLE]) or 0.0
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enroll = num(r[COL_ENROLL]) or 0
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pct = num(r[COL_ENROLLPCT]) or 0.0
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daily.append({
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"date": date,
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"install": int(install),
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"payable_spend": round(float(spend), 2),
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"enroll_session": int(enroll),
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"enroll_session_pct": round(float(pct), 2),
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})
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# 记录价格(取当月出现的最新价)
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p = num(r[11])
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if p is not None:
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price_seen = p
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# 抓取 meta(Remark 区块的 key/value)
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k = r[COL_METAK].strip() if len(r) > COL_METAK else ""
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v = r[COL_METAV].strip() if len(r) > COL_METAV else ""
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if k and v:
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kl = k.lower()
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if "budget" in kl:
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meta["sep_budget"] = num(v)
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elif kl == "spend":
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meta["spend"] = num(v)
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elif kl == "left":
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meta["left"] = num(v)
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elif kl == "%":
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meta["spend_pct"] = v if v.endswith('%') else (v + '%')
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elif "daily install" in kl:
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meta["rec_daily_install"] = num(v)
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if price_seen is not None:
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meta["price"] = price_seen
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data = {"meta": meta, "daily": daily}
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with open(out_path, "w", encoding="utf-8") as f:
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json.dump(data, f, ensure_ascii=False, indent=2)
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print(f"Wrote {len(daily)} days to {out_path}")
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PY
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echo "Done. Last run: $(date)"
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