# Removing all stopwords from a list of words

What is the fastest Pythonic way to remove all stopwords from a list of words in a document? Right now I am using a list comprehension that contains a for loop.

from nltk.corpus import stopwords

''' Push stopwords to a list '''
stop = stopwords.words('english')
Document = ' Some huge text .......................... '
''' Tokenize the doc '''
words = nltk.word_tokenize(Document)
''' Comparing two lists '''
stopwordsfree_words = [word for word in words if word not in stop]


Is there a faster way to do this?

If stop is a list containing $s$ stopwords, and words is a list containing $w$ words, then the loop in the list comprehension will be $O(w s)$, since it basically has to iterate over both lists in a nested loop.
However, if you make the stopwords into a set
stop = set(stopwords.words('english'))

… then each lookup can be done in $O(1)$ time. You would get $O(w)$ running time just by changing the data structure like that.
Another minor issue is that by convention, Document should be lowercase, because it is a variable rather than a class.