ParallelDots 3.2.6

Python Wrapper for ParallelDots APIs

ParallelDots-Python-API
=======================

A wrapper for the `ParallelDots API <http://www.paralleldots.com>`__.

Installation
------------

From PyPI:

::

pip install paralleldots

From Source:

::

https://github.com/ParallelDots/ParallelDots-Python-API.git
python setup.py install

API Keys & Setup
----------------

Signup and get your free API key from
`ParallelDots <http://www.paralleldots.com/pricing>`__. You will receive
a mail containing the API key at the registered email id.

Configuration:

::

>>> from paralleldots import set_api_key, get_api_key

# Setting your API key
>>> set_api_key( "YOUR API KEY" )

# Viewing your API key
>>> get_api_key()

Languages Supported:
-------------------

- Portuguese ( pt )
- Simplified Chinese ( Not available in multilingual keyword generator API ) ( zh )
- Spanish ( es )
- German ( de )
- French ( fr )
- Dutch ( nl )
- Italian ( it )
- Japanese ( ja )
- Thai ( th )
- Danish ( da )
- Finnish ( fi )
- Greek ( el )
- Russian ( ru )
- Arabic ( ar )

Supported APIs:
---------------

- Abuse
- Custom Classifier
- Emotion
- Facial Emotion
- Intent
- Keywords
- Multilanguage Keywords ( Supports Multiple Languages )
- Named Entity Extraction/Recognition ( NER )
- Not Safe For Work ( NSFW Image Classifier )
- Phrase Extractor
- Popularity ( Image Classifier )
- Object Recognizer
- Sentiment Analysis
- Semantic Similarity
- Taxonomy
- Text Parser
- Usage

Examples
--------

::

Examples
--------

>>> import paralleldots

>>> api_key = "xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
>>> text = "Prime Minister Narendra Modi tweeted a link to the speech Human Resource Development Minister Smriti Irani made in the Lok Sabha during the bate on the ongoing JNU row and the suicide of Dalit scholar Rohith Vemula at the Hyderabad Central University."
>>> path = "/home/my_computer/Downloads/image_1.jpg"
>>> lang_code = "fr"
>>> lang_text = "C'est un environnement très hostile, si vous choisissez de débattre ici, vous serez vicieusement attaqué par l'opposition."
>>> category = { "finance": [ "markets", "economy", "shares" ], "world politics": [ "diplomacy", "UN", "war" ], "india": [ "congress", "india", "bjp" ] }
>>> url = "http://i.imgur.com/klb812s.jpg"
>>> data = [ "drugs are fun", "don\'t do drugs, stay in school", "lol you a fag son", "I have a throat infection" ]


>>> paralleldots.set_api_key( api_key )
>>> print( "API Key: %s" % paralleldots.get_api_key() )

>>> print( "\nAbuse" )
>>> print( paralleldots.abuse( text ) )
{"usage":"By accessing ParallelDots API or using information generated by ParallelDots API, you are agreeing to be bound by the ParallelDots API Terms of Use: http://www.paralleldots.com/terms-and-conditions", "sentence_type":"Non Abusive", "confidence_score":0.876953}

>>> print( "\nBatch Abuse" )
>>> print( paralleldots.batch_abuse( data ) )
{'batch': [{'confidence_score': 0.904297, 'code': 200, 'sentence_type': 'Non Abusive'}, {'confidence_score': 0.953125, 'code': 200, 'sentence_type': 'Non Abusive'}, {'confidence_score': 0.884766, 'code': 200, 'sentence_type': 'Abusive'}, {'confidence_score': 0.859375, 'code': 200, 'sentence_type': 'Non Abusive'}]}

>>> print( "\nCustom Classifier" )
>>> print( paralleldots.custom_classifier( text, category ) )
{"usage":"By accessing ParallelDots API or using information generated by ParallelDots API, you are agreeing to be bound by the ParallelDots API Terms of Use: http://www.paralleldots.com/terms-and-conditions", "taxonomy":[{"tag":"world politics", "confidence_score":0.580833}, {"tag":"finance", "confidence_score":0.259185}]}

>>> print( "\nEmotion" )
>>> print( paralleldots.emotion( text ) )
{"emotion":{"emotion":"Happy", "probabilities":{"Sarcasm":0.0, "Angry":0.04090321436524391, "Sad":0.0, "Fear":0.0, "Bored":0.0, "Excited":0.07638891041278839, "Happy":0.1223890483379364}}, "usage":"By accessing ParallelDots API or using information generated by ParallelDots API, you are agreeing to be bound by the ParallelDots API Terms of Use: http://www.paralleldots.com/terms-and-conditions"}

>>> print( "\nBatch Emotion" )
>>> print( paralleldots.batch_emotion( data ) )
{'batch': [{'emotion': {'probabilities': {'Sarcasm': 0.14361357966835644, 'Angry': 0.08368749025924326, 'Sad': 0.025132654797074747, 'Fear': 0.344180628127824, 'Bored': 0.06818537695928778, 'Excited': 0.2082173830066366, 'Happy': 0.1269828871815771}, 'emotion': 'Fear'}, 'code': 200}, {'emotion': {'probabilities': {'Sarcasm': 0.09578231410218406, 'Angry': 0.28458333402617014, 'Sad': 0.05735552847026735, 'Fear': 0.13348989058422842, 'Bored': 0.21483391837268373, 'Excited': 0.10118401124107868, 'Happy': 0.11277100320338784}, 'emotion': 'Angry'}, 'code': 200}, {'emotion': {'probabilities': {'Sarcasm': 0.11124312097614852, 'Angry': 0.1216389498218648, 'Sad': 0.05410169293913279, 'Fear': 0.18020579627989994, 'Bored': 0.2922536573298578, 'Excited': 0.16457090063285224, 'Happy': 0.07598588202024392}, 'emotion': 'Bored'}, 'code': 200}, {'emotion': {'probabilities': {'Sarcasm': 0.05327575096045899, 'Angry': 0.46982189055546925, 'Sad': 0.3672790882763135, 'Fear': 0.09443579921654321, 'Bored': 0.005730775686542725, 'Excited': 0.004337021311595699, 'Happy': 0.005119673993076841}, 'emotion': 'Angry'}, 'code': 200}]}

>>> print( "\nEmotion - Lang: Fr". )
>>> print( paralleldots.emotion( lang_text, lang_code ) )
{"emotion":{"emotion":"Angry", "probabilities":{"Sarcasm":0.052613839507102966, "Angry":0.07304570078849792, "Sad":0.051657479256391525, "Fear":0.07096020132303238, "Bored":0.0, "Excited":0.0, "Happy":0.0}}, "usage":"By accessing ParallelDots API or using information generated by ParallelDots API, you are agreeing to be bound by the ParallelDots API Terms of Use: http://www.paralleldots.com/terms-and-conditions"}

>>> print( "\nFacial Emotion" )
>>> print( paralleldots.facial_emotion( path ) )
{"usage":"By accessing ParallelDots API or using information generated by ParallelDots API, you are agreeing to be bound by the ParallelDots API Terms of Use: http://www.paralleldots.com/terms-and-conditions", "output":"No face detected."}

>>> print( "\nFacial Emotion: URL Method" )
>>> print( paralleldots.facial_emotion_url( url ) )
{"facial_emotion":[{"score":0.439317524433136, "tag":"Angry"}, {"score":0.18545667827129364, "tag":"Surprise"}, {"score":0.11217296868562698, "tag":"Sad"}, {"score":0.08146321028470993, "tag":"Neutral"}, {"score":0.06052987277507782, "tag":"Happy"}, {"score":0.06052987277507782, "tag":"Fear"}, {"score":0.06052987277507782, "tag":"Disgust"}], "usage":"By accessing ParallelDots API or using information generated by ParallelDots API, you are agreeing to be bound by the ParallelDots API Terms of Use: https://www.paralleldots.com/terms-and-conditions"}

>>> print( "\nIntent" )
>>> print( paralleldots.intent( text ) )
{"probabilities":{"marketing":0.042, "spam/junk":0.003, "news":0.927, "feedback/opinion":0.024, "query":0.004}, "usage":"By accessing ParallelDots API or using information generated by ParallelDots API, you are agreeing to be bound by the ParallelDots API Terms of Use: http://www.paralleldots.com/terms-and-conditions", "intent":"news"}

>>> print( "\nBatch Intent" )
>>> print( paralleldots.batch_intent( data ) )
{'batch': [{'probabilities': {'marketing': 0.116, 'spam/junk': 0.66, 'query': 0.002, 'feedback/opinion': 0.141, 'news': 0.08}, 'code': 200, 'intent': 'spam/junk'}, {'probabilities': {'marketing': 0.106, 'spam/junk': 0.423, 'query': 0.027, 'feedback/opinion': 0.393, 'news': 0.051}, 'code': 200, 'intent': 'spam/junk'}, {'probabilities': {'marketing': 0.001, 'spam/junk': 0.664, 'query': 0.001, 'feedback/opinion': 0.333, 'news': 0.001}, 'code': 200, 'intent': 'spam/junk'}, {'probabilities': {'marketing': 0.0, 'spam/junk': 0.124, 'query': 0.404, 'feedback/opinion': 0.469, 'news': 0.004}, 'code': 200, 'intent': 'feedback/opinion'}]}

>>> print( "\nKeywords" )
>>> print( paralleldots.keywords( text ) )
{"keywords":[{"keyword":"Prime Minister Narendra Modi", "confidence_score":0.857594}, {"keyword":"link", "confidence_score":0.913924}, {"keyword":"speech Human Resource", "confidence_score":0.70655}, {"keyword":"Smriti", "confidence_score":0.860351}, {"keyword":"Lok", "confidence_score":0.945534}], "usage":"By accessing ParallelDots API or using information generated by ParallelDots API, you are agreeing to be bound by the ParallelDots API Terms of Use: http://www.paralleldots.com/terms-and-conditions"}

>>> print( "\nBatch Keywords" )
>>> print( paralleldots.batch_keywords( data ) )
{'batch': [{'keywords': [{'keyword': 'fun', 'confidence_score': 0.560126}], 'code': 200}, {'keywords': [{'keyword': 'drugs', 'confidence_score': 0.89078}, {'keyword': 'school', 'confidence_score': 0.867192}], 'code': 200}, {'keywords': [{'keyword': 'son', 'confidence_score': 0.731249}], 'code': 200}, {'keywords': [{'keyword': 'throat infection', 'confidence_score': 0.87782}], 'code': 200}]}

>>> print( "\nLanguage Detection" )
>>> print( paralleldots.language_detection( lang_text ) )
{"usage":"By accessing ParallelDots API or using information generated by ParallelDots API, you are agreeing to be bound by the ParallelDots API Terms of Use: http://www.paralleldots.com/terms-and-conditions", "output":"French", "code":200, "prob":0.9999592304229736}

>>> print( "\nBatch Language Detection" )
>>> print( paralleldots.batch_language_detection( data ) )
{'batch': [{'output': 'English', 'code': 200, 'prob': 0.960185170173645}, {'output': 'English', 'code': 200, 'prob': 0.9313138127326965}, {'output': 'English', 'code': 200, 'prob': 0.5287713408470154}, {'output': 'English', 'code': 200, 'prob': 0.8692556619644165}]}

>>> print( "\nMultilang Keywords - Lang: Fr". )
>>> print( paralleldots.multilang_keywords( lang_text, lang_code ) )
{"keywords":["cest", "très", "vicieusement", "attaqué", "hostile", "environnement", "débattre", "choisissez", "lopposition", "si"], "usage":"By accessing ParallelDots API or using information generated by ParallelDots API, you are agreeing to be bound by the ParallelDots API Terms of Use: http://www.paralleldots.com/terms-and-conditions"}

>>> print( "\nNER" )
>>> print( paralleldots.ner( text ) )
{"usage":"By accessing ParallelDots API or using information generated by ParallelDots API, you are agreeing to be bound by the ParallelDots API Terms of Use: http://www.paralleldots.com/terms-and-conditions", "entities":[{"category":"name", "name":"Narendra Modi", "confidence_score":0.990574}, {"category":"name", "name":"Smriti Irani", "confidence_score":0.989922}, {"category":"name", "name":"Rohith Vemula", "confidence_score":0.839291}, {"category":"group", "name":"Lok Sabha", "confidence_score":0.80819}, {"category":"group", "name":"Dalit", "confidence_score":0.655424}, {"category":"group", "name":"Central University", "confidence_score":0.708817}, {"category":"place", "name":"Hyderabad", "confidence_score":0.591985}]}

>>> print( "\nBatch NER" )
>>> print( paralleldots.batch_ner( data ) )
{'batch': [{'entities': 'The statement belongs to none of the categories.', 'code': 200}, {'entities': [{'category': 'name', 'name': 'don', 'confidence_score': 0.671695}], 'code': 200}, {'entities': 'The statement belongs to none of the categories.', 'code': 200}, {'entities': 'The statement belongs to none of the categories.', 'code': 200}]}

>>> print( "\nNSFW" )
>>> print( paralleldots.nsfw( path ) )
{"usage":"By accessing ParallelDots API or using information generated by ParallelDots API, you are agreeing to be bound by the ParallelDots API Terms of Use: http://www.paralleldots.com/terms-and-conditions", "output":"not safe to open at work", "prob":0.9995405673980713}

>>> print( "\nNSFW: URL Method" )
>>> print( paralleldots.nsfw_url( url ) )
{"usage":"By accessing ParallelDots API or using information generated by ParallelDots API, you are agreeing to be bound by the ParallelDots API Terms of Use: https://www.paralleldots.com/terms-and-conditions", "output":"safe to open at work", "prob":0.979527473449707}

>>> print( "\nObject Recognizer" )
>>> print( paralleldots.object_recognizer( path ) )
{"usage":"By accessing ParallelDots API or using information generated by ParallelDots API, you are agreeing to be bound by the ParallelDots API Terms of Use: http://www.paralleldots.com/terms-and-conditions", "output":[{"score":0.8445611596107483, "tag":"Muscle"}, {"score":0.6443125605583191, "tag":"Limb"}, {"score":0.5493743419647217, "tag":"Arm"}, {"score":0.5155590772628784, "tag":"Person"}, {"score":0.39905625581741333, "tag":"Human body"}, {"score":0.39764025807380676, "tag":"Leg"}, {"score":0.3255367875099182, "tag":"Hand"}, {"score":0.2798691689968109, "tag":"Male person"}, {"score":0.25423258543014526, "tag":"Adult"}, {"score":0.2470093071460724, "tag":"Man"}]}

>>> print( "\nObject Recognizer: URL Method" )
>>> print( paralleldots.object_recognizer_url( url ) )
{"usage":"By accessing ParallelDots API or using information generated by ParallelDots API, you are agreeing to be bound by the ParallelDots API Terms of Use: https://www.paralleldots.com/terms-and-conditions", "output":[{"score":0.8752718567848206, "tag":"Dog"}, {"score":0.8702095746994019, "tag":"Pet"}, {"score":0.8646901249885559, "tag":"Mammal"}, {"score":0.8270695209503174, "tag":"Animal"}, {"score":0.2900576591491699, "tag":"Snow"}, {"score":0.22053982317447662, "tag":"Winter"}, {"score":0.1604217290878296, "tag":"Dog breed"}, {"score":0.14872552454471588, "tag":"Carnivore"}, {"score":0.08632490038871765, "tag":"Puppy"}, {"score":0.07958601415157318, "tag":"Wildlife"}]}

>>> print( "\nPhrase Extractor" )
>>> print( paralleldots.phrase_extractor( text ) )
{"keywords":[{"relevance_score":3, "keyword":"Hyderabad Central University"}, {"relevance_score":2, "keyword":"Rohith Vemula"}, {"relevance_score":2, "keyword":"JNU row"}, {"relevance_score":6, "keyword":"Human Resource Development Minister Smriti Irani"}, {"relevance_score":2, "keyword":"Lok Sabha"}, {"relevance_score":4, "keyword":"Prime Minister Narendra Modi"}, {"relevance_score":2, "keyword":"Dalit scholar"}], "usage":"By accessing ParallelDots API or using information generated by ParallelDots API, you are agreeing to be bound by the ParallelDots API Terms of Use: http://www.paralleldots.com/terms-and-conditions"}

>>> print( "\nBatch Phrase Extractor" )
>>> print( paralleldots.batch_phrase_extractor( data ) )
{'batch': [{'keywords': [], 'code': 200}, {'keywords': [{'relevance_score': 1, 'keyword': 'school'}], 'code': 200}, {'keywords': [{'relevance_score': 2, 'keyword': 'fag son'}], 'code': 200}, {'keywords': [{'relevance_score': 2, 'keyword': 'throat infection'}], 'code': 200}]}

>>> print( "\nPopularity" )
>>> print( paralleldots.popularity( path ) )
{"Popular":"38.1271243095", "usage":"By accessing ParallelDots API or using information generated by ParallelDots API, you are agreeing to be bound by the ParallelDots API Terms of Use: http://www.paralleldots.com/terms-and-conditions", "Not Popular":"61.8728756905"}

>>> print( "\nPopularity: URL Method" )
>>> print( paralleldots.popularity_url( url ) )
{"Popular":"68.9268052578", "usage":"By accessing ParallelDots API or using information generated by ParallelDots API, you are agreeing to be bound by the ParallelDots API Terms of Use: https://www.paralleldots.com/terms-and-conditions", "Not Popular":"31.0731947422"}

>>> print( "\nSentiment" )
>>> print( paralleldots.sentiment( text ) )
{"probabilities":{"positive":0.266, "neutral":0.549, "negative":0.185}, "usage":"By accessing ParallelDots API or using information generated by ParallelDots API, you are agreeing to be bound by the ParallelDots API Terms of Use: http://www.paralleldots.com/terms-and-conditions", "sentiment":"neutral"}

>>> print( "\nBatch Sentiment" )
>>> print( paralleldots.batch_sentiment( data ) )
{'batch': [{'probabilities': {'positive': 0.69, 'neutral': 0.265, 'negative': 0.046}, 'code': 200, 'sentiment': 'positive'}, {'probabilities': {'positive': 0.061, 'neutral': 0.578, 'negative': 0.361}, 'code': 200, 'sentiment': 'neutral'}, {'probabilities': {'positive': 0.527, 'neutral': 0.198, 'negative': 0.275}, 'code': 200, 'sentiment': 'positive'}, {'probabilities': {'positive': 0.077, 'neutral': 0.015, 'negative': 0.908}, 'code': 200, 'sentiment': 'negative'}]}

>>> print( "\nSentiment - Lang: Fr". )
>>> print( paralleldots.sentiment( lang_text, lang_code ) )
{"probabilities":{"positive":0.02, "neutral":0.291, "negative":0.689}, "usage":"By accessing ParallelDots API or using information generated by ParallelDots API, you are agreeing to be bound by the ParallelDots API Terms of Use: http://www.paralleldots.com/terms-and-conditions", "sentiment":"negative"}

>>> print( "\nSimilarity" )
>>> print( paralleldots.similarity( "I love fish and ice cream!", "fish and ice cream are the best!" ) )
{"usage":"By accessing ParallelDots API or using information generated by ParallelDots API, you are agreeing to be bound by the ParallelDots API Terms of Use: http://www.paralleldots.com/terms-and-conditions", "actual_score":0.848528, "normalized_score":4.936506}

>>> print( "\nTaxonomy" )
>>> print( paralleldots.taxonomy( text ) )
{"usage":"By accessing ParallelDots API or using information generated by ParallelDots API, you are agreeing to be bound by the ParallelDots API Terms of Use: http://www.paralleldots.com/terms-and-conditions", "taxonomy":[{"tag":"News and Politics/Law", "confidence_score":0.845402}, {"tag":"Hobbies & Interests/Workshops and Classes", "confidence_score":0.878964}, {"tag":"Business and Finance/Industries", "confidence_score":0.7353}]}

>>> print( "\nBatch Taxonomy" )
>>> print( paralleldots.batch_taxonomy( data ) )
{'batch': [{'taxonomy': [{'tag': 'health and fitness/drugs', 'confidence_score': 0.996437}, {'tag': 'family and parenting/babies and toddlers', 'confidence_score': 0.967404}, {'tag': 'automotive and vehicles/motor shows', 'confidence_score': 0.6848993897438049}], 'code': 200}, {'taxonomy': [{'tag': 'health and fitness/dental care', 'confidence_score': 0.977439}, {'tag': 'family and parenting/babies and toddlers', 'confidence_score': 0.961832}, {'tag': 'education/school', 'confidence_score': 0.970684}], 'code': 200}, {'taxonomy': [{'tag': 'family and parenting/parenting teens', 'confidence_score': 0.9779467582702637}, {'tag': 'health and fitness/therapy', 'confidence_score': 0.972425}, {'tag': 'pets/cats', 'confidence_score': 0.9049649834632874}], 'code': 200}, {'taxonomy': [{'tag': 'health and fitness/disease', 'confidence_score': 0.985712}, {'tag': 'family and parenting/adoption', 'confidence_score': 0.974752}, {'tag': 'pets/cats', 'confidence_score': 0.97041}], 'code': 200}]}

>>> print( "\nText Parser" )
>>> print( paralleldots.text_parser( text ) )
{"usage":"By accessing ParallelDots API or using information generated by ParallelDots API, you are agreeing to be bound by the ParallelDots API Terms of Use: http://www.paralleldots.com/terms-and-conditions", "output":[{"text":"Prime", "Dependency":"compound", "Tags":"noun"}, {"text":"Minister", "Dependency":"compound", "Tags":"noun"}, {"text":"Narendra", "Dependency":"compound", "Tags":"noun"}, {"text":"Modi", "Dependency":"nominal subject", "Tags":"noun"}, {"text":"tweeted", "Dependency":"root", "Tags":"verb"}, {"text":"a", "Dependency":"determiner", "Tags":"determiner"}, {"text":"link", "Dependency":"direct object", "Tags":"noun"}, {"text":"to", "Dependency":"prepositional modifier", "Tags":"preposition or conjunction"}, {"text":"the", "Dependency":"determiner", "Tags":"determiner"}, {"text":"speech", "Dependency":"compound", "Tags":"noun"}, {"text":"Human", "Dependency":"compound", "Tags":"noun"}, {"text":"Resource", "Dependency":"compound", "Tags":"noun"}, {"text":"Development", "Dependency":"compound", "Tags":"noun"}, {"text":"Minister", "Dependency":"compound", "Tags":"noun"}, {"text":"Smriti", "Dependency":"compound", "Tags":"noun"}, {"text":"Irani", "Dependency":"object of a preposition", "Tags":"noun"}, {"text":"in", "Dependency":"prepositional modifier", "Tags":"preposition or conjunction"}, {"text":"the", "Dependency":"determiner", "Tags":"determiner"}, {"text":"Lok", "Dependency":"compound", "Tags":"noun"}, {"text":"Sabha", "Dependency":"object of a preposition", "Tags":"noun"}, {"text":"during", "Dependency":"prepositional modifier", "Tags":"preposition or conjunction"}, {"text":"the", "Dependency":"determiner", "Tags":"determiner"}, {"text":"debate", "Dependency":"object of a preposition", "Tags":"noun"}, {"text":"on", "Dependency":"prepositional modifier", "Tags":"preposition or conjunction"}, {"text":"the", "Dependency":"determiner", "Tags":"determiner"}, {"text":"ongoing", "Dependency":"adjectival modifier", "Tags":"adjective"}, {"text":"JNU", "Dependency":"compound", "Tags":"noun"}, {"text":"row", "Dependency":"object of a preposition", "Tags":"noun"}, {"text":"and", "Dependency":"coordinating conjunction", "Tags":"conjuction"}, {"text":"the", "Dependency":"determiner", "Tags":"determiner"}, {"text":"suicide", "Dependency":"conjunct", "Tags":"noun"}, {"text":"of", "Dependency":"prepositional modifier", "Tags":"preposition or conjunction"}, {"text":"Dalit", "Dependency":"compound", "Tags":"noun"}, {"text":"scholar", "Dependency":"compound", "Tags":"noun"}, {"text":"Rohith", "Dependency":"compound", "Tags":"noun"}, {"text":"Vemula", "Dependency":"object of a preposition", "Tags":"noun"}, {"text":"at", "Dependency":"prepositional modifier", "Tags":"preposition or conjunction"}, {"text":"the", "Dependency":"determiner", "Tags":"determiner"}, {"text":"Hyderabad", "Dependency":"compound", "Tags":"noun"}, {"text":"Central", "Dependency":"compound", "Tags":"noun"}, {"text":"University", "Dependency":"object of a preposition", "Tags":"noun"}]}

>>> paralleldots.usage()
{ "paying": False, "visual_monthly_quota": 100, "visual_daily_quota": 1000, "monthly_quota": 10000, "daily_quota": 1000, "excel_monthly_quota": 1000, "excel_daily_quota": 100 }