Metadata-Version: 1.1
Name: polyglot
Version: 15.10.03
Summary: Polyglot is a natural language pipeline that supports massive multilingual applications.
Home-page: https://github.com/aboSamoor/polyglot
Author: Rami Al-Rfou
Author-email: rmyeid@gmail.com
License: GPLv3
Description: 
        polyglot
        ========
        
        |Downloads| |Latest Version| |Build Status| |Documentation Status|
        
        .. |Downloads| image:: https://img.shields.io/pypi/dm/polyglot.svg
           :target: https://pypi.python.org/pypi/polyglot
        .. |Latest Version| image:: https://badge.fury.io/py/polyglot.svg
           :target: https://pypi.python.org/pypi/polyglot
        .. |Build Status| image:: https://travis-ci.org/aboSamoor/polyglot.png?branch=master
           :target: https://travis-ci.org/aboSamoor/polyglot
        .. |Documentation Status| image:: https://readthedocs.org/projects/polyglot/badge/?version=latest
           :target: https://readthedocs.org/builds/polyglot/
        
        Polyglot is a natural language pipeline that supports massive
        multilingual applications.
        
        -  Free software: GPLv3 license
        -  Documentation: http://polyglot.readthedocs.org.
        
        Features
        ~~~~~~~~
        
        -  Tokenization (165 Languages)
        -  Language detection (196 Languages)
        -  Named Entity Recognition (40 Languages)
        -  Part of Speech Tagging (16 Languages)
        -  Sentiment Analysis (136 Languages)
        -  Word Embeddings (137 Languages)
        -  Morphological analysis (135 Languages)
        -  Transliteration (69 Languages)
        
        Developer
        ~~~~~~~~~
        
        -  Rami Al-Rfou @ ``rmyeid gmail com``
        
        Quick Tutorial
        --------------
        
        .. code:: python
        
            import polyglot
            from polyglot.text import Text, Word
        
        Language Detection
        ~~~~~~~~~~~~~~~~~~
        
        .. code:: python
        
            text = Text("Bonjour, Mesdames.")
            print("Language Detected: Code={}, Name={}\n".format(text.language.code, text.language.name))
        
        
        .. parsed-literal::
        
            Language Detected: Code=fr, Name=French
            
        
        
        Tokenization
        ~~~~~~~~~~~~
        
        .. code:: python
        
            zen = Text("Beautiful is better than ugly. "
                       "Explicit is better than implicit. "
                       "Simple is better than complex.")
            print(zen.words)
        
        
        .. parsed-literal::
        
            [u'Beautiful', u'is', u'better', u'than', u'ugly', u'.', u'Explicit', u'is', u'better', u'than', u'implicit', u'.', u'Simple', u'is', u'better', u'than', u'complex', u'.']
        
        
        .. code:: python
        
            print(zen.sentences)
        
        
        .. parsed-literal::
        
            [Sentence("Beautiful is better than ugly."), Sentence("Explicit is better than implicit."), Sentence("Simple is better than complex.")]
        
        
        Part of Speech Tagging
        ~~~~~~~~~~~~~~~~~~~~~~
        
        .. code:: python
        
            text = Text(u"O primeiro uso de desobediência civil em massa ocorreu em setembro de 1906.")
            
            print("{:<16}{}".format("Word", "POS Tag")+"\n"+"-"*30)
            for word, tag in text.pos_tags:
                print(u"{:<16}{:>2}".format(word, tag))
        
        
        .. parsed-literal::
        
            Word            POS Tag
            ------------------------------
            O               DET
            primeiro        ADJ
            uso             NOUN
            de              ADP
            desobediência   NOUN
            civil           ADJ
            em              ADP
            massa           NOUN
            ocorreu         ADJ
            em              ADP
            setembro        NOUN
            de              ADP
            1906            NUM
            .               PUNCT
        
        
        Named Entity Recognition
        ~~~~~~~~~~~~~~~~~~~~~~~~
        
        .. code:: python
        
            text = Text(u"In Großbritannien war Gandhi mit dem westlichen Lebensstil vertraut geworden")
            print(text.entities)
        
        
        .. parsed-literal::
        
            [I-LOC([u'Gro\xdfbritannien']), I-PER([u'Gandhi'])]
        
        
        Polarity
        ~~~~~~~~
        
        .. code:: python
        
            print("{:<16}{}".format("Word", "Polarity")+"\n"+"-"*30)
            for w in zen.words[:6]:
                print("{:<16}{:>2}".format(w, w.polarity))
        
        
        .. parsed-literal::
        
            Word            Polarity
            ------------------------------
            Beautiful        0
            is               0
            better           1
            than             0
            ugly            -1
            .                0
        
        
        Embeddings
        ~~~~~~~~~~
        
        .. code:: python
        
            word = Word("Obama", language="en")
            print("Neighbors (Synonms) of {}".format(word)+"\n"+"-"*30)
            for w in word.neighbors:
                print("{:<16}".format(w))
            print("\n\nThe first 10 dimensions out the {} dimensions\n".format(word.vector.shape[0]))
            print(word.vector[:10])
        
        
        .. parsed-literal::
        
            Neighbors (Synonms) of Obama
            ------------------------------
            Bush            
            Reagan          
            Clinton         
            Ahmadinejad     
            Nixon           
            Karzai          
            McCain          
            Biden           
            Huckabee        
            Lula            
            
            
            The first 10 dimensions out the 256 dimensions
            
            [-2.57382345  1.52175975  0.51070285  1.08678675 -0.74386948 -1.18616164
              2.92784619 -0.25694436 -1.40958667 -2.39675403]
        
        
        Morphology
        ~~~~~~~~~~
        
        .. code:: python
        
            word = Text("Preprocessing is an essential step.").words[0]
            print(word.morphemes)
        
        
        .. parsed-literal::
        
            [u'Pre', u'process', u'ing']
        
        
        Transliteration
        ~~~~~~~~~~~~~~~
        
        .. code:: python
        
            from polyglot.transliteration import Transliterator
            transliterator = Transliterator(source_lang="en", target_lang="ru")
            print(transliterator.transliterate(u"preprocessing"))
        
        
        .. parsed-literal::
        
            препрокессинг
        
        
        
        
        
        History
        -------
        
        "14.11" (2014-01-11)
        ---------------------
        
        * First release on PyPI.
        
        
        "15.5.2" (2015-05-02)
        ---------------------
        
        * Polyglot is feature complete.
        
        
        "15.10.03" (2015-10-03)
        ---------------------------
        
        * Change the polyglot models mirror to Stony Brook University DSL lab instead
          of Google cloud storage.
        
Keywords: polyglot
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Environment :: Console
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Education
Classifier: License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)
Classifier: Natural Language :: Afrikaans
Classifier: Natural Language :: Arabic
Classifier: Natural Language :: Bengali
Classifier: Natural Language :: Bosnian
Classifier: Natural Language :: Bulgarian
Classifier: Natural Language :: Catalan
Classifier: Natural Language :: Chinese (Simplified)
Classifier: Natural Language :: Chinese (Traditional)
Classifier: Natural Language :: Croatian
Classifier: Natural Language :: Czech
Classifier: Natural Language :: Danish
Classifier: Natural Language :: Dutch
Classifier: Natural Language :: English
Classifier: Natural Language :: Esperanto
Classifier: Natural Language :: Finnish
Classifier: Natural Language :: French
Classifier: Natural Language :: Galician
Classifier: Natural Language :: German
Classifier: Natural Language :: Greek
Classifier: Natural Language :: Hebrew
Classifier: Natural Language :: Hindi
Classifier: Natural Language :: Hungarian
Classifier: Natural Language :: Icelandic
Classifier: Natural Language :: Indonesian
Classifier: Natural Language :: Italian
Classifier: Natural Language :: Japanese
Classifier: Natural Language :: Javanese
Classifier: Natural Language :: Korean
Classifier: Natural Language :: Latin
Classifier: Natural Language :: Latvian
Classifier: Natural Language :: Macedonian
Classifier: Natural Language :: Malay
Classifier: Natural Language :: Marathi
Classifier: Natural Language :: Norwegian
Classifier: Natural Language :: Panjabi
Classifier: Natural Language :: Persian
Classifier: Natural Language :: Polish
Classifier: Natural Language :: Portuguese
Classifier: Natural Language :: Portuguese (Brazilian)
Classifier: Natural Language :: Romanian
Classifier: Natural Language :: Russian
Classifier: Natural Language :: Serbian
Classifier: Natural Language :: Slovak
Classifier: Natural Language :: Slovenian
Classifier: Natural Language :: Spanish
Classifier: Natural Language :: Swedish
Classifier: Natural Language :: Tamil
Classifier: Natural Language :: Telugu
Classifier: Natural Language :: Thai
Classifier: Natural Language :: Turkish
Classifier: Natural Language :: Ukranian
Classifier: Natural Language :: Urdu
Classifier: Natural Language :: Vietnamese
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Text Processing :: Linguistic
