import pandas as pd
import psycopg2
from psycopg2.extras import RealDictCursor

# 数据库连接配置
conn = psycopg2.connect(
    host="bj-postgres-16pob4sg.sql.tencentcdb.com",
    port=28591,
    user="ai_member",
    password="LdfjdjL83h3h3^$&**YGG*",
    dbname="vala_bi"
)

user_ids = [51, 17690, 17646, 2705]

# 1. 查询用户注册信息
query_register = """
SELECT id as user_id, created_at as register_time, status as user_status, tel as user_mobile
FROM bi_vala_app_account
WHERE id IN %s
"""
df_register = pd.read_sql(query_register, conn, params=(tuple(user_ids),))

# 2. 查询用户购课情况
query_purchase = """
SELECT account_id as user_id, 
       COUNT(*) as purchased_course_count, 
       SUM(pay_amount_int)/100.0 as total_paid_amount, 
       MAX(created_at) as last_purchase_time
FROM bi_vala_order
WHERE account_id IN %s AND pay_amount_int > 0
GROUP BY account_id
"""
df_purchase = pd.read_sql(query_purchase, conn, params=(tuple(user_ids),))

# 3. 查询用户学习进度
query_learn = """
SELECT account_id as user_id,
       course_level,
       latest_unit_index as current_unit,
       latest_lesson_index as current_lesson,
       learn_duration as total_learn_seconds,
       last_learn_time
FROM bi_user_course_detail
WHERE account_id IN %s
"""
df_learn = pd.read_sql(query_learn, conn, params=(tuple(user_ids),))

# 合并数据
df_result = df_register.merge(df_purchase, on='user_id', how='left')
df_result = df_result.merge(df_learn, on='user_id', how='left')

# 填充空值
df_result = df_result.fillna({
    'purchased_course_count': 0,
    'total_paid_amount': 0,
    'learning_course_count': 0,
    'average_progress_percent': 0
})

# 格式化时间列
df_result['register_time'] = df_result['register_time'].dt.strftime('%Y-%m-%d %H:%M:%S')
df_result['last_purchase_time'] = pd.to_datetime(df_result['last_purchase_time']).dt.strftime('%Y-%m-%d %H:%M:%S')
df_result['last_learn_time'] = pd.to_datetime(df_result['last_learn_time']).dt.strftime('%Y-%m-%d %H:%M:%S')

# 导出为Excel
output_path = '/root/.openclaw/workspace/用户详细信息.xlsx'
df_result.to_excel(output_path, index=False, sheet_name='用户信息')

print(f"文件已生成：{output_path}")
print("数据预览：")
print(df_result.to_csv(sep='\t', na_rep='无'))

conn.close()