🤖 每日自动备份 - 2026-04-23 08:00:02
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小溪
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commit
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@ -12,3 +12,4 @@ vala-component-practice-stat 8e768e2641019d27bd41f4647d2d90f24182a0554dad5ad9f41
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cron-schedule e103cbb1806b28c891b9c856963325086ecaff32edec208f0a841865f26e8f3e
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refund-user-learning-analysis 648fd4ae2b29167fd66eab4245bdaaef00242db3131f4919cc02f07ca2a9b59c
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phone-chapter-query ac429b4da5a89db16efdf1066edf4ecb1c050b93aff20dd4c652af5f5568e44f
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vala-order-amortization-stat 9a07c4466a98a55e62d0b0c4948ec709fda7a8e607c9497a0cfba32b77046c50
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@ -64,6 +64,9 @@
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- `course_lesson`：课时，如 L01、L02、L03、L04、L05（每单元固定5节课）
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- 示例：L1 S0 U00 L01 → id=343，L2 S0 U00 L01 → id=55
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- [李承龙确认] 以后匹配课程统一使用此表，不再从 MySQL 配置表手动查找
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- 订单表与退费表关联规则：
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- `bi_vala_order.trade_no` ↔ `bi_refund_order.trade_no` 关联
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- `bi_vala_order.out_trade_no` ↔ `bi_refund_order.out_trade_no` 关联
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## 业务知识库
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- **已收集13个常用SQL查询模板**
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29
scripts/check_seasonal_ticket_fields.py
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29
scripts/check_seasonal_ticket_fields.py
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@ -0,0 +1,29 @@
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import psycopg2
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# 读取密码
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DB_PASSWORD = ""
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with open('/root/.openclaw/workspace/secrets.env', 'r') as f:
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for line in f:
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if line.startswith('PG_ONLINE_PASSWORD='):
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DB_PASSWORD = line.strip().split('=', 1)[1].strip('"\'')
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break
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# 数据库连接
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conn = psycopg2.connect(
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host='bj-postgres-16pob4sg.sql.tencentcdb.com',
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port=28591,
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user='ai_member',
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password=DB_PASSWORD,
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database='vala_bi'
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)
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cur = conn.cursor()
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# 查询表结构
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cur.execute("SELECT column_name FROM information_schema.columns WHERE table_name = 'bi_vala_seasonal_ticket'")
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columns = cur.fetchall()
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print("bi_vala_seasonal_ticket表字段：")
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for col in columns:
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print(col[0])
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cur.close()
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conn.close()
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30
scripts/check_tables.py
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30
scripts/check_tables.py
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import psycopg2
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# 读取密码
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DB_PASSWORD = ""
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with open('/root/.openclaw/workspace/secrets.env', 'r') as f:
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for line in f:
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if line.startswith('PG_ONLINE_PASSWORD='):
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DB_PASSWORD = line.strip().split('=', 1)[1].strip('"\'')
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break
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# 数据库连接
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conn = psycopg2.connect(
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host='bj-postgres-16pob4sg.sql.tencentcdb.com',
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port=28591,
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user='ai_member',
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password=DB_PASSWORD,
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database='vala_bi'
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)
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cur = conn.cursor()
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# 查询所有表
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cur.execute("SELECT table_name FROM information_schema.tables WHERE table_schema = 'public'")
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tables = cur.fetchall()
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print("vala_bi库public模式下的表：")
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for table in tables:
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if 'seasonal' in table[0] or 'ticket' in table[0]:
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print(f"→ {table[0]}")
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cur.close()
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conn.close()
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47
scripts/find_202602_order_202603_refund.py
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47
scripts/find_202602_order_202603_refund.py
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import psycopg2
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import pandas as pd
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# 读取密码
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DB_PASSWORD = ""
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with open('/root/.openclaw/workspace/secrets.env', 'r') as f:
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for line in f:
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if line.startswith('PG_ONLINE_PASSWORD='):
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DB_PASSWORD = line.strip().split('=', 1)[1].strip('"\'')
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break
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# 数据库连接
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conn = psycopg2.connect(
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host='bj-postgres-16pob4sg.sql.tencentcdb.com',
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port=28591,
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user='ai_member',
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password=DB_PASSWORD,
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database='vala_bi'
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)
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# 查询2月下单3月退费的订单
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sql = """
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SELECT
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o.out_trade_no AS order_no,
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o.created_at AS order_create_time,
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o.pay_amount_int / 100 AS pay_amount,
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o.order_status,
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r.updated_at AS refund_time,
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CAST(r.refund_amount AS NUMERIC) / 100 AS refund_amount,
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CASE r.refund_type WHEN 1 THEN '仅退款' WHEN 2 THEN '全额退货退款' WHEN 3 THEN '部分退货退款' END AS refund_type
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FROM bi_vala_order o
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JOIN bi_refund_order r ON o.out_trade_no = r.trade_no
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WHERE
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o.created_at BETWEEN '2026-02-01 00:00:00' AND '2026-02-28 23:59:59'
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AND r.updated_at BETWEEN '2026-03-01 00:00:00' AND '2026-03-31 23:59:59'
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AND r.status = 3
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"""
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df = pd.read_sql(sql, conn)
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conn.close()
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print("🔍 2026年2月下单、2026年3月退费的订单列表：")
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print(f"共找到{len(df)}条符合条件的记录：")
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if not df.empty:
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print(df.to_string(index=False))
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else:
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print("无符合条件的记录")
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47
scripts/find_history_order_202603_refund.py
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47
scripts/find_history_order_202603_refund.py
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import psycopg2
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import pandas as pd
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# 读取密码
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DB_PASSWORD = ""
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with open('/root/.openclaw/workspace/secrets.env', 'r') as f:
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for line in f:
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if line.startswith('PG_ONLINE_PASSWORD='):
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DB_PASSWORD = line.strip().split('=', 1)[1].strip('"\'')
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break
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# 数据库连接
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conn = psycopg2.connect(
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host='bj-postgres-16pob4sg.sql.tencentcdb.com',
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port=28591,
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user='ai_member',
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password=DB_PASSWORD,
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database='vala_bi'
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)
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# 查询2025年9月到2026年2月下单3月退费的订单
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sql = """
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SELECT
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o.out_trade_no AS order_no,
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DATE(o.created_at) AS order_create_date,
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o.pay_amount_int / 100 AS pay_amount,
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o.order_status,
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DATE(r.updated_at) AS refund_date,
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CAST(r.refund_amount AS NUMERIC) / 100 AS refund_amount,
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CASE r.refund_type WHEN 1 THEN '仅退款' WHEN 2 THEN '全额退货退款' WHEN 3 THEN '部分退货退款' END AS refund_type
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FROM bi_vala_order o
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JOIN bi_refund_order r ON o.out_trade_no = r.trade_no
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WHERE
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o.created_at BETWEEN '2025-09-01 00:00:00' AND '2026-02-28 23:59:59'
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AND r.updated_at BETWEEN '2026-03-01 00:00:00' AND '2026-03-31 23:59:59'
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AND r.status = 3
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"""
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df = pd.read_sql(sql, conn)
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conn.close()
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print("🔍 2025年9月-2026年2月下单、2026年3月退费的订单列表：")
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print(f"共找到{len(df)}条符合条件的记录：")
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if not df.empty:
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print(df.to_string(index=False))
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else:
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print("无符合条件的记录")
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51
scripts/query_order_all_refund.py
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51
scripts/query_order_all_refund.py
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import psycopg2
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import pandas as pd
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# 读取密码
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DB_PASSWORD = ""
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with open('/root/.openclaw/workspace/secrets.env', 'r') as f:
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for line in f:
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if line.startswith('PG_ONLINE_PASSWORD='):
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DB_PASSWORD = line.strip().split('=', 1)[1].strip('"\'')
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break
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# 数据库连接
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conn = psycopg2.connect(
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host='bj-postgres-16pob4sg.sql.tencentcdb.com',
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port=28591,
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user='ai_member',
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password=DB_PASSWORD,
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database='vala_bi'
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)
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# 查询指定订单的所有退费记录（不限制状态）
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order_no = "dd202602111013471770776027390252"
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sql = """
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SELECT
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r.id AS refund_id,
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r.trade_no AS order_no,
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r.created_at AS refund_apply_time,
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r.updated_at AS refund_update_time,
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CAST(r.refund_amount AS NUMERIC) / 100 AS refund_amount,
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r.status AS refund_status_code,
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CASE r.status
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WHEN 0 THEN '待审核'
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WHEN 1 THEN '审核通过'
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WHEN 2 THEN '审核拒绝'
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WHEN 3 THEN '退款成功'
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WHEN 4 THEN '退款失败'
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ELSE '其他状态'
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END AS refund_status_name,
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CASE r.refund_type WHEN 1 THEN '仅退款' WHEN 2 THEN '全额退货退款' WHEN 3 THEN '部分退货退款' END AS refund_type
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FROM bi_refund_order r
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WHERE r.trade_no = %s
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"""
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df = pd.read_sql(sql, conn, params=(order_no,))
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conn.close()
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if df.empty:
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print(f"订单号 {order_no} 无任何退费申请记录")
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else:
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print(f"🔍 订单 {order_no} 的所有退费记录：")
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print(df.to_string(index=False))
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53
scripts/query_order_refund_time.py
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53
scripts/query_order_refund_time.py
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import psycopg2
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import pandas as pd
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# 读取密码
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DB_PASSWORD = ""
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with open('/root/.openclaw/workspace/secrets.env', 'r') as f:
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for line in f:
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if line.startswith('PG_ONLINE_PASSWORD='):
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DB_PASSWORD = line.strip().split('=', 1)[1].strip('"\'')
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break
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# 数据库连接
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conn = psycopg2.connect(
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host='bj-postgres-16pob4sg.sql.tencentcdb.com',
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port=28591,
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user='ai_member',
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password=DB_PASSWORD,
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database='vala_bi'
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)
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# 查询指定订单
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order_no = "dd202602111013471770776027390252"
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sql = """
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SELECT
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o.out_trade_no AS order_no,
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o.created_at AS order_create_time,
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o.pay_amount_int / 100 AS pay_amount,
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o.order_status,
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r.updated_at AS refund_finish_time,
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CAST(r.refund_amount AS NUMERIC) / 100 AS refund_amount,
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CASE r.refund_type WHEN 1 THEN '仅退款' WHEN 2 THEN '全额退货退款' WHEN 3 THEN '部分退货退款' END AS refund_type
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FROM bi_vala_order o
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LEFT JOIN bi_refund_order r ON o.out_trade_no = r.trade_no AND r.status = 3
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WHERE o.out_trade_no = %s
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"""
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df = pd.read_sql(sql, conn, params=(order_no,))
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conn.close()
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if df.empty:
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print(f"未找到订单号为 {order_no} 的记录")
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else:
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row = df.iloc[0]
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print(f"订单号：{row['order_no']}")
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print(f"下单时间：{row['order_create_time'].strftime('%Y-%m-%d %H:%M:%S') if pd.notna(row['order_create_time']) else '无'}")
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print(f"订单金额：{row['pay_amount']}元")
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print(f"订单状态：{row['order_status']}")
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if pd.notna(row['refund_finish_time']):
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print(f"退款完成时间：{row['refund_finish_time'].strftime('%Y-%m-%d %H:%M:%S')}")
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print(f"退款金额：{row['refund_amount']}元")
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print(f"退款类型：{row['refund_type']}")
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else:
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print("该订单无退费记录")
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371
scripts/vala_order_amortization_stat_202603.py
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371
scripts/vala_order_amortization_stat_202603.py
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import os
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import pandas as pd
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import psycopg2
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from datetime import datetime, timedelta
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# 手动读取secrets.env获取数据库密码
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DB_PASSWORD = ""
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with open('/root/.openclaw/workspace/secrets.env', 'r') as f:
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for line in f:
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if line.startswith('PG_ONLINE_PASSWORD='):
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DB_PASSWORD = line.strip().split('=', 1)[1].strip('"\'')
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break
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# 数据库连接配置
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DB_CONFIG = {
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'host': 'bj-postgres-16pob4sg.sql.tencentcdb.com',
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'port': 28591,
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'user': 'ai_member',
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'password': DB_PASSWORD,
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'database': 'vala_bi'
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}
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# 账期参数
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ACCOUNT_START = datetime(2026, 3, 1).date()
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ACCOUNT_END = datetime(2026, 3, 31).date()
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def get_db_connection():
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"""获取数据库连接"""
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return psycopg2.connect(**DB_CONFIG)
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def query_order_base():
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"""查询符合条件的订单基础信息"""
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sql = """
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SELECT
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o.id AS order_id,
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o.out_trade_no AS order_no,
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o.pay_amount_int / 100 AS pay_amount,
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o.created_at,
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DATE(o.created_at) + INTERVAL '7 day' AS amortization_start_date,
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o.order_status,
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CASE WHEN DATE(o.created_at) < '2026-05-01' THEN 0.01 ELSE 0.06 END AS tax_rate,
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(o.pay_amount_int / 100) * CASE WHEN DATE(o.created_at) < '2026-05-01' THEN 0.01 ELSE 0.06 END AS tax_amount,
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(o.pay_amount_int / 100) * (1 - CASE WHEN DATE(o.created_at) < '2026-05-01' THEN 0.01 ELSE 0.06 END) AS after_tax_amount
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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
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WHERE
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o.created_at >= '2025-09-01'
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AND o.order_status IN (3,4)
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AND o.pay_amount_int >= 1000
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AND a.status = 1
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"""
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conn = get_db_connection()
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df = pd.read_sql(sql, conn)
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conn.close()
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# 处理日期格式
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df['created_at'] = pd.to_datetime(df['created_at']).dt.date
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df['amortization_start_date'] = pd.to_datetime(df['amortization_start_date']).dt.date
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# 标记订单是否为账期内新增
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df['is_new_in_account'] = df['created_at'].between(ACCOUNT_START, ACCOUNT_END)
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# 标记是否为正式订单（截止账期结束日已过试用期）
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df['is_formal'] = df['amortization_start_date'] <= ACCOUNT_END
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return df
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def query_order_cycle(order_nos):
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"""查询订单总均摊周期"""
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if not order_nos:
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return pd.DataFrame(columns=['order_no', 'total_cycle_days'])
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order_no_str = "', '".join(order_nos)
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sql = f"""
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SELECT
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out_trade_no AS order_no,
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COUNT(DISTINCT id) * 90 AS total_cycle_days
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FROM bi_vala_seasonal_ticket
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WHERE status != -1 AND out_trade_no IN ('{order_no_str}')
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GROUP BY out_trade_no
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"""
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conn = get_db_connection()
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df = pd.read_sql(sql, conn)
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conn.close()
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return df
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def query_refund_records():
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"""查询账期内的退费记录"""
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sql = """
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SELECT
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r.out_trade_no AS order_no,
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CAST(r.refund_amount AS NUMERIC) / 100.0 AS refund_amount,
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r.refund_type,
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DATE(r.updated_at) AS refund_date
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FROM bi_refund_order r
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WHERE
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r.status = 3
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AND r.updated_at BETWEEN %s AND %s
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"""
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conn = get_db_connection()
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df = pd.read_sql(sql, conn, params=(ACCOUNT_START, ACCOUNT_END))
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conn.close()
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return df
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def calculate_amortization_days(amort_start, total_cycle, period_start, period_end):
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"""计算账期内的均摊天数"""
|
||||
if pd.isna(amort_start) or pd.isna(total_cycle) or total_cycle <= 0:
|
||||
return 0
|
||||
amort_end = amort_start + timedelta(days=total_cycle - 1)
|
||||
# 计算实际均摊区间和账期的交集
|
||||
start = max(amort_start, period_start)
|
||||
end = min(amort_end, period_end)
|
||||
if start > end:
|
||||
return 0
|
||||
return (end - start).days + 1
|
||||
|
||||
def main():
|
||||
print("开始计算2026年3月订单均摊数据...")
|
||||
|
||||
# 1. 获取订单基础数据
|
||||
order_base_df = query_order_base()
|
||||
if order_base_df.empty:
|
||||
print("无符合条件的订单数据")
|
||||
return
|
||||
|
||||
# 2. 获取退费记录
|
||||
refund_df = query_refund_records()
|
||||
# 处理重复订单退费记录，保留最新的一条
|
||||
if not refund_df.empty:
|
||||
refund_df = refund_df.sort_values('refund_date', ascending=False).drop_duplicates('order_no', keep='first')
|
||||
# 转成字典方便查询
|
||||
refund_dict = refund_df.set_index('order_no').to_dict('index')
|
||||
|
||||
# 新增规则：过滤账期内下单且账期内全额退费的订单，直接排除
|
||||
# 账期内下单且账期内部分退费的订单，直接计算剩余金额，不需要冲销
|
||||
exclude_order_nos = []
|
||||
for _, order_row in order_base_df.iterrows():
|
||||
order_no = order_row['order_no']
|
||||
is_new_in_account = order_row['is_new_in_account']
|
||||
if order_no in refund_dict and is_new_in_account:
|
||||
refund_type = refund_dict[order_no]['refund_type']
|
||||
if refund_type == 2:
|
||||
# 账期内下单+账期内全额退费：直接排除
|
||||
exclude_order_nos.append(order_no)
|
||||
elif refund_type == 3:
|
||||
# 账期内下单+账期内部分退费：直接更新税后金额为剩余金额
|
||||
refund_amount = refund_dict[order_no]['refund_amount']
|
||||
order_base_df.loc[order_base_df['order_no'] == order_no, 'after_tax_amount'] = (order_row['pay_amount'] - refund_amount) * (1 - order_row['tax_rate'])
|
||||
order_base_df.loc[order_base_df['order_no'] == order_no, 'tax_amount'] = (order_row['pay_amount'] - refund_amount) * order_row['tax_rate']
|
||||
|
||||
# 剔除全额退费的订单
|
||||
order_base_df = order_base_df[~order_base_df['order_no'].isin(exclude_order_nos)].reset_index(drop=True)
|
||||
|
||||
# 3. 获取订单均摊周期
|
||||
order_cycle_df = query_order_cycle(order_base_df['order_no'].tolist())
|
||||
order_df = pd.merge(order_base_df, order_cycle_df, on='order_no', how='left')
|
||||
order_df['total_cycle_days'] = order_df['total_cycle_days'].fillna(0)
|
||||
|
||||
# 4. 计算基础指标
|
||||
# 订单类指标
|
||||
total_orders = order_df[order_df['is_new_in_account']].shape[0]
|
||||
formal_orders = order_df[(order_df['is_new_in_account']) & (order_df['is_formal'])].shape[0]
|
||||
trial_orders = total_orders - formal_orders
|
||||
|
||||
# 计算冲销前税费
|
||||
pre_writeoff_tax = order_df[(order_df['is_new_in_account']) & (order_df['is_formal'])]['tax_amount'].sum()
|
||||
|
||||
# 计算冲销税费
|
||||
writeoff_tax = 0
|
||||
# 计算冲销均摊金额
|
||||
writeoff_amort = 0
|
||||
# 计算补充税费和补充均摊金额
|
||||
supplement_tax = 0
|
||||
supplement_amort = 0
|
||||
|
||||
# 处理退费订单：仅处理历史订单（非账期内下单的订单），账期内订单已提前处理
|
||||
for _, refund_row in refund_df.iterrows():
|
||||
order_no = refund_row['order_no']
|
||||
refund_type = refund_row['refund_type']
|
||||
refund_amount = refund_row['refund_amount']
|
||||
order_info = order_df[order_df['order_no'] == order_no]
|
||||
if order_info.empty:
|
||||
continue
|
||||
order_info = order_info.iloc[0]
|
||||
# 跳过账期内下单的订单，已提前处理
|
||||
if order_info['is_new_in_account']:
|
||||
continue
|
||||
|
||||
# 累加冲销税费
|
||||
writeoff_tax += order_info['pay_amount'] * order_info['tax_rate']
|
||||
|
||||
# 计算该订单历史均摊金额（2025-09-01至2026-02-28的均摊）
|
||||
amort_start = order_info['amortization_start_date']
|
||||
total_cycle = order_info['total_cycle_days']
|
||||
history_amort_days = calculate_amortization_days(amort_start, total_cycle, datetime(2025,9,1).date(), datetime(2026,2,28).date())
|
||||
daily_amort = order_info['after_tax_amount'] / total_cycle if total_cycle > 0 else 0
|
||||
history_amort_amount = history_amort_days * daily_amort
|
||||
writeoff_amort += history_amort_amount
|
||||
|
||||
# 部分退费处理
|
||||
if refund_type == 3:
|
||||
remaining_amount = order_info['pay_amount'] - refund_amount
|
||||
remaining_after_tax = remaining_amount * (1 - order_info['tax_rate'])
|
||||
# 补充税费
|
||||
supplement_tax += remaining_amount * order_info['tax_rate']
|
||||
# 补充均摊：从转正日到账期最后一日的均摊，应用最后一天补差规则
|
||||
days = calculate_amortization_days(amort_start, total_cycle, amort_start, ACCOUNT_END)
|
||||
daily_amort_partial = remaining_after_tax / total_cycle if total_cycle > 0 else 0
|
||||
if total_cycle > 0 and days >= total_cycle:
|
||||
supplement_amort += round(remaining_after_tax, 2)
|
||||
else:
|
||||
supplement_amort += round(days * daily_amort_partial, 2)
|
||||
|
||||
# 计算冲销后税费
|
||||
after_writeoff_tax = pre_writeoff_tax - writeoff_tax + supplement_tax
|
||||
|
||||
# 计算冲销前均摊金额
|
||||
pre_writeoff_amort = 0
|
||||
# 历史未退费订单的账期均摊（排除历史退费订单）
|
||||
refund_order_nos = list(refund_dict.keys())
|
||||
for _, order_row in order_df[~order_df['order_no'].isin(refund_order_nos)].iterrows():
|
||||
if not order_row['is_formal'] or order_row['total_cycle_days'] <= 0:
|
||||
continue
|
||||
amort_start = order_row['amortization_start_date']
|
||||
days = calculate_amortization_days(amort_start, order_row['total_cycle_days'], ACCOUNT_START, ACCOUNT_END)
|
||||
daily_amort = order_row['after_tax_amount'] / order_row['total_cycle_days']
|
||||
pre_writeoff_amort += days * daily_amort
|
||||
# 账期内正式订单的账期均摊
|
||||
for _, order_row in order_df[order_df['is_new_in_account'] & order_df['is_formal']].iterrows():
|
||||
if order_row['total_cycle_days'] <= 0:
|
||||
continue
|
||||
amort_start = order_row['amortization_start_date']
|
||||
days = calculate_amortization_days(amort_start, order_row['total_cycle_days'], ACCOUNT_START, ACCOUNT_END)
|
||||
daily_amort = order_row['after_tax_amount'] / order_row['total_cycle_days']
|
||||
pre_writeoff_amort += days * daily_amort
|
||||
|
||||
# 计算冲销后均摊金额
|
||||
after_writeoff_amort = pre_writeoff_amort - writeoff_amort + supplement_amort
|
||||
|
||||
# 5. 生成汇总表
|
||||
summary_df = pd.DataFrame([{
|
||||
'指标': '订单数',
|
||||
'数值': total_orders
|
||||
}, {
|
||||
'指标': '正式订单数',
|
||||
'数值': formal_orders
|
||||
}, {
|
||||
'指标': '试用订单数',
|
||||
'数值': trial_orders
|
||||
}, {
|
||||
'指标': '冲销前税费（元）',
|
||||
'数值': round(pre_writeoff_tax, 2)
|
||||
}, {
|
||||
'指标': '冲销税费（元）',
|
||||
'数值': round(writeoff_tax, 2)
|
||||
}, {
|
||||
'指标': '补充税费（元）',
|
||||
'数值': round(supplement_tax, 2)
|
||||
}, {
|
||||
'指标': '冲销后税费（元）',
|
||||
'数值': round(after_writeoff_tax, 2)
|
||||
}, {
|
||||
'指标': '冲销前均摊金额（税后，元）',
|
||||
'数值': round(pre_writeoff_amort, 2)
|
||||
}, {
|
||||
'指标': '冲销均摊金额（税后，元）',
|
||||
'数值': round(writeoff_amort, 2)
|
||||
}, {
|
||||
'指标': '补充均摊金额（税后，元）',
|
||||
'数值': round(supplement_amort, 2)
|
||||
}, {
|
||||
'指标': '冲销后均摊金额（税后净收入，元）',
|
||||
'数值': round(after_writeoff_amort, 2)
|
||||
}])
|
||||
|
||||
# 6. 生成订单明细表
|
||||
order_detail_list = []
|
||||
for _, order_row in order_df.iterrows():
|
||||
# 计算历史均摊金额（2025-09-01至2026-02-28）
|
||||
amort_start = order_row['amortization_start_date']
|
||||
total_cycle = order_row['total_cycle_days']
|
||||
history_days = calculate_amortization_days(amort_start, total_cycle, datetime(2025,9,1).date(), datetime(2026,2,28).date())
|
||||
daily_amort = order_row['after_tax_amount'] / total_cycle if total_cycle > 0 else 0
|
||||
# 周期最后一天补差规则
|
||||
if total_cycle > 0 and history_days >= total_cycle:
|
||||
history_amort = round(order_row['after_tax_amount'], 2)
|
||||
else:
|
||||
history_amort = round(history_days * daily_amort, 2)
|
||||
|
||||
# 计算账期均摊金额
|
||||
account_days = calculate_amortization_days(amort_start, total_cycle, ACCOUNT_START, ACCOUNT_END)
|
||||
total_used_days = history_days + account_days
|
||||
# 周期最后一天补差规则
|
||||
if total_cycle > 0 and total_used_days >= total_cycle:
|
||||
# 如果累计天数超过总周期，账期均摊=总金额-历史均摊
|
||||
account_amort = round(order_row['after_tax_amount'] - history_amort, 2)
|
||||
if account_amort < 0:
|
||||
account_amort = 0
|
||||
else:
|
||||
account_amort = round(account_days * daily_amort, 2)
|
||||
|
||||
# 未确认收入
|
||||
total_amort = history_amort + account_amort
|
||||
unconfirmed_income = round(order_row['after_tax_amount'] - total_amort, 2)
|
||||
if unconfirmed_income < 0:
|
||||
unconfirmed_income = 0
|
||||
|
||||
# 剩余周期
|
||||
used_days = history_days + account_days
|
||||
remaining_cycle = max(0, total_cycle - used_days)
|
||||
|
||||
# 新增字段：下单时间
|
||||
create_time = order_row['created_at'].strftime('%Y-%m-%d')
|
||||
|
||||
# 新增字段：退费时间
|
||||
refund_time = ""
|
||||
refund_type = None
|
||||
if order_row['order_no'] in refund_dict:
|
||||
refund_time = refund_dict[order_row['order_no']]['refund_date'].strftime('%Y-%m-%d')
|
||||
refund_type = refund_dict[order_row['order_no']]['refund_type']
|
||||
|
||||
# 新增字段：订单分类
|
||||
order_category = ""
|
||||
if refund_type is not None:
|
||||
if refund_type == 2:
|
||||
order_category = "历史新增全额退费订单"
|
||||
elif refund_type == 3:
|
||||
order_category = "历史新增部分退费订单"
|
||||
else:
|
||||
if order_row['is_new_in_account']:
|
||||
if order_row['is_formal']:
|
||||
order_category = "账期新增正式订单"
|
||||
else:
|
||||
order_category = "账期新增试用订单"
|
||||
else:
|
||||
order_category = "历史正式订单"
|
||||
|
||||
order_detail_list.append({
|
||||
'订单号': order_row['order_no'],
|
||||
'下单时间': create_time,
|
||||
'退费时间': refund_time,
|
||||
'订单分类': order_category,
|
||||
'订单金额（元）': round(order_row['pay_amount'], 2),
|
||||
'税率': f"{order_row['tax_rate'] * 100}%",
|
||||
'税额（元）': round(order_row['tax_amount'], 2),
|
||||
'税后金额（元）': round(order_row['after_tax_amount'], 2),
|
||||
'总均摊周期（天）': int(total_cycle),
|
||||
'已均摊天数（天）': used_days,
|
||||
'历史均摊金额（元）': history_amort,
|
||||
'账期均摊金额（元）': account_amort,
|
||||
'未确认收入（元）': unconfirmed_income,
|
||||
'剩余周期（天）': remaining_cycle
|
||||
})
|
||||
detail_df = pd.DataFrame(order_detail_list)
|
||||
|
||||
# 7. 写入Excel
|
||||
output_path = f"/root/.openclaw/workspace/output/订单均摊结算报表_{ACCOUNT_START}_{ACCOUNT_END}.xlsx"
|
||||
with pd.ExcelWriter(output_path) as writer:
|
||||
summary_df.to_excel(writer, sheet_name='汇总表', index=False)
|
||||
detail_df.to_excel(writer, sheet_name='订单明细', index=False)
|
||||
|
||||
print(f"报表生成完成，保存路径：{output_path}")
|
||||
print("\n📊 账期2026-03-01至2026-03-31均摊结算结果：")
|
||||
print(f"总订单数：{total_orders}单")
|
||||
print(f"正式订单数：{formal_orders}单")
|
||||
print(f"试用订单数：{trial_orders}单")
|
||||
print(f"冲销后税费：{round(after_writeoff_tax, 2)}元")
|
||||
print(f"冲销后均摊金额（税后净收入）：{round(after_writeoff_amort, 2)}元")
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
143
skills/vala-order-amortization-stat/SKILL.md
Normal file
143
skills/vala-order-amortization-stat/SKILL.md
Normal file
@ -0,0 +1,143 @@
|
||||
# SKILL.md - vala-order-amortization-stat 订单均摊结算统计技能
|
||||
## 技能描述
|
||||
用于统计指定账期内的订单均摊收入、退费冲销，按天计算均摊金额，支持部分退费场景的剩余金额和周期自动计算。
|
||||
## 触发场景
|
||||
当用户提到以下关键词组合时激活本技能：
|
||||
1. 订单均摊、按天均摊、收入均摊
|
||||
2. 账期结算、月度结算、季度结算
|
||||
3. 退费冲销、部分退款均摊
|
||||
## 前置依赖
|
||||
1. 已连接线上PostgreSQL数据库 vala_bi 库
|
||||
2. 依赖表：
|
||||
- bi_vala_order：订单主表
|
||||
- bi_refund_order：退费订单表
|
||||
- bi_vala_seasonal_ticket：季卡周期表
|
||||
- bi_vala_app_account：用户账户表（用于剔除测试账号）
|
||||
3. 表关联规则：
|
||||
- bi_vala_order.trade_no ↔ bi_refund_order.trade_no 关联
|
||||
- bi_vala_order.out_trade_no ↔ bi_refund_order.out_trade_no 关联
|
||||
## 操作流程
|
||||
### 步骤1：确认核心参数
|
||||
执行前必须向用户确认以下参数：
|
||||
- 账期起始日期（格式：YYYY-MM-DD）
|
||||
- 账期结束日期（格式：YYYY-MM-DD）
|
||||
- 默认输出维度：账期整体汇总，无需按天/周/月拆分，无需分渠道统计
|
||||
### 步骤2：数据过滤规则
|
||||
1. 订单范围：
|
||||
- 2025-09-01 至 账期结束日 内创建的所有订单
|
||||
- bi_vala_order.status IN (3,4)（已完成、已退款订单）
|
||||
- 订单实际支付金额≥10元：bi_vala_order.pay_amount_int ≥ 1000（单位：分）
|
||||
- 关联bi_vala_app_account表，仅保留bi_vala_app_account.status = 1的非测试账号订单
|
||||
2. 退费范围：
|
||||
- 退费完成时间落在账期内的所有退款成功记录，判定条件：bi_refund_order.updated_at（退款处理完成时间）在账期起止时间范围内
|
||||
- bi_refund_order.status = 3（退款处理完成）
|
||||
3. 账期前退费订单处理规则：
|
||||
- 退费完成时间在账期起始日之前的订单，不会纳入本账期的冲销逻辑：
|
||||
- 全额退费订单：冲销动作已在退费发生的对应账期执行完毕，本账期完全不统计该订单的任何数据
|
||||
- 部分退费订单：冲销动作、剩余金额/剩余周期调整已在退费发生的对应账期完成，本账期仅按调整后的剩余金额计算均摊，不产生额外冲销金额
|
||||
### 步骤3：核心计算逻辑
|
||||
#### 3.1 周期计算
|
||||
- 每个订单的总均摊周期 = bi_vala_seasonal_ticket中同一order_no下status != -1的不同id数量 × 90天
|
||||
- 转正日期规则：试用期7天，包含下单日：
|
||||
- 均摊起始日（转正日期）= 订单下单日 + 7天，下单日取bi_vala_order.created_at的日期部分
|
||||
- 示例：4月22日下单，4月29日00:00:00为转正日，即均摊起始日
|
||||
- 税率规则：
|
||||
- 订单下单时间在2026年5月1日之前：税率1%
|
||||
- 订单下单时间在2026年5月1日及之后：税率6%
|
||||
- 订单税后金额 = (bi_vala_order.pay_amount_int / 100) × (1 - 税率)（单位：元）
|
||||
- 订单税费金额 = (bi_vala_order.pay_amount_int / 100) × 税率（单位：元）
|
||||
- **均摊规则更新**：所有均摊计算均基于税后金额进行，含税金额和税费单独统计
|
||||
- 日均摊金额（税后）= 订单税后金额 / 总均摊周期
|
||||
- 🔹 周期最后一天补差规则：订单均摊周期的最后一天，均摊金额不按日均摊计算，采用补差方式确保总额完全匹配：
|
||||
- 正常订单：最后一天均摊金额 = 订单税后总金额 - 前（总均摊周期-1）天累计已均摊金额
|
||||
- 部分退费订单：最后一天均摊金额 = 订单剩余税后金额 - 剩余均摊周期前（剩余天数-1）天累计已均摊金额
|
||||
避免浮点精度导致的金额尾差
|
||||
#### 3.2 退费场景计算
|
||||
所有退费冲销金额均为税后金额，税费同步对应冲销
|
||||
1. **所有退费订单（全额/部分）通用计算**：
|
||||
- 历史退费订单冲销均摊金额：从2026年9月1日起至账期起始日之前，该订单已产生的全部税后均摊金额（统一显示为负数，用于冲销）
|
||||
- 历史退费订单冲销税费金额：上述历史均摊金额对应的税费（统一显示为负数，用于冲销）
|
||||
2. **全额退费（bi_refund_order.refund_type = 2）**：无需额外计算补充均摊，仅执行上述通用冲销逻辑
|
||||
3. **部分退费（bi_refund_order.refund_type = 3）**：在通用冲销逻辑基础上，额外计算：
|
||||
- 历史部分退费订单补充均摊金额：部分退费后剩余的待均摊税后金额，在本账期内产生的均摊收入
|
||||
- 历史部分退费订单补充税费金额：上述补充均摊金额对应的税费
|
||||
#### 3.3 账期内收入计算
|
||||
账期内总收入 = 账期内所有正常订单的日均摊金额总和 + 账期内所有退费冲销金额总和
|
||||
## 核心SQL模板
|
||||
```sql
|
||||
-- 步骤1：获取所有符合条件的订单基础信息
|
||||
WITH order_base AS (
|
||||
SELECT
|
||||
o.id AS order_id,
|
||||
o.order_no,
|
||||
o.pay_amount_int / 100 AS pay_amount,
|
||||
-- 计算税率、税费、税后金额
|
||||
CASE WHEN DATE(o.created_at) < '2026-05-01' THEN 0.01 ELSE 0.06 END AS tax_rate,
|
||||
(o.pay_amount_int / 100) * CASE WHEN DATE(o.created_at) < '2026-05-01' THEN 0.01 ELSE 0.06 END AS tax_amount,
|
||||
(o.pay_amount_int / 100) * (1 - CASE WHEN DATE(o.created_at) < '2026-05-01' THEN 0.01 ELSE 0.06 END) AS after_tax_amount,
|
||||
DATE_ADD(DATE(o.created_at), INTERVAL 7 DAY) AS amortization_start_date,
|
||||
o.status AS order_status,
|
||||
a.id AS account_id,
|
||||
o.key_from,
|
||||
o.sale_channel
|
||||
FROM bi_vala_order o
|
||||
JOIN bi_vala_app_account a ON o.account_id = a.id
|
||||
WHERE
|
||||
o.created_at >= '2025-09-01'
|
||||
AND o.status IN (3,4)
|
||||
AND o.pay_amount_int >= 1000
|
||||
AND a.status = 1
|
||||
),
|
||||
-- 步骤2：计算每个订单的总均摊周期
|
||||
order_cycle AS (
|
||||
SELECT
|
||||
order_no,
|
||||
COUNT(DISTINCT id) * 90 AS total_cycle_days
|
||||
FROM bi_vala_seasonal_ticket
|
||||
WHERE status != -1
|
||||
GROUP BY order_no
|
||||
),
|
||||
-- 步骤3：获取账期内的退费记录
|
||||
refund_records AS (
|
||||
SELECT
|
||||
r.out_trade_no AS order_no,
|
||||
CAST(r.refund_amount AS NUMERIC) / 100 AS refund_amount,
|
||||
r.refund_type,
|
||||
DATE(r.updated_at) AS refund_date
|
||||
FROM bi_refund_order r
|
||||
JOIN order_base o ON r.out_trade_no = o.order_no
|
||||
WHERE
|
||||
r.status = 3
|
||||
AND r.updated_at BETWEEN '${账期起始日}' AND '${账期结束日}'
|
||||
)
|
||||
-- 后续按需求聚合维度计算日均摊金额和冲销金额
|
||||
```
|
||||
## 输出格式
|
||||
1. 优先输出Excel报表，存放于output/目录下，命名格式：`订单均摊结算报表_${账期起始日}_${账期结束日}.xlsx`
|
||||
2. 报表包含以下Sheet：
|
||||
- 汇总表：订单数、正式订单数、试用订单数、冲销前税费、冲销税费、补充税费、冲销后税费、冲销前均摊金额、冲销均摊金额、补充均摊金额、冲销后均摊金额
|
||||
- 订单明细：订单号、订单金额、税率、税额、税后金额、总均摊周期、已均摊天数、历史均摊金额、账期均摊金额、未确认收入、剩余周期
|
||||
3. 文字回复核心指标：
|
||||
> 📊 账期${账期起始日}至${账期结束日}均摊结算结果：
|
||||
> 总订单数：XXX单
|
||||
> 正式订单数：XXX单
|
||||
> 试用订单数：XXX单
|
||||
> 冲销后税费：XXX元
|
||||
> 冲销后均摊金额（税后净收入）：XXX元
|
||||
## 汇总指标计算逻辑（所有均摊金额均为税后金额）
|
||||
1. **订单数**：账期内（下单日落在账期起止时间范围内）新增的所有符合条件的订单总数量
|
||||
2. **正式订单数**：账期内新增的订单中，截止账期结束日已过7天试用期（下单日+7天 ≤ 账期结束日）的订单数量，仅正式订单开始参与均摊计算
|
||||
3. **试用订单数**：账期内新增的订单中，截止账期结束日仍处于7天试用期内（下单日+7天 > 账期结束日）的订单数量，试用订单未开始均摊，不参与金额计算
|
||||
4. **冲销前税费**：账期内所有正式订单的含税订单总金额 × 各订单对应税率 的总和
|
||||
5. **冲销税费**：本账期内发生退费的所有订单的含税订单总金额 × 各订单对应税率 的总和（正数展示，计算时扣除）
|
||||
6. **补充税费**：本账期内发生部分退费的订单，退费后剩余的含税订单金额 × 各订单对应税率 的总和，其中：部分退费订单剩余含税金额 = 原订单含税金额 - 退费含税金额
|
||||
7. **冲销后税费**：账期内最终确认的总税费，计算公式：`冲销后税费 = 冲销前税费 - 冲销税费 + 补充税费`
|
||||
8. **冲销前均摊金额（税后）**：历史未退费订单 + 账期内正式订单 在本账期内产生的税后均摊收入总和
|
||||
9. **冲销均摊金额（税后）**：本账期内发生退费的所有订单，需要冲销的历史均摊金额总和（正数展示，计算时扣除）
|
||||
10. **补充均摊金额（税后）**：本账期内发生部分退费的订单，从转正日起至账期最后一日产生的税后均摊金额总和
|
||||
11. **冲销后均摊金额（税后）**：账期内最终确认的税后净收入，计算公式：`冲销后均摊金额 = 冲销前均摊金额 - 冲销均摊金额 + 补充均摊金额`
|
||||
## 注意事项
|
||||
1. 所有金额保留2位小数，百分比保留1位小数
|
||||
2. 部分退费场景需确保bi_vala_seasonal_ticket中对应退费部分的status已更新为-1
|
||||
3. 自动剔除测试账号，无需额外过滤
|
||||
4. 冲销金额统一显示为负数
|
||||
Loading…
Reference in New Issue
Block a user