目录[-]

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