Metadata-Version: 1.1
Name: textblob-de
Version: 0.4.2
Summary: German language support for TextBlob.
Home-page: https://github.com/markuskiller/textblob-de
Author: Markus Killer
Author-email: m.killer@langui.ch
License: 

Copyright 2014 Markus Killer

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The above copyright notice and this permission notice shall be included in
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Description: ==================
        textblob-de README
        ==================
        
        
        .. image:: https://img.shields.io/pypi/v/textblob-de.svg
            :target: https://pypi.python.org/pypi/textblob-de/
            :alt: textblob_de - latest PyPI version
        
        .. image:: https://travis-ci.org/markuskiller/textblob-de.png?branch=master
            :target: https://travis-ci.org/markuskiller/textblob-de
            :alt: Travis-CI
            
        .. image:: https://readthedocs.org/projects/textblob-de/badge/?version=latest
            :target: http://textblob-de.readthedocs.org/en/latest/
            :alt: Documentation Status
        
        .. image:: https://img.shields.io/pypi/dm/textblob-de.svg
            :target: https://pypi.python.org/pypi/textblob-de/
            :alt: Number of PyPI downloads
        
        .. image:: https://img.shields.io/github/license/markuskiller/textblob-de.svg
            :target: http://choosealicense.com/licenses/mit/
            :alt: LICENSE info
        
        German language support for `TextBlob <http://textblob.readthedocs.org/en/dev/>`_ by Steven Loria.
        
        This python package is being developed as a ``TextBlob`` **Language Extension**.
        See `Extension Guidelines <https://textblob.readthedocs.org/en/dev/contributing.html>`_ for details.
        
        
        Features
        --------
        
        * All directly accessible ``textblob_de`` classes (e.g. ``Sentence()`` or ``Word()``) are initialized with default models for German
        * Properties or methods that do not yet work for German raise a ``NotImplementedError``
        * German sentence boundary detection and tokenization (``NLTKPunktTokenizer``)
        * Consistent use of specified tokenizer for all tools (``NLTKPunktTokenizer`` or ``PatternTokenizer``)
        * Part-of-speech tagging (``PatternTagger``) with keyword ``include_punc=True`` (defaults to ``False``)
        * **NEW:** Tagset conversion in ``PatternTagger`` with keyword ``tagset='penn'|'universal'|'stts'`` (defaults to ``penn``)
        * Parsing (``PatternParser``) with all ``pattern`` keywords, plus ``pprint=True`` (defaults to ``False``)
        * Noun Phrase Extraction (``PatternParserNPExtractor``)
        * Lemmatization (``PatternParserLemmatizer``)
        * Polarity detection (``PatternAnalyzer``) - Still **EXPERIMENTAL**, does not yet have information on subjectivity
        * Full ``pattern.text.de`` API support on Python3
        * Supports Python 2 and 3
        * See `working features overview <http://langui.ch/nlp/python/textblob-de/>`_ for details
        
        
        Installing/Upgrading
        --------------------
        ::
        
            $ pip install -U textblob-de
            $ python -m textblob.download_corpora
        
            
        Or the latest development release (apparently this does not always work on Windows see 
        `issues #1744/5 <https://github.com/pypa/pip/pull/1745>`_ for details)::
        
            $ pip install -U git+https://github.com/markuskiller/textblob-de.git@dev
            $ python -m textblob.download_corpora
        
        
        .. note::
        
           ``TextBlob`` will be installed/upgraded automatically when running 
           ``pip install``. The second line (``python -m textblob.download_corpora``) 
           downloads/updates nltk corpora and language models used in ``TextBlob``.
        
        
        Usage
        -----
        
        .. code-block:: python
        
            >>> from textblob_de import TextBlobDE as TextBlob
            >>> text = '''Heute ist der 3. Mai 2014 und Dr. Meier feiert seinen 43. Geburtstag. 
            Ich muss unbedingt daran denken, Mehl, usw. für einen Kuchen einzukaufen. Aber leider 
            habe ich nur noch EUR 3.50 in meiner Brieftasche.'''
            >>> blob = TextBlob(text)
            >>> blob.sentences
            [Sentence("Heute ist der 3. Mai 2014 und Dr. Meier feiert seinen 43. Geburtstag."),
             Sentence("Ich muss unbedingt daran denken, Mehl, usw. für einen Kuchen einzukaufen."),
             Sentence("Aber leider habe ich nur noch EUR 3.50 in meiner Brieftasche.")]
            >>> blob.tokens
            WordList(['Heute', 'ist', 'der', '3.', 'Mai', ...]
            >>> blob.tags
            [('Heute', 'RB'), ('ist', 'VB'), ('der', 'DT'), ('3.', 'LS'), ('Mai', 'NN'), 
            ('2014', 'CD'), ...]
            # Default: Only noun_phrases that consist of two or more meaningful parts are displayed.
            # Not perfect, but a start (relies heavily on parser accuracy)
            >>> blob.noun_phrases
            WordList(['Mai 2014', 'Dr. Meier', 'seinen 43. Geburtstag', 'Kuchen einzukaufen', 
            'meiner Brieftasche'])
            
        
        .. code-block:: python
        
            >>> blob = TextBlob("Das Auto ist sehr schön.")
            >>> blob.parse()
            'Das/DT/B-NP/O Auto/NN/I-NP/O ist/VB/B-VP/O sehr/RB/B-ADJP/O schön/JJ/I-ADJP/O'
            >>> from textblob_de import PatternParser
            >>> blob = TextBlobDE("Das ist ein schönes Auto.", parser=PatternParser(pprint=True, lemmata=True))
            >>> blob.parse()
                  WORD   TAG    CHUNK   ROLE   ID     PNP    LEMMA   
                                                                     
                   Das   DT     -       -      -      -      das     
                   ist   VB     VP      -      -      -      sein    
                   ein   DT     NP      -      -      -      ein     
               schönes   JJ     NP ^    -      -      -      schön   
                  Auto   NN     NP ^    -      -      -      auto    
                     .   .      -       -      -      -      .       
            >>> from textblob_de import PatternTagger
            >>> blob = TextBlob(text, pos_tagger=PatternTagger(include_punc=True))
            [('Das', 'DT'), ('Auto', 'NN'), ('ist', 'VB'), ('sehr', 'RB'), ('schön', 'JJ'), ('.', '.')]
        
        
        .. code-block:: python
            
            >>> blob = TextBlob("Das Auto ist sehr schön.")
            >>> blob.sentiment
            Sentiment(polarity=1.0, subjectivity=0.0)
            >>> blob = TextBlob("Das ist ein hässliches Auto.")     
            >>> blob.sentiment
            Sentiment(polarity=-1.0, subjectivity=0.0)
        
        
        .. warning::
        
            **WORK IN PROGRESS:** The German polarity lexicon contains only uninflected
            forms and there are no subjectivity scores yet. As of version 0.2.3, lemmatized
            word forms are submitted to the ``PatternAnalyzer``, increasing the accuracy
            of polarity values. New in version 0.2.7: return type of ``.sentiment`` is now
            adapted to the main `TextBlob <http://textblob.readthedocs.org/en/dev/>`_ library (``:rtype: namedtuple``).
        
        
        .. code-block:: python
        
            >>> blob.words.lemmatize()
            WordList(['das', 'sein', 'ein', 'hässlich', 'Auto'])
            >>> from textblob_de.lemmatizers import PatternParserLemmatizer
            >>> _lemmatizer = PatternParserLemmatizer()
            >>> _lemmatizer.lemmatize("Das ist ein hässliches Auto.")
            [('das', 'DT'), ('sein', 'VB'), ('ein', 'DT'), ('hässlich', 'JJ'), ('Auto', 'NN')]
        
        
        .. note::
        
            Make sure that you use unicode strings on Python2 if your input contains
            non-ascii characters (e.g. ``word = u"schön"``).
        
        
        Access to ``pattern`` API in Python3
        ------------------------------------
        
        .. code-block:: python
        
            >>> from textblob_de.packages import pattern_de as pd
            >>> print(pd.attributive("neugierig", gender=pd.FEMALE, role=pd.INDIRECT, article="die"))
            neugierigen
            
        .. note::
        
           Alternatively, the path to ``textblob_de/ext`` can be added to the ``PYTHONPATH``, which allows
           the use of ``pattern.de`` in almost the same way as described in its 
           `Documentation <http://www.clips.ua.ac.be/pages/pattern-de>`_.
           The only difference is that you will have to prepend an underscore: 
           ``from _pattern.de import ...``. This is a precautionary measure in case the ``pattern``
           library gets native Python3 support in the future.
        
        
        Documentation and API Reference
        -------------------------------
        
        - http://textblob-de.readthedocs.org/en/latest
        
        
        Requirements
        ------------
        
        - Python >= 2.6 or >= 3.3
        
        TODO
        ----
        
        - `Planned Extensions <http://textblob-de.readthedocs.org/en/latest/extensions.html>`_
        - Additional PoS tagging options, e.g. NLTK tagging (``NLTKTagger``)
        - Improve noun phrase extraction (e.g. based on ``RFTagger`` output)
        - Improve sentiment analysis (find suitable subjectivity scores)
        - Improve functionality of ``Sentence()`` and ``Word()`` objects
        - Adapt more tests from the main `TextBlob <http://textblob.readthedocs.org/en/dev/>`_ library (esp. for ``TextBlobDE()`` in ``test_blob.py``)
        
        
        License
        -------
        
        `MIT licensed <http://choosealicense.com/licenses/mit/>`_. See the bundled ``LICENSE``  file for more details.
        
        
        Thanks
        ------
        
        Coded with Wing IDE 5.0 (free open source developer license)
        
        .. image:: https://wingware.com/images/wingware-logo-180x58.png
            :target: https://wingware.com/store/free
            :alt: Python IDE for Python - wingware.com
        
        
        
        Changelog
        ---------
        
        0.4.2 (02/05/2015)
        ++++++++++++++++++
        
        * Removed dependency on `NLTK, <https://github.com/nltk/nltk/>`_ as it already is a `TextBlob <http://textblob.readthedocs.org/en/dev/>`_ dependency
        * Temporary workaround for `NLTK Issue #824 <https://github.com/nltk/nltk/issues/824>`_ for tox/Travis-CI
        * (update 13/01/2015) `NLTK Issue #824 <https://github.com/nltk/nltk/issues/824>`_ fixed, workaround removed
        * Enabled ``pattern`` tagset conversion (``'penn'|'universal'|'stts'``) for ``PatternTagger``
        * Added tests for tagset conversion
        * Fixed test for Arabic translation example (Google translation has changed)
        * Added tests for lemmatizer
        * Bugfix: ``PatternAnalyzer`` no longer breaks on subsequent ocurrences of the same ``(word, tag)`` pairs on Python3 see comments to `Pull Request #11 <https://github.com/markuskiller/textblob-de/pull/11>`_
        * Bugfix/performance enhancement: Sentiment dictionary in ``PatternAnalyzer`` no longer reloaded for every sentence `Pull Request #11 <https://github.com/markuskiller/textblob-de/pull/11>`_ (tanks @Arttii)
        
        0.4.1 (03/10/2014)
        ++++++++++++++++++
        
        * Docs hosted on `RTD <http://textblob-de.readthedocs.org>`_
        * Removed dependency on nltk's depricated ``PunktWordTokenizer`` and replaced it with ``TreebankWordTokenizer`` see  `nltk/nltk#746 (comment) <https://github.com/nltk/nltk/pull/746#issuecomment-57625756>`_ for details
        
        0.4.0 (17/09/2014)
        ++++++++++++++++++
        
        * Fixed `Issue #7 <https://github.com/markuskiller/textblob-de/issues/7>`_ (restore ``textblob>=0.9.0`` compatibility)
        * Depend on ``nltk3``. Vendorized ``nltk`` was removed in ``textblob>=0.9.0``
        * Fixed ``ImportError`` on Python2 (``unicodecsv``)
        
        
        0.3.1 (29/08/2014)
        ++++++++++++++++++
        
        * Improved ``PatternParserNPExtractor`` (less false positives in verb filter)
        * Made sure that all keyword arguments with default ``None`` are checked with ``is not None``
        * Fixed shortcut to ``_pattern.de`` in vendorized library
        * Added ``Makefile`` to facilitate development process
        * Added docs and API reference
        
        0.3.0 (14/08/2014)
        ++++++++++++++++++
        
        * Fixed `Issue #5 <https://github.com/markuskiller/textblob-de/issues/5>`_ (text + space + period)
        
        0.2.9 (14/08/2014)
        ++++++++++++++++++
        
        * Fixed tokenization in ``PatternParser`` (if initialized manually, punctuation was not always separated from words)
        * Improved handling of empty strings (Issue #3) and of strings containing single punctuation marks (Issue #4) in ``PatternTagger`` and ``PatternParser``
        * Added tests for empty strings and for strings containing single punctuation marks
        
        0.2.8 (14/08/2014)
        ++++++++++++++++++
        
        * Fixed `Issue #3 <https://github.com/markuskiller/textblob-de/issues/3>`_ (empty string)
        * Fixed `Issue #4 <https://github.com/markuskiller/textblob-de/issues/4>`_ (space + punctuation)
        
        0.2.7 (13/08/2014)
        ++++++++++++++++++
        
        * Fixed `Issue #1 <https://github.com/markuskiller/textblob-de/issues/1>`_ lemmatization of strings containing a forward slash (``/``)
        * Enhancement `Issue #2 <https://github.com/markuskiller/textblob-de/issues/2>`_ use the same rtype as ``textblob`` for sentiment detection.
        * Fixed tokenization in ``PatternParserLemmatizer``
        
        0.2.6 (04/08/2014)
        ++++++++++++++++++
        
        * Fixed ``MANIFEST.in`` for package data in ``sdist``
        
        0.2.5 (04/08/2014)
        ++++++++++++++++++
        
        * ``sdist`` is non-functional as important files are missing due to a misconfiguration in ``MANIFEST.in`` - does not affect ``wheels``
        * Major internal refactoring (but no backwards-incompatible API changes) with the aim of restoring complete compatibility to original ``pattern>=2.6`` library on Python2
        * Separation of ``textblob`` and ``pattern`` code
        * On Python2 the vendorized version of ``pattern.text.de`` is only used if original is not installed (same as ``nltk``)
        * Made ``pattern.de.pprint`` function and all parser keywords accessible to customise parser output
        * Access to complete ``pattern.text.de`` API on Python2 and Python3 ``from textblob_de.packages import pattern_de as pd``
        * ``tox`` passed on all major platforms (Win/Linux/OSX)
        
        0.2.3 (26/07/2014)
        ++++++++++++++++++
        
        * Lemmatizer: ``PatternParserLemmatizer()`` extracts lemmata from Parser output
        * Improved polarity analysis through look-up of lemmatised word forms
        
        0.2.2 (22/07/2014)
        ++++++++++++++++++
        
        * Option: Include punctuation in ``tags``/``pos_tags`` properties (``b = TextBlobDE(text, tagger=PatternTagger(include_punc=True))``)
        * Added ``BlobberDE()`` class initialized with German models
        * ``TextBlobDE()``, ``Sentence()``, ``WordList()`` and ``Word()`` classes are now all initialized with German models
        * Restored complete API compatibility with ``textblob.tokenizers`` module of the main `TextBlob <http://textblob.readthedocs.org/en/dev/>`_ library
        
        0.2.1 (20/07/2014)
        ++++++++++++++++++
        
        * Noun Phrase Extraction: ``PatternParserNPExtractor()`` extracts NPs from Parser output
        * Refactored the way ``TextBlobDE()`` passes on arguments and keyword arguments to individual tools
        * *Backwards-incompatible*: Deprecate ``parser_show_lemmata=True`` keyword in ``TextBlob()``. Use ``parser=PatternParser(lemmata=True)`` instead.
        
        0.2.0 (18/07/2014)
        ++++++++++++++++++
        
        * vastly improved tokenization (``NLTKPunktTokenizer`` and ``PatternTokenizer`` with tests)
        * consistent use of specified tokenizer for all tools
        * ``TextBlobDE`` with initialized default models for German
        * Parsing (``PatternParser``) plus ``test_parsers.py``
        * **EXPERIMENTAL** implementation of Polarity detection (``PatternAnalyzer``)
        * first attempt at extracting German Polarity clues into ``de-sentiment.xml``
        * tox tests passing for py26, py27, py33 and py34
        
        0.1.3 (09/07/2014)
        ++++++++++++++++++
        
        * First release on PyPI
        
        0.1.0 - 0.1.2 (09/07/2014)
        ++++++++++++++++++++++++++
        
        * First release on github
        * A number of experimental releases for testing purposes
        * Adapted version badges, tests & travis-ci config
        * Code adapted from sample extension `textblob-fr <https://github.com/sloria/textblob-fr>`_
        * Language specific linguistic resources copied from `pattern-de <https://github.com/clips/pattern/tree/master/pattern/text/de>`_
        
Keywords: textblob,textblob_de,nlp,linguistics,nltk,pattern
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Information Technology
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: German
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Programming Language :: Python :: Implementation :: PyPy
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Text Processing
Classifier: Topic :: Text Processing :: Linguistic
