python - 大きな文字列を、Pythonを介して「n」個の単語を含む複数のサブ文字列に分割します

Question

ソーステキスト：米国独立宣言

上記のソーステキストを、「n」個の単語を含むいくつかのサブ文字列に分割するにはどうすればよいですか？

split（''）を使用して各単語を抽出しますが、1回の操作で複数の単語を使用してこれを行う方法がわかりません。

自分が持っている単語のリストを調べて、最初のリストの単語を（スペースを追加しながら）接着することで別の単語を作成できます。しかし、私の方法はあまりPython的ではありません。

Answer 1

text = """
When in the course of human Events, it becomes necessary for one People to dissolve the Political Bands which have connected them with another, and to assume among the Powers of the Earth, the separate and equal Station to which the Laws of Nature and of Nature?s God entitle them, a decent Respect to the Opinions of Mankind requires that they should declare the causes which impel them to the Separation.

We hold these Truths to be self-evident, that all Men are created equal, that they are endowed by their Creator with certain unalienable Rights, that among these are Life, Liberty, and the pursuit of Happiness?-That to secure these Rights, Governments are instituted among Men, deriving their just Powers from the Consent of the Governed, that whenever any Form of Government becomes destructive of these Ends, it is the Right of the People to alter or abolish it, and to institute a new Government, laying its Foundation on such Principles, and organizing its Powers in such Form, as to them shall seem most likely to effect their Safety and Happiness. Prudence, indeed, will dictate that Governments long established should not be changed for light and transient Causes; and accordingly all Experience hath shewn, that Mankind are more disposed to suffer, while Evils are sufferable, than to right themselves by abolishing the Forms to which they are accustomed. But when a long Train of Abuses and Usurpations, pursuing invariably the same Object, evinces a Design to reduce them under absolute Despotism, it is their Right, it is their Duty, to throw off such Government, and to provide new Guards for their future Security. Such has been the patient Sufferance of these Colonies; and such is now the Necessity which constrains them to alter their former Systems of Government. The History of the Present King of Great-Britain is a History of repeated Injuries and Usurpations, all having in direct Object the Establishment of an absolute Tyranny over these States. To prove this, let Facts be submitted to a candid World.
"""

words = text.split()
subs = []
n = 4
for i in range(0, len(words), n):
    subs.append(" ".join(words[i:i+n]))
print subs[:10]

プリント：

['When in the course', 'of human Events, it', 'becomes necessary for one', 'People to dissolve the', 'Political Bands which have', 'connected them with another,', 'and to assume among', 'the Powers of the', 'Earth, the separate and', 'equal Station to which']

または、リスト内包として：

subs = [" ".join(words[i:i+n]) for i in range(0, len(words), n)]

Answer 2

n-gramを作成しようとしていますか？NLTKを使用してこれを行う方法は次のとおりです。

punct = re.compile(r'^[^A-Za-z0-9]+|[^a-zA-Z0-9]+$')
is_word=re.compile(r'[a-z]', re.IGNORECASE)
sentence_tokenizer = nltk.data.load('tokenizers/punkt/english.pickle')
word_tokenizer=nltk.tokenize.punkt.PunktWordTokenizer()

def get_words(sentence):
    return [punct.sub('',word) for word in word_tokenizer.tokenize(sentence) if is_word.search(word)]

def ngrams(text, n):
    for sentence in sentence_tokenizer.tokenize(text.lower()):
        words = get_words(sentence)
        for i in range(len(words)-(n-1)):
            yield(' '.join(words[i:i+n]))

それで

for ngram in ngrams(sometext, 3):
    print ngram

Answer 3

大きな文字列の場合、速度とメモリフットプリントが少ないため、イテレータをお勧めします。

import re, itertools

# Original text
text = "When in the course of human Events, it becomes necessary for one People to dissolve the Political Bands which have connected them with another, and to assume among the Powers of the Earth, the separate and equal Station to which the Laws of Nature and of Nature?s God entitle them, a decent Respect to the Opinions of Mankind requires that they should declare the causes which impel them to the Separation."
n = 10

# An iterator which will extract words one by one from text when needed
words = itertools.imap(lambda m:m.group(), re.finditer(r'\w+', text))
# The final iterator that combines words into n-length groups
word_groups = itertools.izip_longest(*(words,)*n)

for g in word_groups: print g

次の結果が得られます。

('When', 'in', 'the', 'course', 'of', 'human', 'Events', 'it', 'becomes', 'necessary')
('for', 'one', 'People', 'to', 'dissolve', 'the', 'Political', 'Bands', 'which', 'have')
('connected', 'them', 'with', 'another', 'and', 'to', 'assume', 'among', 'the', 'Powers')
('of', 'the', 'Earth', 'the', 'separate', 'and', 'equal', 'Station', 'to', 'which')
('the', 'Laws', 'of', 'Nature', 'and', 'of', 'Nature', 's', 'God', 'entitle')
('them', 'a', 'decent', 'Respect', 'to', 'the', 'Opinions', 'of', 'Mankind', 'requires')
('that', 'they', 'should', 'declare', 'the', 'causes', 'which', 'impel', 'them', 'to')
('the', 'Separation', None, None, None, None, None, None, None, None)