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indicoio-python

A wrapper for the indico API.

The indico API is free to use, and no training data is required.

Installation

From PyPI:

pip install indicoio

From source:

git clone https://github.com/IndicoDataSolutions/IndicoIo-python.git
python setup.py install

API Keys + Setup

For API key registration and setup, checkout our quickstart guide.

Full Documentation

Detailed documentation and further code examples are available at indico.io/docs.

Supported APIs:

  • Positive/Negative Sentiment Analysis
  • Political Sentiment Analysis
  • Image Feature Extraction
  • Facial Emotion Recognition
  • Facial Feature Extraction
  • Language Detection
  • Text Topic Tagging

Examples

>>> from indicoio import political, sentiment, language, text_tags, keywords, fer, facial_features, image_features

>>> indicoio.config.api_key = "YOUR_API_KEY"

>>> political("Guns don't kill people. People kill people.")
{u'Libertarian': 0.47740164630834825, u'Green': 0.08454409540443657, u'Liberal': 0.16617097211030055, u'Conservative': 0.2718832861769146}

>>> sentiment('Worst movie ever.')
0.07062467665597527

>>> sentiment('Really enjoyed the movie.')
0.8105182526856075

>>> text_tags("Facebook blog posts about Android tech make better journalism than most news outlets.")

>>> text_tags(test_text, threshold=0.1) # return only keys with value > 0.1
{u'startups_and_entrepreneurship': 0.21888586688354486}

>>> text_tags(test_text, top_n=1) # return only keys with top_n values
{u'startups_and_entrepreneurship': 0.21888586688354486}

>>> import numpy as np

>>> test_face = np.linspace(0,50,48*48).reshape(48,48)

>>> fer(test_face)
{u'Angry': 0.08843749137458341, u'Sad': 0.39091163159204684, u'Neutral': 0.1947947999669361, u'Surprise': 0.03443785859010413, u'Fear': 0.17574534848440568, u'Happy': 0.11567286999192382}

>>> facial_features(test_face)
[0.0, -0.02568680526917187, 0.21645604230056517, ..., 3.0342637531932777]

>>> language('Quis custodiet ipsos custodes')
{u'Swedish': 0.00033330636691921914, u'Lithuanian': 0.007328693814717631, u'Vietnamese': 0.0002686116137658802, u'Romanian': 8.133913804076592e-06, ...}

>>> keywords("Facebook blog posts about Android tech make better journalism than most news outlets.", top_n=3)
{u'android': 0.10602030910588661,
 u'journalism': 0.13466866170166855,
 u'outlets': 0.13930405357808642}

Batch API

Each indicoio function can process many examples with a single request. Simply pass in a list of inputs and receive a list of results in return.

>>> from indicoio import sentiment

>>> sentiment(['Best day ever', 'Worst day ever'])
[0.9899001220871786, 0.005709885173415242]