how to convert the topics into just a list of the top 20 words in each topic in LDA in python

I am currently working on LDA logarithm in python. I want to covert the topics into just a list of the top 20 words in each topic. I tried below code but got different output. I want my output in following format: topic=2,words=20.

['men', 'kill', 'soldier', 'order', 'patient', 'night', 'priest', 'becom', 'new', 'speech', 'friend', 'decid', 'young', 'ward', 'state', 'front', 'would', 'home', 'two', 'father']

["n't", 'go', 'fight', 'doe', 'home', 'famili', 'car', 'night', 'say', 'next', 'ask', 'day', 'want', 'show', 'goe', 'friend', 'two', 'polic', 'name', 'meet']

I got below output:

["(u'ngma', 0.034841332255132154)", "(u'video', 0.0073756817356584745)", "(u'youtube', 0.006524039676605746)", "(u'liked', 0.0065240394176856644)",]
["(u'ngma', 0.024537057880333127)", "(u'photography', 0.0068263432438681482)", "(u'tvallwhite', 0.0029535361359022566)", "(u'3', 0.0029252727655122079)"]

My code:

`ldamodel = Lda(doc_term_matrix, num_topics=2, id2word = dictionary,passes=50)
lda=ldamodel.print_topics(num_topics=2, num_words=3)

f=open('LDA.txt','w')
f.write(str(lda))
f.close()

topics_matrix = ldamodel.show_topics(formatted=False,num_words=10)
topics_matrix = np.array((topics_matrix),dtype=list)
topic_words = topics_matrix[:, 1]
for i in topic_words:
    print([str(word) for word in i])
    print()`

edit-1:

topic_words = []
for i in range(3):
    tt = ldamodel.get_topic_terms(i,10)
    topic_words.append([pair[0] for pair in tt])
    print topic_words

resulted in non expected output:

[[1897, 135, 130, 127, 70, 162, 445, 656, 608, 1019], [1897, 364, 56, 1236, 181, 172, 449, 48, 15, 18], [1897, 163, 11, 70, 166, 345, 480, 9, 60, 351]]