396 lines
16 KiB
Python
396 lines
16 KiB
Python
#!/usr/bin/env python3
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"""
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课消指标 v2：剔除 U0 序章，4张图按 L1/L2 拆分
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"""
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import psycopg2
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from collections import defaultdict
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from datetime import datetime, timedelta, date
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import openpyxl
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from openpyxl.styles import Font, Alignment, PatternFill, Border, Side
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from openpyxl.chart import LineChart, BarChart, Reference
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from openpyxl.chart.series import DataPoint
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from openpyxl.chart.label import DataLabelList
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from openpyxl.utils import get_column_letter
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conn = psycopg2.connect(
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host="bj-postgres-16pob4sg.sql.tencentcdb.com",
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port=28591, user="ai_member",
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password="LdfjdjL83h3h3^$&**YGG*", dbname="vala_bi"
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)
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cur = conn.cursor()
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# ===== U0 chapter_ids to exclude =====
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u0_chapters = {55, 56, 57, 58, 59, 343, 344, 345, 346, 348}
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print(f"剔除 U0 序章: {sorted(u0_chapters)}")
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# ===== 时间参数 =====
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overall_start = date(2025, 9, 1)
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overall_end = date(2026, 5, 11)
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weeks = []
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d = overall_start
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while d < overall_end:
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ws = d
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days_to_sunday = 6 - d.weekday()
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we = d + timedelta(days=days_to_sunday)
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if we >= overall_end:
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we = overall_end - timedelta(days=1)
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weeks.append((ws, we))
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d = we + timedelta(days=1)
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# ===== Step 1: 用户分类 =====
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print("\nStep 1: 分类付费用户...")
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cur.execute("""
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SELECT o.account_id, o.trade_no, o.order_status, o.pay_success_date,
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CASE WHEN o.goods_id IN (57, 60, 63) THEN 'L1'
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WHEN o.goods_id = 61 THEN 'L1+L2'
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WHEN o.goods_id IN (31, 32, 33, 54) THEN 'L2'
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ELSE '其他' END as level_type
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FROM bi_vala_order o
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INNER JOIN bi_vala_app_account a ON o.account_id = a.id
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WHERE a.status = 1 AND a.deleted_at IS NULL AND o.pay_success_date IS NOT NULL
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""")
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orders = cur.fetchall()
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cur.execute("SELECT trade_no FROM bi_refund_order WHERE status = 3")
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refund_trades = set(r[0] for r in cur.fetchall())
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user_data = defaultdict(lambda: {'levels': set(), 'orders': []})
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for aid, trade_no, order_status, pay_date, lt in orders:
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is_refunded = (order_status == 4 and trade_no in refund_trades)
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user_data[aid]['levels'].add(lt)
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user_data[aid]['orders'].append((pay_date.date(), is_refunded, lt))
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def classify_user(levels):
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has_l1, has_l2 = 'L1' in levels, 'L2' in levels
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return 'L1+L2' if ('L1+L2' in levels or (has_l1 and has_l2)) else ('仅L1' if has_l1 else ('仅L2' if has_l2 else '其他'))
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for aid in user_data:
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user_data[aid]['category'] = classify_user(user_data[aid]['levels'])
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def is_paid_as_of(aid, as_of_date):
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return sum(1 for pd, ref, lt in user_data[aid]['orders'] if pd <= as_of_date and not ref) > 0
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# ===== Step 2: 课消 (剔除 U0) =====
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print("\nStep 2: 查询课消（剔除U0）...")
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consumption_map = {}
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u0_skipped = 0
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for table_idx in range(8):
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tbl = f"bi_user_chapter_play_record_{table_idx}"
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cur.execute(f"""
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SELECT user_id, chapter_id, updated_at
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FROM {tbl}
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WHERE play_status = 1 AND updated_at >= '2025-09-01' AND updated_at < '2026-05-11'
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""")
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for user_id, chapter_id, updated_at in cur.fetchall():
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if chapter_id in u0_chapters:
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u0_skipped += 1
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continue
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key = (user_id, chapter_id)
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d = updated_at.date() if hasattr(updated_at, 'date') else datetime.strptime(str(updated_at)[:10], '%Y-%m-%d').date()
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if key not in consumption_map or d < consumption_map[key]:
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consumption_map[key] = d
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print(f" 剔除U0课消: {u0_skipped} 条, 去重后: {len(consumption_map)} 条")
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# ===== Step 3: 角色映射 =====
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print("Step 3: 角色映射...")
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all_uids = list(set(k[0] for k in consumption_map))
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char2acct = {}
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bs = 500
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for i in range(0, len(all_uids), bs):
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batch = all_uids[i:i+bs]
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ph = ','.join(['%s'] * len(batch))
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cur.execute(f"SELECT id, account_id FROM bi_vala_app_character WHERE id IN ({ph})", batch)
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for cid, aid in cur.fetchall():
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char2acct[cid] = aid
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print(f" 映射: {len(char2acct)}")
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# ===== Step 4: 按周汇总 =====
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print("Step 4: 按周汇总...")
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results = []
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for ws, we in weeks:
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paid_by_cat = defaultdict(set)
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for aid in user_data:
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if is_paid_as_of(aid, we):
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paid_by_cat[user_data[aid]['category']].add(aid)
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cons_by_cat = defaultdict(int)
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cons_users_by_cat = defaultdict(set)
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for (uid, ch_id), cons_date in consumption_map.items():
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if ws <= cons_date <= we:
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aid = char2acct.get(uid)
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if aid:
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cat = user_data.get(aid, {}).get('category', '其他')
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if aid in paid_by_cat.get(cat, set()):
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cons_by_cat[cat] += 1
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cons_users_by_cat[cat].add(aid)
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row = {'ws': ws, 'we': we}
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for cat in ['仅L1', '仅L2', 'L1+L2', '其他', '合计']:
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if cat == '合计':
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n_paid = sum(len(v) for v in paid_by_cat.values())
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n_cons = sum(cons_by_cat.values())
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n_cons_users = len(set.union(*cons_users_by_cat.values())) if cons_users_by_cat else 0
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else:
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n_paid = len(paid_by_cat.get(cat, set()))
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n_cons = cons_by_cat.get(cat, 0)
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n_cons_users = len(cons_users_by_cat.get(cat, set()))
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row[f'{cat}_paid'] = n_paid
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row[f'{cat}_cons'] = n_cons
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row[f'{cat}_cons_users'] = n_cons_users
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row[f'{cat}_no_cons'] = n_paid - n_cons_users
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row[f'{cat}_avg_all'] = round(n_cons / n_paid, 2) if n_paid > 0 else 0
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row[f'{cat}_avg_cons'] = round(n_cons / n_cons_users, 2) if n_cons_users > 0 else 0
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results.append(row)
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cur.close()
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conn.close()
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# ===== 过滤: 仅保留有足够数据的周（付费人数>0）=====
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for cat in ['仅L1', '仅L2', 'L1+L2']:
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# 找到第一个付费>0的周
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first_idx = next((i for i, r in enumerate(results) if r[f'{cat}_paid'] > 0), 0)
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print(f"{cat} 数据起于第 {first_idx+1} 周 ({results[first_idx]['ws']})")
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# ===== 生成 Excel =====
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print("\n生成 Excel...")
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wb = openpyxl.Workbook()
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wb.remove(wb.active)
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# 样式
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header_font = Font(name='微软雅黑', bold=True, size=9, color='FFFFFF')
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header_fill = PatternFill(start_color='2F5496', end_color='2F5496', fill_type='solid')
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data_font = Font(name='微软雅黑', size=9)
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title_font = Font(name='微软雅黑', bold=True, size=14, color='2F5496')
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subtitle_font = Font(name='微软雅黑', bold=True, size=11, color='2F5496')
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border = Border(left=Side(style='thin'), right=Side(style='thin'), top=Side(style='thin'), bottom=Side(style='thin'))
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center = Alignment(horizontal='center', vertical='center')
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l1_color = '4A90D9'
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l2_color = 'E85D47'
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l1l2_color = '7B9E4B'
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def apply_cell(ws, row, col, value, font=data_font, fill=None, align=center, border_style=border):
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c = ws.cell(row=row, column=col, value=value)
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c.font, c.border, c.alignment = font, border_style, align
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if fill: c.fill = fill
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return c
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def apply_header(ws, row, col, value):
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c = ws.cell(row=row, column=col, value=value)
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c.font, c.fill, c.border, c.alignment = header_font, header_fill, border, center
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return c
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# ===== Sheet 1: 概览 =====
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ws1 = wb.create_sheet("概览")
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ws1.merge_cells('A1:H1')
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apply_cell(ws1, 1, 1, "付费用户 L1/L2 课消分析（剔除U0序章）", font=title_font, border_style=None, align=Alignment(horizontal='left'))
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notes = [
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"口径：剔除L1/L2的U0序章课时（L1 U00: 343-348, L2 U00: 55-59），仅统计U1及之后的课消",
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"课消：用户首次完成某一课时；付费用户：status=1 + 未删除 + 有订单 + 未全部退款",
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]
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for i, n in enumerate(notes):
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ws1.merge_cells(f'A{3+i}:H{3+i}')
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apply_cell(ws1, 3+i, 1, n, font=Font(name='微软雅黑', size=9, color='666666'), border_style=None, align=Alignment(horizontal='left'))
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# ===== Sheet 2: 每周明细 =====
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ws2 = wb.create_sheet("每周明细")
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headers_main = ['周', '周一起', '周日'] + ['合计付费', '合计有消', '合计无消', '合计课消', '合计人均', '合计有消人均',
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'仅L1付费', '仅L1有消', '仅L1无消', '仅L1课消', '仅L1人均', '仅L1有消人均',
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'仅L2付费', '仅L2有消', '仅L2无消', '仅L2课消', '仅L2人均', '仅L2有消人均',
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'L1+L2付费', 'L1+L2有消', 'L1+L2无消', 'L1+L2课消', 'L1+L2人均', 'L1+L2有消人均']
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for j, h in enumerate(headers_main, 1):
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apply_header(ws2, 1, j, h)
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for ri, r in enumerate(results):
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row = ri + 2
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wl = f"{r['ws'].strftime('%m/%d')}-{r['we'].strftime('%m/%d')}"
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apply_cell(ws2, row, 1, wl)
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apply_cell(ws2, row, 2, r['ws'].strftime('%Y-%m-%d'))
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apply_cell(ws2, row, 3, r['we'].strftime('%Y-%m-%d'))
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col = 4
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for prefix in ['合计', '仅L1', '仅L2', 'L1+L2']:
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for metric in ['paid', 'cons_users', 'no_cons', 'cons', 'avg_all', 'avg_cons']:
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val = r[f'{prefix}_{metric}']
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apply_cell(ws2, row, col, val if isinstance(val, str) else val)
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col += 1
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for ci in range(1, len(headers_main)+1):
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ws2.column_dimensions[get_column_letter(ci)].width = 11 if ci <= 3 else 10
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ws2.freeze_panes = 'D2'
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# ===== Sheet 3: L1 图表 =====
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sheet_names = {'仅L1': ('L1图表', 'L1', l1_color, '4A90D9'), '仅L2': ('L2图表', 'L2', l2_color, 'E85D47')}
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for cat, (sname, label, color, light_color) in sheet_names.items():
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ws_chart_data = wb.create_sheet(sname)
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# 只取该分类有付费用户的周
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first_idx = next((i for i, r in enumerate(results) if r[f'{cat}_paid'] > 0), 0)
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cat_results = results[first_idx:]
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# Header
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headers = ['周', '付费用户', '有课消用户', '无课消用户', '课消总数', '人均课消', '有消人均']
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for j, h in enumerate(headers, 1):
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apply_header(ws_chart_data, 1, j, h)
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for ri, r in enumerate(cat_results):
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row = ri + 2
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wl = f"{r['ws'].strftime('%m/%d')}"
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apply_cell(ws_chart_data, row, 1, wl)
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apply_cell(ws_chart_data, row, 2, r[f'{cat}_paid'])
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apply_cell(ws_chart_data, row, 3, r[f'{cat}_cons_users'])
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apply_cell(ws_chart_data, row, 4, r[f'{cat}_no_cons'])
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apply_cell(ws_chart_data, row, 5, r[f'{cat}_cons'])
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apply_cell(ws_chart_data, row, 6, r[f'{cat}_avg_all'])
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apply_cell(ws_chart_data, row, 7, r[f'{cat}_avg_cons'])
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n_rows = len(cat_results)
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cats_ref = Reference(ws_chart_data, min_col=1, min_row=2, max_row=n_rows+1)
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# --- Chart 1: 堆叠柱状图 (有课消/无课消) ---
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chart1 = BarChart()
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chart1.type = "col"
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chart1.grouping = "stacked"
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chart1.title = f"{label} 付费用户课消分布（剔除U0序章）"
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chart1.style = 10
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chart1.width = 24
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chart1.height = 13
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# 有课消用户
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ref1 = Reference(ws_chart_data, min_col=3, min_row=1, max_row=n_rows+1)
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chart1.add_data(ref1, titles_from_data=True)
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chart1.set_categories(cats_ref)
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chart1.series[0].graphicalProperties.solidFill = light_color
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# 无课消用户
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ref2 = Reference(ws_chart_data, min_col=4, min_row=1, max_row=n_rows+1)
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chart1.add_data(ref2, titles_from_data=True)
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chart1.series[1].graphicalProperties.solidFill = 'D9D9D9'
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chart1.y_axis.title = '用户数'
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chart1.legend.position = 'b'
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ws_chart_data.add_chart(chart1, "A9")
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# --- Chart 2: 折线图 (人均课消 + 有消人均) ---
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chart2 = LineChart()
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chart2.title = f"{label} 周人均课消趋势（剔除U0序章）"
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chart2.style = 10
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chart2.width = 24
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chart2.height = 13
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chart2.y_axis.title = '课消数（节/周）'
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ref3 = Reference(ws_chart_data, min_col=6, min_row=1, max_row=n_rows+1)
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chart2.add_data(ref3, titles_from_data=True)
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chart2.set_categories(cats_ref)
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chart2.series[0].graphicalProperties.line.solidFill = '999999'
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chart2.series[0].graphicalProperties.line.width = 20000
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chart2.series[0].graphicalProperties.line.dashStyle = 'dash'
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ref4 = Reference(ws_chart_data, min_col=7, min_row=1, max_row=n_rows+1)
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chart2.add_data(ref4, titles_from_data=True)
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chart2.series[1].graphicalProperties.line.solidFill = color
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chart2.series[1].graphicalProperties.line.width = 28000
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chart2.y_axis.scaling.min = 0
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chart2.legend.position = 'b'
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ws_chart_data.add_chart(chart2, "A27")
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# Column widths
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for ci in range(1, 8):
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ws_chart_data.column_dimensions[get_column_letter(ci)].width = 12
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# ===== Sheet 4: L1+L2 图表（第三个分类）=====
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ws_l1l2 = wb.create_sheet("L1+L2图表")
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cat = 'L1+L2'
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color = l1l2_color
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light_color = 'A8C88E'
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first_idx = next((i for i, r in enumerate(results) if r[f'{cat}_paid'] > 0), 0)
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cat_results = results[first_idx:]
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headers = ['周', '付费用户', '有课消用户', '无课消用户', '课消总数', '人均课消', '有消人均']
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for j, h in enumerate(headers, 1):
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apply_header(ws_l1l2, 1, j, h)
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n_rows = len(cat_results)
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for ri, r in enumerate(cat_results):
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row = ri + 2
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wl = f"{r['ws'].strftime('%m/%d')}"
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apply_cell(ws_l1l2, row, 1, wl)
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apply_cell(ws_l1l2, row, 2, r[f'{cat}_paid'])
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apply_cell(ws_l1l2, row, 3, r[f'{cat}_cons_users'])
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apply_cell(ws_l1l2, row, 4, r[f'{cat}_no_cons'])
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apply_cell(ws_l1l2, row, 5, r[f'{cat}_cons'])
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apply_cell(ws_l1l2, row, 6, r[f'{cat}_avg_all'])
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apply_cell(ws_l1l2, row, 7, r[f'{cat}_avg_cons'])
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cats_ref = Reference(ws_l1l2, min_col=1, min_row=2, max_row=n_rows+1)
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chart1 = BarChart()
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chart1.type = "col"
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chart1.grouping = "stacked"
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chart1.title = f"L1+L2 付费用户课消分布（剔除U0序章）"
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chart1.style = 10
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chart1.width = 24
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chart1.height = 13
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ref1 = Reference(ws_l1l2, min_col=3, min_row=1, max_row=n_rows+1)
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chart1.add_data(ref1, titles_from_data=True)
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chart1.set_categories(cats_ref)
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chart1.series[0].graphicalProperties.solidFill = light_color
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ref2 = Reference(ws_l1l2, min_col=4, min_row=1, max_row=n_rows+1)
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chart1.add_data(ref2, titles_from_data=True)
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chart1.series[1].graphicalProperties.solidFill = 'D9D9D9'
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chart1.y_axis.title = '用户数'
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chart1.legend.position = 'b'
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ws_l1l2.add_chart(chart1, "A9")
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chart2 = LineChart()
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chart2.title = f"L1+L2 周人均课消趋势（剔除U0序章）"
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chart2.style = 10
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chart2.width = 24
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chart2.height = 13
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chart2.y_axis.title = '课消数（节/周）'
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ref3 = Reference(ws_l1l2, min_col=6, min_row=1, max_row=n_rows+1)
|
||
chart2.add_data(ref3, titles_from_data=True)
|
||
chart2.set_categories(cats_ref)
|
||
chart2.series[0].graphicalProperties.line.solidFill = '999999'
|
||
chart2.series[0].graphicalProperties.line.width = 20000
|
||
chart2.series[0].graphicalProperties.line.dashStyle = 'dash'
|
||
|
||
ref4 = Reference(ws_l1l2, min_col=7, min_row=1, max_row=n_rows+1)
|
||
chart2.add_data(ref4, titles_from_data=True)
|
||
chart2.series[1].graphicalProperties.line.solidFill = color
|
||
chart2.series[1].graphicalProperties.line.width = 28000
|
||
|
||
chart2.y_axis.scaling.min = 0
|
||
chart2.legend.position = 'b'
|
||
ws_l1l2.add_chart(chart2, "A27")
|
||
|
||
for ci in range(1, 8):
|
||
ws_l1l2.column_dimensions[get_column_letter(ci)].width = 12
|
||
|
||
# 保存
|
||
path = '/root/.openclaw/workspace/output/course_consumption_by_level_v2.xlsx'
|
||
wb.save(path)
|
||
print(f"\n✅ Excel v2 已保存: {path}")
|
||
|
||
# 简要摘要
|
||
last = results[-1]
|
||
print(f"""
|
||
=== 剔除U0后最终数据（截至5/10） ===
|
||
仅L1: 付费{last['仅L1_paid']} 有消{last['仅L1_cons_users']} 无消{last['仅L1_no_cons']} 人均{last['仅L1_avg_all']} 有消人均{last['仅L1_avg_cons']}
|
||
仅L2: 付费{last['仅L2_paid']} 有消{last['仅L2_cons_users']} 无消{last['仅L2_no_cons']} 人均{last['仅L2_avg_all']} 有消人均{last['仅L2_avg_cons']}
|
||
L1+L2: 付费{last['L1+L2_paid']} 有消{last['L1+L2_cons_users']} 无消{last['L1+L2_no_cons']} 人均{last['L1+L2_avg_all']} 有消人均{last['L1+L2_avg_cons']}
|
||
合计: 付费{last['合计_paid']} 有消{last['合计_cons_users']} 无消{last['合计_no_cons']} 人均{last['合计_avg_all']} 有消人均{last['合计_avg_cons']}
|
||
""")
|