ReadFile.rar_Python获取通达信日线数据_python readFile_tdx_tentmev_通达信

import struct import os import math import string import pandas as pd pd.set_option('expand_frame_repr', False) __sz_minute_dir = r"C:\jcb_hczq\vipdoc\sz\minline" #定义深市日交易数据路径 __sh_minute_dir = r"C:\jcb_hczq\vipdoc\sh\minline" #定义沪市日交易数据路径 __sz_day_dir = r"C:\jcb_hczq\vipdoc\sz\lday" #定义深市日交易数据路径 __sh_day_dir = r"C:\jcb_hczq\vipdoc\sh\lday" #定义沪市日交易数据路径 __stock_name_file_sz = r"D:\Stock\深交所股票代码及名称.txt" __stock_name_file_sh = r"D:\Stock\上交所股票代码及名称.txt" #根据数据结构按块读取文件中的交易信息（日） def get_stock_day(block_day): trade_day = struct.unpack('i',block_day[0:4])[0] #交易日期 open_price = struct.unpack('i',block_day[4:8])[0] #开盘价 highest_price = struct.unpack('i', block_day[8:12])[0] #最高价 lowest_price = struct.unpack('i', block_day[12:16])[0] #最低价 close_price = struct.unpack('i', block_day[16:20])[0] #收盘价 traded_charge = struct.unpack('f', block_day[20:24])[0] #交易金额 traded_volum = struct.unpack('i', block_day[24:28])[0] #交易量 note = struct.unpack('i', block_day[28:])[0] #备注(未使用) day_result = [trade_day, open_price, highest_price, lowest_price, close_price, traded_charge, traded_volum, note] #形成列表返回 return day_result #返回日交易信息 #分钟数据中获取日期 def get_day(num): year = math.floor(num/2048) + 2004 month = math.floor(math.fmod(num,2048)/100) day = math.fmod(math.fmod(num,2048),100) date_result = int(year * 10000 + month * 100 + day) return date_result #根据数据结构按块读取文件中的交易信息(分钟) def get_stock_minute(block_day): trade_day = get_day(struct.unpack('h', block_day[0:2])[0]) # 交易日期 trade_min = struct.unpack('h', block_day[2:4])[0] open_price = round(struct.unpack('f', block_day[4:8])[0],2) # 开盘价 highest_price = round(struct.unpack('f', block_day[8:12])[0],2) # 最高价 lowest_price = round(struct.unpack('f', block_day[12:16])[0],2) # 最低价 close_price = round(struct.unpack('f', block_day[16:20])[0],2) # 收盘价 traded_charge = struct.unpack('f', block_day[20:24])[0] # 交易金额 traded_volum = struct.unpack('i', block_day[24:28])[0] # 交易量 note = struct.unpack('i', block_day[28:])[0] # 备注(未使用) minute_result = [trade_day, trade_min, open_price, highest_price, lowest_price, close_price, traded_charge, traded_volum, note] #形成列表返回 return minute_result #返回日交易信息 #取目录下所有股票名编码对应的文件名称(返回列表数据) def get_stock_filenames(path): file_list = os.listdir(path) #读取目录下所有的文件信息 li_files=[] #定义文件列表 for item in file_list: if((item[0:2] == "sz") or (item[0:2] == "sh")): li_files.append(item[0:8]) return li_files #返回文件列表 file_list = get_stock_filenames(__sz_day_dir) print(file_list) #将文件夹中的股票信息（名称与代码相分离）取出到列表中 def get_stock_code_and_name(path): item = "" re_list = [] with open(path,'r') as file_name: while True: item = file_name.readline() if item == "": break; tuple_t = tuple([item[:item.find("(")],item[item.find("(")+1:item.find(")")]]) re_list.append(tuple_t) return re_list #获取股票日数据，得到每日交易情况列表 def get_stock_data_day(path, file_item): stock_code = file_item[2:8] with open(path + "\\" + file_item,'rb') as v_temp_file_name: stock_data_day = [] loop_flag = True while loop_flag: block_day = v_temp_file_name.read(32) if block_day == b'': break day_item = get_stock_day(block_day) day_item.insert(1, stock_code) stock_data_day.append(day_item) #将List转换 stock_data_day = pd.DataFrame(stock_data_day,columns=['trade_day', 'stock_code', 'open_price', 'highest_price', 'lowest_price', 'close_price', 'traded_charge', 'traded_volum', 'note']) stock_data_day.sort_values(by='trade_day', ascending=1, inplace=True) # stock_data_day.reset_index(inplace=True) # stock_data_day.__delitem__('index') return (stock_data_day) #, avg_40_line, avg_60_line #获取股票分钟数据，得到每分钟交易情况列表 def get_stock_data_minute(path, file_item): stock_code = file_item[2:8] serial_id = 0 with open(path + "\\" + file_item,'rb') as v_temp_file_name: stock_data_minute = [] loop_flag = True while loop_flag: block_day = v_temp_file_name.read(32) if block_day == b'': break serial_id += 1 day_item = get_stock_minute(block_day) day_item.insert(2,stock_code) stock_data_minute.append(day_item) stock_data_minute = pd.DataFrame(stock_data_minute,columns=['trade_day', 'trade_min', 'stock_code', 'open_price', 'highest_price', 'lowest_price', 'close_price', 'traded_charge', 'traded_volum', 'note']) stock_data_minute.sort_values(by=['trade_day','trade_min'], ascending=[1,1], inplace=True) # stock_data_minute.reset_index(inplace=True) # stock_data_minute.__delitem__('index') return stock_data_minute