Metadata-Version: 1.1
Name: bookworm
Version: 0.2.1
Summary: Text analysis api
Home-page: https://github.com/crawlica/bookworm-client
Author: Crawlica
Author-email: tech@crawlica.com
License: Apache 2.0
Download-URL: https://github.com/crawlica/bookworm-client/tarball/0.2.1
Description: Bookworm
        ========
        
        This is a Python client for the Bookworm natural language API, made available by Crawlica.
        
        You can register to receive an API key at https://bookworm.crawlica.com/request_api_key/
        
        
        Example usage
        -------------
        
        .. code-block:: python
        
            import tabulate
            from bookworm import Bookworm
        
        
            API_KEY = '...'
        
            documents = ['De två största städerna i Sverige är Stockholm och Göteborg',
                         'Donald Trump blir Barack Obamas efterträdare']
        
            b = Bookworm(API_KEY, 'sv')
            res = b.entities(documents)
        
            for ents in res:
                data = [[ent['entity'], ent['type'], ', '.join(ent['variants'])] for ent in ents]
                print(tabulate.tabulate(data, headers=['Entity', 'Type', 'Variants']))
                print('')
        
        
        
        ::
        
            Entity     Type    Variants
            ---------  ------  ----------
            Sverige    geo     Sverige
            Stockholm  geo     Stockholm
            Göteborg   geo     Göteborg
        
            Entity        Type    Variants
            ------------  ------  -------------
            Donald Trump  person  Donald Trump
            Barack Obama  person  Barack Obamas
        
        
        Installation
        ------------
        
        .. code-block:: bash
        
          $ pip install bookworm
        
        
        
        Functionality currently available
        ---------------------------------
        
        * *autotag* - Automatically tag documents with the best matching tags from our large database of tags.
        * *wordsmash* - Compare document sets to get the essence of what makes a subset special. Get the defining words and phrases.
        * *entities* - Extract named entities (people, organisations, and places) from each document
        * *sentiment* - Get a numerical representation of how positive or negative each document is
        * *wordcount* - Get a count of the distinct words in the documents. Declinations are grouped into the base form and stop words can be removed.
        * *cluster* - Automatically collect documents into groups, based on their topics, and describe those groups.
        * *categorize* - Automatically put documents in a set of categories that you choose. The categories are defined by topic words, but the documents need not contain any of those words, just “close” words.
Platform: POSIX
