nltk.tokenize.WordPunctTokenizer

class nltk.tokenize.WordPunctTokenizer

Bases: RegexpTokenizer

Tokenize a text into a sequence of alphabetic and non-alphabetic characters, using the regexp \w+|[^\w\s]+.

>>> from nltk.tokenize import WordPunctTokenizer
>>> s = "Good muffins cost $3.88\nin New York.  Please buy me\ntwo of them.\n\nThanks."
>>> WordPunctTokenizer().tokenize(s)
['Good', 'muffins', 'cost', '$', '3', '.', '88', 'in', 'New', 'York',
'.', 'Please', 'buy', 'me', 'two', 'of', 'them', '.', 'Thanks', '.']

__init__()

span_tokenize(text)

Identify the tokens using integer offsets (start_i, end_i), where s[start_i:end_i] is the corresponding token.

Return type

Iterator[Tuple[int, int]]

span_tokenize_sents(strings: List[str]) → Iterator[List[Tuple[int, int]]]

Apply self.span_tokenize() to each element of strings. I.e.:

return [self.span_tokenize(s) for s in strings]

Yield

List[Tuple[int, int]]

Parameters

strings (List[str]) –

Return type

Iterator[List[Tuple[int, int]]]

tokenize(text)

Return a tokenized copy of s.

Return type

List[str]

tokenize_sents(strings: List[str]) → List[List[str]]

Apply self.tokenize() to each element of strings. I.e.:

return [self.tokenize(s) for s in strings]

Return type

List[List[str]]

Parameters

strings (List[str]) –