如何以最有效的内存和时间方式获取大文件的行数?

def file_len(filename):
    with open(filename) as f:
        for i, _ in enumerate(f):
            pass
    return i + 1

当前回答

这个呢?

import sys
sys.stdin=open('fname','r')
data=sys.stdin.readlines()
print "counted",len(data),"lines"

其他回答

对我来说,这个变体是最快的:

#!/usr/bin/env python

def main():
    f = open('filename')                  
    lines = 0
    buf_size = 1024 * 1024
    read_f = f.read # loop optimization

    buf = read_f(buf_size)
    while buf:
        lines += buf.count('\n')
        buf = read_f(buf_size)

    print lines

if __name__ == '__main__':
    main()

原因:缓冲比逐行和逐字符串读取快。计数也非常快

如果你想在Linux下的Python中廉价地获取行数,我推荐这个方法:

import os
print os.popen("wc -l file_path").readline().split()[0]

File_path可以是抽象文件路径,也可以是相对路径。希望这能有所帮助。

类似的:

lines = 0
with open(path) as f:
    for line in f:
        lines += 1

创建一个可执行脚本文件count.py:

#!/usr/bin/python

import sys
count = 0
for line in sys.stdin:
    count+=1

然后将文件的内容导入python脚本:cat huge.txt | ./count.py。管道也适用于Powershell,因此您将最终计算行数。

对我来说,在Linux上它比简单的解决方案快30%:

count=1
with open('huge.txt') as f:
    count+=1

简单的方法:

1)

>>> f = len(open("myfile.txt").readlines())
>>> f

430
>>> f = open("myfile.txt").read().count('\n')
>>> f
430
>>>
num_lines = len(list(open('myfile.txt')))