spacy2.py

from spacy.lang.en import English

# Load English tokenizer, tagger, parser, NER and word vectors
nlp = English()

# Create the pipeline 'sentencizer' component
sbd = nlp.create_pipe('sentencizer')

# Add the component to the pipeline
nlp.add_pipe(sbd)

text = """Founded in 2002, SpaceX’s mission is to enable humans to become a spacefaring civilization and a multi-planet 
species by building a self-sustaining city on Mars. In 2008, SpaceX’s Falcon 1 became the first privately developed 
liquid-fuel launch vehicle to orbit the Earth."""

#  "nlp" Object is used to create documents with linguistic annotations.
doc = nlp(text)

# create list of sentence tokens
sents_list = []
for sent in doc.sents:
    sents_list.append(sent.text)
sents_list