Sentence tokenization in spaCy?

While trying to do sentence tokenization in spaCy, I ran into the following problem while trying to tokenize sentences:

from __future__ import unicode_literals, print_function
from spacy.en import English
nlp = English()
doc = nlp('Hello, world. Here are two sentences.')
sentence = doc.sents.next()

It was unclear to me how to get the text of the sentence object. I tried using dir() to find a method that would allow this and was unsuccessful. Any code that I have found from others trying to do sentence tokenization doesn’t seem to function properly.

[honnibal]

Argh.

The last snippet I sent you was wrong — sorry, it’s late and I was hasty.

from __future__ import unicode_literals, print_function
from spacy.en import English

raw_text = 'Hello, world. Here are two sentences.'
nlp = English()
doc = nlp(raw_text)
sentences = [sent.string.strip() for sent in doc.sents]

The Doc object has an attribute, sents, which gives you Span objects for the sentences.

[honnibal]

from __future__ import unicode_literals, print_function
from spacy.en import English

raw_text = 'Hello, world. Here are two sentences.'
nlp = English()
doc = nlp(raw_text)
sentences = [sent.string.strip() for sent in doc]