Remove ner

indicoio/__init__.py

@@ -9,7 +9,6 @@ from indicoio.text.sentiment import political, posneg
 from indicoio.text.sentiment import posneg as sentiment
 from indicoio.text.lang import language
 from indicoio.text.classification import classification
-from indicoio.text.ner import named_entities
 from indicoio.images.fer import fer
 from indicoio.images.features import facial_features
 from indicoio.images.features import image_features
@@ -23,4 +22,3 @@ fer = partial(fer, config.api_root)
 facial_features = partial(facial_features, config.api_root)
 image_features = partial(image_features, config.api_root)
 classification = partial(classification, config.api_root)
-named_entities = partial(named_entities, config.api_root)

indicoio/local/__init__.py

@@ -7,7 +7,6 @@ from indicoio.text.sentiment import political, posneg
 from indicoio.text.sentiment import posneg as sentiment
 from indicoio.text.lang import language
 from indicoio.text.classification import classification
-from indicoio.text.ner import named_entities
 from indicoio.images.fer import fer
 from indicoio.images.features import facial_features
 from indicoio.images.features import image_features
@@ -21,4 +20,3 @@ fer = partial(fer, config.local_api_root)
 facial_features = partial(facial_features, config.local_api_root)
 image_features = partial(image_features, config.local_api_root)
 classification = partial(classification, config.local_api_root)
-named_entities = partial(named_entities, config.local_api_root)

indicoio/text/ner.py

@@ -1,23 +0,0 @@
-from indicoio.utils import api_handler
-
-def named_entities(api_root, text):
-    """
-    Given input text, returns a mapping from named entities to 
-    named entity categories.
-
-    Example usage:
-
-    .. code-block:: python
-
-       >>> import indicoio
-       >>> import numpy as np
-       >>> text = 'On Monday, president Barack Obama will be...'
-       >>> indicoio.named_entities(text)
-       >>> "{'Monday': 'Time', 'Barack Obama': 'Person'}"
-
-    :param text: The text to be analyzed.
-    :type text: str or unicode
-    :rtype: Dictionary of named entity, category pairs
-    """
-    
-    return api_handler(text, api_root + "ner")

tests/local/test_local.py

@@ -26,12 +26,6 @@ class FullAPIRun(unittest.TestCase):
         results = classification(text)
         self.assertTrue(categories < set(results.keys()))
 
-    def test_named_entity_recognition(self):
-        categories = set(['arts'])
-        text = "On Monday, president Barack Obama will be..."
-        results = named_entities(text)
-        self.assertTrue('named entity' in set(results.keys()))
-
     def test_political(self):
         political_set = set(['Libertarian', 'Liberal', 'Conservative', 'Green'])
         test_string = "Guns don't kill people, people kill people."

tests/remote/test_remote.py

@@ -4,8 +4,7 @@ import os
 import numpy as np
 import skimage.io
 
-from indicoio import political, sentiment, fer, facial_features, language, image_features, \
+from indicoio import political, sentiment, fer, facial_features, language, image_features, classification
-                     classification, named_entities
 
 DIR = os.path.dirname(os.path.realpath(__file__))
 
@@ -29,12 +28,6 @@ class FullAPIRun(unittest.TestCase):
         results = classification(text)
         self.assertTrue(categories < set(results.keys()))
 
-    def test_named_entity_recognition(self):
-        categories = set(['arts'])
-        text = "On Monday, president Barack Obama will be..."
-        results = named_entities(text)
-        self.assertTrue('named entity' in set(results.keys()))
-
     def test_political(self):
         political_set = set(['Libertarian', 'Liberal', 'Conservative', 'Green'])
         test_string = "Guns don't kill people, people kill people."