NLTK的安装教程及安装错误解决方案
成功解决NLTK包的安装错误
- 创建环境
NLP_Pre_train
l环境
conda create -n NLP_Pre_train python=3.8
- 激活
conda activate NLP_Pre_train
- 安装NLTK,套用以下命令
pip install NLTK
- 之后是验证NLTK是否安装成功,采用的步骤如下所示:
import nltk
nltk.download()
但是不出意外的是,很多人出现的错误,如下所示:
为了解决此项问题,我们可以采用离线安装的方式进行解决。
NLTK的离线安装
- 首先现在离线安装包,我们直接去官网进行下载:https://GitHub.com/nltk/nltk_data,安装的文件,如下所示:
- 我们将下载的文件存放的位置如下所示
- 我们将下载的以下文件文件,放进文件2所展示的位置,这样便大功告成!
NLTK的验证
我们可以打印出,NLTK的英文停用词(STOP Word)。
from nltk.corpus import stopwords
print(stopwords.words('english'))
打印结果如下所示:
['i', 'me', 'my', 'myself', 'we', 'our', 'ours', 'ourselves', 'you', "you're",
"you've", "you'll", "you'd", 'your', 'yours', 'yourself', 'yourselves', 'he',
'him', 'his', 'himself', 'she', "she's", 'her', 'hers', 'herself', 'it', "it's",
'its', 'itself', 'they', 'them', 'their', 'theirs', 'themselves', 'what', 'which',
'who', 'whom', 'this', 'that', "that'll", 'these', 'those', 'am', 'is', 'are',
'was', 'were', 'be', 'been', 'being', 'have', 'has', 'had', 'having', 'do',
'does', 'did', 'doing', 'a', 'an', 'the', 'and', 'but', 'if', 'or', 'because',
'as', 'until', 'while', 'of', 'at', 'by', 'for', 'with', 'about', 'against',
'between', 'into', 'through', 'during', 'before', 'after', 'above', 'below',
'to', 'from', 'up', 'down', 'in', 'out', 'on', 'off', 'over', 'under', 'again',
'further', 'then', 'once', 'here', 'there', 'when', 'where', 'why', 'how',
'all', 'any', 'both', 'each', 'few', 'more', 'most', 'other', 'some', 'such', 'no',
'nor', 'not', 'only', 'own', 'same', 'so', 'than', 'too', 'very', 's', 't',
'can', 'will', 'just', 'don', "don't", 'should', "should've", 'now', 'd', 'll',
'm', 'o', 're', 've', 'y', 'ain', 'aren', "aren't", 'couldn', "couldn't",
'didn', "didn't", 'doesn', "doesn't", 'hadn', "hadn't", 'hasn', "hasn't",
'haven', "haven't", 'isn', "isn't", 'ma', 'mightn', "mightn't", 'mustn',
"mustn't", 'needn', "needn't", 'shan', "shan't", 'shouldn', "shouldn't",
'wasn', "wasn't", 'weren', "weren't", 'won', "won't", 'wouldn', "wouldn't"
本文详细介绍了NLTK的安装方法和常见错误解决方案,对初学者很有帮助。另外,本文还对比了NLTK和其他自然语言处理工具的优缺点,为读者提供了选型参考。总的来说,NLTK是一款功能强大、易于使用的自然语言处理工具,值得学习和使用。
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