Merge pull request #55 from IndicoDataSolutions/Chris/multi-api

ADD: Endpoint for multi api requests

indicoio/__init__.py

@@ -16,18 +16,11 @@ from indicoio.text.tagging import text_tags
 from indicoio.images.fer import fer
 from indicoio.images.features import facial_features
 from indicoio.images.features import image_features
+from indicoio.utils.multi import predict_image, predict_text
 
-apis = [
-    'political',
-    'posneg',
-    'sentiment',
-    'language',
-    'fer',
-    'facial_features',
-    'image_features',
-    'text_tags'
-]
-apis = dict((api, globals().get(api)) for api in apis)
+from indicoio.config import API_NAMES
+
+apis = dict((api, globals().get(api)) for api in API_NAMES)
 
 for api in apis:
     globals()[api] = partial(apis[api])

indicoio/config.py

@@ -45,11 +45,26 @@ class Settings(ConfigParser.ConfigParser):
             None
         )
 
+TEXT_APIS = [
+    'text_tags',
+    'political',
+    'sentiment',
+    'language'
+]
+
+IMAGE_APIS = [
+    'fer',
+    'facial_features',
+    'image_features'
+]
+
+API_NAMES = IMAGE_APIS + TEXT_APIS + ["predict_text", "predict_image"]
 
 SETTINGS = Settings(files=[
     os.path.expanduser("~/.indicorc"),
     os.path.join(os.getcwd(), '.indicorc')
 ])
+
 api_key = SETTINGS.api_key()
 cloud = SETTINGS.cloud()
 PUBLIC_API_HOST = 'apiv2.indico.io'

indicoio/images/features.py

@@ -25,7 +25,7 @@ def facial_features(image, cloud=None, batch=False, api_key=None, **kwargs):
     :rtype: List containing feature responses
     """
     image = image_preprocess(image, batch=batch)
-    return api_handler(image, cloud=cloud, api="facialfeatures", batch=batch, api_key=api_key, **kwargs)
+    return api_handler(image, cloud=cloud, api="facialfeatures", url_params={"batch":batch, "api_key":api_key}, **kwargs)
 
 def image_features(image, cloud=None, batch=False, api_key=None, **kwargs):
     """
@@ -58,4 +58,4 @@ def image_features(image, cloud=None, batch=False, api_key=None, **kwargs):
     :rtype: List containing features
     """
     image = image_preprocess(image, batch=batch, size=(64,64))
-    return api_handler(image, cloud=cloud, api="imagefeatures", batch=batch, api_key=api_key, **kwargs)
+    return api_handler(image, cloud=cloud, api="imagefeatures", url_params={"batch":batch, "api_key":api_key}, **kwargs)

indicoio/images/fer.py

@@ -27,4 +27,4 @@ def fer(image, cloud=None, batch=False, api_key=None, **kwargs):
     :rtype: Dictionary containing emotion probability pairs
     """
     image = image_preprocess(image, batch=batch)
-    return api_handler(image, cloud=cloud, api="fer", batch=batch, api_key=api_key, **kwargs)
+    return api_handler(image, cloud=cloud, api="fer", url_params={"batch":batch, "api_key":api_key}, **kwargs)

indicoio/text/lang.py

@@ -24,4 +24,4 @@ def language(text, cloud=None, batch=False, api_key=None, **kwargs):
     :rtype: Dictionary of language probability pairs
     """
 
-    return api_handler(text, cloud=cloud, api="language", batch=batch, api_key=api_key, **kwargs)
+    return api_handler(text, cloud=cloud, api="language", url_params={"batch":batch, "api_key":api_key}, **kwargs)

indicoio/text/sentiment.py

@@ -26,7 +26,7 @@ def political(text, cloud=None, batch=False, api_key=None, **kwargs):
     :rtype: Dictionary of party probability pairs
     """
 
-    return api_handler(text, cloud=cloud, api="political", batch=batch, api_key=api_key, **kwargs)
+    return api_handler(text, cloud=cloud, api="political", url_params={"batch":batch, "api_key":api_key}, **kwargs)
 
 def posneg(text, cloud=None, batch=False, api_key=None, **kwargs):
     """
@@ -49,4 +49,4 @@ def posneg(text, cloud=None, batch=False, api_key=None, **kwargs):
     :rtype: Float
     """
 
-    return api_handler(text, cloud=cloud, api="sentiment", batch=batch, api_key=api_key, **kwargs)
+    return api_handler(text, cloud=cloud, api="sentiment", url_params={"batch":batch, "api_key":api_key}, **kwargs)

indicoio/text/tagging.py

@@ -23,4 +23,4 @@ def text_tags(text, cloud=None, batch=False, api_key=None, **kwargs):
     :rtype: Dictionary of class probability pairs
     """
 
-    return api_handler(text, cloud=cloud, api="texttags", batch=batch, api_key=api_key, **kwargs)
+    return api_handler(text, cloud=cloud, api="texttags", url_params={"batch":batch, "api_key":api_key}, **kwargs)

indicoio/utils/__init__.py

@@ -8,7 +8,7 @@ from indicoio import config
 B64_PATTERN = re.compile("^([A-Za-z0-9+/]{4})*([A-Za-z0-9+/]{4}|[A-Za-z0-9+/]{3}=|[A-Za-z0-9+/]{2}==)")
 
 
-def api_handler(arg, cloud, api, batch=False, api_key=None, **kwargs):
+def api_handler(arg, cloud, api, url_params = {"batch":False, "api_key":None}, **kwargs):
     data = {'data': arg}
     data.update(**kwargs)
     json_data = json.dumps(data)
@@ -21,13 +21,11 @@ def api_handler(arg, cloud, api, batch=False, api_key=None, **kwargs):
         # default to indico public cloud
         host = config.PUBLIC_API_HOST
 
-    if not api_key:
-        api_key = config.api_key
-
     url = config.url_protocol + "//%s/%s" % (host, api)
-    url = url + "/batch" if batch else url
-    url += "?key=%s" % api_key
-
+    url = url + "/batch" if url_params.get("batch", False) else url
+    url += "?key=%s" % (url_params.get("api_key", None) or config.api_key)
+    if "apis" in url_params:
+        url += "&apis=%s" % ",".join(url_params["apis"])
 
     response = requests.post(url, data=json_data, headers=JSON_HEADERS)
     if response.status_code == 503 and cloud != None:

indicoio/utils/multi.py

@@ -0,0 +1,117 @@
+from indicoio.config import TEXT_APIS, IMAGE_APIS, API_NAMES
+from indicoio.utils import api_handler
+
+
+CLIENT_SERVER_MAP = dict((api, api.strip().replace("_", "").lower()) for api in API_NAMES)
+SERVER_CLIENT_MAP = dict((v, k) for k, v in CLIENT_SERVER_MAP.iteritems())
+
+def multi(data, type, apis, available, batch=False, **kwargs):
+    """
+    Helper to make multi requests of different types.
+
+    :param data: data to be sent in JSON.
+    :param type: String type of API request
+    :param apis: List of apis to use.
+    :param apis: List of apis available for use.
+    :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
+    invalid_apis = [api for api in apis if api not in available]
+    if invalid_apis:
+        raise ValueError("%s are not valid %s APIs. Please reference the available APIs below:\n%s"
+                            % (", ".join(invalid_apis), type, ", ".join(available))
+                        )
+    # Convert client api names to server names before sending request
+    apis = map(CLIENT_SERVER_MAP.get, apis)
+    result = api_handler(data, url_params = {"apis":apis, "batch":batch}, **kwargs)
+    return handle_response(result)
+
+def handle_response(result):
+    try:
+        # Parse out the results to a dicionary of api: result
+        return dict((SERVER_CLIENT_MAP[api], parsed_response(res))
+            for api, res in result.iteritems())
+    except KeyError:
+        for api in result:
+            if "error" in result[api]:
+                raise ValueError(result[api]["error"])
+        raise Exception("Sorry, %s API returned an unexpected response:\n%s" % (api, result[api]))
+
+
+def predict_text(input_text, apis=TEXT_APIS, cloud=None, batch=False, api_key=None, **kwargs):
+    """
+    Given input text, returns the results of specified text apis. Possible apis
+    include: [ 'text_tags', 'political', 'sentiment', 'language' ]
+
+    Example usage:
+
+    .. code-block:: python
+
+       >>> import indicoio
+       >>> text = 'Monday: Delightful with mostly sunny skies. Highs in the low 70s.'
+       >>> results = indicoio.text(data = text, apis = ["language", "sentiment"])
+       >>> language_results = results["langauge"]
+       >>> sentiment_results = results["sentiment"]
+
+    :param text: The text to be analyzed.
+    :param apis: List of apis to use.
+    :type text: str or unicode
+    :type apis: list of str
+    :rtype: Dictionary of api responses
+    """
+
+    return multi(
+        api="apis",
+        data=input_text,
+        type="text",
+        available = TEXT_APIS,
+        cloud=cloud,
+        batch=batch,
+        api_key=api_key,
+        apis=apis,
+        **kwargs)
+
+
+def predict_image(image, apis=IMAGE_APIS, cloud=None, batch=False, api_key=None, **kwargs):
+    """
+    Given input image, returns the results of specified image apis. Possible apis
+    include: ['fer', 'facial_features', 'image_features']
+
+    Example usage:
+
+    .. code-block:: python
+
+       >>> import indicoio
+       >>> import numpy as np
+       >>> face = np.zeros((48,48)).tolist()
+       >>> results = indicoio.image(image = face, apis = ["fer", "facial_features"])
+       >>> fer = results["fer"]
+       >>> facial_features = results["facial_features"]
+
+    :param text: The text to be analyzed.
+    :param apis: List of apis to use.
+    :type text: str or unicode
+    :type apis: list of str
+    :rtype: Dictionary of api responses
+    """
+
+    return multi(
+        api="apis",
+        data=image,
+        type="image",
+        available=IMAGE_APIS,
+        cloud=cloud,
+        batch=batch,
+        api_key=api_key,
+        apis=apis,
+        **kwargs)
+
+def parsed_response(response):
+    result = response.get('results') or response.get('error', False)
+    if result:
+        return result
+    raise KeyError

tests/test_remote.py

@@ -9,6 +9,7 @@ from indicoio import config
 from indicoio import political, sentiment, fer, facial_features, language, image_features, text_tags
 from indicoio import batch_political, batch_sentiment, batch_fer, batch_facial_features
 from indicoio import batch_language, batch_image_features, batch_text_tags
+from indicoio import predict_image, predict_text, batch_predict_image, batch_predict_text
 
 DIR = os.path.dirname(os.path.realpath(__file__))
 
@@ -113,6 +114,58 @@ class BatchAPIRun(unittest.TestCase):
         self.assertTrue(isinstance(response, list))
         self.assertTrue(response[0]['English'] > 0.25)
 
+    def test_multi_api_image(self):
+        test_data = generate_array((48,48))
+        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))
+
+    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)
+
+        self.assertTrue(isinstance(response, dict))
+        self.assertTrue(set(response.keys()) == set(config.TEXT_APIS))
+
+    def test_batch_multi_api_image(self):
+        test_data = [generate_array((48,48))]
+        response = batch_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))
+
+    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)
+
+        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)
+
+        self.assertTrue(isinstance(response, dict))
+        self.assertTrue(set(response.keys()) == set(config.TEXT_APIS))
+
+    def test_multi_api_bad_api(self):
+        self.assertRaises(ValueError,
+                          batch_predict_text,
+                          "this shouldn't work",
+                          apis=["sentiment", "somethingbad"])
+
+    def test_multi_bad_mixed_api(self):
+        self.assertRaises(ValueError,
+                            predict_text,
+                            "this shouldn't work",
+                            apis=["fer", "sentiment", "facial_features"])
+    def test_batch_multi_bad_mixed_api(self):
+        self.assertRaises(ValueError,
+                            batch_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,