python读取通达信期货本地下载数据

1.函数：
def kline(cls, file)
用途：自动读取本地文件日线或分钟数据
返回：str,pd.DataFrame??
参数：?
? ? --file : str 类似'\lday\28#APL9.day' 或'\minline\28#AP2401.lc1'
? ?

# -*- coding: utf-8 -*-
"""
@Project:TcyQuant
@File:   tdx.py
@Auth:   tcy
@Date:   2023/12/12 13:36
@Desc:
@Ver :   0.0.1
@Emial:  3615693665@qq.com
@City:   China Shanghai Songjiang Yexie
"""
import re
import os
import struct
import numpy as np
import pandas as pd
from tool.file.file import File


class Tdx(object):

    daypath = r'C:\new_tdx\vipdoc\ds\lday'  # 28#APL9.day
    minpath = r'C:\new_tdx\vipdoc\ds\minline'  # 28#AP2401.lc1
    dstpath = r'D:\futuresdata_cn\data\day\tdxday'

    @classmethod
    def _get_codemon_(cls, file):
        if file.endswith('L9.day'):
            file = file.replace('L9.day', '')
        s = re.findall(r'[\d+#]+([\da-z]+)\.?', file, re.I)[0]
        if s.isalpha():
            s = s + '99'
        s = s.upper()
        var = re.sub(r'\d+', '', s)
        return var, s

    @classmethod
    def kline(cls, file):  # 日线分钟读取
        """
        读取通达信日线分钟本地下载数据；返回var,df
        df cols= date,codemon,open,high,low,close,position,volume,settle
        """
        def _op1(a):
            v = str(a[0])
            ts = '%s-%s-%s' % (v[:4], v[4:6], v[6:8])
            return [ts] + list(a[1:])

        def _op2(a):
            d = a[0] + 25412
            h = a[1] // 60
            m = a[1] % 60
            delta = pd.Timedelta(days=d, hours=h, minutes=m)
            ts = (pd.Timestamp('2023-12-12') + delta).strftime('%Y-%m-%d')
            return [ts] + list(a[2:])

        fmt = 'lffffllf' if file.endswith('.day') else 'hhffffllf'
        op = _op1 if file.endswith('.day') else _op2
        with open(file, "rb") as f:
            buf = f.read()

        row = int(len(buf) / 32)
        cols = "date,open,high,low,close,position,volume,settle"
        datas = []
        for i in range(row):
            a = struct.unpack(fmt, buf[i * 32:(i + 1) * 32])
            datas.append(op(a))
        df = pd.DataFrame(datas, columns=cols.split(','))
        var, val = cls._get_codemon_(file)
        df.insert(loc=1, column='codemon', value=val)
        return var, df

    @classmethod
    def rwdata(cls):
        cols2 = ['varmon', 'date']
        okcols = ['date', 'codemon', 'varmon', 'open', 'high', 'low',
                  'close', 'volume', 'amount', 'position', 'settle',
                  '前结算', 'main', 'var']
        files = File.listdir2(cls.daypath, 'L9.day')
        for file in files:
            var, df = cls.kline(file)
            df['varmon'] = df['codemon']
            df['amount'] = np.nan
            df['前结算'] = np.nan
            df['main'] = 'index'
            df['var'] = var
            df = df[okcols]

            newfile = r'%s\%s.csv' % (cls.dstpath, var)
            if File.exist_file(newfile):
                dfold = pd.read_csv(newfile)
                df = pd.concat([dfold, df])
                df = df.drop_duplicates(cols2)
                df = df.sort_values(cols2)
            df.to_csv(newfile, index=False)


if __name__ == '__main__':
    file = r'C:\new_tdx\vipdoc\ds\lday\28#APL9.day'
    file1 = r'C:\new_tdx\vipdoc\ds\minline\28#AP2401.lc1'
    var, df = Tdx.kline(file)
    print('var=',var,'\n',df.tail(2))
    var, df = Tdx.kline(file1)
    print('var=',var,'\n',df.tail(2))
    # Tdx.rwdata()

var= AP 
             date codemon    open    high  ...   close  position  volume  settle
1447  2023-12-11    AP99  8620.0  8620.0  ...  8516.0    107892   64517     0.0
1448  2023-12-12    AP99  8515.0  8575.0  ...  8527.0    105098   36468     0.0

[2 rows x 9 columns]
var= AP 
              date codemon         open  ...  position  volume  settle
45673  2023-12-12  AP2401  9097.000977  ...     20493      50     0.0
45674  2023-12-12  AP2401  9102.000977  ...     20470      67     0.0

[2 rows x 9 columns]