Python多进程高效读取超大文件的技巧

本文详细介绍了如何使用Python的多进程技术来高效地分块读取超大文件，并将其输出为多个文件。通过这种方式，可以显著提高读取速度和处理效率。具体内容如下：

读取超大的文本文件时，使用多进程分块读取方法，可以将每个分块单独输出成文件。

# -*- coding: UTF-8 -*-

import os

import datetime

from multiprocessing import Process, Queue, Array, RLock

"""

多进程分块读取文件

"""

WORKERS = 4

BLOCKSIZE = 100000000

FILE_SIZE = 0

def get_file_size(file_path):

"""

获取文件的大小

"""

global FILE_SIZE

with open(file_path, 'r') as f:

f.seek(0, os.SEEK_END)

FILE_SIZE = f.tell()

def process_block(pid, array, file_path, rlock):

"""

处理文件块的函数

Args:

pid: 进程编号

array: 进程间共享数组，用于标记各进程所读的文件块结束位置

file_path: 要读取的文件路径

"""

global FILE_SIZE

with open(file_path, 'r') as f:

while True:

rlock.acquire()

start_position = max(array)

end_position = min(start_position + BLOCKSIZE, FILE_SIZE)

array[pid] = end_position

rlock.release()

if start_position == FILE_SIZE:

print(f'Process {pid} finished')

break

if start_position != 0:

f.seek(start_position)

f.readline() # 读取并丢弃一行，防止行被截断

with open(f'/data/output/block_{pid}_{start_position}.txt', 'w') as out_f:

while f.tell()

line = f.readline()

out_f.write(line)

def main():

global FILE_SIZE

print(datetime.datetime.now().strftime('%Y/%m/%d %H:%M:%S'))

file_path = '/data/large_file.txt'

get_file_size(file_path)

print(f'File size: {FILE_SIZE} bytes')

rlock = RLock()

array = Array('l', [0] * WORKERS, lock=rlock)

processes = []

for i in range(WORKERS):

p = Process(target=process_block, args=(i, array, file_path, rlock))

processes.append(p)

p.start()

for p in processes:

p.join()

print(datetime.datetime.now().strftime('%Y/%m/%d %H:%M:%S'))

if __name__ == '__main__':

main()

希望本文所述对大家Python程序设计有所帮助。