python中，可以把多行代碼簡化為一行，把for循環和if條件判斷都集中到一行裏來寫，示例如下：

>>> from nltk.corpus import stopwords
>>> english_stopwords = stopwords.words(‘english‘)#加載nltk中的英文停用詞數據
#創建一個列表，內含3個單詞列表
>>> texts_tokenized = [[‘writing‘, ‘ii‘, ‘rhetorical‘, ‘composing‘, ‘rhetorical‘, ‘composing‘],[‘engages
 
‘, ‘series‘, ‘interactive‘, ‘reading‘],[‘research‘, ‘composing‘, ‘activities‘, ‘along‘, ‘assignments‘, ‘designed‘, ‘help‘]]
#用多行代碼對texts_tokenized去停用詞
>>> text_filtered_stopwords = [[word for word in document if not word in english_stopwords] for document in texts_tokenized]
>>> text_filtered_stopwords
[[
 
‘writing‘, ‘ii‘, ‘rhetorical‘, ‘composing‘, ‘rhetorical‘, ‘composing‘], [‘engages‘, ‘series‘, ‘interactive‘, ‘reading‘], [‘research‘, ‘composing‘, ‘activities‘, ‘along‘, ‘assignments‘, ‘designed‘, ‘help‘]]

然後改成用多行的常規寫法：

>>> texts_tokenized = [[‘writing‘, ‘ii‘, ‘rhetorical‘, ‘composing‘, ‘
 
rhetorical‘, ‘composing‘],[‘engages‘, ‘series‘, ‘interactive‘, ‘reading‘],[‘research‘, ‘composing‘, ‘activities‘, ‘along‘, ‘assignments‘, ‘designed‘, ‘help‘]]
>>> documents = []
>>> texts_filtered_stopwords =[]
>>> for document in texts_tokenized:
    　　for word in document:
        　　if word not in english_stopwords:
            　　documents.append(word)
    　　texts_filtered_stopwords.append(document)

    
>>> texts_filtered_stopwords
[[‘writing‘, ‘ii‘, ‘rhetorical‘, ‘composing‘, ‘rhetorical‘, ‘composing‘], [‘engages‘, ‘series‘, ‘interactive‘, ‘reading‘], [‘research‘, ‘composing‘, ‘activities‘, ‘along‘, ‘assignments‘, ‘designed‘, ‘help‘]]

可以看到得出一樣的結果，但是代碼的效率和簡潔程度大大提升

python多行代碼簡化