.. Copyright (C) 2001-2022 NLTK Project
.. For license information, see LICENSE.TXT

==========
 Stemmers
==========

Overview
~~~~~~~~

Stemmers remove morphological affixes from words, leaving only the
word stem.

    >>> from nltk.stem import *

Unit tests for the Porter stemmer
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

    >>> from nltk.stem.porter import *

Create a new Porter stemmer.

    >>> stemmer = PorterStemmer()

Test the stemmer on various pluralised words.

    >>> plurals = ['caresses', 'flies', 'dies', 'mules', 'denied',
    ...            'died', 'agreed', 'owned', 'humbled', 'sized',
    ...            'meeting', 'stating', 'siezing', 'itemization',
    ...            'sensational', 'traditional', 'reference', 'colonizer',
    ...            'plotted']

    >>> singles = [stemmer.stem(plural) for plural in plurals]

    >>> print(' '.join(singles))
    caress fli die mule deni die agre own humbl size meet
    state siez item sensat tradit refer colon plot


Unit tests for Snowball stemmer
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

    >>> from nltk.stem.snowball import SnowballStemmer

See which languages are supported.

    >>> print(" ".join(SnowballStemmer.languages))
    arabic danish dutch english finnish french german hungarian italian
    norwegian porter portuguese romanian russian spanish swedish

Create a new instance of a language specific subclass.

    >>> stemmer = SnowballStemmer("english")

Stem a word.

    >>> print(stemmer.stem("running"))
    run

Decide not to stem stopwords.

    >>> stemmer2 = SnowballStemmer("english", ignore_stopwords=True)
    >>> print(stemmer.stem("having"))
    have
    >>> print(stemmer2.stem("having"))
    having

The 'english' stemmer is better than the original 'porter' stemmer.

    >>> print(SnowballStemmer("english").stem("generously"))
    generous
    >>> print(SnowballStemmer("porter").stem("generously"))
    gener

.. note::

    Extra stemmer tests can be found in `nltk.test.unit.test_stem`.

Unit tests for ARLSTem Stemmer
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

    >>> from nltk.stem.arlstem import ARLSTem

Create a Stemmer instance.

    >>> stemmer = ARLSTem()

Stem a word.

    >>> stemmer.stem('يعمل')
    'عمل'

Unit tests for ARLSTem2 Stemmer
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

    >>> from nltk.stem.arlstem2 import ARLSTem2

Create a Stemmer instance.

    >>> stemmer = ARLSTem2()

Stem a word.

    >>> stemmer.stem('يعمل')
    'عمل'