earthjasonlin
77d5f053f0
- Add `convert` orders for direct base/quote token exchange without order book - Distinguish buy/sell validation: buy uses quoteOrderQty, sell uses quantity - Support automatic amount estimation when only one of quantity/quoteOrderQty is provided - Update README: replace old order type list, document convert usage with BASE/QUOTE symbols and new examples - Lowercase order_type and side values throughout documentation
132 lines
4.2 KiB
Python
132 lines
4.2 KiB
Python
"""CSV 文件处理模块
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该模块用于合并同一证券在同一天的多笔交易记录，并生成汇总后的交易记录。
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"""
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import csv
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import os
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import re
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from collections import defaultdict
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def process_csv(input_file, output_file):
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"""处理CSV文件，合并相同证券在同一天的交易记录
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Args:
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input_file (str): 输入CSV文件路径
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output_file (str): 输出CSV文件路径
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"""
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merged_records = defaultdict(
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lambda: {
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"buy_shares": 0.0,
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"buy_amount": 0.0,
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"sell_shares": 0.0,
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"sell_amount": 0.0,
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"order_ids": set(),
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"first_record": None,
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"time_part": None,
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}
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)
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with open(input_file, mode="r", newline="", encoding="utf-8") as infile:
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reader = csv.DictReader(infile)
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for row in reader:
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datetime_str = row["日期"]
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date_part, time_part = datetime_str.split("T")
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match = re.search(r"Order ID[^:]*:\s*([^\s,]+)", row["备注"])
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order_id = match.group(1) if match else row["备注"]
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merge_key = (date_part, row["证券代码"])
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record = merged_records[merge_key]
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if record["first_record"] is None:
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record["first_record"] = row
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record["time_part"] = time_part
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record["order_ids"].add(order_id)
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if row["类型"] == "买入":
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record["buy_shares"] += float(row["份额"])
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record["buy_amount"] += float(row["净额"])
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elif row["类型"] == "卖出":
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record["sell_shares"] += float(row["份额"])
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record["sell_amount"] += float(row["净额"])
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output_rows = []
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for key, record in merged_records.items():
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date_part, symbol = key
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first_row = record["first_record"]
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net_shares = record["buy_shares"] - record["sell_shares"]
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net_amount = record["buy_amount"] - record["sell_amount"]
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if net_shares >= 0:
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operation_type = "买入"
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display_shares = net_shares
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display_amount = net_amount
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else:
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operation_type = "卖出"
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display_shares = -net_shares
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display_amount = -net_amount
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# 格式化为完整小数形式，不使用科学计数法
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formatted_shares = (
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f"{display_shares:f}".rstrip("0").rstrip(".")
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if "." in f"{display_shares:f}"
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else f"{display_shares:f}"
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)
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formatted_amount = (
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f"{display_amount:f}".rstrip("0").rstrip(".")
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if "." in f"{display_amount:f}"
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else f"{display_amount:f}"
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)
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merged_row = {
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"日期": f"{date_part}T{record['time_part']}",
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"类型": operation_type,
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"证券代码": symbol,
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"份额": formatted_shares,
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"净额": formatted_amount,
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"现金账户": first_row["现金账户"],
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"目标账户": first_row["目标账户"],
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"备注": f"MEXC API - Order ID: {', '.join(sorted(record['order_ids']))}",
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}
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output_rows.append(merged_row)
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# 写入输出文件
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with open(output_file, mode="w", newline="", encoding="utf-8") as outfile:
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fieldnames = [
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"日期",
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"类型",
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"证券代码",
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"份额",
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"净额",
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"现金账户",
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"目标账户",
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"备注",
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]
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writer = csv.DictWriter(outfile, fieldnames=fieldnames)
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writer.writeheader()
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writer.writerows(output_rows)
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def process_all_csvs(input_dir="output"):
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"""处理指定目录下的所有CSV文件
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Args:
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input_dir (str): 包含CSV文件的目录路径
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"""
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for filename in os.listdir(input_dir):
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if filename.endswith(".csv") and not filename.startswith("merged_"):
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input_path = os.path.join(input_dir, filename)
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output_path = os.path.join(input_dir, f"merged_{filename}")
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process_csv(input_path, output_path)
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print(f"处理完成: {filename} -> merged_{filename}")
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if __name__ == "__main__":
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process_all_csvs()
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print("所有文件处理完成")
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