From 2f2516749615da866e96d8d24e499b7ecbb63a3e Mon Sep 17 00:00:00 2001
From: Administrator <admin@example.com>
Date: 星期一, 23 六月 2025 12:28:52 +0800
Subject: [PATCH] 默认交易模式变更/真实下单位置计算位置修改
---
data_parser/transaction_big_order_parser.py | 163 ++++++++++++++++++++++++++++++++++++++++++++++++++++-
1 files changed, 158 insertions(+), 5 deletions(-)
diff --git a/data_parser/transaction_big_order_parser.py b/data_parser/transaction_big_order_parser.py
index 2ff872e..84dae46 100644
--- a/data_parser/transaction_big_order_parser.py
+++ b/data_parser/transaction_big_order_parser.py
@@ -2,11 +2,16 @@
澶у崟鎴愪氦鏁版嵁瑙ｆ瀽鍣�
"""
import os
+import re
from multiprocessing import Pool
import pandas as pd
from utils import tool
+
+
+def print_log(*args):
+ print(f"[{tool.get_now_time_str()}]", *args)
class BigOrderDealParser:
@@ -54,7 +59,7 @@
child_path = os.path.join(children_dir, f"{index}.csv")
if os.path.exists(child_path):
return
- print(f"澶勭悊Transaction绗瑊index}鎵规", os.getpid())
+ print_log(f"澶勭悊Transaction绗瑊index}鎵规", os.getpid())
df["TradePrice"] = df["TradePrice"].apply(BigOrderDealParser.str_to_float)
df["SecurityID"] = df["SecurityID"].apply(BigOrderDealParser.code_format)
df = df[df["SecurityID"].str.startswith(("30", "00", "60"), na=False)]
@@ -62,7 +67,7 @@
df['TradeAmount'] = df['TradePrice'] * df['TradeVolume']
df = df[df["TradeAmount"] > 0]
# 鍒ゆ柇鏄惁涓虹┖
- # print(df.empty)
+ # print_log(df.empty)
# 鎸塖ecurityID鍜孊uyNo鍒嗙粍
grouped = df.groupby(['SecurityID', 'BuyNo'])
# 搴旂敤鑱氬悎鍑芥暟
@@ -105,7 +110,7 @@
child_path = os.path.join(children_dir, f"{index}.csv")
if os.path.exists(child_path):
return
- print(f"澶勭悊NGTSTick绗瑊index}鎵规")
+ log(f"澶勭悊NGTSTick绗瑊index}鎵规")
df = df[df["TickType"] == 'T']
df["Price"] = df["Price"].apply(BigOrderDealParser.str_to_float)
df["SecurityID"] = df["SecurityID"].apply(BigOrderDealParser.code_format)
@@ -141,9 +146,10 @@
"""
combined_path = os.path.join(dir_path, 'combined.csv')
if os.path.exists(combined_path):
+ print_log("鍚堝苟鐨勭洰鏍囨枃浠跺凡瀛樺湪")
return
file_list = os.listdir(dir_path)
- file_list.sort(key=lambda x: int(x.split(".")[0]))
+ file_list.sort(key=lambda x: int(re.findall(r'\d+', x)[0]))
df_list = []
for file in file_list:
df = pd.read_csv(os.path.join(dir_path, file))
@@ -151,17 +157,164 @@
continue
df["SecurityID"] = df["SecurityID"].apply(BigOrderDealParser.code_format)
df_list.append(df)
+ print_log("鍑嗗鍚堝苟鐨勬枃浠舵暟閲忥細", len(df_list))
combined_df = pd.concat(df_list, ignore_index=True)
+
+ print_log("鍚堝苟瀹屾垚锛屽噯澶囧啓鍏ユ枃浠讹紒")
# 淇濆瓨缁撴灉
combined_df.to_csv(combined_path, index=False)
+ print_log("鍐欏叆鏂囦欢瀹屾垚锛�")
def concat_pre_transactions(dir_path):
__concat_pre_datas(dir_path)
+def concat_pre_ngtsticks(dir_path):
+ __concat_pre_datas(dir_path)
+
+
+def process_combined_transaction(dir_path):
+ """
+ 澶勭悊鎷兼帴璧锋潵鐨勬暟鎹�
+ @param dir_path:
+ @return:
+ """
+ combined_path = os.path.join(dir_path, 'combined.csv')
+ if not os.path.exists(combined_path):
+ print_log("鎷兼帴鏁版嵁涓嶅瓨鍦�")
+ return
+ df = pd.read_csv(combined_path)
+ df_copy = df.copy()
+ grouped = df_copy.groupby(["SecurityID"])
+ # 搴旂敤鑱氬悎鍑芥暟
+ chunk_result = grouped.apply(pd.Series({}))
+ # chunk_result["SecurityID"] = chunk_result["SecurityID"].apply(BigOrderDealParser.code_format)
+ print_log(chunk_result.to_string(
+ index=False, # 涓嶆樉绀虹储寮�
+ justify='left', # 宸﹀榻�
+ float_format='%.3f' # 娴偣鏁版牸寮�
+ ))
+
+
+__combined_df_cache = {}
+
+
+def extract_big_order_of_all(dir_path, process_count=4):
+ combined_path = os.path.join(dir_path, 'combined.csv')
+ if not os.path.exists(combined_path):
+ print_log("鎷兼帴鏁版嵁涓嶅瓨鍦�")
+ return
+ codes = extract_big_order_codes(dir_path)
+ print_log("鎬讳唬鐮佹暟閲忥細", len(codes))
+ for code in codes:
+ extract_big_order_of_code(dir_path, code)
+
+ combined_path = os.path.join(dir_path, 'combined.csv')
+ if not os.path.exists(combined_path):
+ print_log("鎷兼帴鏁版嵁涓嶅瓨鍦�")
+ return
+ output_path = os.path.join(dir_path, f"big_buy_{code}.csv")
+ if os.path.exists(output_path):
+ print_log("璺緞宸插瓨鍦�:", output_path)
+ return
+ df = __combined_df_cache.get(combined_path, None)
+ if df is None:
+ df = pd.read_csv(combined_path)
+ __combined_df_cache[combined_path] = df
+ args = [(code, df) for code in codes]
+ # 鏂板啓娉�
+ with Pool(processes=process_count) as pool:
+ pool.map(__extract_big_order_of_code, args)
+
+
+def __extract_big_order_of_code(args):
+ def first_last(group):
+ """
+ 鑾峰彇绗竴鏉℃暟鎹笌鏈�鍚庝竴鏉�
+ @param group:
+ @return:
+ """
+ return pd.Series({
+ 'SecurityID': group['SecurityID'].iloc[0],
+ 'BuyNo': group['BuyNo'].iloc[0],
+ 'TotalVolume': group['TotalVolume'].sum(),
+ 'TotalAmount': group['TotalAmount'].sum(),
+ 'EndTime': group['EndTime'].iloc[-1],
+ 'EndPrice': group['EndPrice'].iloc[-1],
+ 'StartTime': group['StartTime'].iloc[0],
+ 'StartPrice': group['StartPrice'].iloc[0]
+ })
+
+ dir_path, code, df = args[0], args[1], args[2]
+ output_path = os.path.join(dir_path, f"big_buy_{code}.csv")
+ if os.path.exists(output_path):
+ print_log("璺緞宸插瓨鍦�:", output_path)
+ return
+ df_copy = df.copy()
+ if code:
+ df_copy = df_copy[df_copy["SecurityID"] == int(code)]
+ if df_copy.empty:
+ print_log("鐩爣浠ｇ爜瀵瑰簲鎴愪氦鏁版嵁涓虹┖")
+ return
+ df_copy["SecurityID"] = df_copy["SecurityID"].apply(BigOrderDealParser.code_format)
+ # 鎸塖ecurityID鍜孊uyNo鍒嗙粍
+ grouped = df_copy.groupby(['SecurityID', 'BuyNo'])
+ grouped_result = grouped.apply(first_last)
+ grouped_result = grouped_result[grouped_result["TotalAmount"] > 500000]
+ # print_log(grouped_result)
+ # 閬嶅巻鍐呭
+ grouped_result.to_csv(output_path, index=False)
+ print_log(f"[{tool.get_now_time_str()}]淇濆瓨鎴愬姛锛岃矾寰勶細{output_path}")
+
+
+def extract_big_order_of_code(dir_path, code):
+ """
+ 鎻愬彇浠ｇ爜鐨勫ぇ鍗�
+ @param dir_path: 鏁版嵁鐩綍
+ @param code: 涓虹┖琛ㄧず瀵煎嚭鍏ㄩ儴
+ @return:
+ """
+
+ combined_path = os.path.join(dir_path, 'combined.csv')
+ if not os.path.exists(combined_path):
+ print_log("鎷兼帴鏁版嵁涓嶅瓨鍦�")
+ return
+
+ df = __combined_df_cache.get(combined_path, None)
+ if df is None:
+ df = pd.read_csv(combined_path)
+ __combined_df_cache[combined_path] = df
+ __extract_big_order_of_code((dir_path, code, df))
+
+
+def extract_big_order_codes(dir_path):
+ """
+ 瀵煎嚭澶у崟浠ｇ爜
+ @param dir_path: 鏁版嵁鐩綍
+ @param code:
+ @return:
+ """
+ combined_path = os.path.join(dir_path, 'combined.csv')
+ if not os.path.exists(combined_path):
+ print_log("鎷兼帴鏁版嵁涓嶅瓨鍦�")
+ return
+ df = pd.read_csv(combined_path)
+ df_copy = df.copy()
+ if df_copy.empty:
+ print_log("鐩爣浠ｇ爜瀵瑰簲鎴愪氦鏁版嵁涓虹┖")
+ return
+ df_copy["SecurityID"] = df_copy["SecurityID"].apply(BigOrderDealParser.code_format)
+ # 鎸塖ecurityID鍜孊uyNo鍒嗙粍
+ grouped = df_copy.groupby(['SecurityID'])
+ return set(grouped.groups.keys())
+
+
if __name__ == "__main__":
+ print_log(1, 2, 3)
# pre_process_transactions("E:/娴嬭瘯鏁版嵁/Transaction_Test.csv")
# pre_process_ngtsticks("E:/娴嬭瘯鏁版嵁/NGTSTick_Test.csv")
- concat_pre_transactions("E:/娴嬭瘯鏁版嵁/Transaction_Test")
+ # concat_pre_transactions("E:/娴嬭瘯鏁版嵁/Transaction_Test")
+ # extract_big_order_codes("E:/娴嬭瘯鏁版嵁/Transaction_Test")
+ extract_big_order_of_all("E:/娴嬭瘯鏁版嵁/Transaction_Test")
--
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