import pandas as pd
import numpy as np
import psycopg2

# 1. 正确计算GSV：同时满足bi_refund_order.status=3 和 bi_vala_order.order_status=4
conn = psycopg2.connect(
    host="bj-postgres-16pob4sg.sql.tencentcdb.com",
    port=28591,
    user="ai_member",
    password="LdfjdjL83h3h3^$&**YGG*",
    database="vala_bi"
)

# 获取退款数据
cur = conn.cursor()
cur.execute("""
    SELECT out_trade_no, SUM(refund_amount_int) as total_refund_int
    FROM bi_refund_order 
    WHERE status = 3 AND created_at >= '2026-03-01 00:00:00+08'
    GROUP BY out_trade_no
""")
refund_data = cur.fetchall()
refund_df = pd.DataFrame(refund_data, columns=['out_trade_no', 'total_refund_int'])
cur.close()
conn.close()

# 获取订单数据
order_df = pd.read_csv('2026年3月1日至今订单_含正确成交标记.csv')

# 合并计算
order_df = pd.merge(order_df, refund_df, on='out_trade_no', how='left')
order_df['total_refund_int'] = order_df['total_refund_int'].fillna(0)
order_df['GMV'] = order_df['pay_amount_int'] / 100
order_df['refund_amount'] = order_df.apply(
    lambda row: row['total_refund_int']/100 if row['order_status'] == 4 else 0, 
    axis=1
)
order_df['GSV'] = order_df['GMV'] - order_df['refund_amount']
order_df['is_valid_refund'] = (order_df['order_status'] == 4) & (order_df['total_refund_int'] > 0)

# 2. 渠道映射（和原表一致）
def map_channel(tag):
    if tag in ['销转', '销转-小龙']:
        return '销转'
    elif tag in ['端内直购', '端内销转']:
        return 'App转化'
    elif tag == '达播':
        return '达播'
    elif tag.startswith('班主任-'):
        return '班主任'
    else:
        return '其他'

order_df['渠道大类'] = order_df['成交标记'].apply(map_channel)

# 3. 按原表格式构建报表
# 原表表头结构
report_data = [
    # 第一部分：3月剩余预测 & 3月实际 汇总
    ['3月剩余预测', 'GMV', '', 'GSV', '', '', '3月实际', 'GMV', '', 'GSV', '', '完成率', ''],
    ['销转', '', '', 100000, '', '', '', '', '', 0, '', '', ''],
    ['App转化', '', '', 20000, '', '', '', '', '', 0, '', '', ''],
    ['达播', '', '', 250000, '', '', '', '', '', 0, '', '', ''],
    ['班主任', '', '', 10000, '', '', '', '', '', 0, '', '', ''],
    ['', '', '', '', '', '', '', '', '', '', '', '', ''],
    # 销转明细
    ['', '', '线索量', '线索成本', '转化率', '客单价', 'GMV', '退款率', 'GSV', '投放成本', '退后ROI', '', ''],
    ['销转', '第一周', 0, 0, 0, 0, 0, 0, 0, 0, 0, '', ''],
    ['', '第二周', 0, 0, 0, 0, 0, 0, 0, 0, 0, '', ''],
    ['', '第三周', 0, 0, 0, 0, 0, 0, 0, 0, 0, '', ''],
    ['', '第四周', 0, 0, 0, 0, 0, 0, 0, 0, 0, '', ''],
    ['', '小计', 0, 0, 0, 0, 0, 0, 0, 0, 0, '', ''],
    ['', '', '', '', '', '', '', '', '', '', '', '', ''],
    # App转化明细
    ['App转化', '', '注册人数', '转化率', '客单价', 'GMV', '退款率', 'GSV', '', '', '', '', ''],
    ['', '自然转化', 0, 0, 0, 0, 0, 0, 0, '', '', '', ''],
    ['', '销售转化', 0, 0, 0, 0, 0, 0, 0, '', '', '', ''],
    ['', '小计', 0, 0, 0, 0, 0, 0, 0, '', '', '', ''],
    ['', '', '', '', '', '', '', '', '', '', '', '', ''],
    # 达播明细
    ['达播', '', '达人', '订单量', '均单价', 'GMV', '退款率', 'GSV', '', '', '', '', ''],
]

# 计算汇总数据
channel_summary = order_df.groupby('渠道大类').agg(
    总订单数=('id', 'count'),
    总GMV=('GMV', 'sum'),
    总GSV=('GSV', 'sum'),
    退款订单数=('is_valid_refund', 'sum'),
    总退款金额=('refund_amount', 'sum')
).reset_index()

# 填充汇总行
channel_map = {'销转': 1, 'App转化': 2, '达播': 3, '班主任': 4}
for _, row in channel_summary.iterrows():
    if row['渠道大类'] in channel_map:
        idx = channel_map[row['渠道大类']]
        report_data[idx][3] = 100000 if idx ==1 else 20000 if idx==2 else 250000 if idx==3 else 10000
        report_data[idx][8] = round(row['总GSV'], 2)
        report_data[idx][9] = round(row['总GMV'], 2)
        report_data[idx][10] = f"{round(row['总GSV']/report_data[idx][3]*100, 1)}%"
        report_data[idx][7] = round(row['总GMV'], 2)
        report_data[idx][11] = f"{round(row['退款订单数']/row['总订单数']*100,1)}%"

# 填充达播达人明细
dabo_orders = order_df[order_df['渠道大类'] == '达播']
dabo_summary = dabo_orders.groupby('key_from').agg(
    订单数=('id', 'count'),
    GMV=('GMV', 'sum'),
    GSV=('GSV', 'sum'),
    退款数=('is_valid_refund', 'sum')
).reset_index()
dabo_summary['退费率'] = (dabo_summary['退款数'] / dabo_summary['订单数'] * 100).round(1)
dabo_summary['均单价'] = (dabo_summary['GMV'] / dabo_summary['订单数']).round(2)

# 匹配达人名称
def get_daren_name(key):
    if '晚柠' in key:
        return '晚柠'
    elif '念妈' in key:
        return '念妈'
    elif '小花生' in key:
        return '小花生'
    elif '盈姐' in key:
        return '盈姐'
    elif '百克力' in key:
        return '百克力'
    elif '海淀妈妈优选' in key:
        return '海淀妈妈优选'
    elif '海淀小水妈' in key:
        return '海淀小水妈'
    else:
        return '其他达人'

dabo_summary['达人'] = dabo_summary['key_from'].apply(get_daren_name)
dabo_final = dabo_summary.groupby('达人').agg(
    订单数=('订单数', 'sum'),
    GMV=('GMV', 'sum'),
    GSV=('GSV', 'sum'),
    退费率=('退费率', 'mean'),
    均单价=('均单价', 'mean')
).reset_index()

for _, row in dabo_final.iterrows():
    report_data.append([
        '', '', row['达人'], row['订单数'], round(row['均单价'],2), round(row['GMV'],2), f"{row['退费率']}%", round(row['GSV'],2), '', '', '', '', ''
    ])

# 添加达播小计
dabo_total = dabo_final.sum()
report_data.append([
    '', '', '小计', dabo_total['订单数'], round(dabo_total['GMV']/dabo_total['订单数'],2), round(dabo_total['GMV'],2), 
    f"{round(dabo_orders['is_valid_refund'].sum()/len(dabo_orders)*100,1)}%", round(dabo_total['GSV'],2), '', '', '', '', ''
])

# 班主任明细
report_data.extend([
    ['', '', '', '', '', '', '', '', '', '', '', '', ''],
    ['班主任', '', '分类', '订单量', 'GMV', '退款订单', '退款金额', 'GSV', '', '', '', '', ''],
    ['', '', '季转年', 0, 0, 0, 0, 0, '', '', '', '', ''],
    ['', '', '年转年', 0, 0, 0, 0, 0, '', '', '', '', ''],
    ['', '', '转介绍', 0, 0, 0, 0, 0, '', '', '', '', ''],
    ['', '', '退费重报', 0, 0, 0, 0, 0, '', '', '', '', ''],
])

banzhuren_orders = order_df[order_df['渠道大类'] == '班主任']
bzr_summary = banzhuren_orders.groupby('成交标记').agg(
    订单数=('id', 'count'),
    GMV=('GMV', 'sum'),
    GSV=('GSV', 'sum'),
    退款数=('is_valid_refund', 'sum'),
    退款金额=('refund_amount', 'sum')
).reset_index()

for _, row in bzr_summary.iterrows():
    if '年续' in row['成交标记'] or '年转年' in row['成交标记']:
        idx = -4
    elif '转介绍' in row['成交标记']:
        idx = -3
    elif '重报' in row['成交标记']:
        idx = -2
    else:
        idx = -5
    report_data[idx][3] = row['订单数']
    report_data[idx][4] = round(row['GMV'],2)
    report_data[idx][5] = row['退款数']
    report_data[idx][6] = round(row['退款金额'],2)
    report_data[idx][7] = round(row['GSV'],2)

# 班主任小计
bzr_total = bzr_summary.sum()
report_data.append([
    '', '', '小计', bzr_total['订单数'], round(bzr_total['GMV'],2), bzr_total['退款数'], round(bzr_total['退款金额'],2), round(bzr_total['GSV'],2), '', '', '', '', ''
])

# 转换为DataFrame并保存
df = pd.DataFrame(report_data)
output_file = '2026年3月收入预测报表_与原表格式一致.xlsx'
with pd.ExcelWriter(output_file, engine='openpyxl') as writer:
    df.to_excel(writer, index=False, header=False, sheet_name='3月收入报表')

print("报表已生成，格式与原表完全一致，GSV已按正确口径重新计算：")
print(channel_summary[['渠道大类', '总GMV', '总GSV', '退款订单数']])
print(f"\n总GSV：{round(order_df['GSV'].sum(),2)} 元，总GMV：{round(order_df['GMV'].sum(),2)} 元，整体退费率：{round(order_df['is_valid_refund'].sum()/len(order_df)*100,1)}%")