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Initial test coverage for new configuration system
This commit is contained in:
Anne Carlson
committed by
Madison May
Madison May
parent
6b9251f4f5
commit
dc47fe5b0a
@@ -1,99 +0,0 @@
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indicoio-python
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===============
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A wrapper for a series of APIs made by indico.
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Check out the main site on:
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http://indico.io
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Check out our documentation on:
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http://indicoiopython.s3-website-us-west-2.amazonaws.com/indicoio.html
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Our APIs are totally free to use, and ready to be used in your application. No data or training required.
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Current APIs
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------------
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Right now this wrapper supports the following apps:
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- Positive/Negative Sentiment Analysis
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- Political Sentiment Analysis
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- Image Feature Extraction
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- Facial Emotion Recognition
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- Facial Feature Extraction
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- Language Detection
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- Text Topic Tagging
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Examples
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--------
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```
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>>> import numpy as np
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>>> from indicoio import political, sentiment, fer, facial_features, language
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>>> political("Guns don't kill people. People kill people.")
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{u'Libertarian': 0.47740164630834825, u'Green': 0.08454409540443657, u'Liberal': 0.16617097211030055, u'Conservative': 0.2718832861769146}
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>>> sentiment('Worst movie ever.')
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{u'Sentiment': 0.07062467665597527}
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>>> sentiment('Really enjoyed the movie.')
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{u'Sentiment': 0.8105182526856075}
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>>> test_text = "Facebook blog posts about Android tech make better journalism than most news outlets."
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>>> tag_dict = text_tags(test_text)
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>>> sorted(tag_dict.keys(), key=lambda x: tag_dict[x], reverse=True)[:3]
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[u'startups_and_entrepreneurship', u'investment', u'business']
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>>> text_tags(test_text, threshold=0.1) # return only keys with value > 0.1
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{u'startups_and_entrepreneurship': 0.21888586688354486}
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>>> text_tags(test_text, top_n=1) # return only keys with top_n values
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{u'startups_and_entrepreneurship': 0.21888586688354486}
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>>> tag_dict
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{u'fashion': 0.011450126534350728, u'art': 0.00358698972755963, u'energy': 0.005537894035625527, ...}
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>>> test_face = np.linspace(0,50,48*48).reshape(48,48).tolist()
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>>> fer(test_face)
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{u'Angry': 0.08843749137458341, u'Sad': 0.39091163159204684, u'Neutral': 0.1947947999669361, u'Surprise': 0.03443785859010413, u'Fear': 0.17574534848440568, u'Happy': 0.11567286999192382}
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>>> facial_features(test_face)
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[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]
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>>> language_dict = language('Quis custodiet ipsos custodes')
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>>> sorted(language_dict.keys(), key=lambda x: language_dict[x], reverse=True)[:5]
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[u'Latin', u'Dutch', u'Greek', u'Portuguese', u'Spanish']
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>>> language_dict
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{u'Swedish': 0.00033330636691921914, u'Lithuanian': 0.007328693814717631, u'Vietnamese': 0.0002686116137658802, u'Romanian': 8.133913804076592e-06, ...}
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```
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If you have a local indico server running, simply import from `indicoio.local`.
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```
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>>> from indicoio.local import political, sentiment, fer, facial_features, language
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```
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If you'd like to use our batch api interface, please send an email to contact@indico.io.
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```
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>>> from indicio import batch_sentiment
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batch_sentiment(['Text to analyze', 'More text'], auth=("example@example.com", "********"))
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```
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Installation
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------------
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```
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pip install indicoio
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```
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Announcement: Indico has partnered with Experfy, a data science consulting marketplace based in the Harvard Innovation Lab. Through Experfy, we are helping our data science community members find lucrative projects and advance their skills. Please signup for Experfy at https://www.experfy.com/ to get started.
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@@ -78,13 +78,6 @@ Examples
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>>> language_dict
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{u'Swedish': 0.00033330636691921914, u'Lithuanian': 0.007328693814717631, u'Vietnamese': 0.0002686116137658802, u'Romanian': 8.133913804076592e-06, ...}
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```
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If you have a local indico server running, simply import from `indicoio.local`.
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```
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>>> from indicoio.local import political, sentiment, fer, facial_features, language
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```
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Batch API Access
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----------------
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@@ -95,3 +88,33 @@ If you'd like to use our batch api interface, please send an email to contact@in
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>>> from indicio import batch_sentiment
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batch_sentiment(['Text to analyze', 'More text'], auth=("example@example.com", "********"))
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```
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Authentication credentials can also be set as the environment variables "INDICO_USERNAME" and "INDICO_PASSWORD" or as 'username' and 'password' in indicorc
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Private Cloud API Access
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------------------------
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If you'd like to use our private cloud interface, please send an email to contact@indico.io.
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```
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>>> from indicio import sentiment
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sentiment("Text to analyze", hostname="http://exampleprivatecloud.io/", auth=("example@example.com", "********"))
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```
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Private cloud hostnames can also be set as the environment variable "INDICO_PRIVATE_CLOUD_URL" or as 'hostname' in indicorc
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indicorc
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------------------------
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Indicoio-python will look first for $HOME/.indicorc then ./.indicorc for the optional configuration file. The indicorc can be used to set an authentication username and password as well as the private cloud hostname, so they don't need to be specified for every call. All sectiions are optional.
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Here is an example of a valid indicorc file:
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```
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[auth]
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username = test@example.com
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password = secret
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[private_cloud]
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hostname = example.indico.io
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```
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+123
@@ -0,0 +1,123 @@
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indicoio-python
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===============
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A wrapper for a series of APIs made by indico.
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Check out the main site on:
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http://indico.io
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Our APIs are totally free to use, and ready to be used in your
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application. No data or training required.
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Installation
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------------
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::
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pip install indicoio
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Documentation
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-------------
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Available at `indico.reame.io <http://indico.readme.io/v1.0/docs>`__
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Current APIs
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------------
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Right now this wrapper supports the following apps:
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- Positive/Negative Sentiment Analysis
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- Political Sentiment Analysis
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- Image Feature Extraction
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- Facial Emotion Recognition
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- Facial Feature Extraction
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- Language Detection
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- Text Topic Tagging
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Examples
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--------
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::
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>>> import numpy as np
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>>> from indicoio import political, sentiment, fer, facial_features, language
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>>> political("Guns don't kill people. People kill people.")
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{u'Libertarian': 0.47740164630834825, u'Green': 0.08454409540443657, u'Liberal': 0.16617097211030055, u'Conservative': 0.2718832861769146}
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>>> sentiment('Worst movie ever.')
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{u'Sentiment': 0.07062467665597527}
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>>> sentiment('Really enjoyed the movie.')
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{u'Sentiment': 0.8105182526856075}
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>>> test_text = "Facebook blog posts about Android tech make better journalism than most news outlets."
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>>> tag_dict = text_tags(test_text)
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>>> sorted(tag_dict.keys(), key=lambda x: tag_dict[x], reverse=True)[:3]
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[u'startups_and_entrepreneurship', u'investment', u'business']
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>>> text_tags(test_text, threshold=0.1) # return only keys with value > 0.1
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{u'startups_and_entrepreneurship': 0.21888586688354486}
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>>> text_tags(test_text, top_n=1) # return only keys with top_n values
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{u'startups_and_entrepreneurship': 0.21888586688354486}
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>>> test_face = np.linspace(0,50,48*48).reshape(48,48).tolist()
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>>> fer(test_face)
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{u'Angry': 0.08843749137458341, u'Sad': 0.39091163159204684, u'Neutral': 0.1947947999669361, u'Surprise': 0.03443785859010413, u'Fear': 0.17574534848440568, u'Happy': 0.11567286999192382}
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>>> facial_features(test_face)
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[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]
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>>> language_dict = language('Quis custodiet ipsos custodes')
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>>> sorted(language_dict.keys(), key=lambda x: language_dict[x], reverse=True)[:5]
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[u'Latin', u'Dutch', u'Greek', u'Portuguese', u'Spanish']
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>>> language_dict
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{u'Swedish': 0.00033330636691921914, u'Lithuanian': 0.007328693814717631, u'Vietnamese': 0.0002686116137658802, u'Romanian': 8.133913804076592e-06, ...}
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Batch API Access
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----------------
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If you'd like to use our batch api interface, please send an email to contact@indico.io.
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from indicio import batch\_sentiment batch\_sentiment(['Text
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to analyze', 'More text'], auth=("example@example.com",
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"\*\*\*\*\*\*\*\*"))
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::
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Authentication credentials can also be set as the environment variables "INDICO_USERNAME" and "INDICO_PASSWORD" or as 'username' and 'password' in indicorc
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Private Cloud API Access
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------------------------
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If you'd like to use our private cloud interface, please send an email to contact@indico.io.
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from indicio import sentiment sentiment("Text to analyze",
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hostname="http://exampleprivatecloud.io/",
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auth=("example@example.com", "\*\*\*\*\*\*\*\*"))
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::
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Private cloud hostnames can also be set as the environment variable "INDICO_PRIVATE_CLOUD_URL" or as 'hostname' in indicorc
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indicorc
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------------------------
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Indicoio-python will look first for $HOME/.indicorc then ./.indicorc for the optional configuration file. The indicorc can be used to set an authentication username and password as well as the private cloud hostname, so they don't need to be specified for every call. All sectiions are optional.
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Here is an example of a valid indicorc file:
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[auth] username = test@example.com password = secret
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[private\_cloud] hostname = example.indico.io \`\`\`
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+3
-1
@@ -1,3 +1,5 @@
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import os
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api_root = os.getenv("INDICO_PRIVATE_CLOUD_URL") or "http://apiv1.indico.io/"
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def get_api_root():
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return os.environ.get("INDICO_PRIVATE_CLOUD_URL") or "http://apiv1.indico.io/"
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api_root = get_api_root()
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@@ -120,7 +120,7 @@ def normalize(array, distribution=1, norm_range=(0, 1), **kwargs):
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def image_preprocess(image, batch=False):
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"""
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Takes an image and prepares it for sending to the api including
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Takes an image and prepares it for sending to the api including
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resizing and image data/structure standardizing.
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"""
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if batch:
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@@ -137,4 +137,4 @@ def image_preprocess(image, batch=False):
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image = image[:,:,:3]
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image = resize(image,(64,64))
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image = image.tolist()
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return image
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return image
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@@ -1,5 +1,6 @@
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import unittest
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import os
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from requests import ConnectionError
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import numpy as np
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import skimage.io
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@@ -49,7 +50,7 @@ class BatchAPIRun(unittest.TestCase):
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self.assertTrue(isinstance(response, list))
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self.assertTrue(isinstance(response[0], list))
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self.assertEqual(len(response[0]), 48)
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def test_batch_image_features_greyscale(self):
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test_data = [np.random.rand(64, 64).tolist()]
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response = batch_image_features(test_data, auth=self.auth)
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@@ -63,13 +64,21 @@ class BatchAPIRun(unittest.TestCase):
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self.assertTrue(isinstance(response, list))
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self.assertTrue(isinstance(response[0], list))
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self.assertEqual(len(response[0]), 2048)
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def test_batch_language(self):
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test_data = ['clearly an english sentence']
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response = batch_language(test_data, auth=self.auth)
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self.assertTrue(isinstance(response, list))
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self.assertTrue(response[0]['English'] > 0.25)
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def test_batch_set_url_root(self):
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test_data = ['clearly an english sentence']
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self.assertRaises(ConnectionError,
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batch_language,
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test_data,
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auth=self.auth,
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url_root='http://not.a.real.url/')
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class FullAPIRun(unittest.TestCase):
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@@ -156,7 +165,7 @@ class FullAPIRun(unittest.TestCase):
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self.assertTrue(isinstance(response, list))
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self.assertEqual(len(response), 48)
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self.check_range(response)
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def test_good_image_features_greyscale(self):
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test_image = np.random.rand(64, 64).tolist()
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response = image_features(test_image)
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@@ -214,6 +223,13 @@ class FullAPIRun(unittest.TestCase):
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self.assertEqual(language_set, set(language_dict.keys()))
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assert language_dict['English'] > 0.25
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def test_set_url_root(self):
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test_data = 'clearly an english sentence'
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self.assertRaises(ConnectionError,
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language,
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test_data,
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url_root='http://not.a.real.url/')
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if __name__ == "__main__":
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unittest.main()
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@@ -0,0 +1,15 @@
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import os
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from indicoio import config
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def test_batch_set_url_root_as_env_var():
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test_data = ['clearly an english sentence']
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old_private_cloud_url = os.environ.get("INDICO_PRIVATE_CLOUD_URL")
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os.environ["INDICO_PRIVATE_CLOUD_URL"] = "http://not.a.real.url/"
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assert config.get_api_root() == "http://not.a.real.url/"
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if old_private_cloud_url:
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os.environ["INDICO_PRIVATE_CLOUD_URL"] = old_private_cloud_url
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else:
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del(os.environ["INDICO_PRIVATE_CLOUD_URL"])
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