Email + password auth from client

indicoio/images/features.py

@@ -5,7 +5,7 @@ import numpy as np
 
 from indicoio.utils import image_preprocess, api_handler
 
-def facial_features(api_root, image, batch=False):
+def facial_features(api_root, image, batch=False, auth=None):
     """
     Given an grayscale input image of a face, returns a 48 dimensional feature vector explaining that face.
     Useful as a form of feature engineering for face oriented tasks.
@@ -27,9 +27,9 @@ def facial_features(api_root, image, batch=False):
     :type image: list of lists
     :rtype: List containing feature responses
     """
-    return api_handler(image, api_root + "facialfeatures", batch=batch)
+    return api_handler(image, api_root + "facialfeatures", batch=batch, auth=auth)
 
-def image_features(api_root, image, batch=False):
+def image_features(api_root, image, batch=False, auth=None):
     """
     Given an input image, returns a 2048 dimensional sparse feature vector explaining that image. 
     Useful as a form of feature engineering for image oriented tasks.
@@ -60,4 +60,4 @@ def image_features(api_root, image, batch=False):
     :rtype: List containing features
     """
     image = image_preprocess(image)
-    return api_handler(image, api_root + "imagefeatures", batch=batch)
+    return api_handler(image, api_root + "imagefeatures", batch=batch, auth=auth)

indicoio/images/fer.py

@@ -4,7 +4,7 @@ import requests
 import numpy as np
 from indicoio.utils import api_handler
 
-def fer(api_root, image, batch=False):
+def fer(api_root, image, batch=False, auth=None):
     """
     Given a grayscale input image of a face, returns a probability distribution over emotional state.
     Input should be in a list of list format, resizing will be attempted internally but for best 
@@ -28,4 +28,4 @@ def fer(api_root, image, batch=False):
     :rtype: Dictionary containing emotion probability pairs
     """
     
-    return api_handler(image, api_root + "fer", batch=batch)
+    return api_handler(image, api_root + "fer", batch=batch, auth=auth)

indicoio/text/lang.py

@@ -1,6 +1,6 @@
 from indicoio.utils import api_handler
 
-def language(api_root, text, batch=False):
+def language(api_root, text, batch=False, auth=None):
     """
     Given input text, returns a probability distribution over 33 possible 
     languages of what language the text was written in.
@@ -23,4 +23,4 @@ def language(api_root, text, batch=False):
     :rtype: Dictionary of language probability pairs
     """
     
-    return api_handler(text, api_root + "language", batch=batch)
+    return api_handler(text, api_root + "language", batch=batch, auth=auth)

indicoio/text/sentiment.py

@@ -1,7 +1,7 @@
 from indicoio import JSON_HEADERS
 from indicoio.utils import api_handler
 
-def political(api_root, text, batch=False):
+def political(api_root, text, batch=False, auth=None):
     """
     Given input text, returns a probability distribution over the political alignment of the speaker.
 
@@ -27,9 +27,9 @@ def political(api_root, text, batch=False):
     :rtype: Dictionary of party probability pairs
     """
 
-    return api_handler(text, api_root + "political", batch=batch)
+    return api_handler(text, api_root + "political", batch=batch, auth=auth)
 
-def posneg(api_root, text, batch=False):
+def posneg(api_root, text, batch=False, auth=None):
     """
     Given input text, returns a scalar estimate of the sentiment of that text.
     Values are roughly in the range 0 to 1 with 0.5 indicating neutral sentiment.
@@ -50,4 +50,4 @@ def posneg(api_root, text, batch=False):
     :rtype: Float
     """
     
-    return api_handler(text, api_root + "sentiment", batch=batch)
+    return api_handler(text, api_root + "sentiment", batch=batch, auth=auth)

indicoio/text/tagging.py

@@ -1,6 +1,6 @@
 from indicoio.utils import api_handler
 
-def text_tags(api_root, text, batch=False):
+def text_tags(api_root, text, batch=False, auth=None):
     """
     Given input text, returns a probability distribution over 100 document categories
 
@@ -22,4 +22,4 @@ def text_tags(api_root, text, batch=False):
     :rtype: Dictionary of class probability pairs
     """
     
-    return api_handler(text, api_root + "texttags", batch=batch)
+    return api_handler(text, api_root + "texttags", batch=batch, auth=None)

indicoio/utils/__init__.py

@@ -1,14 +1,31 @@
-import inspect, json, requests
+import inspect, json, getpass, os
+import requests
 import numpy as np
 from skimage.transform import resize
 
 from indicoio import JSON_HEADERS
 
-def api_handler(arg, url, batch=False):
+def auth_query():
+    email = os.environ.get("INDICO_EMAIL")
+    password = os.environ.get("INDICO_PASSWORD")
+
+    # store settings
+    if not email:
+        email = raw_input("Email: ")
+        os.environ["INDICO_EMAIL"] = email
+
+    if not password:
+        password = getpass.getpass("Password: ")
+        os.environ["INDICO_PASSWORD"] = password
+
+    return (email, password)
+
+def api_handler(arg, url, batch=False, auth=None):
     data_dict = json.dumps({'data': arg})
     if batch:
         url += "/batch"
-    response = requests.post(url, data=data_dict, headers=JSON_HEADERS).json()
+        auth = auth_query()
+    response = requests.post(url, data=data_dict, headers=JSON_HEADERS, auth=auth).json()
     results = response.get('results', False)
     if not results:
         error = response.get('error')