如何在使用spaCy时同时删除停用词和词汇化？

import spacy
from spacy.lang.en.stop_words import STOP_WORDS
from spacy.lang.en import English

nlp = spacy.load('en_core_web_sm')
stop_words = spacy.lang.en.stop_words.STOP_WORDS

def process_text(text):
    # 分词
    tokens = nlp(text)
    
    # 删除停用词和标点符号
    tokens = [token.text.lower() for token in tokens if token.text.lower() not in stop_words and not token.is_punct]
    
    # 词汇化
    tokens = [token.lemma_ for token in tokens]
    
    return tokens

text = "This is an example sentence."
processed_text = process_text(text)
print(processed_text)

['example', 'sentence']