Extracting all Nouns from a text file using nltk

Question

Is there a more efficient way of doing this? My code reads a text file and extracts all Nouns.

import nltk

File = open(fileName) #open file
lines = File.rea         


        

Answer 1

import nltk

lines = 'lines is some string of words'
# function to test if something is a noun
is_noun = lambda pos: pos[:2] == 'NN'
# do the nlp stuff
tokenized = nltk.word_tokenize(lines)
nouns = [word for (word, pos) in nltk.pos_tag(tokenized) if is_noun(pos)] 

print nouns
>>> ['lines', 'string', 'words']

Useful tip: it is often the case that list comprehensions are a faster method of building a list than adding elements to a list with the .insert() or append() method, within a 'for' loop.