Merge pull request #16 from IndicoDataSolutions/batch-support

Batch support

.travis.yml

@@ -1,24 +0,0 @@
-language: python
-python:
-  - 2.7
- 
-# Setup anaconda
-before_install:
-  - wget http://repo.continuum.io/miniconda/Miniconda-latest-Linux-x86_64.sh -O miniconda.sh
-  - chmod +x miniconda.sh
-  - ./miniconda.sh -b
-  - export PATH=/home/travis/miniconda/bin:$PATH
-  - conda update --yes conda
-  # The next couple lines fix a crash with multiprocessing on Travis and are not specific to using Miniconda
-  - sudo rm -rf /dev/shm
-  - sudo ln -s /run/shm /dev/shm
-
-# Install packages
-install:
-  - conda install --yes python=$TRAVIS_PYTHON_VERSION atlas numpy scipy matplotlib nose dateutil pandas statsmodels requests requests six scikit-image
-  - python setup.py install
- 
-# Run test
-script:
-  - nosetests -w ./tests/remote
- 

CHANGES.txt

@@ -13,4 +13,5 @@ v0.4.4, Thu Sep 25 -- Added dependencies installation to setup.py
 v0.4.5, Thu Sep 25 -- Added interface to local indico server
 v0.4.6, Fri Oct 27 -- Updated to point to new indico api servers, cleaner REST API
 v0.4.8, Fri Nov 7 -- Updated API interface to include new text tags API
-v0.4.11, Wed Dec 18 -- Updated tests for text tags
+v0.4.11, Wed Dec 18 -- Updated tests for text tags
+v0.4.12, Thu Dec 19 -- Added batch support interface

README.md

@@ -78,6 +78,14 @@ If you have a local indico server running, simply import from `indicoio.local`.
 >>> from indicoio.local import political, sentiment, fer, facial_features, language
 ```
 
+If you'd like to use our batch api interface, please send an email to contact@indico.io.
+
+```
+>>> from indicio import batch_sentiment
+batch_sentiment(['Text to analyze', 'More text'], auth=("example@example.com", "********"))
+```
+
+
 Installation
 ------------
 ```

indicoio/__init__.py

@@ -3,7 +3,7 @@ import indicoio.config as config
 
 JSON_HEADERS = {'Content-type': 'application/json', 'Accept': 'text/plain'}
 
-Version, version, __version__, VERSION = ('0.4.11',) * 4
+Version, version, __version__, VERSION = ('0.4.12',) * 4
 
 from indicoio.text.sentiment import political, posneg
 from indicoio.text.sentiment import posneg as sentiment
@@ -13,12 +13,14 @@ from indicoio.images.fer import fer
 from indicoio.images.features import facial_features
 from indicoio.images.features import image_features
 
-political = partial(political, config.api_root)
-posneg = partial(posneg, config.api_root)
-sentiment = partial(sentiment, config.api_root)
-posneg = partial(sentiment, config.api_root)
-language = partial(language, config.api_root)
-fer = partial(fer, config.api_root)
-facial_features = partial(facial_features, config.api_root)
-image_features = partial(image_features, config.api_root)
-text_tags = partial(text_tags, config.api_root)
+apis = ['political', 'posneg', 'sentiment', 'language', 'fer', 
+        'facial_features', 'image_features', 'text_tags']
+apis = dict((api, globals().get(api)) for api in apis)
+class Namespace(object): pass
+local = Namespace()
+
+for api in apis:
+	globals()[api] = partial(apis[api], config.api_root)
+	globals()['batch_' + api] = partial(apis[api], config.api_root, batch=True)
+	setattr(local, api, partial(apis[api], config.local_api_root))
+	setattr(local, 'batch_' + api, partial(apis[api], config.local_api_root, batch=True))

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):
+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):
     :type image: list of lists
     :rtype: List containing feature responses
     """
-    return api_handler(image, api_root + "facialfeatures")
+    return api_handler(image, api_root + "facialfeatures", batch=batch, auth=auth)
 
-def image_features(api_root, image):
+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):
     :rtype: List containing features
     """
     image = image_preprocess(image)
-    return api_handler(image, api_root + "imagefeatures")
+    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):
+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):
     :rtype: Dictionary containing emotion probability pairs
     """
     
-    return api_handler(image, api_root + "fer")
+    return api_handler(image, api_root + "fer", batch=batch, auth=auth)

indicoio/local/__init__.py

@@ -1,22 +0,0 @@
-from functools import partial
-import indicoio.config as config
-
-JSON_HEADERS = {'Content-type': 'application/json', 'Accept': 'text/plain'}
-
-from indicoio.text.sentiment import political, posneg
-from indicoio.text.sentiment import posneg as sentiment
-from indicoio.text.lang import language
-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
-
-political = partial(political, config.local_api_root)
-posneg = partial(posneg, config.local_api_root)
-sentiment = partial(sentiment, config.local_api_root)
-posneg = partial(sentiment, config.local_api_root)
-language = partial(language, config.local_api_root)
-fer = partial(fer, config.local_api_root)
-facial_features = partial(facial_features, config.local_api_root)
-image_features = partial(image_features, config.local_api_root)
-text_tags = partial(text_tags, config.local_api_root)

indicoio/text/lang.py

@@ -1,6 +1,6 @@
 from indicoio.utils import api_handler
 
-def language(api_root, text):
+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):
     :rtype: Dictionary of language probability pairs
     """
     
-    return api_handler(text, api_root + "language")
+    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):
+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):
     :rtype: Dictionary of party probability pairs
     """
 
-    return api_handler(text, api_root + "political")
+    return api_handler(text, api_root + "political", batch=batch, auth=auth)
 
-def posneg(api_root, text):
+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):
     :rtype: Float
     """
     
-    return api_handler(text, api_root + "sentiment")
+    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):
+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):
     :rtype: Dictionary of class probability pairs
     """
     
-    return api_handler(text, api_root + "texttags")
+    return api_handler(text, api_root + "texttags", batch=batch, auth=None)

indicoio/utils/__init__.py

@@ -1,12 +1,32 @@
-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):
+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})
-    response = requests.post(url, data=data_dict, headers=JSON_HEADERS).json()
+    if batch:
+        url += "/batch"
+        if not auth:
+            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')

setup.py

@@ -8,13 +8,12 @@ except ImportError:
 
 setup(
     name="IndicoIo",
-    version='0.4.11',
+    version='0.4.12',
     packages=[
         "indicoio",
         "indicoio.text",
         "indicoio.images",
         "indicoio.utils",
-        "indicoio.local",
         "tests",
     ],
     description="""

tests/local/test_local.py

@@ -1,4 +1,5 @@
 import unittest
+import os
 
 import numpy as np