Merge pull request #105 from IndicoDataSolutions/Chris/twitter-engagement

ADD: Twitter Engagement

indicoio/__init__.py

@@ -10,6 +10,7 @@ JSON_HEADERS = {
     'version-number': VERSION
 }
 
+from indicoio.text.twitter_engagement import twitter_engagement
 from indicoio.text.sentiment import political, posneg, sentiment_hq
 from indicoio.text.sentiment import posneg as sentiment
 from indicoio.text.lang import language
@@ -41,7 +42,7 @@ def detect_batch_decorator(f):
             kwargs['batch'] = True
         return f(*args, **kwargs)
     return wrapper
-    
+
 apis = dict((api, globals().get(api)) for api in API_NAMES)
 
 for api in apis:

indicoio/config.py

@@ -52,7 +52,8 @@ TEXT_APIS = [
     'language',
     'sentiment_hq',
     'keywords',
-    'named_entities'
+    'named_entities',
+    'twitter_engagement'
 ]
 
 IMAGE_APIS = [

indicoio/text/twitter_engagement.py

@@ -0,0 +1,22 @@
+from indicoio.utils.api import api_handler
+import indicoio.config as config
+
+def twitter_engagement(text, cloud=None, batch=False, api_key=None, **kwargs):
+    """
+    Given input text, returns an engagment score between 0 and 1
+
+    Example usage:
+
+    .. code-block:: python
+
+       >>> import indicoio
+       >>> import numpy as np
+       >>> text = 'Monday: Delightful with mostly sunny skies. Highs in the low 70s.'
+       >>> engagement = indicoio.twitter_engagement(text)
+
+    :param text: The text to be analyzed.
+    :type text: str or unicode
+    :rtype: Float of engagement between 0 and 1
+    """
+    url_params = {"batch": batch, "api_key": api_key}
+    return api_handler(text, cloud=cloud, api="twitterengagement", url_params=url_params, **kwargs)