解决spacy3.2报错：Can‘t find model ‘en‘.

（1）下载spacy一直没成功，把​​pip install spacy​​​改成​​conda install spacy​​​就可以了；
（2）在命令行输入 ​​​python3 -m spacy download en​​​ 来下载英语语言包（如果是其他语言则下载其他包了），不过​​en​​​现在最好用全称​​en_core_web_sm​​​，这一步也可以先下载tar再​​pip install en_core_web_md-2.2.5.tar.gz​​（但是注意把文件放对路径）。

然后测试下代码：

import spacy
import nltk

# load spacy's English-language models
en_nlp = spacy.load('en')
# instantiate nltk's Porter stemmer
stemmer = nltk.stem.PorterStemmer()

# define function to compare lemmatization in spacy with stemming in nltk
def compare_normalization(doc):
    # tokenize document in spacy
    doc_spacy = en_nlp(doc)
    # print lemmas found by spacy
    print("Lemmatization:")
    print([token.lemma_ for token in doc_spacy])
    # print tokens found by Porter stemmer
    print("Stemming:")
    print([stemmer.stem(token.norm_.lower()) for token in doc_spacy])

发现又报错：

OSError: [E941] Can't find model 'en'. 
It looks like you're trying to load a model from a shortcut, 
which is obsolete as of spaCy v3.0. 
To load the model, use its full name instead:

nlp = spacy.load("en_core_web_sm")

For more details on the available models, see the models directory: 
https://spacy.io/models. 
If you want to create a blank model, use spacy.blank: nlp = spacy.blank("en")

是说上面load model的方法是spacy 3.0版本以前才这么用的，要改成​​nlp = spacy.load("en_core_web_sm")​​，然后就ok了，得到对应的spacy中的词形还原与nltk中的词干提取的对比结果：

Lemmatization:
['our', 'meeting', 'today', 'be', 'bad', 'than', 'yesterday', ',', 'I', 'be', 'scared', 'of', 'meet', 'the', 'client', 'tomorrow', '.']
Stemming:
['our', 'meet', 'today', 'wa', 'wors', 'than', 'yesterday', ',', 'i', 'am', 'scare', 'of', 'meet', 'the', 'client', 'tomorrow', '.']