使用输入输出文件在Python中进行并行处理

如何解决使用输入输出文件在Python中进行并行处理

import numpy as np
import pandas as pd
import math
j = 0
k = 0
time_array = []
average_pa = []
for i in range(3600):
    time_array.append(j)
    average_pa.append(k)
    j += 0.1
time_array1 = tuple(time_array)
pa1 = 0.0
time1 = 0.0
chunk_size = 1000
for chunk in pd.read_csv("data_fiftydyne.txt",header=1,delimiter='\t',chunksize=chunk_size,skip_blank_lines=True,error_bad_lines=False,keep_default_na=False):
    file2 = chunk.to_numpy()
    for jj in range(file2.shape[0]):
        time1 = file2[jj][9]
        if type(time1) == str:
            time1 = 362
        pa1 = file2[jj][11]
        ff = open("aver_pa_time_fiftydyne.csv","a")
        ff.truncate(0)
        ff.seek(0)
        for ii in range(3600):
            if math.floor(10 * time_array1[ii]) == math.floor(float(10 * time1)):
                average_pa[ii] += pas1
                print(pa1)
                print(time1)
            ff.write(str(average_pa[ii]) + ',' + str(time_array1[ii]) + '\n')
        ff.close()

这是串行工作的代码。如何并行化此代码？文件大小为67GB。在具有4.2GHz和8GB RAM的CPU上串行运行需要5天。