gistfile1.txt

import re, string, sys, nltk, timeit
from nltk.stem.wordnet import WordNetLemmatizer
from nltk.corpus import wordnet
from joblib import Parallel, delayed
 
lmtzr = WordNetLemmatizer()
pattern=re.compile(r'[^a-zA-Z ]')
 
tag_to_type = {'J': wordnet.ADJ, 'V': wordnet.VERB, 'R': wordnet.ADV}
def get_wordnet_pos(treebank_tag):
    return tag_to_type.get(treebank_tag[:1], wordnet.NOUN)

def clean(text):
    text = pattern.sub('', text.lower().replace('<image>', '').replace('\r', '').replace('\n', ''))
    words = nltk.word_tokenize(text)
    tags = nltk.pos_tag(words)
    return ' '.join(
        lmtzr.lemmatize(word, get_wordnet_pos(tag[1]))
        for word, tag in zip(words, tags)
    )
 
def final_clean(x):
    if 'applnabstract' in x:
        print('Skipping header.')
    else:
        a = x.split(',',1)
        if len(a)==2:
            c = a[1].replace(',','')
            b = clean(c)
            return b

tic = timeit.default_timer()
with open("abstracts.txt","rb") as f:
    head = f.readlines(1000)
    abstracts = Parallel(n_jobs=32)(delayed(final_clean)(line) for line in head)
    f.close()
toc = timeit.default_timer()
time = toc-tic
print('Writing to file now. %s abstracts processed in %s seconds.' % (len(abstracts),time))
with open("abstractsfinal.txt","w") as f:
    f.truncate()
    for item in abstracts:
        print>>f, item
    f.close()