如何使用Python快速高效地统计出大文件的总行数, 下面是一些实现方法和性能的比较。
- 1.readline读所有行
使用readlines方法读取所有行:
def readline_count(file_name):
return len(open(file_name).readlines())
- 2.依次读取每行
依次读取文件每行内容进行计数:
def simple_count(file_name):
lines = 0
for _ in open(file_name):
lines += 1
return lines
- 3.sum计数
使用sum函数计数:
def sum_count(file_name):
return sum(1 for _ in open(file_name))
- 4.enumerate枚举计数:
def enumerate_count(file_name):
with open(file_name) as f:
for count, _ in enumerate(f, 1):
pass
return count
- 5.buff count
每次读取固定大小,然后统计行数:
def buff_count(file_name):
with open(file_name, 'rb') as f:
count = 0
buf_size = 1024 * 1024
buf = f.read(buf_size)
while buf:
count += buf.count(b'\n')
buf = f.read(buf_size)
return count
- 6.wc count
调用使用wc命令计算行:
def wc_count(file_name):
import subprocess
out = subprocess.getoutput("wc -l %s" % file_name)
return int(out.split()[0])
- 7.partial count
在buff_count基础上引入partial:
def partial_count(file_name):
from functools import partial
buffer = 1024 * 1024
with open(file_name) as f:
return sum(x.count('\n') for x in iter(partial(f.read, buffer), ''))
- 8.iter count
在buff_count基础上引入itertools模块 :
def iter_count(file_name):
from itertools import (takewhile, repeat)
buffer = 1024 * 1024
with open(file_name) as f:
buf_gen = takewhile(lambda x: x, (f.read(buffer) for _ in repeat(None)))
return sum(buf.count('\n') for buf in buf_gen)
下面是在我本机 4c8g python3.6的环境下,分别测试100m、500m、1g、10g大小文件运行的时间，单位秒：
方法 100M 500M 1G 10G readline_count 0.25 1.82 3.27 45.04 simple_count 0.13 0.85 1.58 13.53 sum_count 0.15 0.77 1.59 14.07 enumerate_count 0.15 0.80 1.60 13.37 buff_count 0.13 0.62 1.18 10.21 wc_count 0.09 0.53 0.99 9.47 partial_count 0.12 0.55 1.11 8.92 iter_count 0.08 0.42 0.83 8.33
Original: https://www.cnblogs.com/jhao/p/13488867.html
Author: j_hao104
Title: Python计算大文件行数方法及性能比较
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