import requests
import json

from indicoio import JSON_HEADERS
from indicoio.utils import normalize

def political(api_root, text):
    """
    Given input text, returns a probability distribution over the political alignment of the speaker.

    Example usage:

    .. code-block:: python

       >>> from indicoio import political
       >>> import numpy as np
       >>> text = 'Wish we had more bike lanes. \
       Hopefully, driverless cars will chance economics from ownership to fee for service.'
       >>> affiliation = political(text)
       >>> affiliation
       {u'Libertarian': 0.4923755446986322, u'Green': 0.2974443102818122, 
       u'Liberal': 0.13730032938784784, u'Conservative': 0.07287981563170784}
       >>> least_like = affiliation.keys()[np.argmin(affiliation.values())]
       >>> most_like = affiliation.keys()[np.argmax(affiliation.values())]
       >>> 'This text is most like %s and least like %s'%(most_like,least_like)
       u'This text is most like Libertarian and least like Conservative'

    :param text: The text to be analyzed.
    :type text: str or unicode
    :rtype: Dictionary of party probability pairs
    """

    data_dict = json.dumps({'text': text})
    response = requests.post(api_root + "political", data=data_dict, headers=JSON_HEADERS)
    response_dict = response.json()
    if len(response_dict) < 2:
      raise ValueError(response_dict.values()[0])
    else:
      return response_dict

def posneg(api_root, text):
    """
    Given input text, returns a scalar estimate of the sentiment of that text.
    Values are roughly in the range 0 to 1 with 0.5 indicating neutral sentiment.
    For reference, 0 suggests very negative sentiment and 1 suggests very positive sentiment.

    Example usage:

    .. code-block:: python

       >>> from indicoio import sentiment
       >>> text = 'Thanks everyone for the birthday wishes!! It was a crazy few days ><'
       >>> sentiment = sentiment(text)
       >>> sentiment
       0.6946439339979863

    :param text: The text to be analyzed.
    :type text: str or unicode
    :rtype: Float
    """
    
    data_dict = json.dumps({'text': text})
    response = requests.post(api_root + "sentiment", data=data_dict, headers=JSON_HEADERS)
    response_dict = response.json()
    if 'Sentiment' not in response_dict:
      raise ValueError(response_dict.values()[0])
    else:
      return response_dict['Sentiment']