拼音检查python

#coding=utf-8
#!/usr/bin/python

import sys, re, collections

#读入文件
def read_file(filename):
    try:
        fp = open(filename)
        text = fp.read()
    except IOError:
        print ("Error opening or reading input file: ",filename)
        sys.exit()
    return text

#分割文件为单词，并将字母都转换为小写
def words(text):
    return re.findall('[a-z]+', text.lower())

# 该函数计算输入文本每个单词出现的次数
def train(features):
    # 生成了一个默认value=1的带key的数据字典
    model = collections.defaultdict(lambda: 1)
    for f in features:
        model[f] += 1
    return model

# big文本中每一个单词及其出现的次数
NWORDS = train(words(read_file('/home/aistudio/data/data12892/big.txt')))

alphabet = 'abcdefghijklmnopqrstxyz'
# 变换输入单词形式，得到那种是最可能的错误
def edist1(word):
    n = len(word)
    return set([word[0:i]+word[i+1: ] for i in range(n)] +                      #删除
               [word[0:i]+word[i+1]+word[i]+word[i+2: ] for i in range(n-1)] +  #错位
               [word[0:i]+c+word[i+1: ] for i in range(n) for c in alphabet] +  #变换
               [word[0:i]+c+word[i: ] for i in range(n+1) for c in alphabet])   #添加
# 在edist1的基础上进一步变换,要去是出现在字典内的词
def known_edist2(word):
    return set(e2 for e1 in edist1(word) for e2 in edist1(e1) if e2 in NWORDS)
# big.txt中已知的单词集合
def known(words):
    wordintxt = set([])
    for w in words:
        if w in NWORDS:
            wordintxt.add(w)
    return wordintxt
    # return set(w for w in words if w in NWORDS)

def correct(word):
    candidates = known([word]) or known(edist1(word)) or known_edist2(word) or [word]
    return max(candidates, key=lambda w:NWORDS[w])

print (correct("acacss"))