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

一行,可能很快:

num_lines = sum(1 for line in open('myfile.txt'))

其他回答

类似的:

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

另一种可能性:

import subprocess

def num_lines_in_file(fpath):
    return int(subprocess.check_output('wc -l %s' % fpath, shell=True).strip().split()[0])

凯尔的回答

num_lines = sum(1 for line in open('my_file.txt'))

最好的替代方案是什么

num_lines =  len(open('my_file.txt').read().splitlines())

这里是两者的性能比较

In [20]: timeit sum(1 for line in open('Charts.ipynb'))
100000 loops, best of 3: 9.79 µs per loop

In [21]: timeit len(open('Charts.ipynb').read().splitlines())
100000 loops, best of 3: 12 µs per loop

您可以执行子进程并运行wc -l filename

import subprocess

def file_len(fname):
    p = subprocess.Popen(['wc', '-l', fname], stdout=subprocess.PIPE, 
                                              stderr=subprocess.PIPE)
    result, err = p.communicate()
    if p.returncode != 0:
        raise IOError(err)
    return int(result.strip().split()[0])

如果文件能放进内存,那么

with open(fname) as f:
    count = len(f.read().split(b'\n')) - 1