=============================== 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('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.