Metadata-Version: 1.1
Name: textblob
Version: 0.3.2
Summary: Simple, Pythonic text processing. Sentiment analysis, POS tagging, noun phrase parsing, and more.
Home-page: https://github.com/sloria/TextBlob
Author: Steven Loria
Author-email: sloria1@gmail.com
License: MIT
Description: TextBlob
        ========
        
        .. image:: https://travis-ci.org/sloria/TextBlob.png
        
        Simplified text processing for Python 2 and 3.
        
        
        Requirements
        ------------
        
        - Python 2.6, 2.7, or 3.3
        
        
        Usage
        -----
        
        Simple.
        
        Create a TextBlob
        +++++++++++++++++
        
        ::
        
            from text.blob import TextBlob
        
            zen = """Beautiful is better than ugly.
            Explicit is better than implicit.
            Simple is better than complex.
            Complex is better than complicated.
            Flat is better than nested.
            Sparse is better than dense.
            Readability counts.
            Special cases aren't special enough to break the rules.
            Although practicality beats purity.
            Errors should never pass silently.
            Unless explicitly silenced.
            In the face of ambiguity, refuse the temptation to guess.
            There should be one-- and preferably only one --obvious way to do it.
            Although that way may not be obvious at first unless you're Dutch.
            Now is better than never.
            Although never is often better than *right* now.
            If the implementation is hard to explain, it's a bad idea.
            If the implementation is easy to explain, it may be a good idea.
            Namespaces are one honking great idea -- let's do more of those!
            """
        
            blob = TextBlob(zen) # Create a new TextBlob
        
        Part-of-speech tags and noun phrases...
        +++++++++++++++++++++++++++++++++++++++
        
        \...are just properties.
        
        ::
        
            blob.pos_tags         # [('beautiful', 'JJ'), ('is', 'VBZ'), ('better', 'RBR'),
                                  # ('than', 'IN'), ('ugly', 'RB'), ...]
        
            blob.noun_phrases     # ['beautiful', 'explicit', 'simple', 'complex', 'flat',
                                  # 'sparse', 'readability', 'special cases',
                                  # 'practicality beats purity', 'errors', 'unless',
                                  # 'obvious way','dutch', 'right now', 'bad idea',
                                  # 'good idea', 'namespaces', 'great idea']
        
        Sentiment analysis
        ++++++++++++++++++
        
        The `sentiment` property returns a tuple of the form `(polarity, subjectivity)` where `polarity` ranges from -1.0 to 1.0 and
        `subjectivity` ranges from 0.0 to 1.0.
        
        ::
        
            blob.sentiment        # (0.20, 0.58)
        
        Tokenization
        ++++++++++++
        
        ::
        
            blob.words            # WordList(['Beautiful', 'is', 'better'...'more',
                                  #           'of', 'those'])
        
            blob.sentences        # [Sentence('Beautiful is better than ugly.'),
                                  #  Sentence('Explicit is better than implicit.'),
                                  #  ...]
        
        Get word and noun phrase frequencies
        ++++++++++++++++++++++++++++++++++++
        
        ::
        
            blob.word_counts['special']   # 2 (not case-sensitive by default)
            blob.words.count('special')   # Same thing
            blob.words.count('special', case_sensitive=True)  # 1
        
            blob.noun_phrases.count('great idea')  # 1
        
        TextBlobs are like Python strings!
        ++++++++++++++++++++++++++++++++++
        
        ::
        
            blob[0:19]            # TextBlob("Beautiful is better")
            blob.upper()          # TextBlob("BEAUTIFUL IS BETTER THAN UGLY...")
            blob.find("purity")   # 293
        
            apple_blob = TextBlob('apples')
            banana_blob = TextBlob('bananas')
            apple_blob < banana_blob           # True
            apple_blob + ' and ' + banana_blob # TextBlob('apples and bananas')
            "{0} and {1}".format(apple_blob, banana_blob)  # 'apples and bananas'
        
        
        Get start and end indices of sentences
        ++++++++++++++++++++++++++++++++++++++
        
        Use `sentence.start` and `sentence.end`. This can be useful for sentence highlighting, for example.
        
        ::
        
            for sentence in blob.sentences:
                print(sentence)  # Beautiful is better than ugly
                print("---- Starts at index {}, Ends at index {}"\
                            .format(sentence.start, sentence.end))  # 0, 30
        
        Get a JSON-serialized version of the blob
        +++++++++++++++++++++++++++++++++++++++++
        
        ::
        
            blob.json   # '[{"sentiment": [0.2166666666666667, ' '0.8333333333333334],
                        # "stripped": "beautiful is better than ugly", '
                        # '"noun_phrases": ["beautiful"], "raw": "Beautiful is better than ugly. ", '
                        # '"end_index": 30, "start_index": 0}
                        #  ...]'
        
        
        Installation
        ------------
        
        If you have `pip`: ::
        
            pip install textblob
        
        Or (if you must): ::
        
            easy_install textblob
        
        **IMPORTANT**: TextBlob depends on some NLTK models to work. The easiest way
        to get these is to run the `download_corpora.py` script included with
        this distribution. You can get it `here <https://raw.github.com/sloria/TextBlob/master/download_corpora.py>`_ .
        Then run: ::
        
            python download_corpora.py
        
        
        Testing
        -------
        Run ::
        
            nosetests
        
        to run all tests.
        
        License
        -------
        
        TextBlob is licenced under the MIT license. See the bundled `LICENSE <https://github.com/sloria/TextBlob/blob/master/LICENSE>`_ file for more details.
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Natural Language :: English
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.3
