Skip to main content

Geotext extracts countriy and city mentions from text

Project description

https://img.shields.io/pypi/v/geotext.svg https://img.shields.io/pypi/pyversions/geotext.svg https://travis-ci.org/elyase/geotext.png?branch=master

Geotext extracts country and city mentions from text

Usage

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

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: 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.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Filename, size & hash SHA256 hash help File type Python version Upload date
geotext-0.4.0-py2.py3-none-any.whl (2.0 MB) Copy SHA256 hash SHA256 Wheel py2.py3
geotext-0.4.0.tar.gz (2.0 MB) Copy SHA256 hash SHA256 Source None

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN SignalFx SignalFx Supporter DigiCert DigiCert EV certificate StatusPage StatusPage Status page