i am trying to make an inversed document index, therefore i need to know from all unique words in a collection in which doc they occur and how often.
i have used this answer in order two create a nested dictionary. The provided solution works fine, with one problem though.
First i open the file and make a list of unique words. These unique words i than want to compare with the original file. When there is a match, the frequency counter should be updated and its value be stored in the two dimensional array.
output should eventually look like this:
word1, {doc1 : freq}, {doc2 : freq} <br>
word2, {doc1 : freq}, {doc2 : freq}, {doc3:freq}
etc....
Problem is that i cannot update the dictionary variable. When trying to do so i get the error:
File "scriptV3.py", line 45, in main
freq = dictionary[keyword][filename] + 1
TypeError: unsupported operand type(s) for +: 'AutoVivification' and 'int'
I think i need to cast in some way the instance of AutoVivification to int....
How to go?
thanks in advance
my code:
#!/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()
I agree you should avoid the extra classes, and especially
__getitem__
. (Small conceptual errors can make__getitem__
or__getattr__
quite painful to debug.)Python
dict
seems quite strong enough for what you are doing.What about straightforward
dict.setdefault
Of course this would be where
dictionary
is just adict
, and not something fromcollections
or a custom class of your own.Then again, isn't this just:
No reason to isolate unique instances, since the dict forces unique keys anyway.
that is not a correct usage i guess, instead try this:
Because, checking the value of a non-existing key raise KeyError. :so You must check if key exists in dictionary...