TextBlob 是一款 Pythonic 的文本处理工具,用于处理文本数据,它提供了一个简单的 API,用于潜入常见的自然语言处理(NLP)任务,如词性标注、名词短语提取、情感分析、分类等
TextBlob是一个用Python编写的开源的文本处理库。它可以用来执行很多自然语言处理的任务,比如,词性标注,名词性成分提取,情感分析,文本翻译,等等,仅为英文分析。
中文则可以使用SnowNLP,能够方便的处理中文文本内容,是受到了TextBlob的启发而写的。
pip install textblob
import textblob
text1 = "No matter how many characters are available for your password you should be sure to use every one of them. " \
"The more characters available for your password and the more you use makes it that much harder to figure out the combination. " \
"Always make use of all characters available for a strong and secure password."
#1.利用textblob的TextBlob生成一个模型
blob1 = textblob.TextBlob(text1)
#sentences方法进行分句
sentences1 = blob1.sentences
print("1.分句是:",sentences1)
1.分句是: [Sentence("No matter how many characters are available for your password you should be sure to use every one of them."), Sentence("The more characters available for your password and the more you use makes it that much harder to figure out the combination."), Sentence("Always make use of all characters available for a strong and secure password.")]
(1)积极(polarity) / 消极 值越大,越积极(-1,1)
(2)主观(subjectivity)/客观 值越大,越主观(0,1)
注:生成的是俩个数值
import textblob
text = "JacksonYee is very handsome "
blob = textblob.TextBlob(text)
result_sentiment = blob.sentiment
print(result_sentiment)
Sentiment(polarity=0.65, subjectivity=1.0)
import textblob
text = "mike is very ugly "
blob = textblob.TextBlob(text)
result_sentiment = blob.sentiment
print(result_sentiment)
Sentiment(polarity=-0.9099999999999999, subjectivity=1.0)
textblob有着很多功能,欢迎大家前去探索!!!
参考文档:https://textblob.readthedocs.io/en/dev/