>>> import numpy as np

>>> from indicoio import political, sentiment, fer, facial_features, language

>>> 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.')
{u'Sentiment': 0.07062467665597527}

>>> sentiment('Really enjoyed the movie.')
{u'Sentiment': 0.8105182526856075}

>>> test_text = "Facebook blog posts about Android tech make better journalism than most news outlets."

>>> tag_dict = text_tags(test_text)

>>> sorted(tag_dict.keys(), key=lambda x: tag_dict[x], reverse=True)[:3]
[u'startups_and_entrepreneurship', u'investment', u'business']

>>> 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}

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

>>> 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, -0.1519435786033145, -0.5648621854611555, 3.0607368045577226, 0.11434321880792693, -0.02163810928547493, -0.44224330594186484, 0.3024315632285246, -2.6068048934495276, 2.497798330306638, 3.040558335205844, 0.741045340525325, 0.37198135618478817, -0.33132377802172325, -0.9804190889833034, 0.5046575784709395, -0.5609132323152847, 1.679107064439151, 0.6825037853544341, -1.5977176226648016, 1.8959464303080562, -0.7812860715595836, -2.998394007543733, -0.22637273967347724, -0.9642457010679496, 1.4557274834236749, 2.412244419186633, 2.3151771738421965, 0.7881483386786367, 1.6622850935863422, 0.1304768990234367, 1.9344501393866649, 3.1271558035162914, -0.10250886439220543, 1.4921395116492966, 2.761645355670677, 1.6903473594991179, 1.009209807271491, 0.07273926986120445, -1.4941708135718021, -2.082786362439631, 1.0160924044870847, 2.5326580674673895, -0.8328208491083264, 2.0390177029762935, 3.0342637531932777]

>>> language_dict = language('Quis custodiet ipsos custodes')

>>> sorted(language_dict.keys(), key=lambda x: language_dict[x], reverse=True)[:5]
[u'Latin', u'Dutch', u'Greek', u'Portuguese', u'Spanish']

>>> language_dict
{u'Swedish': 0.00033330636691921914, u'Lithuanian': 0.007328693814717631, u'Vietnamese': 0.0002686116137658802, u'Romanian': 8.133913804076592e-06, ...}


Batch API Access
----------------

If you'd like to use our batch api interface, please send an email to contact@indico.io.

from indicio import batch_sentiment batch_sentiment(['Text to analyze', 'More text'], auth=("example@example.com", "********"))


Authentication credentials can also be set as the environment variables "INDICO_USERNAME" and "INDICO_PASSWORD" or as 'username' and 'password' in indicorc

Private Cloud API Access
------------------------

If you'd like to use our private cloud interface, please send an email to contact@indico.io.

from indicio import sentiment sentiment("Text to analyze", hostname="http://exampleprivatecloud.io/", auth=("example@example.com", "********"))


Private cloud hostnames can also be set as the environment variable "INDICO_PRIVATE_CLOUD_URL" or as 'hostname' in indicorc

indicorc
------------------------

Indicoio-python will look first for $HOME/.indicorc then ./.indicorc for the optional configuration file. The indicorc can be used to set an authentication username and password as well as the private cloud hostname, so they don't need to be specified for every call. All sectiions are optional.

Here is an example of a valid indicorc file:

[auth] username = test@example.com password = secret

[private_cloud] hostname = example.indico.io