本文实例讲述了Python统计纯文本文件中英文单词出现个数的方法。分享给大家供大家参考，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.
PS：这里再为大家推荐2款相关统计工具供大家参考：
在线字数统计工具：
http://tools.haodaima.com/code/zishutongji
在线字符统计与编辑工具：
http://tools.haodaima.com/code/char_tongji
希望本文所述对大家Python程序设计有所帮助。
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