How to break up document by sentences with with Spacy

The up-to-date answer is this:

from __future__ import unicode_literals, print_function
from spacy.lang.en import English # updated

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

From spacy's github support page

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]

Answer

import spacy
nlp = spacy.load('en_core_web_sm')

text = 'My first birthday was great. My 2. was even better.'
sentences = [i for i in nlp(text).sents]

Additional info
This assumes that you have already installed the model "en_core_web_sm" on your system. If not, you can easily install it by running the following command in your terminal:

$ python -m spacy download en_core_web_sm

(See here for an overview of all available models.)

Depending on your data this can lead to better results than just using spacy.lang.en.English. One (very simple) comparison example:

import spacy
from spacy.lang.en import English

nlp_simple = English()
nlp_simple.add_pipe(nlp_simple.create_pipe('sentencizer'))

nlp_better = spacy.load('en_core_web_sm')


text = 'My first birthday was great. My 2. was even better.'

for nlp in [nlp_simple, nlp_better]:
    for i in nlp(text).sents:
        print(i)
    print('-' * 20)

Outputs:

>>> My first birthday was great.
>>> My 2.
>>> was even better.
>>> --------------------
>>> My first birthday was great.
>>> My 2. was even better.
>>> --------------------