Metadata-Version: 1.1
Name: geotext
Version: 0.4.0
Summary: Geotext extracts countriy and city mentions from text
Home-page: https://github.com/elyase/geotext
Author: Yaser Martinez Palenzuela
Author-email: yaser.martinez@gmail.com
License: MIT
Description: ===============================
        geotext
        ===============================
        
        .. image:: https://img.shields.io/pypi/v/geotext.svg
                :target: https://pypi.python.org/pypi/geotext
        
        .. image:: https://img.shields.io/pypi/pyversions/geotext.svg
                :target: https://pypi.python.org/pypi/geotext
                
        .. image:: https://travis-ci.org/elyase/geotext.png?branch=master
                :target: https://travis-ci.org/elyase/geotext
        
        
        Geotext extracts country and city mentions from text
        
        * Free software: MIT license
        * Documentation: https://geotext.readthedocs.org.
        
        Usage
        -----
        .. code-block:: python
        
                from geotext import GeoText
                
                places = GeoText("London is a great city")
                places.cities
                # "London"
        
                # filter by country code
                result = geotext.GeoText('I loved Rio de Janeiro and Havana', 'BR').cities
                # 'Rio de Janeiro'
                
                GeoText('New York, Texas, and also China').country_mentions
                # OrderedDict([(u'US', 2), (u'CN', 1)])
        
        Installation
        ------------
        .. code-block:: bash
        
                pip install https://github.com/elyase/geotext/archive/master.zip
        
        
        Features
        --------
        - No external dependencies
        - Fast
        - Data from http://www.geonames.org licensed under the Creative Commons Attribution 3.0 License.
        
        Similar projects
        ----------------
        `geography
        <https://github.com/ushahidi/geograpy>`_: geography is more advanced and bigger in scope compared to geotext and can do everything geotext does. On the other hand geotext is leaner: has no external dependencies, is faster (re vs nltk) and also depends on libraries and data covered with more permissive licenses.
        
        
        
        
        History
        -------
        
        0.4.0 (2018-07-30)
        ++++++++++++++++++
        Fix unicode errors
        
        0.3.0 (2017-12-03)
        ++++++++++++++++++
        Support for Brazilian cities (credit to @joseluizcoe)
        
        0.2.0 (2017-07-01)
        ++++++++++++++++++
        
        * Python 3 support (credit to @freezer9)
        
        0.1.0 (2014-01-11)
        ---------------------
        
        * First release on PyPI.
Keywords: geotext
Platform: UNKNOWN
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
