perdido 0.1.32

PERDIDO Geoparser python library

Perdido Geoparser Python library

Installation

To install the latest stable version, you can use:

pip install --upgrade perdido

Quick start

Geoparsing

Import

from perdido.geoparser import Geoparser

Run geoparser

geoparser = Geoparser(version='Standard')
doc = geoparser('Je visite la ville de Lyon, Annecy et Chamonix.')

• The version parameter can take 2 values: Standard (default), Encyclopedie.

Get tokens

• Access token attributes:

for token in doc:
    print(f'{token.text}\tlemma: {token.lemma}\tpos: {token.pos}')

• Get the IOB format:

for token in doc:
    print(token.iob_format())

• Get a TSV-IOB format:

for token in doc:
    print(token.tsv_format())

Print the XML-TEI output

print(doc.tei)

Print the GeoJSON output

print(doc.geojson)

Get the list of named entities

for entity in doc.named_entities:
    print(f'entity: {entity.text}\ttag: {entity.tag}')
    if entity.tag == 'place':
        for t in entity.toponym_candidates:
            print(f' latitude: {t.lat}\tlongitude: {t.lng}\tsource {t.source}')

Get the list of nested named entities

for nested_entity in doc.nested_named_entities:
    print(f'entity: {nested_entity.text}\ttag: {nested_entity.tag}')
    if nested_entity.tag == 'place':
        for t in nested_entity.toponym_candidates:
            print(f' latitude: {t.lat}\tlongitude: {t.lng}\tsource {t.source}')

Shows named entities and nested named entities using the displacy library from spaCy

displacy.render(doc.to_spacy_doc(), style="ent", jupyter=True)

displacy.render(doc.to_spacy_doc(), style="span", jupyter=True)

Saving results

doc.to_xml('filename.xml')

doc.to_geojson('filename.geojson')

doc.to_iob('filename.tsv')

doc.to_csv('filename.csv')

Geocoding

Import

from perdido.geocoder import Geocoder

Geocode a single place name

geocoder = Geocoder()
doc = geocoder('Lyon')

Geocode a list of place names

geocoder = Geocoder()
doc = geocoder(['Lyon', 'Annecy', 'Chamonix'])

Get the geojson result

print(doc.geojson)

Get the list of toponym candidates

for t in doc.toponyms: 
    print(f'lat: {t.lat}\tlng: {t.lng}\tsource {t.source}\tsourceName {t.source_name}')

Get the toponym candidates as a GeoDataframe

print(doc.to_geodataframe())

Perdido Geoparser REST APIs

http://choucas.univ-pau.fr/docs#

Example: call REST API in Python

import requests

url = 'http://choucas.univ-pau.fr/PERDIDO/api/'
service = 'geoparsing'
data = {'content': 'Je visite la ville de Lyon, Annecy et le Mont-Blanc.'}
parameters = {'api_key': 'demo'}

r = requests.post(url+service, params=parameters, json=data)

print(r.text)

Acknowledgements

Perdido is an active project still under developpement.

This work was partially supported by the following projects:

• GEODE (2020-2024): LabEx ASLAN (ANR-10-LABX-0081)
• GeoDISCO (2019-2020): MSH Lyon St-Etienne (ANR‐16‐IDEX‐0005)
• CHOUCAS (2017-2022): ANR (ANR-16-CE23-0018)
• PERDIDO (2012-2015): CDAPP and IGN