Noun phrases with spacy

Question

How can I extract noun phrases from text using spacy?
I am not referring to part of speech tags. In the documentation I cannot find anything about noun phrases or regul

Answer 1

import spacy
nlp = spacy.load("en_core_web_sm")
doc =nlp('Bananas are an excellent source of potassium.')
for np in doc.noun_chunks:
    print(np.text)
'''
  Bananas
  an excellent source
  potassium
'''

for word in doc:
    print('word.dep:', word.dep, ' | ', 'word.dep_:', word.dep_)
'''
  word.dep: 429  |  word.dep_: nsubj
  word.dep: 8206900633647566924  |  word.dep_: ROOT
  word.dep: 415  |  word.dep_: det
  word.dep: 402  |  word.dep_: amod
  word.dep: 404  |  word.dep_: attr
  word.dep: 443  |  word.dep_: prep
  word.dep: 439  |  word.dep_: pobj
  word.dep: 445  |  word.dep_: punct
'''

from spacy.symbols import *
np_labels = set([nsubj, nsubjpass, dobj, iobj, pobj])
print('np_labels:', np_labels)
'''
  np_labels: {416, 422, 429, 430, 439}
'''

https://www.geeksforgeeks.org/use-yield-keyword-instead-return-keyword-python/

def iter_nps(doc):
    for word in doc:
        if word.dep in np_labels:
            yield(word.dep_)

iter_nps(doc)
'''
  
'''

## Modified method:
def iter_nps(doc):
    for word in doc:
        if word.dep in np_labels:
            print(word.text, word.dep_)

iter_nps(doc)
'''
  Bananas nsubj
  potassium pobj
'''

doc = nlp('BRCA1 is a tumor suppressor protein that functions to maintain genomic stability.')
for np in doc.noun_chunks:
    print(np.text)
'''
  BRCA1
  a tumor suppressor protein
  genomic stability
'''

iter_nps(doc)
'''
  BRCA1 nsubj
  that nsubj
  stability dobj
'''