我正在尝试制作一个反向文档索引,因此我需要从集合中的所有唯一单词中知道它们出现在哪个文档中以及它们出现的频率。
我已经使用了这个答案来创建一个嵌套字典。提供的解决方案工作正常,但有一个问题。
首先,我打开文件并列出唯一单词。这些独特的词我想与原始文件进行比较。当有匹配时,频率计数器应该被更新并且它的值被存储在二维数组中。
输出最终应如下所示:
word1, {doc1 : freq}, {doc2 : freq} <br>
word2, {doc1 : freq}, {doc2 : freq}, {doc3:freq}
etc....
问题是我无法更新字典变量。尝试这样做时,我收到错误:
File "scriptV3.py", line 45, in main
freq = dictionary[keyword][filename] + 1
TypeError: unsupported operand type(s) for +: 'AutoVivification' and 'int'
我想我需要以某种方式将 AutoVivification 的实例转换为 int....
怎么去?
提前致谢
我的代码:
#!/usr/bin/env python
# encoding: utf-8
import sys
import os
import re
import glob
import string
import sets
class AutoVivification(dict):
"""Implementation of perl's autovivification feature."""
def __getitem__(self, item):
try:
return dict.__getitem__(self, item)
except KeyError:
value = self[item] = type(self)()
return value
def main():
pad = 'temp/'
dictionary = AutoVivification()
docID = 0
for files in glob.glob( os.path.join(pad, '*.html') ): #for all files in specified folder:
docID = docID + 1
filename = "doc_"+str(docID)
text = open(files, 'r').read() #returns content of file as string
text = extract(text, '<pre>', '</pre>') #call extract function to extract text from within <pre> tags
text = text.lower() #all words to lowercase
exclude = set(string.punctuation) #sets list of all punctuation characters
text = ''.join(char for char in text if char not in exclude) # use created exclude list to remove characters from files
text = text.split() #creates list (array) from string
uniques = set(text) #make list unique (is dat handig? we moeten nog tellen)
for keyword in uniques: #For every unique word do
for word in text: #for every word in doc:
if (word == keyword and dictionary[keyword][filename] is not None): #if there is an occurence of keyword increment counter
freq = dictionary[keyword][filename] #here we fail, cannot cast object instance to integer.
freq = dictionary[keyword][filename] + 1
print(keyword,dictionary[keyword])
else:
dictionary[word][filename] = 1
#extract text between substring 1 and 2
def extract(text, sub1, sub2):
return text.split(sub1, 1)[-1].split(sub2, 1)[0]
if __name__ == '__main__':
main()