Metadata-Version: 1.1
Name: ParallelDots
Version: 3.0.1
Summary: Python Wrapper for ParallelDots APIs
Home-page: https://github.com/ParallelDots/ParallelDots-Python-API.git
Author: Ahwan Kumar,Meghdeep Ray
Author-email: ahwan@paralleldots.com,meghdeepr@paralleldots.com
License: MIT
Description: 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()
        
        Supported APIs:
        ---------------
        
        - Abuse
        - Custom Classifier
        - Emotion ( Supports all `ISO 639-1 Languages via their language code <https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes>`__ )
        - Intent
        - Keywords
        - Multilanguage Keywords ( Supports Multiple Languages )
        - Named Entity Extraction/Recognition ( NER )
        - Not Safe For Work ( NSFW Image Classifier )
        - Phrase Extractor
        - Popularity ( Image Classifier )
        - Sentiment Analysis ( Supports all `ISO 639-1 Languages via their language code <https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes>`__ )
        - Semantic Similarity
        - Taxonomy
        - Text Parser
        - Usage
        
        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 debate 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" ] }
        
        	>>> paralleldots.set_api_key( api_key )
        	>>> print( "API Key: %s" % paralleldots.get_api_key() )
        
        	>>> print( "\nAbuse" )
        	>>> print( paralleldots.abuse( text ) )
        	{'confidence_score': 0.876953, 'sentence_type': 'Non Abusive', '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( "\nCustom Classifier" )
        	>>> print( paralleldots.custom_classifier( text, category ) )
        	{'taxonomy': [{'confidence_score': 0.737156, 'tag': 'india'}, {'confidence_score': 0.580833, 'tag': 'world politics'}, {'confidence_score': 0.259185, 'tag': 'finance'}], '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( "\nEmotion" )
        	>>> print( paralleldots.emotion( 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', 'emotion': 'happy', 'probabilities': {'indifferent': 0.307, 'sad': 0.071, 'angry': 0.05, 'happy': 0.449, 'excited': 0.123}}
        
        	>>> print( "\nEmotion - Lang: Fr" )
        	>>> print( paralleldots.emotion( lang_text, lang_code ) )
        	{'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', 'emotion': 'sad', 'probabilities': {'indifferent': 0.229, 'sad': 0.364, 'angry': 0.349, 'happy': 0.049, 'excited': 0.009}}
        
        	>>> print( "\nIntent" )
        	>>> print( paralleldots.intent( text ) )
        	{'intent': 'news', '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', 'probabilities': {'query': 0.004, 'marketing': 0.042, 'spam/junk': 0.003, 'feedback/opinion': 0.024, 'news': 0.927}}
        
        	>>> print( "\nKeywords" )
        	>>> print( paralleldots.keywords( text ) )
        	{'keywords': [{'confidence_score': 0.857594, 'keyword': 'Prime Minister Narendra Modi'}, {'confidence_score': 0.913924, 'keyword': 'link'}, {'confidence_score': 0.70655, 'keyword': 'speech Human Resource'}, {'confidence_score': 0.860351, 'keyword': 'Smriti'}, {'confidence_score': 0.945534, 'keyword': 'Lok'}], '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( "\nMultilang Keywords - Lang: Fr" )
        	>>> print( paralleldots.multilang_keywords( lang_text, lang_code ) )
        	{'keywords': ['ici', 'hostile', 'attaqué', 'très', 'choisissez', 'si', 'cest', 'vicieusement', 'lopposition', 'débattre'], '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': [{'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': 'name'}, {'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': 'group'}, {'name': 'Hyderabad', 'confidence_score': 0.591985, 'category': 'place'}]}
        
        	>>> print( "\nNSFW" )
        	>>> print( paralleldots.nsfw( path ) )
        	{'prob': 0.9995405673980713, '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'}
        
        	>>> print( "\nPhrase Extractor" )
        	>>> print( paralleldots.phrase_extractor( text ) )
        	{'keywords': [{'relevance_score': 4, 'keyword': 'Prime Minister Narendra Modi'}, {'relevance_score': 6, 'keyword': 'Human Resource Development Minister Smriti Irani'}, {'relevance_score': 2, 'keyword': 'Lok Sabha'}, {'relevance_score': 1, 'keyword': 'ongoing'}, {'relevance_score': 2, 'keyword': 'JNU row'}, {'relevance_score': 2, 'keyword': 'Dalit scholar'}, {'relevance_score': 2, 'keyword': 'Rohith Vemula'}, {'relevance_score': 3, 'keyword': 'Hyderabad Central University'}], '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( "\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( "\nSentiment" )
        	>>> print( paralleldots.sentiment( 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', 'sentiment': 'neutral', 'probabilities': {'negative': 0.185, 'neutral': 0.549, 'positive': 0.266}}
        
        	>>> print( "\nSentiment - Lang: Fr" )
        	>>> print( paralleldots.sentiment( lang_text, lang_code ) )
        	{'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', 'probabilities': {'negative': 0.689, 'neutral': 0.291, 'positive': 0.02}}
        
        	>>> print( "\nSimilarity" )
        	>>> print( paralleldots.similarity( "I love fish and ice cream!", "fish and ice cream are the best!" ) )
        	{'normalized_score': 4.936506, 'actual_score': 0.848528, '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( "\nTaxonomy" )
        	>>> print( paralleldots.taxonomy( text ) )
        	{'taxonomy': [{'confidence_score': 0.845402, 'tag': 'News and Politics/Law'}, {'confidence_score': 0.878964, 'tag': 'Hobbies & Interests/Workshops and Classes'}, {'confidence_score': 0.7353, 'tag': 'Business and Finance/Industries'}], '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( "\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': [{'Tags': 'noun', 'text': 'Prime', 'Dependency': 'compound'}, {'Tags': 'noun', 'text': 'Minister', 'Dependency': 'compound'}, {'Tags': 'noun', 'text': 'Narendra', 'Dependency': 'compound'}, {'Tags': 'noun', 'text': 'Modi', 'Dependency': 'nominal subject'}, {'Tags': 'verb', 'text': 'tweeted', 'Dependency': 'root'}, {'Tags': 'determiner', 'text': 'a', 'Dependency': 'determiner'}, {'Tags': 'noun', 'text': 'link', 'Dependency': 'direct object'}, {'Tags': 'preposition or conjunction', 'text': 'to', 'Dependency': 'prepositional modifier'}, {'Tags': 'determiner', 'text': 'the', 'Dependency': 'determiner'}, {'Tags': 'noun', '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': 'preposition or conjunction', 'text': 'in', 'Dependency': 'prepositional modifier'}, {'Tags': 'determiner', 'text': 'the', 'Dependency': 'determiner'}, {'Tags': 'noun', 'text': 'Lok', 'Dependency': 'compound'}, {'Tags': 'noun', 'text': 'Sabha', 'Dependency': 'object of a preposition'}, {'Tags': 'preposition or conjunction', 'text': 'during', 'Dependency': 'prepositional modifier'}, {'Tags': 'determiner', 'text': 'the', 'Dependency': 'determiner'}, {'Tags': 'noun', 'text': 'debate', 'Dependency': 'object of a preposition'}, {'Tags': 'preposition or conjunction', 'text': 'on', 'Dependency': 'prepositional modifier'}, {'Tags': 'determiner', 'text': 'the', 'Dependency': 'determiner'}, {'Tags': 'adjective', 'text': 'ongoing', 'Dependency': 'adjectival modifier'}, {'Tags': 'noun', 'text': 'JNU', 'Dependency': 'compound'}, {'Tags': 'noun', 'text': 'row', 'Dependency': 'object of a preposition'}, {'Tags': 'conjuction', 'text': 'and', 'Dependency': 'coordinating conjunction'}, {'Tags': 'determiner', 'text': 'the', 'Dependency': 'determiner'}, {'Tags': 'noun', 'text': 'suicide', 'Dependency': 'conjunct'}, {'Tags': 'preposition or conjunction', 'text': 'of', 'Dependency': 'prepositional modifier'}, {'Tags': 'noun', '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': 'preposition or conjunction', 'text': 'at', 'Dependency': 'prepositional modifier'}, {'Tags': 'determiner', 'text': 'the', 'Dependency': 'determiner'}, {'Tags': 'noun', 'text': 'Hyderabad', 'Dependency': 'compound'}, {'Tags': 'noun', 'text': 'Central', 'Dependency': 'compound'}, {'Tags': 'noun', 'text': 'University', 'Dependency': 'object of a preposition'}]}
        
        	>>> usage()
        	{'visual_monthly_quota': 954, 'daily_quota': 1000, 'paying': True, 'visual_daily_quota': 100, 'monthly_quota': 0.0}
        
Keywords: paralleldots sentiment taxonomy ner semantic similarity deeplearning intent emotion abuse nsfw image visual api phrase text parser popularity
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Build Tools
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.0
Classifier: Programming Language :: Python :: 3.1
Classifier: Programming Language :: Python :: 3.2
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
