flashgeotext 0.1.0

Extract and count countries and cities (+their synonyms) from text

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flashgeotext :zap::earth_africa:

Extract and count countries and cities (+their synonyms) from text, like GeoText on steroids using FlashText, a Aho-Corasick implementation. Flashgeotext is a fast, batteries-included (and BYOD) and native python library that extracts one or more sets of given city and country names (+ synonyms) from an input text.

documentation: https://flashgeotext.iwpnd.pw/

Usage

from flashgeotext.geotext import GeoText

geotext = GeoText(use_demo_data=True)

input_text = '''Shanghai. The Chinese Ministry of Finance in Shanghai said that China plans
                to cut tariffs on $75 billion worth of goods that the country
                imports from the US. Washington welcomes the decision.'''

geotext.extract(input_text=input_text, span_info=True)
>> {
    'cities': {
        'Shanghai': {
            'count': 2,
            'span_info': [(0, 8), (45, 53)]
            },
        'Washington, D.C.': {
            'count': 1,
            'span_info': [(175, 185)]
            }
        },
    'countries': {
        'China': {
            'count': 1,
            'span_info': [(64, 69)]
            },
        'United States': {
            'count': 1,
            'span_info': [(171, 173)]
            }
        }
    }

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.

Installing

for usage:

pip install flashgeotext

for development:

git clone https://github.com/iwpnd/flashgeotext.git
pip install flit
flit install

Running the tests

pytest flashgeotext/tests -v

Authors

• Benjamin Ramser - Initial work - iwpnd

See also the list of contributors who participated in this project.

License

This project is licensed under the MIT License - see the LICENSE.md file for details

Demo Data cities from http://www.geonames.org licensed under the Creative Commons Attribution 3.0 License.

Acknowledgments

• Hat tip to @vi3k6i5 for his paper and implementation