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Python如何统计纯文本文件中英文单词出现个数

发布时间:2021-08-07 14:05:08 来源:亿速云 阅读:133 作者:小新 栏目:开发技术

这篇文章将为大家详细讲解有关Python如何统计纯文本文件中英文单词出现个数,小编觉得挺实用的,因此分享给大家做个参考,希望大家阅读完这篇文章后可以有所收获。

具体如下:

第一版: 效率低

# -*- coding:utf-8 -*-
#!python3
path = 'test.txt'
with open(path,encoding='utf-8',newline='') as f:
  word = []
  words_dict= {}
  for letter in f.read():
    if letter.isalnum():
      word.append(letter)
    elif letter.isspace(): #空白字符 空格 \t \n
      if word:
        word = ''.join(word).lower() #转小写
        if word not in words_dict:
          words_dict[word] = 1
        else:
          words_dict[word] += 1
        word = []
#处理最后一个单词
if word:
  word = ''.join(word).lower() # 转小写
  if word not in words_dict:
    words_dict[word] = 1
  else:
    words_dict[word] += 1
  word = []
for k,v in words_dict.items():
  print(k,v)

运行结果:

we 4
are 1
busy 1
all 1
day 1
like 1
swarms 1
of 6
flies 1
without 1
souls 1
noisy 1
restless 1
unable 1
to 1
hear 1
the 7
voices 1
soul 1
as 1
time 1
goes 1
by 1
childhood 1
away 2
grew 1
up 1
years 1
a 1
lot 1
memories 1
once 1
have 2
also 1
eroded 1
bottom 1
childish 1
innocence 1
regardless 1
shackles 1
mind 1
indulge 1
in 1
world 1
buckish 1
focus 1
on 1
beneficial 1
principle 1
lost 1
themselves 1

第二版:

缺点:遇到大文件要一次读入内存,性能不好

# -*- coding:utf-8 -*-
#!python3
import re
path = 'test.txt'
with open(path,'r',encoding='utf-8') as f:
  data = f.read()
  word_reg = re.compile(r'\w+')
  #word_reg = re.compile(r'\w+\b')
  word_list = word_reg.findall(data)
  word_list = [word.lower() for word in word_list] #转小写
  word_set = set(word_list) #避免重复查询
  # words_dict = {}
  # for word in word_set:
  #   words_dict[word] = word_list.count(word)
  # 简洁写法
  words_dict = {word: word_list.count(word) for word in word_set}
  for k,v in words_dict.items():
    print(k,v)

运行结果:

on 1
also 1
souls 1
focus 1
soul 1
time 1
noisy 1
grew 1
lot 1
childish 1
like 1
voices 1
indulge 1
swarms 1
buckish 1
restless 1
we 4
hear 1
childhood 1
as 1
world 1
themselves 1
are 1
bottom 1
memories 1
the 7
of 6
flies 1
without 1
have 2
day 1
busy 1
to 1
eroded 1
regardless 1
unable 1
innocence 1
up 1
a 1
in 1
mind 1
goes 1
by 1
lost 1
principle 1
once 1
away 2
years 1
beneficial 1
all 1
shackles 1

第三版:

# -*- coding:utf-8 -*-
#!python3
import re
path = 'test.txt'
with open(path, 'r', encoding='utf-8') as f:
  word_list = []
  word_reg = re.compile(r'\w+')
  for line in f:
    #line_words = word_reg.findall(line)
    #比上面的正则更加简单
    line_words = line.split()
    word_list.extend(line_words)
  word_set = set(word_list) # 避免重复查询
  words_dict = {word: word_list.count(word) for word in word_set}
  for k, v in words_dict.items():
    print(k, v)

运行结果:

childhood 1
innocence, 1
are 1
of 6
also 1
lost 1
We 1
regardless 1
noisy, 1
by, 1
on 1
themselves. 1
grew 1
lot 1
bottom 1
buckish, 1
time 1
childish 1
voices 1
once 1
restless, 1
shackles 1
world 1
eroded 1
As 1
all 1
day, 1
swarms 1
we 3
soul. 1
memories, 1
in 1
without 1
like 1
beneficial 1
up, 1
unable 1
away 1
flies 1
goes 1
a 1
have 2
away, 1
mind, 1
focus 1
principle, 1
hear 1
to 1
the 7
years 1
busy 1
souls, 1
indulge 1

第四版:使用Counter统计

# -*- coding:utf-8 -*-
#!python3
import collections
import re
path = 'test.txt'
with open(path, 'r', encoding='utf-8') as f:
  word_list = []
  word_reg = re.compile(r'\w+')
  for line in f:
    line_words = line.split()
    word_list.extend(line_words)
  words_dict = dict(collections.Counter(word_list)) #使用Counter统计
  for k, v in words_dict.items():
    print(k, v)

运行结果:

We 1
are 1
busy 1
all 1
day, 1
like 1
swarms 1
of 6
flies 1
without 1
souls, 1
noisy, 1
restless, 1
unable 1
to 1
hear 1
the 7
voices 1
soul. 1
As 1
time 1
goes 1
by, 1
childhood 1
away, 1
we 3
grew 1
up, 1
years 1
away 1
a 1
lot 1
memories, 1
once 1
have 2
also 1
eroded 1
bottom 1
childish 1
innocence, 1
regardless 1
shackles 1
mind, 1
indulge 1
in 1
world 1
buckish, 1
focus 1
on 1
beneficial 1
principle, 1
lost 1
themselves. 1

注:这里使用的测试文本test.txt如下:

We are busy all day, like swarms of flies without souls, noisy, restless, unable to hear the voices of the soul. As time goes by, childhood away, we grew up, years away a lot of memories, once have also eroded the bottom of the childish innocence, we regardless of the shackles of mind, indulge in the world buckish, focus on the beneficial principle, we have lost themselves.

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