? ? ? ? TextBlob（https://textblob.readthedocs.io/en/dev/index.html）是一個用于處理文本數據的Python庫。它提供一個簡單的API，可用于深入研究常見的NLP任務，如詞性標注、名詞短語提取、情感分析、文本翻譯、分類等。

官方文檔：https://textblob.readthedocs.io/en/dev/

目錄

1. 情感分析

2.詞性標注

3.?分詞和分句

4.?名詞短語列表

5. 詞形還原及詞干提取

（1）單復數

（2）Word 類

（3）WordNet：獲取近義詞

6. 拼寫矯正

（1）直接矯正

（2）Word 拼寫檢查

7. 單詞詞頻

（1）單詞詞頻

（2）短語頻次

8.?翻譯及語言檢測語言

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1. 情感分析

? ? ? ? 情感指的是隱藏在句子中的觀點，極性（polarity）定義句子中的消極性或積極性，主觀性（subjectivity）暗示句子的表達的含糊的、還是肯定的。

? ? ? ? 返回一個元組?Sentiment(polarity,?subjectivity).?

? ? ? ?polarity： [-1.0, 1.0].? ? ?-1.0 消極，1.0積極

? ? ? subjectivity： [0.0, 1.0]? ? ? 0.0 表示客觀，1.0表示主觀.

from textblob import TextBlobtext = "Textblob is amazingly simple to use. What great fun!" blob = TextBlob(text) # 創建一個textblob對象 from textblob import TextBlobresult = blob.sentiment # Sentiment(polarity=0.39166666666666666, subjectivity=0.4357142857142857)polarity = blob.sentiment.polarity # 0.39166666666666666

2.詞性標注

wiki = TextBlob("Python is a high-level, general-purpose programming language.") tag = wiki.tags# [('Python', 'NNP'), ('is', 'VBZ'), ('a', 'DT'), ('high-level', 'JJ'), ('general-purpose', 'JJ'), ('programming', 'NN'), ('language', 'NN')]

3.?分詞和分句

blob = TextBlob("Beautiful is better than ugly. ""Explicit is better than implicit. ""Simple is better than complex.")word = blob.words sentence = blob.sentences''' ['Beautiful', 'is', 'better', 'than', 'ugly', 'Explicit', 'is', 'better', 'than', 'implicit', 'Simple', 'is', 'better', 'than', 'complex'][Sentence("Beautiful is better than ugly."), Sentence("Explicit is better than implicit."), Sentence("Simple is better than complex.")] '''

4.?名詞短語列表

list = wiki.noun_phrases# ['python']

5. 詞形還原及詞干提取

（1）單復數

? ? ? ?singularize() 變單數， pluralize（）變復數，用在對名詞進行處理，且會考慮特殊名詞單復數形式

sentence = TextBlob('Use 4 spaces per indentation level.') word = sentence.wordsdanshu = word[2].singularize() # space fushu = word[-1].pluralize() # levels

（2）Word 類

? ? ?lemmatize() 方法? 對單詞進行詞形還原，名詞找單數，動詞找原型。所以需要一次處理名詞，一次處理動詞。

from textblob import Wordw1 = Word('apples') result1 = w1.lemmatize() # 默認只處理名詞 applew2 = Word('went') result2 = w2.lemmatize("v") # 對動詞原型處理 go

（3）WordNet：獲取近義詞

# 1.獲取近義詞 from textblob import Word from textblob.wordnet import VERB result1 = Word("hack").synsets result2 = Word("hack").get_synsets(pos=VERB) #get_synsets()： 只查找 該詞作為 動詞 的集合，參數為空時和synsets方法相同''' result1：[Synset('hack.n.01'), Synset('machine_politician.n.01'), Synset('hack.n.03'), Synset('hack.n.04'), Synset('cab.n.03'), Synset('hack.n.06'), Synset('hack.n.07'), Synset('hack.n.08'), Synset('chop.v.05'), Synset('hack.v.02'), Synset('hack.v.03'), Synset('hack.v.04'), Synset('hack.v.05'), Synset('hack.v.06'), Synset('hack.v.07'), Synset('hack.v.08')]result2：[Synset('chop.v.05'), Synset('hack.v.02'), Synset('hack.v.03'), Synset('hack.v.04'), Synset('hack.v.05'), Synset('hack.v.06'), Synset('hack.v.07'), Synset('hack.v.08')] '''2. 獲取近義詞的定義 defi = result1[1].definition() # 獲取定義#defi結果： a politician who belongs to a small clique that controls a political party for private rather than public ends3. 獲取單詞本身的定義 defi = Word("octopus").definitions# ['tentacles of octopus prepared as food', 'bottom-living cephalopod having a soft oval body with eight long tentacles']

6. 拼寫矯正

（1）直接矯正

b = TextBlob("I havv goood speling!") b_corr = b.correct() print(b_corr) # I have good spelling!

（2）Word 拼寫檢查

? ? ? word.spellcheck()方法，返回帶有拼寫建議的（word，confidence）元組列表

from textblob import Word w = Word('falibility') w_ = w.spellcheck() print(w_) # [('fallibility', 1.0)]

7. 單詞詞頻

（1）單詞詞頻

monty = TextBlob("We are no longer the Knights who say Ni. ""We are now the Knights who say Ekki ekki ekki PTANG.")#（1）方式1 counts = monty.word_counts['ekki'] # 不區分大小寫 print(counts) # 3 #（2）方式2 counts2 = monty.words.count('ekki') print(counts2) # 3#（3）方式3 counts3 = monty.words.count('ekki', case_sensitive=True) # 設置大小寫敏感，默認不區分 print(counts3) # 2

（2）短語頻次

counts4 = wiki.noun_phrases.count('python') # 短語頻次 print(counts4) # 1

8.?翻譯及語言檢測語言

en_blob = TextBlob('Simple is better than complex.') lang = en_blob.translate(to='es') # from_lang默認 en print(lang) # TextBlob("Simple es mejor que complejo.")chinese_blob = TextBlob("美麗優于丑陋") lang = chinese_blob.translate(from_lang="zh-CN", to='en') print(lang) # TextBlob("Beautiful is better than ugly")

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