爲什麼NLTK庫中有不同的Lemmatizers？

Question

>> from nltk.stem import WordNetLemmatizer as lm1 
>> from nltk import WordNetLemmatizer as lm2 
>> from nltk.stem.wordnet import WordNetLemmatizer as lm3 

對我來說，三種方法的工作方式都是一樣的，但只是爲了確認，他們是否提供了不同的東西？

Answer 1

不，他們沒有不同，他們都是一樣的。

from nltk.stem import WordNetLemmatizer as lm1 
from nltk import WordNetLemmatizer as lm2 
from nltk.stem.wordnet import WordNetLemmatizer as lm3 

lm1 == lm2 
>>> True 


lm2 == lm3 
>>> True 


lm1 == lm3 
>>> True 

由於修正通過erip爲什麼發生這種情況是因爲：

該類（WordNetLemmatizer）是origanlly寫在nltk.stem.wordnet所以你可以做from nltk.stem.wordnet import WordNetLemmatizer as lm3

裏面還導入NLTK __init__.py file所以你可以做from nltk import WordNetLemmatizer as lm2

而且還導入__init__.py nltk.stem模塊所以你可以做from nltk.stem import WordNetLemmatizer as lm1

Answer 2

答案：他們都是一樣的。

inspect有用的工具來檢查對象是否是同一

>>> import inspect 
>>> from nltk.stem import WordNetLemmatizer as wnl1 
>>> from nltk.stem.wordnet import WordNetLemmatizer as wnl2 
>>> inspect.getfile(wnl1) 
'/Library/Python/2.7/site-packages/nltk/stem/wordnet.pyc' 
# They come from the same file: 
>>> inspect.getfile(wnl1) == inspect.getfile(wnl2) 
True 
>>> print inspect.getdoc(wnl1) 
WordNet Lemmatizer 

Lemmatize using WordNet's built-in morphy function. 
Returns the input word unchanged if it cannot be found in WordNet. 

    >>> from nltk.stem import WordNetLemmatizer 
    >>> wnl = WordNetLemmatizer() 
    >>> print(wnl.lemmatize('dogs')) 
    dog 
    >>> print(wnl.lemmatize('churches')) 
    church 
    >>> print(wnl.lemmatize('aardwolves')) 
    aardwolf 
    >>> print(wnl.lemmatize('abaci')) 
    abacus 
    >>> print(wnl.lemmatize('hardrock')) 
    hardrock 

您可以查看源代碼太：

>>> print inspect.getsource(wnl1) 
class WordNetLemmatizer(object): 
    """ 
    WordNet Lemmatizer 

    Lemmatize using WordNet's built-in morphy function. 
    Returns the input word unchanged if it cannot be found in WordNet. 

     >>> from nltk.stem import WordNetLemmatizer 
     >>> wnl = WordNetLemmatizer() 
     >>> print(wnl.lemmatize('dogs')) 
     dog 
     >>> print(wnl.lemmatize('churches')) 
     church 
     >>> print(wnl.lemmatize('aardwolves')) 
     aardwolf 
     >>> print(wnl.lemmatize('abaci')) 
     abacus 
     >>> print(wnl.lemmatize('hardrock')) 
     hardrock 
    """ 

    def __init__(self): 
     pass 

    def lemmatize(self, word, pos=NOUN): 
     lemmas = wordnet._morphy(word, pos) 
     return min(lemmas, key=len) if lemmas else word 

    def __repr__(self): 
     return '<WordNetLemmatizer>' 

# They have the same source code too: 
>>> print inspect.getsource(wnl1) == inspect.getsource(wnl2) 
True 

在NLTK進口的WordNetLemmatizer的結構如下：

\nltk 
    __init__.py 
    \stem. 
     __init__.py 
     wordnet.py  # This is where WordNetLemmatizer code resides. 

我們從其中最低的居住WordNetLemmatizer在nltk.stem.wordnet.pyhttps://github.com/nltk/nltk/blob/develop/nltk/stem/wordnet.py#L15，所以你可以做：

from nltk.stem.wordnet import WordNetLemmatizer 

從nltk.stem。 初始化的.py，我們看到在https://github.com/nltk/nltk/blob/develop/nltk/stem/init.py#L30上面的導入，使nltk.stem訪問WordNetLemmatizer，這樣就可以做

from nltk.stem import WordNetLemmatizer 

從nltk.__init__.py我們看到：

from nltk.stem import * 

這使最頂層nltk導入以訪問nltk.stem有權訪問的所有內容。因此，在頂層nltk，我們可以這樣做：

from nltk import WordNetLemmatizer 

---

但有一件事要注意，這是不總是對象/名稱相同的模塊是指NLTK同一個對象的情況下，例如：

>>> from nltk.corpus import wordnet as wn1 
>>> from nltk.corpus.reader import wordnet as wn2 
>>> wn1 == wn2 
False 

>>> wn1.synsets('dog') 
[Synset('dog.n.01'), Synset('frump.n.01'), Synset('dog.n.03'), Synset('cad.n.01'), Synset('frank.n.02'), Synset('pawl.n.01'), Synset('andiron.n.01'), Synset('chase.v.01')] 

>>> wn2.synsets('dog') 
Traceback (most recent call last): 
    File "<stdin>", line 1, in <module> 
AttributeError: 'module' object has no attribute 'synsets' 

第一共發現wn1是LazyCorpusLoader對象將在nltk_data打開WordNet的文件，它允許您訪問的同義詞集：https://github.com/nltk/nltk/blob/develop/nltk/corpus/init.py#L246

第二wn2是wordnet.py文件本身駐留在nltk.corpus.wordnet.py ：https://github.com/nltk/nltk/blob/develop/nltk/corpus/reader/wordnet.py

它會變得更加棘手時：

>>> from nltk.corpus import wordnet as wn1 
>>> from nltk.corpus.reader import wordnet as wn2 
>>> from nltk.stem import wordnet as wn3 
>>> wn3 == wn1 
False 
>>> wn3 == wn2 
False 

在wn3的情況下，它指的是包含WordNetLemmatizer的文件nltk.stem.wordnet.py，它與wordnet的wordnet語料庫對象或語料庫閱讀器無關。