Require api keys

2026-08-02 12:20:18 +08:00 · 2015-04-07 19:08:40 -04:00
parent 7cde7a7fdb
commit f7c263dc9c
16 changed files with 182 additions and 253 deletions
@@ -20,3 +20,4 @@ v0.4.14, Sat Dec 20 -- Fix for batch image features preprocessing, increased tes
 v0.4.15, Sat Dec 20 -- Bug fix release
 v0.5.0, Friday Feb 27 -- Updated to support private cloud, allows for indicorc file to reduce redundant authorization calls, README updates
 v0.5.1, Friday Feb 27 -- More README updates, fixed rst formatting issue, added classifiers
 v0.5.2, Tue March 7 -- Required API keys, configuration settings
@@ -1,29 +1,36 @@
 indicoio-python
 ===============
-A wrapper for a series of APIs made by indico.
+A wrapper for the [indico API](http://indico.io).
-Check out the main site on:
+The indico API is free to use, and no training data is required.  
 http://indico.io
 Our APIs are totally free to use, and ready to be used in your application. No data or training required.
 Installation
 ------------
-```
+From PyPI:
 ```bash
 pip install indicoio
 ```
-Documentation
+Installation
 ------------
-Available at [indico.readme.io](http://indico.readme.io/v1.0/docs)
+From source:
 ```bash
 git clone https://github.com/IndicoDataSolutions/IndicoIo-python.git 
 python setup.py install
 ```
-Current APIs
+API Keys + Setup
 ----------------
 For API key registration and setup, checkout our [quickstart guide](https://dash.readme.io/project/indico/v2.0/docs/api-keys).
 Full Documentation
 ------------
 Detailed documentation and further code examples are available at [indico.reame.io](http://indico.readme.io/v2.0/docs/python).
-Right now this wrapper supports the following apps:
+Supported APIs:
 ------------
 - Positive/Negative Sentiment Analysis
 - Political Sentiment Analysis
@@ -35,26 +42,21 @@ Right now this wrapper supports the following apps:
 Examples
 --------
-```
+```python
->>> import numpy as np
+>>> from indicoio import political, sentiment, language, text_tags, fer, facial_features, image_features
->>> from indicoio import political, sentiment, fer, facial_features, language
+>>> indicoio.config.api_key = "YOUR_API_KEY"
 >>> political("Guns don't kill people. People kill people.")
 {u'Libertarian': 0.47740164630834825, u'Green': 0.08454409540443657, u'Liberal': 0.16617097211030055, u'Conservative': 0.2718832861769146}
 >>> sentiment('Worst movie ever.')
-{u'Sentiment': 0.07062467665597527}
+0.07062467665597527
 >>> sentiment('Really enjoyed the movie.')
-{u'Sentiment': 0.8105182526856075}
+0.8105182526856075
->>> test_text = "Facebook blog posts about Android tech make better journalism than most news outlets."
+>>> text_tags("Facebook blog posts about Android tech make better journalism than most news outlets.")
 >>> tag_dict = text_tags(test_text)
 >>> sorted(tag_dict.keys(), key=lambda x: tag_dict[x], reverse=True)[:3]
 [u'startups_and_entrepreneurship', u'investment', u'business']
 >>> text_tags(test_text, threshold=0.1) # return only keys with value > 0.1
 {u'startups_and_entrepreneurship': 0.21888586688354486}
@@ -62,73 +64,26 @@ Examples
 >>> text_tags(test_text, top_n=1) # return only keys with top_n values
 {u'startups_and_entrepreneurship': 0.21888586688354486}
 >>> import numpy as np 
 >>> test_face = np.linspace(0,50,48*48).reshape(48,48).tolist()
 >>> fer(test_face)
 {u'Angry': 0.08843749137458341, u'Sad': 0.39091163159204684, u'Neutral': 0.1947947999669361, u'Surprise': 0.03443785859010413, u'Fear': 0.17574534848440568, u'Happy': 0.11567286999192382}
 >>> facial_features(test_face)
-[0.0, -0.02568680526917187, 0.21645604230056517, -0.1519435786033145, -0.5648621854611555, 3.0607368045577226, 0.11434321880792693, -0.02163810928547493, -0.44224330594186484, 0.3024315632285246, -2.6068048934495276, 2.497798330306638, 3.040558335205844, 0.741045340525325, 0.37198135618478817, -0.33132377802172325, -0.9804190889833034, 0.5046575784709395, -0.5609132323152847, 1.679107064439151, 0.6825037853544341, -1.5977176226648016, 1.8959464303080562, -0.7812860715595836, -2.998394007543733, -0.22637273967347724, -0.9642457010679496, 1.4557274834236749, 2.412244419186633, 2.3151771738421965, 0.7881483386786367, 1.6622850935863422, 0.1304768990234367, 1.9344501393866649, 3.1271558035162914, -0.10250886439220543, 1.4921395116492966, 2.761645355670677, 1.6903473594991179, 1.009209807271491, 0.07273926986120445, -1.4941708135718021, -2.082786362439631, 1.0160924044870847, 2.5326580674673895, -0.8328208491083264, 2.0390177029762935, 3.0342637531932777]
+[0.0, -0.02568680526917187, 0.21645604230056517, ..., 3.0342637531932777]
->>> language_dict = language('Quis custodiet ipsos custodes')
+>>> language('Quis custodiet ipsos custodes')
 >>> sorted(language_dict.keys(), key=lambda x: language_dict[x], reverse=True)[:5]
 [u'Latin', u'Dutch', u'Greek', u'Portuguese', u'Spanish']
 >>> language_dict
 {u'Swedish': 0.00033330636691921914, u'Lithuanian': 0.007328693814717631, u'Vietnamese': 0.0002686116137658802, u'Romanian': 8.133913804076592e-06, ...}
 ```
 Batch API Access
 ----------------
-
+Each `indicoio` function has a corresponding batch function for analyzing many examples with a single request. Simply pass in a list of inputs and receive a list of results in return.
-If you'd like to use our batch api interface, please check out the [pricing page](https://indico.io/pricing) on our website to find the right plan for you.
+```python
 ```
 >>> from indicoio import batch_sentiment
->>> batch_sentiment(['Text to analyze', 'More text'], auth=("example@example.com", "********"))
+
 >>> batch_sentiment(['Best day ever', 'Worst day ever'])
 [0.9899001220871786, 0.005709885173415242]
 ```
 Authentication credentials can also be set as the environment variables `$INDICO_USERNAME` and `$INDICO_PASSWORD` or as `username` and `password` in the indicorc file.
 Private cloud API Access
 ------------------------
 If you're looking to use indico's API for high throughput applications, please check out the [pricing page](https://indico.io/pricing) on our website to find the right plan for you.
 ```
 >>> from indicoio import sentiment
 >>> sentiment("Text to analyze", cloud="example", auth=("example@example.com", "********"))
 ```
 The `cloud` parameter redirects API calls to your private cloud hosted at `[cloud].indico.domains` 
 Private cloud subdomains can also be set as the environment variable `$INDICO_CLOUD` or as `cloud` in the indicorc file.
 Configuration
 ------------------------
 Indicoio-python will search ./.indicorc and $HOME/.indicorc for the optional configuration file. Values in the local configuration file (./.indicorc) take precedence over those found in a global configuration file ($HOME/.indicorc). The indicorc file can be used to set an authentication username and password or a private cloud subdomain, so these arguments don't need to be specified for every api call. All sections are optional.
 Here is an example of a valid indicorc file:
 ```
 [auth]
 username = test@example.com
 password = secret
 [private_cloud]
 cloud = example
 ```
 Environment variables take precedence over any configuration found in the indicorc file.
 The following environment variables are valid:
 ```
 $INDICO_USERNAME
 $INDICO_PASSWORD
 $INDICO_CLOUD
 ```
 Finally, any values explicitly passed in to an api call will override configuration options set in the indicorc file or in an environment variable.
@@ -1,31 +1,40 @@
 indicoio-python
 ===============
-A wrapper for a series of APIs made by indico.
+A wrapper for the `indico API <http://indico.io>`__.
-Check out the main site on:
+The indico API is free to use, and no training data is required.
 http://indico.io
 Our APIs are totally free to use, and ready to be used in your
 application. No data or training required.
 Installation
 ------------
-::
+From PyPI:
 .. code:: bash
    pip install indicoio
-Documentation
+From source:
 -------------
-Available at `indico.reame.io <http://indico.readme.io/v1.0/docs>`__
+.. code:: bash
-Current APIs
+    git clone https://github.com/IndicoDataSolutions/IndicoIo-python.git 
------------
+    python setup.py install
-Right now this wrapper supports the following apps:
+API Keys + Setup
 ----------------
 For API key registration and setup, checkout our `quickstart
 guide <https://dash.readme.io/project/indico/v2.0/docs/api-keys>`__.
 Full Documentation
 ------------------
 Detailed documentation and further code examples are available at
 `indico.reame.io <http://indico.readme.io/v2.0/docs/python>`__.
 Supported APIs:
 ---------------
 -  Positive/Negative Sentiment Analysis
 -  Political Sentiment Analysis
@@ -38,27 +47,22 @@ Right now this wrapper supports the following apps:
 Examples
 --------
-::
+.. code:: python
-    >>> import numpy as np
+    >>> from indicoio import political, sentiment, language, text_tags, fer, facial_features, image_features
-    >>> from indicoio import political, sentiment, fer, facial_features, language
+    >>> indicoio.config.api_key = "YOUR_API_KEY"
    >>> political("Guns don't kill people. People kill people.")
    {u'Libertarian': 0.47740164630834825, u'Green': 0.08454409540443657, u'Liberal': 0.16617097211030055, u'Conservative': 0.2718832861769146}
    >>> sentiment('Worst movie ever.')
-    {u'Sentiment': 0.07062467665597527}
+    0.07062467665597527
    >>> sentiment('Really enjoyed the movie.')
-    {u'Sentiment': 0.8105182526856075}
+    0.8105182526856075
-    >>> test_text = "Facebook blog posts about Android tech make better journalism than most news outlets."
+    >>> text_tags("Facebook blog posts about Android tech make better journalism than most news outlets.")
    >>> tag_dict = text_tags(test_text)
    >>> sorted(tag_dict.keys(), key=lambda x: tag_dict[x], reverse=True)[:3]
    [u'startups_and_entrepreneurship', u'investment', u'business']
    >>> text_tags(test_text, threshold=0.1) # return only keys with value > 0.1
    {u'startups_and_entrepreneurship': 0.21888586688354486}
@@ -66,87 +70,30 @@ Examples
    >>> text_tags(test_text, top_n=1) # return only keys with top_n values
    {u'startups_and_entrepreneurship': 0.21888586688354486}
    >>> import numpy as np 
    >>> test_face = np.linspace(0,50,48*48).reshape(48,48).tolist()
    >>> fer(test_face)
    {u'Angry': 0.08843749137458341, u'Sad': 0.39091163159204684, u'Neutral': 0.1947947999669361, u'Surprise': 0.03443785859010413, u'Fear': 0.17574534848440568, u'Happy': 0.11567286999192382}
    >>> facial_features(test_face)
-    [0.0, -0.02568680526917187, 0.21645604230056517, -0.1519435786033145, -0.5648621854611555, 3.0607368045577226, 0.11434321880792693, -0.02163810928547493, -0.44224330594186484, 0.3024315632285246, -2.6068048934495276, 2.497798330306638, 3.040558335205844, 0.741045340525325, 0.37198135618478817, -0.33132377802172325, -0.9804190889833034, 0.5046575784709395, -0.5609132323152847, 1.679107064439151, 0.6825037853544341, -1.5977176226648016, 1.8959464303080562, -0.7812860715595836, -2.998394007543733, -0.22637273967347724, -0.9642457010679496, 1.4557274834236749, 2.412244419186633, 2.3151771738421965, 0.7881483386786367, 1.6622850935863422, 0.1304768990234367, 1.9344501393866649, 3.1271558035162914, -0.10250886439220543, 1.4921395116492966, 2.761645355670677, 1.6903473594991179, 1.009209807271491, 0.07273926986120445, -1.4941708135718021, -2.082786362439631, 1.0160924044870847, 2.5326580674673895, -0.8328208491083264, 2.0390177029762935, 3.0342637531932777]
+    [0.0, -0.02568680526917187, 0.21645604230056517, ..., 3.0342637531932777]
-    >>> language_dict = language('Quis custodiet ipsos custodes')
+    >>> language('Quis custodiet ipsos custodes')
    >>> sorted(language_dict.keys(), key=lambda x: language_dict[x], reverse=True)[:5]
    [u'Latin', u'Dutch', u'Greek', u'Portuguese', u'Spanish']
    >>> language_dict
    {u'Swedish': 0.00033330636691921914, u'Lithuanian': 0.007328693814717631, u'Vietnamese': 0.0002686116137658802, u'Romanian': 8.133913804076592e-06, ...}
 Batch API Access
 ----------------
-If you'd like to use our batch api interface, please check out the
+Each ``indicoio`` function has a corresponding batch function for
-`pricing
+analyzing many examples with a single request. Simply pass in a list of
-page <https://github.com/IndicoDataSolutions/IndicoIo-python>`__ on our
+inputs and receive a list of results in return.
 website to find the right plan for you.
-::
+.. code:: python
-    >>> from indicio import batch_sentiment
+    >>> from indicoio import batch_sentiment
    >>> batch_sentiment(['Text to analyze', 'More text'], auth=("example@example.com", "********"))
-Authentication credentials can also be set as the environment variables
+    >>> batch_sentiment(['Best day ever', 'Worst day ever'])
-``$INDICO_USERNAME`` and ``$INDICO_PASSWORD`` or as ``username`` and
+    [0.9899001220871786, 0.005709885173415242]
 ``password`` in the indicorc file.
 Private cloud API Access
 ------------------------
 If you're looking to use indico's API for high throughput applications,
 please check out the `pricing
 page <https://github.com/IndicoDataSolutions/IndicoIo-python>`__ on our
 website to find the right plan for you.
 ::
    >>> from indicio import sentiment
    >>> sentiment("Text to analyze", cloud="example", auth=("example@example.com", "********"))
 The ``cloud`` parameter redirects API calls to your private cloud hosted
 at ``[cloud].indico.domains``
 Private cloud subdomains can also be set as the environment variable
 ``$INDICO_CLOUD`` or as ``cloud`` in the indicorc file.
 Configuration
 -------------
 Indicoio-python will search ./.indicorc and
 HOME/.indicorc for the optional configuration file. Values in the local configuration file (./.indicorc) take precedence over those found in a global configuration file (`\ HOME/.indicorc).
 The indicorc file can be used to set an authentication username and
 password or a private cloud subdomain, so these arguments don't need to
 be specified for every api call. All sections are optional.
 Here is an example of a valid indicorc file:
 ::
    [auth]
    username = test@example.com
    password = secret
    [private_cloud]
    cloud = example
 Environment variables take precedence over any configuration found in
 the indicorc file. The following environment variables are valid:
 ::
    $INDICO_USERNAME
    $INDICO_PASSWORD
    $INDICO_CLOUD
 Finally, any values explicitly passed in to an api call will override
 configuration options set in the indicorc file or in an environment
 variable.
@@ -2,7 +2,7 @@ from functools import partial
 JSON_HEADERS = {'Content-type': 'application/json', 'Accept': 'text/plain'}
-Version, version, __version__, VERSION = ('0.5.1',) * 4
+Version, version, __version__, VERSION = ('0.5.2',) * 4
 from indicoio.text.sentiment import political, posneg
 from indicoio.text.sentiment import posneg as sentiment
@@ -38,17 +38,19 @@ class Settings(ConfigParser.ConfigParser):
            None
        )
-    def auth(self):
+    def api_key(self):
        return (
-            os.getenv("INDICO_USERNAME") or self.auth_settings.get('username'),
+            os.getenv("INDICO_API_KEY") or
-            os.getenv("INDICO_PASSWORD") or self.auth_settings.get('password')
+            self.auth_settings.get('api_key') or
            None
        )
 SETTINGS = Settings(files=[
    os.path.expanduser("~/.indicorc"),
    os.path.join(os.getcwd(), '.indicorc')
 ])
-
+api_key = SETTINGS.api_key()
-AUTH = SETTINGS.auth()
+cloud = SETTINGS.cloud()
-CLOUD = SETTINGS.cloud()
+PUBLIC_API_HOST = 'apiv2.indico.io'
-PUBLIC_API_HOST = 'apiv1.indico.io'
+url_protocol = "https:"
@@ -4,7 +4,7 @@ import numpy as np
 from indicoio.utils import image_preprocess, api_handler, is_url
 import indicoio.config as config
-def facial_features(image, cloud=config.CLOUD, batch=False, auth=None, **kwargs):
+def facial_features(image, cloud=None, batch=False, api_key=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.
@@ -26,9 +26,9 @@ def facial_features(image, cloud=config.CLOUD, batch=False, auth=None, **kwargs)
    :type image: list of lists
    :rtype: List containing feature responses
    """
-    return api_handler(image, cloud=cloud, api="facialfeatures", batch=batch, auth=auth, **kwargs)
+    return api_handler(image, cloud=cloud, api="facialfeatures", batch=batch, api_key=api_key, **kwargs)
-def image_features(image, cloud=config.CLOUD, batch=False, auth=None, **kwargs):
+def image_features(image, cloud=None, batch=False, api_key=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.
@@ -58,6 +58,5 @@ def image_features(image, cloud=config.CLOUD, batch=False, auth=None, **kwargs):
    :type image: numpy.ndarray
    :rtype: List containing features
    """
-    if not is_url(image, batch=batch):
+    image = image_preprocess(image, batch=batch)
-        image = image_preprocess(image, batch=batch)
+    return api_handler(image, cloud=cloud, api="imagefeatures", batch=batch, api_key=api_key, **kwargs)
    return api_handler(image, cloud=cloud, api="imagefeatures", batch=batch, auth=auth, **kwargs)
@@ -4,7 +4,7 @@ import numpy as np
 from indicoio.utils import api_handler
 import indicoio.config as config
-def fer(image, cloud=config.CLOUD, batch=False, auth=None, **kwargs):
+def fer(image, cloud=None, batch=False, api_key=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
@@ -28,4 +28,4 @@ def fer(image, cloud=config.CLOUD, batch=False, auth=None, **kwargs):
    :rtype: Dictionary containing emotion probability pairs
    """
-    return api_handler(image, cloud=cloud, api="fer", batch=batch, auth=auth, **kwargs)
+    return api_handler(image, cloud=cloud, api="fer", batch=batch, api_key=api_key, **kwargs)
@@ -1,7 +1,7 @@
 from indicoio.utils import api_handler
 import indicoio.config as config
-def language(text, cloud=config.CLOUD, batch=False, auth=None, **kwargs):
+def language(text, cloud=None, batch=False, api_key=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, cloud=config.CLOUD, batch=False, auth=None, **kwargs):
    :rtype: Dictionary of language probability pairs
    """
-    return api_handler(text, cloud=cloud, api="language", batch=batch, auth=auth, **kwargs)
+    return api_handler(text, cloud=cloud, api="language", batch=batch, api_key=api_key, **kwargs)
@@ -2,7 +2,7 @@ from indicoio import JSON_HEADERS
 from indicoio.utils import api_handler
 import indicoio.config as config
-def political(text, cloud=config.CLOUD, batch=False, auth=None, **kwargs):
+def political(text, cloud=None, batch=False, api_key=None, **kwargs):
    """
    Given input text, returns a probability distribution over the political alignment of the speaker.
@@ -28,9 +28,9 @@ def political(text, cloud=config.CLOUD, batch=False, auth=None, **kwargs):
    :rtype: Dictionary of party probability pairs
    """
-    return api_handler(text, cloud=cloud, api="political", batch=batch, auth=auth, **kwargs)
+    return api_handler(text, cloud=cloud, api="political", batch=batch, api_key=api_key, **kwargs)
-def posneg(text, cloud=config.CLOUD, batch=False, auth=None, **kwargs):
+def posneg(text, cloud=None, batch=False, api_key=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, cloud=config.CLOUD, batch=False, auth=None, **kwargs):
    :rtype: Float
    """
-    return api_handler(text, cloud=cloud, api="sentiment", batch=batch, auth=auth, **kwargs)
+    return api_handler(text, cloud=cloud, api="sentiment", batch=batch, api_key=api_key, **kwargs)
@@ -1,7 +1,7 @@
 from indicoio.utils import api_handler
 import indicoio.config as config
-def text_tags(text, cloud=config.CLOUD, batch=False, auth=None, **kwargs):
+def text_tags(text, cloud=None, batch=False, api_key=None, **kwargs):
    """
    Given input text, returns a probability distribution over 100 document categories
@@ -23,4 +23,4 @@ def text_tags(text, cloud=config.CLOUD, batch=False, auth=None, **kwargs):
    :rtype: Dictionary of class probability pairs
    """
-    return api_handler(text, cloud=cloud, api="texttags", batch=batch, auth=auth, **kwargs)
+    return api_handler(text, cloud=cloud, api="texttags", batch=batch, api_key=api_key, **kwargs)
@@ -6,11 +6,12 @@ from skimage.transform import resize
 from indicoio import JSON_HEADERS
 from indicoio import config
-
+def api_handler(arg, cloud, api, batch=False, api_key=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 not cloud:
        cloud=config.cloud
    if cloud:
        host = "%s.indico.domains" % cloud
@@ -18,14 +19,15 @@ def api_handler(arg, cloud, api, batch=False, auth=None, **kwargs):
        # default to indico public cloud
        host = config.PUBLIC_API_HOST
-    url = "http://%s/%s" % (host, api)
+    if not api_key:
-    if batch:
+        api_key = config.api_key
        url += "/batch"
-    if not auth:
+    url = config.url_protocol + "//%s/%s" % (host, api)
-        auth = config.AUTH
+    url = url + "/batch" if batch else url
    url += "?key=%s" % api_key
-    response = requests.post(url, data=json_data, headers=JSON_HEADERS, auth=auth)
+
    response = requests.post(url, data=json_data, headers=JSON_HEADERS)
    if response.status_code == 503 and cloud != None:
        raise Exception("Private cloud '%s' does not include api '%s'" % (cloud, api))
@@ -8,7 +8,7 @@ except ImportError:
 setup(
    name="IndicoIo",
-    version='0.5.1',
+    version='0.5.2',
    packages=[
        "indicoio",
        "indicoio.text",
@@ -27,11 +27,9 @@ class TestConfigureEnv(unittest.TestCase):
        """
        Ensure cloud authentication credentials are read in from environment variables
        """
-        username = "test"
+        api_key = "text"
-        password = "password"
+        os.environ["INDICO_API_KEY"] = api_key
-        os.environ["INDICO_USERNAME"] = username
+        assert config.SETTINGS.api_key() == api_key
        os.environ["INDICO_PASSWORD"] = password
        assert config.SETTINGS.auth() == (username, password)
 class TestConfigurationFile(unittest.TestCase):
@@ -40,17 +38,15 @@ class TestConfigurationFile(unittest.TestCase):
    """
    def setUp(self):
-        self.username = "test"
+        self.api_key = "test"
        self.password = "password"
        self.cloud = "localhost"
        config = """
        [auth]
-        username = %s
+        api_key = %s
        password = %s
        [private_cloud]
        cloud = %s
-        """ % (self.username, self.password, self.cloud)
+        """ % (self.api_key, self.cloud)
        config_file = StringIO(textwrap.dedent(config))
        self.settings = Settings(files=[config_file])
@@ -66,7 +62,7 @@ class TestConfigurationFile(unittest.TestCase):
        """
        Ensure cloud authentication credentials are read in from file
        """
-        assert self.settings.auth() == (self.username, self.password)        
+        assert self.settings.api_key() == self.api_key        
 class TestPrecedence(unittest.TestCase):
@@ -75,27 +71,23 @@ class TestPrecedence(unittest.TestCase):
    """
    def setUp(self):
-        self.file_username = "file-username"
+        self.file_api_key = "file-api-key"
        self.file_password = "file-password"
        self.file_cloud = "file-cloud"
-        self.env_username = "env-username"
+        self.env_api_key = "env-api-key"  
        self.env_password = "env-password"      
        self.env_cloud = "env-cloud"
        config = """
        [auth]
-        username = %s
+        api_key = %s
        password = %s
        [private_cloud]
        cloud = %s
-        """ % (self.file_username, self.file_password, self.file_cloud)
+        """ % (self.file_api_key, self.file_cloud)
        config_file = StringIO(textwrap.dedent(config))
        os.environ = {
            'INDICO_CLOUD': self.env_cloud,
-            'INDICO_USERNAME': self.env_username,
+            'INDICO_API_KEY': self.env_api_key
            'INDICO_PASSWORD': self.env_password
        }
        self.settings = Settings(files=[config_file])
@@ -110,7 +102,7 @@ class TestPrecedence(unittest.TestCase):
        Ensure cloud authentication credentials set in environment variables 
        are used over those in config files
        """
-        assert self.settings.auth() == (self.env_username, self.env_password)        
+        assert self.settings.api_key() == self.env_api_key       
 class TestConfigFilePrecedence(unittest.TestCase):
@@ -119,37 +111,31 @@ class TestConfigFilePrecedence(unittest.TestCase):
    """
    def setUp(self):
-        self.high_priority_username = "high-priority-username"
+        self.high_priority_api_key = "high-priority-api-key"
        self.high_priority_password = "high-priority-password"
        self.high_priority_cloud = "high-priority-cloud"
-        self.low_priority_username = "low-priority-username"
+        self.low_priority_api_key = "low-priority-api-key"
        self.low_priority_password = "low-priority-password"
        self.low_priority_cloud = "low-priority-cloud"
        high_priority_config = """
        [auth]
-        username = %s
+        api_key = %s
        password = %s
        [private_cloud]
        cloud = %s
        """ % (
-            self.high_priority_username, 
+            self.high_priority_api_key,
            self.high_priority_password, 
            self.high_priority_cloud
        )
        low_priority_config = """
        [auth]
        username = %s
        password = %s
        [private_cloud]
        cloud = %s
        """ % (
-            self.low_priority_username, 
+            self.low_priority_api_key,
            self.low_priority_password, 
            self.low_priority_cloud
        )
@@ -172,4 +158,4 @@ class TestConfigFilePrecedence(unittest.TestCase):
        """
        Ensure the cloud auth priority is handled properly
        """
-        assert self.settings.auth() == (self.high_priority_username, self.high_priority_password)        
+        assert self.settings.api_key() == self.high_priority_api_key
@@ -16,36 +16,40 @@ DIR = os.path.dirname(os.path.realpath(__file__))
 class BatchAPIRun(unittest.TestCase):
    def setUp(self):
-        self.auth = config.AUTH
+        self.api_key = config.api_key
        config.url_protocol = "http:"
-        if not all(self.auth):
+        if not all(self.api_key):
            raise SkipTest
    def tearDown(self):
        config.url_protocol = "https:"
    def test_batch_texttags(self):
        test_data = ["On Monday, president Barack Obama will be..."]
-        response = batch_text_tags(test_data, auth=self.auth)
+        response = batch_text_tags(test_data, api_key=self.api_key)
        self.assertTrue(isinstance(response, list))
    def test_batch_posneg(self):
        test_data = ['Worst song ever', 'Best song ever']
-        response = batch_sentiment(test_data, auth=self.auth)
+        response = batch_sentiment(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, auth=self.auth)
+        response = batch_political(test_data, api_key=self.api_key)
        self.assertTrue(isinstance(response, list))
    def test_batch_fer(self):
        test_data = [np.random.rand(48, 48).tolist()]
-        response = batch_fer(test_data, auth=self.auth)
+        response = batch_fer(test_data, api_key=self.api_key)
        self.assertTrue(isinstance(response, list))
        self.assertTrue(isinstance(response[0], dict))
    def test_batch_facial_features(self):
        test_data = [np.random.rand(48, 48).tolist()]
-        response = batch_facial_features(test_data, auth=self.auth)
+        response = batch_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)
@@ -65,21 +69,21 @@ class BatchAPIRun(unittest.TestCase):
    def test_batch_image_features_greyscale(self):
        test_data = [np.random.rand(64, 64).tolist()]
-        response = batch_image_features(test_data, auth=self.auth)
+        response = batch_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 = [np.random.rand(64, 64, 3).tolist()]
-        response = batch_image_features(test_data, auth=self.auth)
+        response = batch_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, auth=self.auth)
+        response = batch_language(test_data, api_key=self.api_key)
        self.assertTrue(isinstance(response, list))
        self.assertTrue(response[0]['English'] > 0.25)
@@ -88,7 +92,7 @@ class BatchAPIRun(unittest.TestCase):
        self.assertRaises(ConnectionError,
                          batch_language,
                          test_data,
-                          auth=self.auth,
+                          api_key=self.api_key,
                          cloud='invalid/cloud')
@@ -124,11 +128,11 @@ class FullAPIRun(unittest.TestCase):
        self.assertTrue(isinstance(response, dict))
        self.assertEqual(political_set, set(response.keys()))
-        test_string = "Save the whales"
+        test_string = "pro-choice"
        response = political(test_string)
        self.assertTrue(isinstance(response, dict))
-        assert response['Green'] > 0.5
+        assert response['Liberal'] > 0.25
    def test_posneg(self):
        test_string = "Worst song ever."
@@ -252,6 +256,39 @@ class FullAPIRun(unittest.TestCase):
                          test_data,
                          cloud='invalid/cloud')
        temp_cloud = config.cloud
        config.cloud = 'invalid/cloud'
        self.assertEqual(config.cloud, 'invalid/cloud')
        self.assertRaises(ConnectionError,
                          language,
                          test_data)
        config.cloud = temp_cloud
        self.assertRaises(ConnectionError,
                          language,
                          test_data,
                          cloud='indico-test')
    def test_set_api_key(self):
        test_data = 'clearly an english sentence'
        self.assertRaises(ValueError,
                          language,
                          test_data,
                          api_key ='invalid_api_key')
        temp_api_key = config.api_key
        config.api_key = 'invalid_api_key'
        self.assertEqual(config.api_key, 'invalid_api_key')
        self.assertRaises(ValueError,
                          language,
                          test_data)
        config.api_key = temp_api_key
 if __name__ == "__main__":
    unittest.main()