Merge pull request #116 from IndicoDataSolutions/development

Development

CHANGES.txt

@@ -34,3 +34,5 @@ v0.8.0 Fri Jul 10 -- Add Content Filtering API, Named Entities API, Facial Emoti
 v0.8.1 Wed Jul 22 -- Add Sentiment HQ to predict_text API
 v0.9.0 Tue Jul 28 -- Deprecate batch function calls in favor of type inference
 v0.9.1 Mon Aug 3 -- Add Facial Localization API, image resizing updates
+v0.9.2 Fri Aug 14 -- Add intersections API, analyzeText, analyzeImage
+

indicoio/__init__.py

@@ -1,7 +1,7 @@
 from functools import wraps, partial
 import warnings
 
-Version, version, __version__, VERSION = ('0.9.1',) * 4
+Version, version, __version__, VERSION = ('0.9.2',) * 4
 
 JSON_HEADERS = {
     'Content-type': 'application/json',
@@ -22,7 +22,7 @@ from indicoio.images.features import facial_features
 from indicoio.images.faciallocalization import facial_localization
 from indicoio.images.features import image_features
 from indicoio.images.filtering import content_filtering
-from indicoio.utils.multi import predict_image, predict_text
+from indicoio.utils.multi import analyze_image, analyze_text, intersections
 
 from indicoio.config import API_NAMES
 

indicoio/config.py

@@ -63,7 +63,13 @@ IMAGE_APIS = [
     'content_filtering'
 ]
 
-API_NAMES = IMAGE_APIS + TEXT_APIS + ["predict_text", "predict_image"]
+OTHER_APIS = [
+    "analyze_text", 
+    "analyze_image",
+    "intersections"
+]
+
+API_NAMES = IMAGE_APIS + TEXT_APIS + OTHER_APIS
 
 SETTINGS = Settings(files=[
     os.path.expanduser("~/.indicorc"),

indicoio/utils/api.py

@@ -19,7 +19,6 @@ def api_handler(arg, cloud, api, url_params=None, **kwargs):
     cloud = cloud or config.cloud
     host = "%s.indico.domains" % cloud if cloud else config.PUBLIC_API_HOST
     url = create_url(host, api, url_params)
-
     response = requests.post(url, data=json_data, headers=JSON_HEADERS)
 
     if response.status_code == 503 and cloud != None:

indicoio/utils/multi.py

@@ -11,19 +11,59 @@ AVAILABLE_APIS = {
     'image': IMAGE_APIS
 }
 
+def invert_dictionary(d):
+    return {
+        element: key for key, values in d.iteritems()
+        for element in values
+    }
+
+API_TYPES = invert_dictionary(AVAILABLE_APIS)
+
+
+def intersections(data, apis = None, **kwargs):
+    """
+    Helper to make multi requests of different types.
+
+    :param data: Data to be sent in API request
+    :param type: String type of API request
+    :rtype: Dictionary of api responses
+    """
+    # Client side api name checking
+
+    # remove auto-inserted batch param
+    kwargs.pop('batch', None)
+
+    if not isinstance(apis, list) or len(apis) != 2:
+        raise IndicoError("Argument 'apis' must be of length 2")
+    if isinstance(data, list) and len(data) < 3:
+        raise IndicoError(
+            "At least 3 examples are required to use the intersections API"
+        )
+
+    api_types = map(API_TYPES.get, apis)
+    if api_types[0] != api_types[1]:
+        raise IndicoError(
+            "Both `apis` must accept the same kind of input to use the intersections API"
+        )
+
+    cloud = kwargs.get("cloud", None)
+
+    url_params = {
+        'batch': False,
+        'api_key': kwargs.pop('api_key', None),
+        'apis': apis
+    }
+
+    return api_handler(data, cloud=cloud, api="apis/intersections", url_params=url_params, **kwargs)
 
 def multi(data, datatype, apis, batch=False, **kwargs):
     """
     Helper to make multi requests of different types.
 
-    :param data: data to be sent in JSON.
+    :param data: Data to be sent in API request
-    :param type: String type of API request
+    :param datatype: String type of API request
     :param apis: List of apis to use.
-    :param apis: List of apis available for use.
+    :param batch: Is this a batch request?
-    :type data: str or image
-    :type type: str or unicode
-    :type apis: list of str
-    :type available: list of str
     :rtype: Dictionary of api responses
     """
     # Client side api name checking - strictly only accept func name api
@@ -36,13 +76,12 @@ def multi(data, datatype, apis, batch=False, **kwargs):
         )
 
     # Convert client api names to server names before sending request
-    apis = map(CLIENT_SERVER_MAP.get, apis)
     cloud = kwargs.pop("cloud", None)
     api_key = kwargs.pop('api_key', None)
     result = api_handler(
         data,
         cloud=cloud,
-        api='apis',
+        api='apis/multiapi',
         url_params={
             "apis":apis,
             "batch":batch,
@@ -55,11 +94,11 @@ def multi(data, datatype, apis, batch=False, **kwargs):
 
 def handle_response(result):
     # Parse out the results to a dicionary of api: result
-    return dict((SERVER_CLIENT_MAP[api], parsed_response(api, res))
+    return dict((api, parsed_response(api, res))
         for api, res in result.iteritems())
 
 
-def predict_text(input_text, apis=TEXT_APIS, **kwargs):
+def analyze_text(input_text, apis=TEXT_APIS, **kwargs):
     """
     Given input text, returns the results of specified text apis. Possible apis
     include: [ 'text_tags', 'political', 'sentiment', 'language' ]
@@ -70,8 +109,8 @@ def predict_text(input_text, apis=TEXT_APIS, **kwargs):
 
        >>> import indicoio
        >>> text = 'Monday: Delightful with mostly sunny skies. Highs in the low 70s.'
-       >>> results = indicoio.text(data = text, apis = ["language", "sentiment"])
+       >>> results = indicoio.analyze_text(data = text, apis = ["language", "sentiment"])
-       >>> language_results = results["langauge"]
+       >>> language_results = results["language"]
        >>> sentiment_results = results["sentiment"]
 
     :param text: The text to be analyzed.
@@ -96,7 +135,7 @@ def predict_text(input_text, apis=TEXT_APIS, **kwargs):
     )
 
 
-def predict_image(image, apis=IMAGE_APIS, **kwargs):
+def analyze_image(image, apis=IMAGE_APIS, **kwargs):
     """
     Given input image, returns the results of specified image apis. Possible apis
     include: ['fer', 'facial_features', 'image_features']
@@ -108,7 +147,7 @@ def predict_image(image, apis=IMAGE_APIS, **kwargs):
        >>> import indicoio
        >>> import numpy as np
        >>> face = np.zeros((48,48)).tolist()
-       >>> results = indicoio.image(image = face, apis = ["fer", "facial_features"])
+       >>> results = indicoio.analyze_image(image = face, apis = ["fer", "facial_features"])
        >>> fer = results["fer"]
        >>> facial_features = results["facial_features"]
 

setup.py

@@ -9,7 +9,7 @@ except ImportError:
 
 setup(
     name="IndicoIo",
-    version="0.9.1",
+    version="0.9.2",
     packages=[
         "indicoio",
         "indicoio.text",

tests/test_remote.py

@@ -15,7 +15,7 @@ from indicoio import keywords, batch_keywords
 from indicoio import sentiment_hq, batch_sentiment_hq
 from indicoio import twitter_engagement, batch_twitter_engagement
 from indicoio import named_entities, batch_named_entities
-from indicoio import predict_image, predict_text, batch_predict_image, batch_predict_text
+from indicoio import intersections, analyze_image, analyze_text, batch_analyze_image, batch_analyze_text
 from indicoio.utils.errors import IndicoError
 
 DIR = os.path.dirname(os.path.realpath(__file__))
@@ -158,7 +158,7 @@ class BatchAPIRun(unittest.TestCase):
     def test_batch_multi_api_image(self):
         test_data = [os.path.normpath(os.path.join(DIR, "data/48by48.png")),
                      os.path.normpath(os.path.join(DIR, "data/48by48.png"))]
-        response = predict_image(test_data, apis=config.IMAGE_APIS, api_key=self.api_key)
+        response = analyze_image(test_data, apis=config.IMAGE_APIS, api_key=self.api_key)
 
         self.assertTrue(isinstance(response, dict))
         self.assertTrue(set(response.keys()) == set(config.IMAGE_APIS))
@@ -166,32 +166,32 @@ class BatchAPIRun(unittest.TestCase):
 
     def test_batch_multi_api_text(self):
         test_data = ['clearly an english sentence']
-        response = predict_text(test_data, apis=config.TEXT_APIS, api_key=self.api_key)
+        response = analyze_text(test_data, apis=config.TEXT_APIS, api_key=self.api_key)
 
         self.assertTrue(isinstance(response, dict))
         self.assertTrue(set(response.keys()) == set(config.TEXT_APIS))
 
     def test_default_multi_api_text(self):
         test_data = ['clearly an english sentence']
-        response = predict_text(test_data, api_key=self.api_key)
+        response = analyze_text(test_data, api_key=self.api_key)
 
         self.assertTrue(isinstance(response, dict))
         self.assertTrue(set(response.keys()) == set(config.TEXT_APIS))
 
     def test_multi_api_bad_api(self):
         self.assertRaises(IndicoError,
-                          predict_text,
+                          analyze_text,
                           "this shouldn't work",
                           apis=["sentiment", "somethingbad"])
 
     def test_multi_bad_mixed_api(self):
         self.assertRaises(IndicoError,
-                            predict_text,
+                            analyze_text,
                             "this shouldn't work",
                             apis=["fer", "sentiment", "facial_features"])
     def test_batch_multi_bad_mixed_api(self):
         self.assertRaises(IndicoError,
-                            predict_text,
+                            analyze_text,
                             ["this shouldn't work"],
                             apis=["fer", "sentiment", "facial_features"])
 
@@ -470,18 +470,58 @@ class FullAPIRun(unittest.TestCase):
 
     def test_multi_api_image(self):
         test_data = os.path.normpath(os.path.join(DIR, "data/48by48.png"))
-        response = predict_image(test_data, apis=config.IMAGE_APIS, api_key=self.api_key)
+        response = analyze_image(test_data, apis=config.IMAGE_APIS, api_key=self.api_key)
 
         self.assertTrue(isinstance(response, dict))
         self.assertTrue(set(response.keys()) == set(config.IMAGE_APIS))
 
     def test_multi_api_text(self):
         test_data = 'clearly an english sentence'
-        response = predict_text(test_data, apis=config.TEXT_APIS, api_key=self.api_key)
+        response = analyze_text(test_data, apis=config.TEXT_APIS, api_key=self.api_key)
 
         self.assertTrue(isinstance(response, dict))
         self.assertTrue(set(response.keys()) == set(config.TEXT_APIS))
 
+    def test_intersections_not_enough_data(self):
+        test_data = ['test_Data']
+        self.assertRaises(
+            IndicoError,
+            intersections,
+            test_data,
+            apis=['text_tags', 'sentiment']
+        )
+
+    def test_intersections_wrong_number_of_apis(self):
+        test_data = ['test data']*3
+        self.assertRaises(
+            IndicoError,
+            intersections,
+            test_data,
+            apis=['text_tags', 'sentiment', 'language']
+        )
+
+    def test_intersections_bad_api_type(self):
+        test_data = ['test data']*3
+        self.assertRaises(
+            IndicoError,
+            intersections,
+            test_data,
+            apis=['text_tags', 'fer']
+        )
+
+    def test_intersections_valid_input(self):
+        test_data = ['test data']*3
+        apis = ['text_tags', 'sentiment']
+        results = intersections(test_data, apis=apis)
+        assert set(results.keys()) < set(apis)
+
+    def test_intersections_valid_raw_input(self):
+        test_data = {
+            'sentiment': [0.1, 0.2, 0.3],
+            'twitter_engagement': [0.1, 0.2, 0.3]
+        }
+        results = intersections(test_data, apis=['sentiment', 'twitter_engagement'])
+        assert set(results.keys()) < set(test_data.keys())
 
     def test_language(self):
         language_set = set([