Update Sep 2026 data; auto-fetch from Google Sheet; daily refresh

data.json

@@ -2,16 +2,223 @@
   "meta": {
     "geo": "EG",
     "product": "Nagwa",
-    "price": 0.30,
+    "sep_budget": 7500,
-    "sep_budget": 7500.00,
+    "spend": 2279.6,
-    "spend": 814.80,
+    "left": 5220.4,
-    "left": 6685.20,
+    "spend_pct": "30.39%",
-    "spend_pct": "10.86%",
+    "rec_daily_install": 593.23,
-    "rec_daily_install": 825.33
+    "price": 0.4
   },
   "daily": [
-    {"date": "2026-09-01", "install": 932, "payable_spend": 279.60, "enroll_session": 698, "enroll_session_pct": 74.89},
+    {
-    {"date": "2026-09-02", "install": 917, "payable_spend": 275.10, "enroll_session": 0, "enroll_session_pct": 0.00},
+      "date": "2026-09-01",
-    {"date": "2026-09-03", "install": 867, "payable_spend": 260.10, "enroll_session": 0, "enroll_session_pct": 0.00}
+      "install": 932,
+      "payable_spend": 279.6,
+      "enroll_session": 698,
+      "enroll_session_pct": 74.89
+    },
+    {
+      "date": "2026-09-02",
+      "install": 917,
+      "payable_spend": 275.1,
+      "enroll_session": 586,
+      "enroll_session_pct": 63.9
+    },
+    {
+      "date": "2026-09-03",
+      "install": 867,
+      "payable_spend": 260.1,
+      "enroll_session": 502,
+      "enroll_session_pct": 57.9
+    },
+    {
+      "date": "2026-09-04",
+      "install": 822,
+      "payable_spend": 246.6,
+      "enroll_session": 676,
+      "enroll_session_pct": 82.24
+    },
+    {
+      "date": "2026-09-05",
+      "install": 894,
+      "payable_spend": 268.2,
+      "enroll_session": 760,
+      "enroll_session_pct": 85.01
+    },
+    {
+      "date": "2026-09-06",
+      "install": 1048,
+      "payable_spend": 314.4,
+      "enroll_session": 782,
+      "enroll_session_pct": 74.62
+    },
+    {
+      "date": "2026-09-07",
+      "install": 858,
+      "payable_spend": 343.2,
+      "enroll_session": 866,
+      "enroll_session_pct": 100.93
+    },
+    {
+      "date": "2026-09-08",
+      "install": 731,
+      "payable_spend": 292.4,
+      "enroll_session": 651,
+      "enroll_session_pct": 89.06
+    },
+    {
+      "date": "2026-09-09",
+      "install": 0,
+      "payable_spend": 0.0,
+      "enroll_session": 0,
+      "enroll_session_pct": 0.0
+    },
+    {
+      "date": "2026-09-10",
+      "install": 0,
+      "payable_spend": 0.0,
+      "enroll_session": 0,
+      "enroll_session_pct": 0.0
+    },
+    {
+      "date": "2026-09-11",
+      "install": 0,
+      "payable_spend": 0.0,
+      "enroll_session": 0,
+      "enroll_session_pct": 0.0
+    },
+    {
+      "date": "2026-09-12",
+      "install": 0,
+      "payable_spend": 0.0,
+      "enroll_session": 0,
+      "enroll_session_pct": 0.0
+    },
+    {
+      "date": "2026-09-13",
+      "install": 0,
+      "payable_spend": 0.0,
+      "enroll_session": 0,
+      "enroll_session_pct": 0.0
+    },
+    {
+      "date": "2026-09-14",
+      "install": 0,
+      "payable_spend": 0.0,
+      "enroll_session": 0,
+      "enroll_session_pct": 0.0
+    },
+    {
+      "date": "2026-09-15",
+      "install": 0,
+      "payable_spend": 0.0,
+      "enroll_session": 0,
+      "enroll_session_pct": 0.0
+    },
+    {
+      "date": "2026-09-16",
+      "install": 0,
+      "payable_spend": 0.0,
+      "enroll_session": 0,
+      "enroll_session_pct": 0.0
+    },
+    {
+      "date": "2026-09-17",
+      "install": 0,
+      "payable_spend": 0.0,
+      "enroll_session": 0,
+      "enroll_session_pct": 0.0
+    },
+    {
+      "date": "2026-09-18",
+      "install": 0,
+      "payable_spend": 0.0,
+      "enroll_session": 0,
+      "enroll_session_pct": 0.0
+    },
+    {
+      "date": "2026-09-19",
+      "install": 0,
+      "payable_spend": 0.0,
+      "enroll_session": 0,
+      "enroll_session_pct": 0.0
+    },
+    {
+      "date": "2026-09-20",
+      "install": 0,
+      "payable_spend": 0.0,
+      "enroll_session": 0,
+      "enroll_session_pct": 0.0
+    },
+    {
+      "date": "2026-09-21",
+      "install": 0,
+      "payable_spend": 0.0,
+      "enroll_session": 0,
+      "enroll_session_pct": 0.0
+    },
+    {
+      "date": "2026-09-22",
+      "install": 0,
+      "payable_spend": 0.0,
+      "enroll_session": 0,
+      "enroll_session_pct": 0.0
+    },
+    {
+      "date": "2026-09-23",
+      "install": 0,
+      "payable_spend": 0.0,
+      "enroll_session": 0,
+      "enroll_session_pct": 0.0
+    },
+    {
+      "date": "2026-09-24",
+      "install": 0,
+      "payable_spend": 0.0,
+      "enroll_session": 0,
+      "enroll_session_pct": 0.0
+    },
+    {
+      "date": "2026-09-25",
+      "install": 0,
+      "payable_spend": 0.0,
+      "enroll_session": 0,
+      "enroll_session_pct": 0.0
+    },
+    {
+      "date": "2026-09-26",
+      "install": 0,
+      "payable_spend": 0.0,
+      "enroll_session": 0,
+      "enroll_session_pct": 0.0
+    },
+    {
+      "date": "2026-09-27",
+      "install": 0,
+      "payable_spend": 0.0,
+      "enroll_session": 0,
+      "enroll_session_pct": 0.0
+    },
+    {
+      "date": "2026-09-28",
+      "install": 0,
+      "payable_spend": 0.0,
+      "enroll_session": 0,
+      "enroll_session_pct": 0.0
+    },
+    {
+      "date": "2026-09-29",
+      "install": 0,
+      "payable_spend": 0.0,
+      "enroll_session": 0,
+      "enroll_session_pct": 0.0
+    },
+    {
+      "date": "2026-09-30",
+      "install": 0,
+      "payable_spend": 0.0,
+      "enroll_session": 0,
+      "enroll_session_pct": 0.0
+    }
   ]
 }

schedule.conf

@@ -1 +1 @@
-03
+24

update.sh

@@ -1,6 +1,120 @@
 #!/bin/bash
-# update.sh - 数据来自手动更新的 data.json
+# update.sh - 自动从 Google Sheet 拉取 EG Nagwa 当月数据并生成 data.json
-# 由于数据源是 Excel 表格（无公开 API），此脚本仅做占位
+# 数据源：公开导出的 Google Sheet CSV
-# 每次有新数据时，直接更新 data.json 并 push 即可
+# 每天由服务器自动执行一次（见 schedule.conf）
-echo "data.json is manually maintained from Excel export."
+set -euo pipefail
-echo "Last check: $(date)"
+
+SHEET_ID="11Npr4IpXT8jtgUnrkrjITJ8s1fHNYTwRRwSGIvcfeIs"
+GID="699511110"
+CSV_URL="https://docs.google.com/spreadsheets/d/${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)"