398 lines
14 KiB
Python
398 lines
14 KiB
Python
#!/usr/bin/env python3
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"""
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刷新 5 月行课记录：查询学情数据并回填 Sheet1 D 列
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"""
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import json
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import subprocess
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import sys
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import os
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from datetime import datetime
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# ========== 1. 读取目标行 ==========
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target_rows = json.load(open('/tmp/target_rows.json'))
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print(f"[1/4] 读取目标行: {len(target_rows)} 条")
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# 提取 account_id 列表
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uid_set = sorted(set(str(r[1]) for r in target_rows if r[1]), key=int)
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print(f" 去重用户数: {len(uid_set)}")
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uid_csv = ','.join(uid_set)
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# ========== 2. 数据库查询 ==========
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print(f"[2/4] 查询学情数据...")
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# 从 secrets.env 获取密码
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secrets = {}
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with open('/root/.openclaw/workspace/secrets.env') as f:
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for line in f:
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line = line.strip()
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if line and not line.startswith('#') and '=' in line:
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k, v = line.split('=', 1)
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secrets[k] = v.strip('"').strip("'")
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pg_pass = secrets.get('PG_ONLINE_PASSWORD', '')
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pg_host = 'bj-postgres-16pob4sg.sql.tencentcdb.com'
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pg_port = '28591'
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# 2a. 课程信息 + 角色ID
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print(" 查询课程信息...")
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course_sql = f"""
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SELECT
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a.id AS account_id,
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c.id AS user_id,
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d.course_level,
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CASE WHEN d.expire_time IS NOT NULL THEN '正式课' ELSE '体验课' END AS course_type
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FROM bi_vala_app_account a
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JOIN bi_vala_app_character c ON c.account_id = a.id AND c.deleted_at IS NULL
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LEFT JOIN bi_user_course_detail d ON d.user_id = c.id AND d.deleted_at IS NULL
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WHERE a.id IN ({uid_csv})
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AND a.status = 1
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AND a.deleted_at IS NULL
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ORDER BY a.id, c.id, d.course_level
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"""
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result = subprocess.run(
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['psql', '-h', pg_host, '-p', pg_port, '-U', 'ai_member', '-d', 'vala_bi',
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'-t', '-A', '-F', '\t'],
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input=course_sql,
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capture_output=True, text=True,
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env={**os.environ, 'PGPASSWORD': pg_pass}
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)
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# 构建 account_id -> {user_id列表, 课程信息} 映射
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user_courses = {} # account_id -> [{'user_id': ..., 'level': ..., 'type': ...}, ...]
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for line in result.stdout.strip().split('\n'):
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if not line:
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continue
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parts = line.split('\t')
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if len(parts) >= 4:
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acc_id, user_id, level, ctype = parts[0], parts[1], parts[2], parts[3]
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if acc_id not in user_courses:
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user_courses[acc_id] = []
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user_courses[acc_id].append({
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'user_id': user_id,
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'level': level,
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'type': ctype
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})
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print(f" 课程信息: {len(user_courses)} 个账号有角色")
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# 2b. 最近行课记录 (分表查询)
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print(" 查询最近行课记录...")
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# 收集所有 user_id
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all_user_ids = set()
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for acc_id, chars in user_courses.items():
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for c in chars:
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all_user_ids.add(c['user_id'])
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# 分表查询
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play_records = {} # user_id -> {'recent_date': ..., 'chapter_id': ..., 'chapter_unique_id': ...}
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tables = [f'bi_user_chapter_play_record_{i}' for i in range(8)]
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for table in tables:
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uid_subset = [u for u in all_user_ids if int(u) % 8 == int(table[-1])]
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if not uid_subset:
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continue
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uid_csv_sub = ','.join(uid_subset)
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sql = f"""
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SELECT DISTINCT ON (user_id)
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user_id,
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created_at::date AS recent_date,
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chapter_id,
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chapter_unique_id
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FROM {table}
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WHERE user_id IN ({uid_csv_sub})
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AND play_status = 1
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ORDER BY user_id, created_at DESC
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"""
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result = subprocess.run(
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['psql', '-h', pg_host, '-p', pg_port, '-U', 'ai_member', '-d', 'vala_bi',
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'-t', '-A', '-F', '\t'],
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input=sql,
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capture_output=True, text=True,
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env={**os.environ, 'PGPASSWORD': pg_pass}
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)
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for line in result.stdout.strip().split('\n'):
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if not line:
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continue
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parts = line.split('\t')
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if len(parts) >= 4:
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play_records[parts[0]] = {
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'recent_date': parts[1],
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'chapter_id': parts[2],
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'chapter_unique_id': parts[3]
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}
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print(f" 行课记录: {len(play_records)} 个角色有行课")
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# 2c. 课程结构映射 (chapter_id -> 课程名称)
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print(" 查询课程结构...")
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chapter_ids = set(r['chapter_id'] for r in play_records.values())
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chapter_map = {}
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if chapter_ids:
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ch_csv = ','.join(chapter_ids)
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ch_sql = f"""
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SELECT id, course_level, course_season, course_unit, course_lesson
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FROM bi_level_unit_lesson
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WHERE id IN ({ch_csv})
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"""
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result = subprocess.run(
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['psql', '-h', pg_host, '-p', pg_port, '-U', 'ai_member', '-d', 'vala_bi',
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'-t', '-A', '-F', '\t'],
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input=ch_sql,
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capture_output=True, text=True,
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env={**os.environ, 'PGPASSWORD': pg_pass}
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)
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for line in result.stdout.strip().split('\n'):
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if not line:
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continue
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parts = line.split('\t')
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if len(parts) >= 5:
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ch_id = parts[0]
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chapter_map[ch_id] = f"{parts[1]}-{parts[2]}-{parts[3]}-{parts[4]}"
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# 2d. 学习时长
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print(" 查询学习时长...")
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study_times = {} # user_id -> total_minutes
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comp_tables = [f'bi_user_component_play_record_{i}' for i in range(8)]
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for table in comp_tables:
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uid_subset = [u for u in all_user_ids if int(u) % 8 == int(table[-1])]
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if not uid_subset:
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continue
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uid_csv_sub = ','.join(uid_subset)
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sql = f"""
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SELECT user_id, COALESCE(SUM(interval_time), 0) / 60000.0 AS total_min
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FROM {table}
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WHERE user_id IN ({uid_csv_sub})
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GROUP BY user_id
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"""
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result = subprocess.run(
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['psql', '-h', pg_host, '-p', pg_port, '-U', 'ai_member', '-d', 'vala_bi',
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'-t', '-A', '-F', '\t'],
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input=sql,
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capture_output=True, text=True,
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env={**os.environ, 'PGPASSWORD': pg_pass}
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)
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for line in result.stdout.strip().split('\n'):
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if not line:
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continue
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parts = line.split('\t')
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if len(parts) >= 2:
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study_times[parts[0]] = float(parts[1])
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# 2e. 付费状态
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print(" 查询付费状态...")
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pay_sql = f"""
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SELECT account_id,
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CASE WHEN COUNT(*) > 0 THEN '已付费' ELSE '未付费' END AS pay_status
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FROM bi_vala_order
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WHERE account_id IN ({uid_csv})
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AND pay_success_date IS NOT NULL
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AND order_status = 3
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GROUP BY account_id
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"""
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result = subprocess.run(
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['psql', '-h', pg_host, '-p', pg_port, '-U', 'ai_member', '-d', 'vala_bi',
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'-t', '-A', '-F', '\t'],
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input=pay_sql,
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capture_output=True, text=True,
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env={**os.environ, 'PGPASSWORD': pg_pass}
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)
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paid_users = set()
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for line in result.stdout.strip().split('\n'):
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if not line:
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continue
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parts = line.split('\t')
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if len(parts) >= 2 and parts[1] == '已付费':
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paid_users.add(parts[0])
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# 查询所有用户（包括未付费的）
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all_paid = set()
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for acc_id in uid_set:
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if acc_id in paid_users:
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all_paid.add(acc_id)
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print(f" 付费用户: {len(paid_users)}")
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# ========== 3. 组装学情数据 ==========
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print(f"[3/4] 组装学情数据...")
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def get_course_info(acc_id):
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"""获取用户最优先的课程信息"""
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chars = user_courses.get(acc_id, [])
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if not chars:
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return None, None, None
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# 选最近有过行课记录的角色
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best_char = None
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best_date = None
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for c in chars:
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uid = c['user_id']
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if uid in play_records:
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d = play_records[uid]['recent_date']
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if best_date is None or d > best_date:
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best_date = d
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best_char = c
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if best_char is None and chars:
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best_char = chars[0] # 回退到第一个角色
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if best_char is None:
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return None, None, None
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uid = best_char['user_id']
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level = best_char['level'] or '?'
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ctype = best_char['type'] or '体验课'
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# 获取当前进度
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pr = play_records.get(uid)
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if pr and pr['chapter_id'] in chapter_map:
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chapter_name = chapter_map[pr['chapter_id']]
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current = f"{level}{ctype}-{chapter_name}"
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else:
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current = f"{level}{ctype}-?"
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recent_date = pr['recent_date'] if pr else '无记录'
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study_min = study_times.get(uid, 0)
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return current, recent_date, int(study_min)
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# 为每个目标行生成 D 列文本
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now_str = datetime.now().strftime('%Y-%m-%d %H:%M')
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updates = [] # [(row_num, d_text)]
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for row_num, acc_id, phone in target_rows:
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acc_id = str(acc_id)
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current, recent_date, study_min = get_course_info(acc_id)
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pay_status = '已付费' if acc_id in paid_users else '未付费'
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# 从原始表取销售名（通过B列用户ID）
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# 销售名需要从原始表A列获取，但这里我们直接用target_rows中没有销售名
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# 实际上我们需要重新读取A列。为了效率，暂时用"用户"占位
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# 让我从之前的扫描中保留销售名...
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# 实际上 target_rows 目前只有 (row_num, acc_id, phone)，没有 sales_name
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# 需要补读销售名列
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# 先临时处理，后续补全
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if current is None:
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d_text = f"用户:{acc_id} | 未匹配到课程信息 | 最近行课:无记录 | 学习0min | {pay_status}"
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else:
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d_text = f"用户:{acc_id} | 当前:{current} | 最近行课:{recent_date} | 学习{study_min}min | {pay_status}"
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updates.append((row_num, d_text, pay_status, recent_date, current))
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print(f" 生成 {len(updates)} 条更新")
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# ========== 需要补读A列（销售名）==========
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# 从 target_rows 中批量读取A列
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print(" 补读销售名列...")
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import urllib.request
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# 获取 TAT
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config = json.load(open('/root/.openclaw/credentials/xiaoxi/config.json'))
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app = config['apps'][0]
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tat_data = json.dumps({"app_id": app['appId'], "app_secret": app['appSecret']}).encode()
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tat_req = urllib.request.Request(
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'https://open.feishu.cn/open-apis/auth/v3/tenant_access_token/internal',
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data=tat_data, headers={'Content-Type': 'application/json; charset=utf-8'})
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tat = json.loads(urllib.request.urlopen(tat_req).read())['tenant_access_token']
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# 读取所有目标行的 A 列
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TOKEN = 'RFIJsXT8FhGHhctY4RwczcOfnac'
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SHEET = '55b0eb'
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# 按行号排序
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target_rows_sorted = sorted(updates, key=lambda x: x[0])
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sales_map = {} # row_num -> sales_name
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# 分批读取A列
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batch_size = 200
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for i in range(0, len(target_rows_sorted), batch_size):
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batch = target_rows_sorted[i:i+batch_size]
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row_nums = [str(r[0]) for r in batch]
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range_str = f"{SHEET}!A{min(row_nums, key=int)}:A{max(row_nums, key=int)}"
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url = f"https://open.feishu.cn/open-apis/sheets/v2/spreadsheets/{TOKEN}/values/{range_str}"
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req = urllib.request.Request(url)
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req.add_header('Authorization', f'Bearer {tat}')
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try:
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resp = json.loads(urllib.request.urlopen(req).read())
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values = resp.get('data', {}).get('valueRange', {}).get('values', [])
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start_row = int(min(row_nums, key=int))
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for j, v in enumerate(values):
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row_num = start_row + j
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if v:
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sales_map[row_num] = v[0]
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except Exception as e:
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print(f" Error reading A col: {e}")
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print(f" 销售名: {len(sales_map)} 条")
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# 重新组装 D 列文本（加入销售名）
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final_updates = []
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for row_num, d_text, pay_status, recent_date, current in target_rows_sorted:
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sales = sales_map.get(row_num, '?')
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# 从原始 target_rows 中找到这个 row_num 对应的 acc_id
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orig = next((r for r in target_rows if r[0] == row_num), None)
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acc_id = str(orig[1]) if orig else '?'
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if current and current != 'None':
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d_text = f"销售:{sales} | 用户:{acc_id} | 当前:{current} | 最近行课:{recent_date} | 学习{study_min}min | {pay_status}"
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else:
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# 需要重新计算
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current2, recent_date2, study_min2 = get_course_info(acc_id)
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pay_status2 = '已付费' if acc_id in paid_users else '未付费'
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if current2:
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d_text = f"销售:{sales} | 用户:{acc_id} | 当前:{current2} | 最近行课:{recent_date2} | 学习{study_min2}min | {pay_status2}"
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else:
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d_text = f"销售:{sales} | 用户:{acc_id} | 未匹配到课程信息 | 最近行课:无记录 | 学习0min | {pay_status2}"
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final_updates.append((row_num, d_text))
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updates = final_updates
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# ========== 4. 批量回填 ==========
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print(f"[4/4] 批量回填 {len(updates)} 条...")
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# 构建批量更新请求
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# 飞书 API 支持范围更新，但 D 列不连续（有大量跳行）
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# 策略：逐行更新，每50行一批
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def update_cell(tat, token, sheet, row, col, value):
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"""更新单个单元格"""
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range_str = f"{sheet}!{col}{row}:{col}{row}"
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url = f"https://open.feishu.cn/open-apis/sheets/v2/spreadsheets/{token}/values"
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body = json.dumps({
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"valueRange": {
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"range": range_str,
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"values": [[value]]
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}
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}).encode()
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req = urllib.request.Request(url, data=body, method='PUT')
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req.add_header('Authorization', f'Bearer {tat}')
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req.add_header('Content-Type', 'application/json; charset=utf-8')
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resp = json.loads(urllib.request.urlopen(req).read())
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return resp.get('code') == 0
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# 分批处理：每50个一批，D列和C列一起更新
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batch_size = 50
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success_d = 0
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success_c = 0
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for i in range(0, len(updates), batch_size):
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batch = updates[i:i+batch_size]
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# 收集 D 列和 C 列的更新
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# 由于行不连续，需要逐行更新
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for row_num, d_text in batch:
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# 更新 D 列
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if update_cell(tat, TOKEN, SHEET, row_num, 'D', d_text):
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success_d += 1
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# 更新 C 列为"已返回"
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if update_cell(tat, TOKEN, SHEET, row_num, 'C', '已返回'):
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success_c += 1
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print(f" 进度: {min(i+batch_size, len(updates))}/{len(updates)} (D:{success_d}, C:{success_c})")
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print(f"\n✅ 完成！D列更新: {success_d}/{len(updates)}，C列更新: {success_c}/{len(updates)}")
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