semvec/pypi-packages huggingface dataset:
geotext 0.4.0
Geotext extracts countriy and city mentions from text
License: MIT
Keywords: geotext

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geotext
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.. 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
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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.