FIX: check if data is a list to determine if batch or single request

indicoio/__init__.py

@@ -1,4 +1,5 @@
-from functools import partial
+from functools import wraps, partial
+import warnings
 
 Version, version, __version__, VERSION = ('0.8.1',) * 4
 
@@ -23,9 +24,26 @@ from indicoio.utils.multi import predict_image, predict_text
 
 from indicoio.config import API_NAMES
 
+def deprecation_decorator(f, api):
+    @wraps(f)
+    def wrapper(*args, **kwargs):
+        warnings.warn(
+            "'batch_" + api + "' will be deprecated in the next major update.  Please call '" + api + "' instead with the same arguments.",
+            DeprecationWarning
+        )
+        return f(*args, **kwargs)
+    return wrapper
 
+def detect_batch_decorator(f):
+    @wraps(f)
+    def wrapper(*args, **kwargs):
+        if isinstance(args[0], list):
+            kwargs['batch'] = True
+        return f(*args, **kwargs)
+    return wrapper
+    
 apis = dict((api, globals().get(api)) for api in API_NAMES)
 
 for api in apis:
-    globals()[api] = partial(apis[api])
-    globals()['batch_' + api] = partial(apis[api], batch=True)
+    globals()[api] = partial(detect_batch_decorator(apis[api]))
+    globals()['batch_' + api] = partial(deprecation_decorator(apis[api], api), batch=True)

indicoio/utils/api.py

@@ -8,12 +8,15 @@ from indicoio.utils.errors import IndicoError, DataStructureException
 from indicoio import JSON_HEADERS
 from indicoio import config
 
-def api_handler(arg, cloud, api, url_params = {"batch":False, "api_key":None}, **kwargs):
+def api_handler(arg, cloud, api, url_params=None, **kwargs):
+    if url_params is None:
+        url_params = {"api_key":None, batch:False }
+
     data = {'data': arg}
     data.update(**kwargs)
     json_data = json.dumps(data)
     if not cloud:
-        cloud=config.cloud
+        cloud = config.cloud
 
     if cloud:
         host = "%s.indico.domains" % cloud

indicoio/utils/image.py

@@ -26,14 +26,8 @@ def image_preprocess(image, size=(48,48), batch=False):
         elif B64_PATTERN.match(b64_str) is not None:
             return b64_str
         else:
-            raise IndicoError("Snose tring provided must be a valid filepath or base64 encoded string")
+            raise IndicoError("String provided must be a valid filepath or base64 encoded string")
 
-    elif isinstance(image, list): # image passed in is a list and not np.array
-        warnings.warn(
-            "Input as lists of pixels will be deprecated in the next major update",
-            DeprecationWarning
-        )
-        out_image = process_list_image(image)
     elif isinstance(image, Image.Image):
         out_image = image
     elif type(image).__name__ == "ndarray": # image is from numpy/scipy
@@ -80,38 +74,3 @@ def get_element_type(_list, dimens):
         elem = elem[0]
     return type(elem)
 
-
-def process_list_image(_list):
-    """
-    Processes list to be [[(int, int, int), ...]]
-    """
-    # Check if list is empty
-    if not _list:
-        return _list
-
-    dimens = get_list_dimensions(_list)
-    data_type = get_element_type(_list, dimens)
-
-    seq_obj = []
-
-    out_image = Image.new("RGB", (dimens[0], dimens[1]))
-    for i in xrange(dimens[0]):
-        for j in xrange(dimens[1]):
-            elem = _list[i][j]
-            if len(dimens) >= 3:
-                #RGB(A)
-                if data_type == float:
-                    seq_obj.append((int(elem[0] * 255), int(elem[1] * 255), int(elem[2] * 255)))
-                else:
-                    seq_obj.append(tuple(elem[0:3]))
-            elif data_type == float:
-                #Grayscale 0 - 1.0f
-                seq_obj.append((int(elem * 255), ) * 3)
-            else:
-                #Grayscale 0 - 255
-                seq_obj.append((elem, ) * 3)
-
-    #Needs to be 0 - 255 in flattened list of (R, G, B)
-    out_image.putdata(data = seq_obj)
-
-    return out_image

tests/test_remote.py

@@ -31,74 +31,74 @@ class BatchAPIRun(unittest.TestCase):
 
     def test_batch_texttags(self):
         test_data = ["On Monday, president Barack Obama will be..."]
-        response = batch_text_tags(test_data, api_key=self.api_key)
+        response = text_tags(test_data, api_key=self.api_key)
         self.assertTrue(isinstance(response, list))
 
     def test_batch_keywords(self):
         test_data = ["A working api is key to the success of our young company"]
         words = [set(text.lower().split()) for text in test_data]
-        response = batch_keywords(test_data, api_key=self.api_key)
+        response = keywords(test_data, api_key=self.api_key)
         self.assertTrue(isinstance(response, list))
         self.assertTrue(set(response[0].keys()).issubset(words[0]))
 
     def test_batch_posneg(self):
         test_data = ['Worst song ever', 'Best song ever']
-        response = batch_sentiment(test_data, api_key=self.api_key)
+        response = sentiment(test_data, api_key=self.api_key)
         self.assertTrue(isinstance(response, list))
         self.assertTrue(response[0] < 0.5)
 
     def test_batch_sentiment_hq(self):
         test_data = ['Worst song ever', 'Best song ever']
-        response = batch_sentiment_hq(test_data, api_key=self.api_key)
+        response = sentiment_hq(test_data, api_key=self.api_key)
         self.assertTrue(isinstance(response, list))
         self.assertTrue(response[0] < 0.5)
 
     def test_batch_political(self):
         test_data = ["Guns don't kill people, people kill people."]
-        response = batch_political(test_data, api_key=self.api_key)
+        response = political(test_data, api_key=self.api_key)
         self.assertTrue(isinstance(response, list))
 
     def test_batch_fer(self):
-        test_data = [generate_array((48,48))]
-        response = batch_fer(test_data, api_key=self.api_key)
+        test_data = [os.path.normpath(os.path.join(DIR, "data/48by48.png"))]
+        response = fer(test_data, api_key=self.api_key)
         self.assertTrue(isinstance(response, list))
         self.assertTrue(isinstance(response[0], dict))
 
     def test_batch_content_filtering(self):
-        test_data = [generate_array((48,48))]
-        response = batch_content_filtering(test_data, api_key=self.api_key)
+        test_data = [os.path.normpath(os.path.join(DIR, "data/48by48.png"))]
+        response = content_filtering(test_data, api_key=self.api_key)
         self.assertTrue(isinstance(response, list))
         self.assertTrue(isinstance(response[0], float))
 
     def test_batch_fer_bad_b64(self):
         test_data = ["$bad#FI jeaf9(#0"]
-        self.assertRaises(IndicoError, batch_fer, test_data, api_key=self.api_key)
+        self.assertRaises(IndicoError, fer, test_data, api_key=self.api_key)
 
     def test_batch_fer_good_b64(self):
         test_data = ["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"]
-        response = batch_fer(test_data, api_key=self.api_key)
+        response = fer(test_data, api_key=self.api_key)
         self.assertTrue(isinstance(response, list))
         self.assertTrue(isinstance(response[0], dict))
 
     def test_batch_fer_filepath(self):
         test_data = [os.path.normpath(os.path.join(DIR, "data/fear.png"))]
-        response = batch_fer(test_data, api_key=self.api_key)
+        response = fer(test_data, api_key=self.api_key)
         self.assertTrue(isinstance(response, list))
         self.assertTrue(isinstance(response[0], dict))
 
     def test_batch_fer_pil_image(self):
         test_data = [Image.open(os.path.normpath(os.path.join(DIR, "data/fear.png")))]
-        response = batch_fer(test_data, api_key=self.api_key)
+        response = fer(test_data, api_key=self.api_key)
         self.assertTrue(isinstance(response, list))
         self.assertTrue(isinstance(response[0], dict))
 
     def test_batch_fer_nonexistant_filepath(self):
         test_data = ["data/unhappy.png"]
-        self.assertRaises(IndicoError, batch_fer, test_data, api_key=self.api_key)
+        self.assertRaises(IndicoError, fer, test_data, api_key=self.api_key)
 
     def test_batch_facial_features(self):
-        test_data = [generate_array((48,48))]
-        response = batch_facial_features(test_data, api_key=self.api_key)
+        test_data = [os.path.normpath(os.path.join(DIR, "data/48by48.png"))]
+        response = facial_features(test_data, api_key=self.api_key)
         self.assertTrue(isinstance(response, list))
         self.assertTrue(isinstance(response[0], list))
         self.assertEqual(len(response[0]), 48)
@@ -117,22 +117,22 @@ class BatchAPIRun(unittest.TestCase):
     # have decided how we are dealing with them
 
     def test_batch_image_features_greyscale(self):
-        test_data = [generate_array((48,48))]
-        response = batch_image_features(test_data, api_key=self.api_key)
+        test_data = [os.path.normpath(os.path.join(DIR, "data/48by48.png"))]
+        response = image_features(test_data, api_key=self.api_key)
         self.assertTrue(isinstance(response, list))
         self.assertTrue(isinstance(response[0], list))
         self.assertEqual(len(response[0]), 2048)
 
     def test_batch_image_features_rgb(self):
-        test_data = [generate_array((48,48))]
-        response = batch_image_features(test_data, api_key=self.api_key)
+        test_data = [os.path.normpath(os.path.join(DIR, "data/48by48rgb.png"))]
+        response = image_features(test_data, api_key=self.api_key)
         self.assertTrue(isinstance(response, list))
         self.assertTrue(isinstance(response[0], list))
         self.assertEqual(len(response[0]), 2048)
 
     def test_batch_language(self):
         test_data = ['clearly an english sentence']
-        response = batch_language(test_data, api_key=self.api_key)
+        response = language(test_data, api_key=self.api_key)
         self.assertTrue(isinstance(response, list))
         self.assertTrue(response[0]['English'] > 0.25)
 
@@ -140,14 +140,15 @@ class BatchAPIRun(unittest.TestCase):
         batch = ["London Underground's boss Mike Brown warned that the strike ..."]
         expected_entities = ("London Underground", "Mike Brown")
         expected_keys = set(["categories", "confidence"])
-        entities = batch_named_entities(batch)[0]
+        entities = named_entities(batch)[0]
         for entity in expected_entities:
             assert entity in expected_entities
             assert not (set(entities[entity]) - expected_keys)
 
     def test_batch_multi_api_image(self):
-        test_data = [generate_array((48,48)), generate_int_array((48,48))]
-        response = batch_predict_image(test_data, apis=config.IMAGE_APIS, api_key=self.api_key)
+        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)
 
         self.assertTrue(isinstance(response, dict))
         self.assertTrue(set(response.keys()) == set(config.IMAGE_APIS))
@@ -155,21 +156,21 @@ class BatchAPIRun(unittest.TestCase):
 
     def test_batch_multi_api_text(self):
         test_data = ['clearly an english sentence']
-        response = batch_predict_text(test_data, apis=config.TEXT_APIS, api_key=self.api_key)
+        response = predict_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 = batch_predict_text(test_data, api_key=self.api_key)
+        response = predict_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,
-                          batch_predict_text,
+                          predict_text,
                           "this shouldn't work",
                           apis=["sentiment", "somethingbad"])
 
@@ -180,14 +181,14 @@ class BatchAPIRun(unittest.TestCase):
                             apis=["fer", "sentiment", "facial_features"])
     def test_batch_multi_bad_mixed_api(self):
         self.assertRaises(IndicoError,
-                            batch_predict_text,
+                            predict_text,
                             ["this shouldn't work"],
                             apis=["fer", "sentiment", "facial_features"])
 
     def test_batch_set_cloud(self):
         test_data = ['clearly an english sentence']
         self.assertRaises(ConnectionError,
-                          batch_language,
+                          language,
                           test_data,
                           api_key=self.api_key,
                           cloud='invalid/cloud')
@@ -290,7 +291,7 @@ class FullAPIRun(unittest.TestCase):
 
     def test_good_fer(self):
         fer_set = set(['Angry', 'Sad', 'Neutral', 'Surprise', 'Fear', 'Happy'])
-        test_face = generate_array((48,48))
+        test_face = os.path.normpath(os.path.join(DIR, "data/48by48.png"))
         response = fer(test_face)
 
         self.assertTrue(isinstance(response, dict))
@@ -298,14 +299,14 @@ class FullAPIRun(unittest.TestCase):
 
     def test_good_int_array_fer(self):
         fer_set = set(['Angry', 'Sad', 'Neutral', 'Surprise', 'Fear', 'Happy'])
-        test_face = generate_int_array((48,48))
+        test_face = os.path.normpath(os.path.join(DIR, "data/48by48.png"))
         response = fer(test_face)
 
         self.assertTrue(isinstance(response, dict))
         self.assertEqual(fer_set, set(response.keys()))
 
     def test_happy_fer(self):
-        test_face = self.load_image("data/happy.png", as_grey=True)
+        test_face = os.path.normpath(os.path.join(DIR, "data/happy.png"))
         response = fer(test_face)
         self.assertTrue(isinstance(response, dict))
         self.assertTrue(response['Happy'] > 0.5)
@@ -317,26 +318,26 @@ class FullAPIRun(unittest.TestCase):
         self.assertTrue(response['Happy'] > 0.5)
 
     def test_fear_fer(self):
-        test_face = self.load_image("data/fear.png", as_grey=True)
+        test_face = os.path.normpath(os.path.join(DIR, "data/fear.png"))
         response = fer(test_face)
         self.assertTrue(isinstance(response, dict))
         self.assertTrue(response['Fear'] > 0.25)
 
     def test_bad_fer(self):
         fer_set = set(['Angry', 'Sad', 'Neutral', 'Surprise', 'Fear', 'Happy'])
-        test_face = generate_array((56, 56))
+        test_face = os.path.normpath(os.path.join(DIR, "data/64by64.png"))
         response = fer(test_face)
 
         self.assertTrue(isinstance(response, dict))
         self.assertEqual(fer_set, set(response.keys()))
 
     def test_safe_content_filtering(self):
-        test_face = self.load_image("data/happy.png", as_grey=True)
+        test_face = os.path.normpath(os.path.join(DIR, "data/happy.png"))
         response = content_filtering(test_face)
         self.assertTrue(response < 0.5)
 
     def test_good_facial_features(self):
-        test_face = generate_array((48,48))
+        test_face = os.path.normpath(os.path.join(DIR, "data/48by48.png"))
         response = facial_features(test_face)
 
         self.assertTrue(isinstance(response, list))
@@ -344,7 +345,7 @@ class FullAPIRun(unittest.TestCase):
         self.check_range(response)
 
     def test_rgba_int_array_facial_features(self):
-        test_face = generate_rgba_int_array((48, 48))
+        test_face = os.path.normpath(os.path.join(DIR, "data/48by48rgba.png"))
         response = facial_features(test_face)
 
         self.assertTrue(isinstance(response, list))
@@ -353,7 +354,7 @@ class FullAPIRun(unittest.TestCase):
 
     def test_good_int_array_facial_features(self):
         fer_set = set(['Angry', 'Sad', 'Neutral', 'Surprise', 'Fear', 'Happy'])
-        test_face = generate_int_array((48,48))
+        test_face = os.path.normpath(os.path.join(DIR, "data/48by48.png"))
         response = facial_features(test_face)
 
         self.assertTrue(isinstance(response, list))
@@ -371,7 +372,7 @@ class FullAPIRun(unittest.TestCase):
     #     self.check_range(response)
 
     def test_good_image_features_greyscale(self):
-        test_image = generate_array((48,48))
+        test_image = os.path.normpath(os.path.join(DIR, "data/48by48.png"))
         response = image_features(test_image)
 
         self.assertTrue(isinstance(response, list))
@@ -379,7 +380,7 @@ class FullAPIRun(unittest.TestCase):
         self.check_range(response)
 
     def test_good_image_features_rgb(self):
-        test_image = [[(random.random(),) * 3 for _ in xrange(48)] for _ in xrange(48)]
+        test_image = os.path.normpath(os.path.join(DIR, "data/48by48rgb.png"))
         response = image_features(test_image)
 
         self.assertTrue(isinstance(response, list))
@@ -387,7 +388,7 @@ class FullAPIRun(unittest.TestCase):
         self.check_range(response)
 
     def test_multi_api_image(self):
-        test_data = generate_array((48,48))
+        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)
 
         self.assertTrue(isinstance(response, dict))
@@ -558,15 +559,5 @@ def flatten(container):
         else:
             yield i
 
-def generate_array(size):
-    return [[random.random() for _ in xrange(size[0])] for _ in xrange(size[1])]
-
-def generate_int_array(size):
-    return [[random.randint(0, 255) for _ in xrange(size[0])] for _ in xrange(size[1])]
-
-def generate_rgba_int_array(size):
-    return [[[random.randint(0, 255) for _ in xrange(3)] for _ in xrange(size[0])] for _ in xrange(size[1])]
-
-
 if __name__ == "__main__":
     unittest.main()