从列表中删除重复项时遇到问题

Question

Having a brain-fart here probably. I'm getting a list using generators and I have trouble removing duplicates from my list the usual way using set

import spacy
import textacy

nlp = spacy.load("en_core_web_lg")
text = ('''The Western compulsion to hedonism has made us lust for money just to show that we have it. Possessions do not make a man—man makes possessions. The Western compulsion to hedonism has made us lust for money just to show that we have it. Possessions do not make a man—man makes possessions.''')
doc = nlp(text)

keywords = list(textacy.extract.ngrams(doc, 1, filter_stops=True, filter_punct=True, filter_nums=False)) + list(textacy.extract.ngrams(doc, 2, filter_stops=True, filter_punct=True, filter_nums=False))

print(list(set(keywords)))

the result contains duplicates:

[man, lust, makes possessions, man, Possessions, makes possessions, man makes, hedonism, man, money, compulsion, Western compulsion, man, possessions, man makes, compulsion, Possessions, Western compulsion, possessions, Western, makes, makes, lust, hedonism, Western, money]

Answer 1

That's because the the items in your list aren't strings, so they aren't actually duplicates.

>>> type(keywords[0])
spacy.tokens.span.Span

To only get the duplicate words, you can use a dictionary comprehension with their string representations as the unique keys, and then just take out the spacy objects with .values() :

uniques = list({keyword.__repr__(): keyword for keyword in keywords}.values())