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#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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期货结算单数据处理脚本
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读取期货结算单Excel，提取期货和期权交易数据，计算盈亏和持仓，合并输出
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"""
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import os
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import glob
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import re
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from datetime import datetime
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from collections import defaultdict
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import xlrd
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import pandas as pd
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def find_header(sheet, keywords):
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"""
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动态识别表头行
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:param sheet: xlrd sheet对象
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:param keywords: 关键词列表，如["合约", "品种合约"]
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:return: 表头行索引
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"""
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for row_idx in range(min(20, sheet.nrows)): # 只扫描前20行
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row_values = [str(sheet.cell_value(row_idx, col_idx)).strip()
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for col_idx in range(sheet.ncols)]
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row_text = ' '.join(row_values)
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# 检查是否包含关键词
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has_keyword = any(kw in row_text for kw in keywords)
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# 检查是否包含辅助关键词
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has_aux = any(aux in row_text for aux in ["买/卖", "成交价", "权利金"])
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if has_keyword and has_aux:
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return row_idx
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return None
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def read_sheet(xls_file, sheet_name, trade_type):
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"""
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读取单个Sheet的数据
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:param xls_file: Excel文件路径
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:param sheet_name: Sheet名称
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:param trade_type: 交易类型（期货/期权）
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:return: DataFrame
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"""
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try:
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wb = xlrd.open_workbook(xls_file)
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if sheet_name not in wb.sheet_names():
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print(f" 警告: {xls_file} 中未找到 {sheet_name}")
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return pd.DataFrame()
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sheet = wb.sheet_by_name(sheet_name)
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if sheet.nrows == 0:
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return pd.DataFrame()
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# 根据类型确定关键词
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if trade_type == '期货':
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keywords = ["合约"]
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else: # 期权
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keywords = ["品种合约"]
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# 查找表头行
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header_row = find_header(sheet, keywords)
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if header_row is None:
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print(f" 警告: {sheet_name} 中未找到表头")
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return pd.DataFrame()
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# 读取表头
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headers = [str(sheet.cell_value(header_row, col_idx)).strip()
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for col_idx in range(sheet.ncols)]
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# 读取数据行
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data = []
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for row_idx in range(header_row + 1, sheet.nrows):
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row_data = {}
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first_cell = str(sheet.cell_value(row_idx, 0)).strip()
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# 跳过合计行
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if first_cell == '合计' or first_cell == '':
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continue
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for col_idx, header in enumerate(headers):
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if col_idx < sheet.ncols:
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value = sheet.cell_value(row_idx, col_idx)
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# 处理"--"
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if str(value).strip() == '--':
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value = None
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row_data[header] = value
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# 添加类型标签
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row_data['类型'] = trade_type
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data.append(row_data)
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df = pd.DataFrame(data)
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print(f" 读取 {sheet_name}: {len(df)} 条记录")
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return df
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except Exception as e:
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print(f" 错误: 读取 {sheet_name} 失败 - {e}")
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return pd.DataFrame()
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def extract_variety(contract):
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"""
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提取品种代码（所有前导字母）
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:param contract: 合约代码
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:return: 品种代码
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"""
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if pd.isna(contract) or not contract:
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return ''
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contract = str(contract).strip()
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match = re.match(r'^([A-Za-z]+)', contract)
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if match:
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return match.group(1).upper()
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return contract[:2].upper()
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def safe_float(value, default=0.0):
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"""
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安全转换为float
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"""
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if pd.isna(value) or value is None or value == '':
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return default
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try:
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return float(value)
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except (ValueError, TypeError):
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return default
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def calc_pnl_futures(df):
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"""
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计算期货盈亏
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"""
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if df.empty:
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return {'平仓盈亏': 0, '手续费': 0, '净盈亏': 0}
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# 平仓盈亏
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pnl_close = 0
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if '平仓盈亏' in df.columns:
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for val in df['平仓盈亏']:
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if not pd.isna(val):
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pnl_close += safe_float(val)
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# 手续费
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commission = 0
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if '手续费' in df.columns:
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for val in df['手续费']:
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commission += safe_float(val)
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net_pnl = pnl_close - commission
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return {
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'平仓盈亏': pnl_close,
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'手续费': commission,
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'净盈亏': net_pnl
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}
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def calc_pnl_options(df):
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"""
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计算期权盈亏
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"""
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if df.empty:
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return {'权利金净收入': 0, '手续费': 0, '净盈亏': 0}
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# 权利金（带方向）
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premium_total = 0
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if '权利金' in df.columns:
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for val in df['权利金']:
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premium_total += safe_float(val)
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# 手续费
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commission = 0
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if '手续费' in df.columns:
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for val in df['手续费']:
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commission += safe_float(val)
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net_pnl = premium_total - commission
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return {
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'权利金净收入': premium_total,
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'手续费': commission,
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'净盈亏': net_pnl
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}
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def calc_position_futures(df):
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"""
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计算期货持仓
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"""
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positions = defaultdict(float)
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if df.empty:
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return positions
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for _, row in df.iterrows():
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contract = str(row.get('合约', '')).strip()
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if not contract or contract == '合计':
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continue
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bs_flag = str(row.get('买/卖', '')).strip()
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oc_flag = str(row.get('开/平', '')).strip()
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volume = safe_float(row.get('手数', 0))
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# 买+开 → +手数；卖+开 → -手数；买+平 → -手数；卖+平 → +手数
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if '买' in bs_flag and '开' in oc_flag:
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positions[contract] += volume
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elif '卖' in bs_flag and '开' in oc_flag:
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positions[contract] -= volume
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elif '买' in bs_flag and '平' in oc_flag:
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positions[contract] -= volume
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elif '卖' in bs_flag and '平' in oc_flag:
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positions[contract] += volume
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# 过滤0持仓
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return {k: v for k, v in positions.items() if abs(v) > 0.001}
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def calc_position_options(df):
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"""
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计算期权持仓
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"""
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positions = defaultdict(float)
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if df.empty:
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return positions
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for _, row in df.iterrows():
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contract = str(row.get('品种合约', '')).strip()
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if not contract or contract == '合计':
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continue
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bs_flag = str(row.get('买/卖', '')).strip()
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volume = safe_float(row.get('成交量', 0))
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if '买' in bs_flag:
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positions[contract] += volume
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elif '卖' in bs_flag:
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positions[contract] -= volume
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# 过滤0持仓
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return {k: v for k, v in positions.items() if abs(v) > 0.001}
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def merge_trades(df_futures, df_options):
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"""
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合并期货和期权交易记录
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"""
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# 统一字段
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columns_map_futures = {
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'合约': '合约代码',
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'买/卖': '买卖',
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'成交价': '价格/权利金单价',
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'手数': '手数/成交量',
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'成交额': '金额/权利金',
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'实际成交日期': '实际成交日期',
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'成交时间': '成交时间'
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}
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columns_map_options = {
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'品种合约': '合约代码',
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'买/卖': '买卖',
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'权利金单价': '价格/权利金单价',
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'成交量': '手数/成交量',
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'权利金': '金额/权利金',
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'成交日期': '实际成交日期',
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'成交时间': '成交时间'
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}
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# 处理期货数据
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if not df_futures.empty:
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df_f = df_futures.rename(columns=columns_map_futures).copy()
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df_f['品种'] = df_f['合约代码'].apply(extract_variety)
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df_f['方向'] = df_f['买卖'].apply(lambda x: '买' if '买' in str(x) else '卖')
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df_f['开平仓'] = df_f.get('开/平', '')
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# 确保必要字段存在
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for col in ['平仓盈亏', '手续费']:
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if col not in df_f.columns:
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df_f[col] = 0
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else:
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df_f = pd.DataFrame()
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# 处理期权数据
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if not df_options.empty:
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df_o = df_options.rename(columns=columns_map_options).copy()
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df_o['品种'] = df_o['合约代码'].apply(extract_variety)
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df_o['方向'] = df_o['买卖'].apply(lambda x: '买' if '买' in str(x) else '卖')
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df_o['开平仓'] = ''
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df_o['平仓盈亏'] = 0
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# 确保必要字段存在
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for col in ['手续费']:
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if col not in df_o.columns:
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df_o[col] = 0
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else:
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df_o = pd.DataFrame()
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# 合并
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common_cols = ['品种', '合约代码', '类型', '买卖', '方向', '成交时间',
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'实际成交日期', '价格/权利金单价', '手数/成交量', '金额/权利金',
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'手续费', '平仓盈亏', '开平仓']
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if not df_f.empty:
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df_f = df_f[[c for c in common_cols if c in df_f.columns]]
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if not df_o.empty:
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df_o = df_o[[c for c in common_cols if c in df_o.columns]]
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if not df_f.empty and not df_o.empty:
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return pd.concat([df_f, df_o], ignore_index=True)
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elif not df_f.empty:
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return df_f
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elif not df_o.empty:
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return df_o
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else:
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return pd.DataFrame()
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def save_output(trades_df, df_futures, df_options, output_dir):
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"""
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保存输出文件
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"""
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os.makedirs(output_dir, exist_ok=True)
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# 文件1：trades_merged.csv
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csv_path = os.path.join(output_dir, 'trades_merged.csv')
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if not trades_df.empty:
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trades_df.to_csv(csv_path, index=False, encoding='utf-8-sig')
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print(f"已保存交易明细: {csv_path}")
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else:
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print("警告: 无交易数据")
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# 计算分析数据
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analysis_data = {}
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# Sheet1: 品种盈亏汇总
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variety_summary = []
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# 期货品种汇总
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if not df_futures.empty:
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df_f = df_futures.copy()
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df_f['品种'] = df_f['合约'].apply(extract_variety)
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for variety, group in df_f.groupby('品种'):
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pnl = calc_pnl_futures(group)
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total_volume = sum(safe_float(v) for v in group.get('手数', []))
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total_amount = sum(safe_float(v) for v in group.get('成交额', []))
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buy_count = sum(1 for v in group.get('买/卖', []) if '买' in str(v))
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sell_count = sum(1 for v in group.get('买/卖', []) if '卖' in str(v))
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variety_summary.append({
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'品种': variety,
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'类型': '期货',
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'总手数': total_volume,
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'总成交额': total_amount,
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'总手续费': pnl['手续费'],
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'平仓盈亏': pnl['平仓盈亏'],
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'净盈亏': pnl['净盈亏'],
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'买入次数': buy_count,
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'卖出次数': sell_count
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})
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# 期权品种汇总
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if not df_options.empty:
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df_o = df_options.copy()
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df_o['品种'] = df_o['品种合约'].apply(extract_variety)
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for variety, group in df_o.groupby('品种'):
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pnl = calc_pnl_options(group)
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total_volume = sum(safe_float(v) for v in group.get('成交量', []))
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total_premium = sum(abs(safe_float(v)) for v in group.get('权利金', []))
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buy_count = sum(1 for v in group.get('买/卖', []) if '买' in str(v))
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sell_count = sum(1 for v in group.get('买/卖', []) if '卖' in str(v))
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variety_summary.append({
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'品种': variety,
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'类型': '期权',
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'总手数': total_volume,
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'总成交额/权利金': total_premium,
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'总手续费': pnl['手续费'],
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'平仓盈亏': 0,
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'净盈亏': pnl['净盈亏'],
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'买入次数': buy_count,
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'卖出次数': sell_count
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})
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df_variety = pd.DataFrame(variety_summary)
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# Sheet2: 期货持仓
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futures_positions = calc_position_futures(df_futures)
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futures_pos_data = []
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for contract, pos in futures_positions.items():
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futures_pos_data.append({
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'合约': contract,
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'净持仓': pos,
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'方向': '多' if pos > 0 else '空'
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})
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df_futures_pos = pd.DataFrame(futures_pos_data)
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# Sheet3: 期权持仓
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options_positions = calc_position_options(df_options)
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options_pos_data = []
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for contract, pos in options_positions.items():
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options_pos_data.append({
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'品种合约': contract,
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'净持仓': pos,
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'方向': '权利' if pos > 0 else '义务'
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})
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df_options_pos = pd.DataFrame(options_pos_data)
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# 文件2：analysis.xlsx
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xlsx_path = os.path.join(output_dir, 'analysis.xlsx')
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with pd.ExcelWriter(xlsx_path, engine='openpyxl') as writer:
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if not df_variety.empty:
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df_variety.to_excel(writer, sheet_name='品种盈亏汇总', index=False)
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if not df_futures_pos.empty:
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df_futures_pos.to_excel(writer, sheet_name='期货持仓', index=False)
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if not df_options_pos.empty:
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df_options_pos.to_excel(writer, sheet_name='期权持仓', index=False)
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print(f"已保存分析结果: {xlsx_path}")
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return {
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'variety_summary': variety_summary,
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'futures_positions': futures_positions,
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'options_positions': options_positions
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}
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|
|
|
|
|
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def print_summary(df_futures, df_options, results):
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"""
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打印摘要
|
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|
"""
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print("\n" + "="*50)
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print("=== 交易摘要 ===")
|
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|
|
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# 期货统计
|
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|
if not df_futures.empty:
|
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|
pnl_f = calc_pnl_futures(df_futures)
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|
varieties_f = df_futures['合约'].apply(extract_variety).nunique()
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|
print(f"期货：{len(df_futures)}笔交易，{varieties_f}个品种")
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print(f" 总盈亏：{pnl_f['净盈亏']:.2f}元（含手续费{pnl_f['手续费']:.2f}元）")
|
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else:
|
|
|
print("期货：无交易")
|
|
|
|
|
|
# 期权统计
|
|
|
if not df_options.empty:
|
|
|
pnl_o = calc_pnl_options(df_options)
|
|
|
varieties_o = df_options['品种合约'].apply(extract_variety).nunique()
|
|
|
print(f"期权：{len(df_options)}笔交易，{varieties_o}个品种")
|
|
|
print(f" 总盈亏：{pnl_o['净盈亏']:.2f}元（含手续费{pnl_o['手续费']:.2f}元）")
|
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|
else:
|
|
|
print("期权：无交易")
|
|
|
|
|
|
# 持仓统计
|
|
|
print("\n=== 收盘持仓 ===")
|
|
|
|
|
|
futures_pos = results['futures_positions']
|
|
|
if futures_pos:
|
|
|
for contract, pos in sorted(futures_pos.items()):
|
|
|
direction = '多' if pos > 0 else '空'
|
|
|
print(f"期货：{contract} {direction} {abs(pos):.0f}手")
|
|
|
else:
|
|
|
print("期货：无持仓")
|
|
|
|
|
|
options_pos = results['options_positions']
|
|
|
if options_pos:
|
|
|
for contract, pos in sorted(options_pos.items()):
|
|
|
direction = '权利' if pos > 0 else '义务'
|
|
|
print(f"期权：{contract} {direction} {abs(pos):.0f}手")
|
|
|
else:
|
|
|
print("期权：无持仓")
|
|
|
|
|
|
print("="*50 + "\n")
|
|
|
|
|
|
|
|
|
def main():
|
|
|
"""
|
|
|
主函数
|
|
|
"""
|
|
|
# 数据目录
|
|
|
data_dir = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'data')
|
|
|
output_dir = os.path.dirname(os.path.abspath(__file__))
|
|
|
|
|
|
print(f"数据目录: {data_dir}")
|
|
|
print(f"输出目录: {output_dir}\n")
|
|
|
|
|
|
# 查找所有xls文件
|
|
|
xls_files = glob.glob(os.path.join(data_dir, '*.xls'))
|
|
|
if not xls_files:
|
|
|
print(f"错误: 在 {data_dir} 中未找到 .xls 文件")
|
|
|
return
|
|
|
|
|
|
print(f"找到 {len(xls_files)} 个结算单文件\n")
|
|
|
|
|
|
# 读取所有文件
|
|
|
all_futures = []
|
|
|
all_options = []
|
|
|
|
|
|
for xls_file in sorted(xls_files):
|
|
|
filename = os.path.basename(xls_file)
|
|
|
print(f"处理: {filename}")
|
|
|
|
|
|
# 读取期货成交明细
|
|
|
df_f = read_sheet(xls_file, '成交明细', '期货')
|
|
|
if not df_f.empty:
|
|
|
all_futures.append(df_f)
|
|
|
|
|
|
# 读取期权成交明细
|
|
|
df_o = read_sheet(xls_file, '期权成交明细', '期权')
|
|
|
if not df_o.empty:
|
|
|
all_options.append(df_o)
|
|
|
|
|
|
# 合并数据
|
|
|
df_futures = pd.concat(all_futures, ignore_index=True) if all_futures else pd.DataFrame()
|
|
|
df_options = pd.concat(all_options, ignore_index=True) if all_options else pd.DataFrame()
|
|
|
|
|
|
print(f"\n汇总: 期货 {len(df_futures)} 条, 期权 {len(df_options)} 条\n")
|
|
|
|
|
|
# 合并交易记录
|
|
|
trades_merged = merge_trades(df_futures, df_options)
|
|
|
|
|
|
# 保存输出
|
|
|
results = save_output(trades_merged, df_futures, df_options, output_dir)
|
|
|
|
|
|
# 打印摘要
|
|
|
print_summary(df_futures, df_options, results)
|
|
|
|
|
|
|
|
|
if __name__ == '__main__':
|
|
|
main()
|
