Cleaner api handler interface + extended tests

indicoio/__init__.py

@@ -2,7 +2,7 @@ from functools import partial
 
 JSON_HEADERS = {'Content-type': 'application/json', 'Accept': 'text/plain'}
 
-Version, version, __version__, VERSION = ('0.4.15',) * 4
+Version, version, __version__, VERSION = ('0.5.0',) * 4
 
 from indicoio.text.sentiment import political, posneg
 from indicoio.text.sentiment import posneg as sentiment

indicoio/config.py

@@ -1,29 +1,54 @@
 import os
+from StringIO import StringIO
 
 import ConfigParser
 
-settings = ConfigParser.ConfigParser()
+class Settings(ConfigParser.ConfigParser):
 
-settings_paths = [
+    def __init__(self, *args, **kwargs):
+        """
+        files: filepaths or open file objects
+        """
+        self.files = kwargs.pop('files')
+
+        ConfigParser.ConfigParser.__init__(self, *args, **kwargs)
+
+        for fd in self.files:
+            try:
+                self.readfp(fd)
+            except AttributeError: 
+                self.read(fd)
+
+        self.auth_settings = self.get_section('auth')
+        self.private_cloud_settings = self.get_section('private_cloud')
+
+    def get_section(self, section):
+        """
+        Retrieve a ConfigParser section as a dictionary, default to {}
+        """
+        try:
+            return dict(self.items(section))
+        except ConfigParser.NoSectionError:
+            return {}
+
+    def cloud(self):
+        return (
+            os.getenv("INDICO_CLOUD") or 
+            self.private_cloud_settings.get('cloud') or 
+            None
+        )
+
+    def auth(self):
+        return (
+            os.getenv("INDICO_USERNAME") or self.auth_settings.get('username'),
+            os.getenv("INDICO_PASSWORD") or self.auth_settings.get('password')
+        )
+
+settings = Settings(files=[
     os.path.expanduser("~/.indicorc"),
     os.path.join(os.getcwd(), '.indicorc')
-]
+])
 
-settings.read(settings_paths)
-
-def get_section(parser, section):
-    try:
-        return dict(parser.items(section))
-    except ConfigParser.NoSectionError:
-        return {}
-
-auth_settings = get_section(settings, 'auth')
-private_cloud_settings = get_section(settings, 'private_cloud')
-
-api_root = (
-    os.getenv("INDICO_PRIVATE_CLOUD_URL") or 
-    private_cloud_settings.get('url_root') or 
-    "http://apiv1.indico.io/"
-)
-
-auth = (auth_settings.get('username'), auth_settings.get('password'))
+auth = settings.auth()
+cloud = settings.cloud()
+public_api_host = 'apiv1.indico.io'

indicoio/images/features.py

@@ -6,7 +6,7 @@ import numpy as np
 from indicoio.utils import image_preprocess, api_handler
 import indicoio.config as config
 
-def facial_features(image, url_root=config.api_root, batch=False, auth=None, **kwargs):
+def facial_features(image, cloud=config.cloud, batch=False, auth=None, **kwargs):
     """
     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.
@@ -28,9 +28,9 @@ def facial_features(image, url_root=config.api_root, batch=False, auth=None, **k
     :type image: list of lists
     :rtype: List containing feature responses
     """
-    return api_handler(image, url_root + "facialfeatures", batch=batch, auth=auth, **kwargs)
+    return api_handler(image, cloud=cloud, api="facialfeatures", batch=batch, auth=auth, **kwargs)
 
-def image_features(image, url_root=config.api_root, batch=False, auth=None, **kwargs):
+def image_features(image, cloud=config.cloud, batch=False, auth=None, **kwargs):
     """
     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.
@@ -61,4 +61,4 @@ def image_features(image, url_root=config.api_root, batch=False, auth=None, **kw
     :rtype: List containing features
     """
     image = image_preprocess(image, batch=batch)
-    return api_handler(image, url_root + "imagefeatures", batch=batch, auth=auth, **kwargs)
+    return api_handler(image, cloud=cloud, api="imagefeatures", batch=batch, auth=auth, **kwargs)

indicoio/images/fer.py

@@ -6,7 +6,7 @@ import numpy as np
 from indicoio.utils import api_handler
 import indicoio.config as config
 
-def fer(image, url_root=config.api_root, batch=False, auth=None, **kwargs):
+def fer(image, cloud=config.cloud, batch=False, auth=None, **kwargs):
     """
     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
@@ -30,4 +30,4 @@ def fer(image, url_root=config.api_root, batch=False, auth=None, **kwargs):
     :rtype: Dictionary containing emotion probability pairs
     """
 
-    return api_handler(image, url_root + "fer", batch=batch, auth=auth, **kwargs)
+    return api_handler(image, cloud=cloud, api="fer", batch=batch, auth=auth, **kwargs)

indicoio/text/lang.py

@@ -1,7 +1,7 @@
 from indicoio.utils import api_handler
 import indicoio.config as config
 
-def language(text, url_root=config.api_root, batch=False, auth=None, **kwargs):
+def language(text, cloud=config.cloud, batch=False, auth=None, **kwargs):
     """
     Given input text, returns a probability distribution over 33 possible
     languages of what language the text was written in.
@@ -24,4 +24,4 @@ def language(text, url_root=config.api_root, batch=False, auth=None, **kwargs):
     :rtype: Dictionary of language probability pairs
     """
 
-    return api_handler(text, url_root + "language", batch=batch, auth=auth, **kwargs)
+    return api_handler(text, cloud=cloud, api="language", batch=batch, auth=auth, **kwargs)

indicoio/text/sentiment.py

@@ -2,7 +2,7 @@ from indicoio import JSON_HEADERS
 from indicoio.utils import api_handler
 import indicoio.config as config
 
-def political(text, url_root=config.api_root, batch=False, auth=None, **kwargs):
+def political(text, cloud=config.cloud, batch=False, auth=None, **kwargs):
     """
     Given input text, returns a probability distribution over the political alignment of the speaker.
 
@@ -28,9 +28,9 @@ def political(text, url_root=config.api_root, batch=False, auth=None, **kwargs):
     :rtype: Dictionary of party probability pairs
     """
 
-    return api_handler(text, url_root + "political", batch=batch, auth=auth, **kwargs)
+    return api_handler(text, cloud=cloud, api="political", batch=batch, auth=auth, **kwargs)
 
-def posneg(text, url_root=config.api_root, batch=False, auth=None, **kwargs):
+def posneg(text, cloud=config.cloud, batch=False, auth=None, **kwargs):
     """
     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.
@@ -51,4 +51,4 @@ def posneg(text, url_root=config.api_root, batch=False, auth=None, **kwargs):
     :rtype: Float
     """
 
-    return api_handler(text, url_root + "sentiment", batch=batch, auth=auth, **kwargs)
+    return api_handler(text, cloud=cloud, api="sentiment", batch=batch, auth=auth, **kwargs)

indicoio/text/tagging.py

@@ -1,7 +1,7 @@
 from indicoio.utils import api_handler
 import indicoio.config as config
 
-def text_tags(text, url_root=config.api_root, batch=False, auth=None, **kwargs):
+def text_tags(text, cloud=config.cloud, batch=False, auth=None, **kwargs):
     """
     Given input text, returns a probability distribution over 100 document categories
 
@@ -23,4 +23,4 @@ def text_tags(text, url_root=config.api_root, batch=False, auth=None, **kwargs):
     :rtype: Dictionary of class probability pairs
     """
 
-    return api_handler(text, url_root + "texttags", batch=batch, auth=auth, **kwargs)
+    return api_handler(text, cloud=cloud, api="texttags", batch=batch, auth=auth, **kwargs)

indicoio/utils/__init__.py

@@ -4,26 +4,22 @@ import numpy as np
 from skimage.transform import resize
 
 from indicoio import JSON_HEADERS
+from indicoio import config
 
-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, **kwargs):
+def api_handler(arg, cloud, api, batch=False, auth=None, **kwargs):
     data = {'data': arg}
     data.update(**kwargs)
     json_data = json.dumps(data)
+
+    if cloud:
+        host = "%s.indico.domains"
+    else: 
+        # default to indico public cloud
+        host = config.public_api_host
+
+    url = "http://%s/%s" % (host, api)
+
     if batch:
         url += "/batch"
 
@@ -34,6 +30,7 @@ def api_handler(arg, url, batch=False, auth=None, **kwargs):
         raise ValueError(error)
     return results
 
+
 class TypeCheck(object):
     """
     Decorator that performs a typecheck on the input to a function
@@ -118,6 +115,7 @@ def normalize(array, distribution=1, norm_range=(0, 1), **kwargs):
         return dict(zip(keys, norm_array))
     return norm_array
 
+
 def image_preprocess(image, batch=False):
     """
     Takes an image and prepares it for sending to the api including