<filename>nlp/simple/spacy.py
# import pandas as pd
# print(pd.__version__)


# import spacy as spacy
# print(spacy)
# nlp = spacy.load("en_core_web_sm")
# doc = nlp("yee yee yeeeeeet")
# for token in doc:
#     print(token.text, token.pos_, token.dep_)
# from spacy.lemmatizer import Lemmatizer
# from spacy.lemmatizer import Lemmatizer
# from spacy.lookups import Lookups
# lemmatizer = Lemmatizer()
# word_list = ['feet', 'foot', 'foots', 'footing']
# lemmatized = [lemmatizer.lookup(word) for word in word_list]
# print(lemmatized)

<filename>nlp/simple/spacy.py
# import pandas as pd
# print(pd.__version__)


# import spacy as spacy
# print(spacy)
# nlp = spacy.load("en_core_web_sm")
# doc = nlp("yee yee yeeeeeet")
# for token in doc:
#     print(token.text, token.pos_, token.dep_)
# from spacy.lemmatizer import Lemmatizer
# from spacy.lemmatizer import Lemmatizer
# from spacy.lookups import Lookups
# lemmatizer = Lemmatizer()
# word_list = ['feet', 'foot', 'foots', 'footing']
# lemmatized = [lemmatizer.lookup(word) for word in word_list]
# print(lemmatized)

# import pandas as pd # print(pd.__version__) # import spacy as spacy # print(spacy) # nlp = spacy.load("en_core_web_sm") # doc = nlp("yee yee yeeeeeet") # for token in doc: #     print(token.text, token.pos_, token.dep_) # from spacy.lemmatizer import Lemmatizer # from spacy.lemmatizer import Lemmatizer # from spacy.lookups import Lookups # lemmatizer = Lemmatizer() # word_list = ['feet', 'foot', 'foots', 'footing'] # lemmatized = [lemmatizer.lookup(word) for word in word_list] # print(lemmatized)