443 lines
18 KiB
Python
443 lines
18 KiB
Python
#!/usr/bin/env python3
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"""
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销售线索转化统计 v9
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- 线索：以销售明细（吴迪/小龙/成都）为准
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- 订单+退款：以数据库为准，通过线索 user_id 匹配
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- 汇总：按线索进线月归因
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- 销转总览 + 落单渠道：均拆分到个人维度
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"""
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import json, requests, os, re, time, psycopg2
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from collections import defaultdict
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CRED_DIR = "/root/.openclaw/credentials/xiaoxi"
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SPREADSHEET_TOKEN = "NoZqsFi47hIOHEt9j8WcfRtbnug"
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SHEET_MAP = {"吴迪": "f975f0", "小龙": "qJF4I", "成都": "qJF4J"}
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TARGET_MONTHS = [3, 4, 5, 6]
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COSTS = {3: 243, 4: 246, 5: 241}
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SALES_ORDER = ["小龙", "吴迪", "Bob", "Tom"]
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PG_HOST = "bj-postgres-16pob4sg.sql.tencentcdb.com"
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PG_PORT = 28591
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PG_USER = "ai_member"
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PG_PASSWORD = "LdfjdjL83h3h3^$&**YGG*"
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PG_DB = "vala_bi"
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# ── 数据库查询 ──────────────────────────────────────────
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def get_orders_for_accounts(account_ids):
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if not account_ids:
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return {}, []
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conn = psycopg2.connect(host=PG_HOST, port=PG_PORT, user=PG_USER, password=PG_PASSWORD, dbname=PG_DB)
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cur = conn.cursor()
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placeholders = ','.join(['%s'] * len(account_ids))
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cur.execute(f"""
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SELECT o.account_id, o.trade_no, o.pay_success_date, o.key_from,
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o.pay_amount_int, o.order_status
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FROM bi_vala_order o
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JOIN bi_vala_app_account a ON o.account_id = a.id AND a.status = 1
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WHERE o.account_id IN ({placeholders})
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AND o.pay_success_date IS NOT NULL
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AND o.order_status IN (3, 4)
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ORDER BY o.account_id, o.pay_success_date
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""", list(account_ids))
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orders_by_account = defaultdict(list)
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all_trade_nos = []
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for row in cur.fetchall():
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aid, trade_no, pay_date, key_from, amount, status = row
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orders_by_account[aid].append({
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'trade_no': trade_no,
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'pay_date': str(pay_date)[:10] if pay_date else '',
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'key_from': key_from or '',
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'amount': float(amount) / 100.0 if amount else 0,
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'status': status,
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})
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all_trade_nos.append(trade_no)
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cur.close()
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conn.close()
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return orders_by_account, all_trade_nos
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def get_refund_for_trade_nos(trade_nos):
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if not trade_nos:
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return {}
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conn = psycopg2.connect(host=PG_HOST, port=PG_PORT, user=PG_USER, password=PG_PASSWORD, dbname=PG_DB)
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cur = conn.cursor()
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refunds = {}
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batch_size = 500
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for i in range(0, len(trade_nos), batch_size):
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batch = trade_nos[i:i+batch_size]
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placeholders = ','.join(['%s'] * len(batch))
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cur.execute(f"""
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SELECT o.trade_no, COALESCE(SUM(r.refund_amount::numeric), 0)/100.0
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FROM bi_vala_order o
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JOIN bi_refund_order r ON o.trade_no = r.trade_no
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WHERE r.status = 3 AND o.order_status = 4
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AND o.trade_no IN ({placeholders})
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GROUP BY o.trade_no
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""", batch)
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for row in cur.fetchall():
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refunds[row[0]] = float(row[1])
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cur.close()
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conn.close()
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return refunds
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# ── 渠道归类 ──────────────────────────────────────────
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def classify_channel(key_from):
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kf = str(key_from).strip()
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if not kf:
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return "其他"
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# 销转渠道
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if kf.startswith("sales-adp"):
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return "销转渠道"
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# 端内
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if kf in ('app-active-h5-0-0', 'app-sales-bj-qhm-0'):
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return "端内"
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if kf.startswith("miniprogram"):
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return "端内"
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# 达人渠道
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if kf.startswith("newmedia-daren") or "daren" in kf.lower():
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return "达人渠道"
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# 直购渠道
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if kf.startswith("newmedia-dianpu-xhs"):
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return "直购渠道"
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if kf.startswith("newmedia-dianpu-douyin"):
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return "直购渠道"
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if "jingxuan" in kf and "douyin" in kf.lower():
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return "直购渠道"
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if kf.startswith("stream-xhs"):
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return "直购渠道"
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if "wxxd" in kf:
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return "直购渠道"
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if kf.startswith("partner"):
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return "直购渠道"
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# 达人渠道
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if kf.startswith("newmedia-dianpu-wwxx"):
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return "达人渠道" # 万物算达人，成本要加佣金
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# 其他新媒体（应该没有了）
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if kf.startswith("newmedia-"):
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return "直购渠道"
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return "其他"
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CHANNEL_ORDER = ["销转渠道", "端内", "直购渠道", "达人渠道", "其他"]
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# ── 飞书 API ──────────────────────────────────────────
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BLUE = "#4472C4"
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WHITE = "#FFFFFF"
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LIGHT_BLUE = "#D6E4F0"
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PURE_WHITE = "#FFFFFF"
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YELLOW = "#FFF2CC"
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YELLOW2 = "#FFF9E6"
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GREEN = "#C6EFCE"
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ORANGE = "#FCE4EC"
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ORANGE2 = "#FFF0F3"
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def get_token():
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with open(os.path.join(CRED_DIR, "config.json")) as f:
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cfg = json.load(f)
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resp = requests.post("https://open.feishu.cn/open-apis/auth/v3/tenant_access_token/internal",
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json={"app_id": cfg["apps"][0]["appId"], "app_secret": cfg["apps"][0]["appSecret"]}, timeout=15)
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return resp.json()["tenant_access_token"]
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def read_sheet(token, sheet_id):
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resp = requests.get(
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f"https://open.feishu.cn/open-apis/sheets/v2/spreadsheets/{SPREADSHEET_TOKEN}/values/{sheet_id}",
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headers={"Authorization": f"Bearer {token}"}, timeout=60)
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return resp.json()["data"]["valueRange"]["values"][2:]
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def parse_month(date_str):
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m = re.match(r'(\d+)月', str(date_str).strip())
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return int(m.group(1)) if m else None
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def parse_row(row):
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def get(idx, default=""):
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return str(row[idx]).strip() if idx < len(row) and row[idx] else default
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return {
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"sales": get(0), "nickname": get(1), "lead_date": get(2),
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"trial_lessons": get(3), "phone": get(4), "grade": get(5),
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"history": get(6), "user_id": get(7), "reg_date": get(8),
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"download_channel": get(9), "is_order": get(10), "order_date": get(11),
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"order_channel": get(12), "product": get(13), "gmv": get(14),
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"refund": get(15), "gsv": get(16), "activated": get(17),
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"progress": get(18), "last_study": get(19), "study_min": get(20),
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"update_time": get(21),
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}
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def safe_float(val):
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try: return float(val)
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except: return 0.0
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def safe_int(val):
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try: return int(float(val))
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except: return 0
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def fmt_pct(val):
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if val == 0: return "0.0%"
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return f"{val*100:.1f}%"
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def fmt_rmb(val):
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return f"¥{int(val):,}"
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def fmt_roi(val):
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return f"{val:.2f}"
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def get_or_create_sheet(token, title):
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"""获取已有 sheet 或创建新 sheet，并清空旧数据"""
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# 先查已有
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resp = requests.get(
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f"https://open.feishu.cn/open-apis/sheets/v2/spreadsheets/{SPREADSHEET_TOKEN}/metainfo",
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headers={"Authorization": f"Bearer {token}"}, timeout=15)
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sheets = resp.json().get("data", {}).get("sheets", [])
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for s in sheets:
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if s.get("title") == title:
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sid = s["sheetId"]
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print(f" 复用已有 sheet: {title} ({sid})，清空旧数据...")
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# 清空 A1:ZZ200
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requests.put(
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f"https://open.feishu.cn/open-apis/sheets/v2/spreadsheets/{SPREADSHEET_TOKEN}/values",
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headers={"Authorization": f"Bearer {token}", "Content-Type": "application/json"},
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json={"valueRange": {"range": f"{sid}!A1:ZZ200", "values": [['']]}}, timeout=30)
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return sid
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# 不存在则创建
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resp = requests.post(
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f"https://open.feishu.cn/open-apis/sheets/v2/spreadsheets/{SPREADSHEET_TOKEN}/sheets_batch_update",
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headers={"Authorization": f"Bearer {token}", "Content-Type": "application/json"},
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json={"requests": [{"addSheet": {"properties": {"title": title, "index": 10}}}]}, timeout=30)
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result = resp.json()
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if result.get("code") == 0:
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replies = result["data"]["replies"]
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if replies and "addSheet" in replies[0]:
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sid = replies[0]["addSheet"]["properties"]["sheetId"]
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print(f" 创建 sheet: {title} ({sid})")
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return sid
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print(f" 创建sheet失败: {result}")
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return None
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def write_values(token, sheet_id, range_str, values):
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resp = requests.put(
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f"https://open.feishu.cn/open-apis/sheets/v2/spreadsheets/{SPREADSHEET_TOKEN}/values",
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headers={"Authorization": f"Bearer {token}", "Content-Type": "application/json"},
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json={"valueRange": {"range": f"{sheet_id}!{range_str}", "values": values}}, timeout=30)
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code = resp.json().get("code")
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if code != 0:
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print(f" ❌ {range_str}: {resp.json()}")
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return code == 0
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def apply_style(token, sheet_id, col_start, row_start, col_end, row_end, style):
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rng = f"{sheet_id}!{col_start}{row_start}:{col_end}{row_end}"
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resp = requests.put(
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f"https://open.feishu.cn/open-apis/sheets/v2/spreadsheets/{SPREADSHEET_TOKEN}/style",
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headers={"Authorization": f"Bearer {token}", "Content-Type": "application/json"},
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json={"appendStyle": {"range": rng, "style": style}}, timeout=30)
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code = resp.json().get("code")
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if code != 0:
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print(f" ❌ {rng}: {resp.json()}")
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return code == 0
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def header_style():
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return {"backcolor": BLUE, "fontColor": WHITE, "bold": True, "fontSize": 10}
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def total_style():
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return {"backcolor": GREEN, "fontSize": 10, "bold": True}
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# ── 主流程 ──────────────────────────────────────────
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def main():
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token = get_token()
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# 1. 读取销售明细（线索）
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print("读取销售明细...")
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all_leads = []
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for sheet_label, sheet_id in SHEET_MAP.items():
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rows = read_sheet(token, sheet_id)
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for row in rows:
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d = parse_row(row)
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all_leads.append(d)
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print(f" 总计: {len(all_leads)} 条线索")
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# 按进线月分组
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by_month = defaultdict(list)
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for r in all_leads:
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m = parse_month(r["lead_date"])
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if m in TARGET_MONTHS:
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by_month[m].append(r)
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for m in TARGET_MONTHS:
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print(f" {m}月: {len(by_month[m])} 条线索")
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# 2. 收集所有线索的 user_id，去数据库查订单
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all_user_ids = set()
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for r in all_leads:
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uid = safe_int(r["user_id"])
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if uid > 0:
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all_user_ids.add(uid)
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print(f"\n查询数据库订单（{len(all_user_ids)} 个用户）...")
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db_orders, all_trade_nos = get_orders_for_accounts(all_user_ids)
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db_order_users = set(db_orders.keys())
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print(f" 有订单的用户: {len(db_order_users)} 人, 订单: {sum(len(v) for v in db_orders.values())} 笔")
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# 3. 查退款
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print(f"查询退款（{len(all_trade_nos)} 笔订单）...")
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refund_by_trade = get_refund_for_trade_nos(all_trade_nos)
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refund_total = sum(refund_by_trade.values())
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refund_users = set()
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for trade_no in refund_by_trade:
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for aid, orders in db_orders.items():
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for o in orders:
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if o['trade_no'] == trade_no:
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refund_users.add(aid)
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print(f" 退款: {len(refund_by_trade)} 笔, ¥{refund_total:,.0f}, {len(refund_users)} 人")
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# 4. 为每条线索匹配数据库订单
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for r in all_leads:
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uid = safe_int(r["user_id"])
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r["_db_orders"] = db_orders.get(uid, [])
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r["_has_order"] = len(r["_db_orders"]) > 0
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# 5. 计算每条线索的 GMV / 退款 / GSV（来自数据库）
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for r in all_leads:
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orders = r["_db_orders"]
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r["_db_gmv"] = sum(o['amount'] for o in orders)
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r["_db_refund"] = sum(refund_by_trade.get(o['trade_no'], 0) for o in orders)
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r["_db_gsv"] = r["_db_gmv"] - r["_db_refund"]
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# 6. 构建数据（供公式和底表使用）
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funnel_rows = []
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for m in TARGET_MONTHS:
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for sales in SALES_ORDER:
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leads = [r for r in by_month[m] if r["sales"] == sales]
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if not leads:
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continue
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lead_count = len(leads)
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has_phone = len([r for r in leads if r["phone"] and r["phone"] != "未注册"])
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registered = len([r for r in leads if r["user_id"] and r["user_id"] != "未注册"])
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trial = [safe_int(r["trial_lessons"]) for r in leads]
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ordered = [r for r in leads if r["_has_order"]]
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order_count = len(ordered)
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gmv = sum(r["_db_gmv"] for r in ordered)
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refund = sum(r["_db_refund"] for r in ordered)
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gsv = gmv - refund
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phone_rate = has_phone / lead_count if lead_count else 0
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reg_rate = registered / lead_count if lead_count else 0
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lesson_data = {}
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for n in range(1, 6):
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cnt = len([t for t in trial if t >= n])
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ord_n = len([r for r in leads if safe_int(r["trial_lessons"]) >= n and r["_has_order"]])
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lesson_data[n] = (cnt, ord_n)
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rates = {}
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for n in range(1, 6):
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cnt, ord_n = lesson_data[n]
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rates[n] = (cnt / lead_count if lead_count else 0, ord_n / cnt if cnt else 0)
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order_conv = order_count / lead_count if lead_count else 0
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funnel_rows.append([
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f"{m}月", sales, lead_count,
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has_phone, fmt_pct(phone_rate),
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registered, fmt_pct(reg_rate),
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lesson_data[1][0], fmt_pct(rates[1][0]), fmt_pct(rates[1][1]),
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lesson_data[2][0], fmt_pct(rates[2][0]), fmt_pct(rates[2][1]),
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lesson_data[3][0], fmt_pct(rates[3][0]), fmt_pct(rates[3][1]),
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lesson_data[4][0], fmt_pct(rates[4][0]), fmt_pct(rates[4][1]),
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lesson_data[5][0], fmt_pct(rates[5][0]), fmt_pct(rates[5][1]),
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order_count, fmt_pct(order_conv),
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gmv, refund, gsv,
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])
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# 渠道底表数据
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channel_rows = []
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for m in TARGET_MONTHS:
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for sales in SALES_ORDER:
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if sum(1 for r in by_month[m] if r["sales"] == sales) == 0:
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continue
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for cat in CHANNEL_ORDER:
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o = 0; g = 0.0
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for r in by_month[m]:
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if r["sales"] != sales: continue
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for odb in r["_db_orders"]:
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if classify_channel(odb['key_from']) == cat:
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o += 1; g += odb['amount']
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if o > 0 or g > 0:
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channel_rows.append([f"{m}月", sales, cat, o, g])
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# 月合计渠道行
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for cat in CHANNEL_ORDER:
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o = 0; g = 0.0
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for r in by_month[m]:
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for odb in r["_db_orders"]:
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if classify_channel(odb['key_from']) == cat:
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o += 1; g += odb['amount']
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if o > 0 or g > 0:
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channel_rows.append([f"{m}月", "合计", cat, o, g])
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# 渠道统计（月 × 销售 × 渠道）供落单渠道分布使用
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ms_channel = defaultdict(lambda: defaultdict(lambda: {"orders": 0, "gmv": 0.0}))
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for m in TARGET_MONTHS:
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for r in by_month[m]:
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sales = r["sales"]
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for o in r["_db_orders"]:
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cat = classify_channel(o['key_from'])
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ms_channel[(m, sales)][cat]["orders"] += 1
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ms_channel[(m, sales)][cat]["gmv"] += o['amount']
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# 7. 过程数据（唯一的数据底表）
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print("\n=== 1. 过程数据（底表） ===")
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sid_funnel = get_or_create_sheet(token, "📊 过程数据")
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# 清除旧数据
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meta = requests.get(
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f"https://open.feishu.cn/open-apis/sheets/v2/spreadsheets/{SPREADSHEET_TOKEN}/metainfo",
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headers={"Authorization": f"Bearer {token}"}, timeout=10).json()
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sheets_info = meta.get('data', {}).get('sheets', [])
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max_rows = 200
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for s in sheets_info:
|
||
if s.get('sheetId') == sid_funnel:
|
||
max_rows = s.get('row_count', 200)
|
||
break
|
||
if max_rows > 0:
|
||
requests.delete(
|
||
f"https://open.feishu.cn/open-apis/sheets/v2/spreadsheets/{SPREADSHEET_TOKEN}/sheets/{sid_funnel}/range?dimension=ROWS&start_index=1&end_index={max_rows}",
|
||
headers={"Authorization": f"Bearer {token}"}, timeout=15)
|
||
time.sleep(0.5)
|
||
|
||
headers3 = [["月份", "销售", "线索总数",
|
||
"拿手机号数", "拿手机号率", "注册数", "注册率",
|
||
"首课人数", "首课率", "一节课转化率",
|
||
"二次课人数", "二次课率", "二节课转化率",
|
||
"三次课人数", "三次课率", "三节课转化率",
|
||
"四次课人数", "四次课率", "四节课转化率",
|
||
"五次课人数", "五次课率", "五节课转化率",
|
||
"订单数", "转化率", "GMV", "退款金额", "GSV",
|
||
]]
|
||
# 批量写入（一次性API调用，避免限流）
|
||
channel_start = 16
|
||
cost_ref_data = [["月份", "月投放成本"]]
|
||
for m in TARGET_MONTHS:
|
||
c = COSTS.get(m, 0)
|
||
if c > 0:
|
||
cost_ref_data.append([f"{m}月", c])
|
||
|
||
batch_data = [
|
||
{"range": f"{sid_funnel}!A1:AA1", "values": headers3},
|
||
{"range": f"{sid_funnel}!A2:AA{1+len(funnel_rows)}", "values": funnel_rows},
|
||
{"range": f"{sid_funnel}!A{channel_start}:E{channel_start}", "values": [["月份", "销售", "渠道", "订单数", "GMV"]]},
|
||
{"range": f"{sid_funnel}!A{channel_start+1}:E{channel_start+len(channel_rows)}", "values": channel_rows},
|
||
{"range": f"{sid_funnel}!G{channel_start}:H{channel_start+len(cost_ref_data)-1}", "values": cost_ref_data},
|
||
]
|
||
resp = requests.post(
|
||
f"https://open.feishu.cn/open-apis/sheets/v2/spreadsheets/{SPREADSHEET_TOKEN}/values_batch_update",
|
||
headers={"Authorization": f"Bearer {token}", "Content-Type": "application/json"},
|
||
json={"valueInputOption": "USER", "valueRanges": batch_data},
|
||
timeout=60)
|
||
code = resp.json().get("code")
|
||
if code != 0:
|
||
print(f" ❌ 批量写入失败: {resp.json()}")
|
||
time.sleep(1)
|
||
|
||
print(" ✅ 数据写入完成")
|
||
|
||
|
||
if __name__ == "__main__":
|
||
main()
|