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
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