Text analysis api
Project description
This is a Python client for the Bookworm natural language API, made available by Crawlica.
You can register to receive an API key at https://bookworm.crawlica.com/request_api_key/
Example usage
import tabulate
from bookworm import Bookworm
API_KEY = '...'
documents = ['De två största städerna i Sverige är Stockholm och Göteborg',
'Donald Trump blir Barack Obamas efterträdare']
b = Bookworm(API_KEY, 'sv')
res = b.entities(documents)
for ents in res:
data = [[ent['entity'], ent['type'], ', '.join(ent['variants'])] for ent in ents]
print(tabulate.tabulate(data, headers=['Entity', 'Type', 'Variants']))
print('')
Entity Type Variants --------- ------ ---------- Sverige geo Sverige Stockholm geo Stockholm Göteborg geo Göteborg Entity Type Variants ------------ ------ ------------- Donald Trump person Donald Trump Barack Obama person Barack Obamas
Installation
$ pip install bookworm
Functionality currently available
autotag - Automatically tag documents with the best matching tags from our large database of tags.
wordsmash - Compare document sets to get the essence of what makes a subset special. Get the defining words and phrases.
entities - Extract named entities (people, organisations, and places) from each document
sentiment - Get a numerical representation of how positive or negative each document is
wordcount - Get a count of the distinct words in the documents. Declinations are grouped into the base form and stop words can be removed.
cluster - Automatically collect documents into groups, based on their topics, and describe those groups.
categorize - Automatically put documents in a set of categories that you choose. The categories are defined by topic words, but the documents need not contain any of those words, just “close” words.
Project details
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