Faster way to remove stop words in Python

Question

I am trying to remove stopwords from a string of text:

from nltk.corpus import stopwords
text = 'hello bye the the hi'
text = ' '.join([word for word in text.split() if word not in (stopwords.words('english'))])

I am processing 6 mil of such strings so speed is important. Profiling my code, the slowest part is the lines above, is there a better way to do this? I'm thinking of using something like regex's re.sub but I don't know how to write the pattern for a set of words. Can someone give me a hand and I'm also happy to hear other possibly faster methods.

Note: I tried someone's suggest of wrapping stopwords.words('english') with set() but that made no difference.

Thank you.

Answer 1

Try caching the stopwords object, as shown below. Constructing this each time you call the function seems to be the bottleneck.

    from nltk.corpus import stopwords

    cachedStopWords = stopwords.words("english")

    def testFuncOld():
        text = 'hello bye the the hi'
        text = ' '.join([word for word in text.split() if word not in stopwords.words("english")])

    def testFuncNew():
        text = 'hello bye the the hi'
        text = ' '.join([word for word in text.split() if word not in cachedStopWords])

    if __name__ == "__main__":
        for i in xrange(10000):
            testFuncOld()
            testFuncNew()

I ran this through the profiler: python -m cProfile -s cumulative test.py. The relevant lines are posted below.

nCalls Cumulative Time

10000 7.723 words.py:7(testFuncOld)

10000 0.140 words.py:11(testFuncNew)

So, caching the stopwords instance gives a ~70x speedup.