A Gavagai API helper library.
$ pip install gavagaiGet your own api key for free at Gavagai Developer Portal.
The api key can be specified when instantiating the client, see examples below. Alternatively, you can set the GAVAGAI_APIKEY environment variable, and just call GavagaiClient().
See Gavagai API documentation for details about available API resources.
The /keywords resource extracts salient concepts from a collection of texts. Order by number of occurrences.
from gavagai.client import GavagaiClient
from pprint import pprint
texts = [
'Stayed here for 3 nights at the beginning of a trip of California. Could not say enough good things about the hotel Monaco. Amazing staff, amazing rooms and the location is brilliant! First stay at a Kimpton hotel, but definitely not the last!!!',
'I did a lot of research looking for a hotel suite for our family vacation in San Francisco. The Hotel Monaco was a perfect choice. What friendly and delightful staff. I will miss the Grand Cafe, but I will make sure to come back to see their new offerings.',
'My partner and I spent four nights here over New Years and loved it. Super staff; lovely, quiet room; excellent location within easy walking to much of Downtown and an overall experience that was perfect.'
]
client = GavagaiClient('use_your_own_api_key')
result = client.keywords(texts)
keywords = result.json()
pprint(keywords)The /tonality resource measures multi-dimensional sentiment, based on lexical analysis. For accuracy, language should be specified.
rom gavagai.client import GavagaiClient
from pprint import pprint
texts = [u'Din idiot!', u'Jag älskar dig.', u'Hen hatar det.']
client = GavagaiClient('use_your_own_api_key')
result = client.tonality(texts, language='sv')
keywords = result.json()
pprint(keywords)From root of this repository:
$ pip install -r requirements.txt$ py.test