pip install paralleldots

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

>>> 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()

>>> from paralleldots import similarity, ner, taxonomy, sentiment, keywords, intent, emotion, multilang, abuse, sentiment_social, custom_classifier

>>> similarity( "Sachin is the greatest batsman", "Tendulkar is the finest cricketer" )
{"actual_score": 0.842932,"normalized_score": 4.931469}

>>> sentiment( "Come on, lets play together" )
{"probabilities": {"positive": 0.568817, "neutral": 0.400776, "negative": 0.030407}, "sentiment": "positive"}

>>> taxonomy( "Narendra Modi is the prime minister of India" )
{[{"tag": "terrorism", "confidence_score": 0.531435}, {"tag": "world politics", "confidence_score": 0.391963}, {"tag": "politics", "confidence_score": 0.358955}, {"tag": "religion", "confidence_score": 0.308195}, {"tag": "defense", "confidence_score": 0.26187}, {"tag": "business", "confidence_score": 0.20885}, {"tag": "entrepreneurship", "confidence_score": 0.18349}, {"tag": "health", "confidence_score": 0.171121}, {"tag": "technology", "confidence_score": 0.168591}, {"tag": "law", "confidence_score": 0.156953}, {"tag": "education", "confidence_score": 0.146511}, {"tag": "science", "confidence_score": 0.101002}, {"tag": "crime", "confidence_score": 0.085016}, {"tag": "entertainment", "confidence_score": 0.080634}, {"tag": "environment", "confidence_score": 0.078024}, {"tag": "disaster", "confidence_score": 0.075295}, {"tag": "weather", "confidence_score": 0.06784}, {"tag": "accident", "confidence_score": 0.066831}, {"tag": "sports", "confidence_score": 0.058329}, {"tag": "advertising", "confidence_score": 0.054868}, {"tag": "history", "confidence_score": 0.043581}, {"tag": "mining", "confidence_score": 0.03833}, {"tag": "travel", "confidence_score": 0.025517}, {"tag": "geography", "confidence_score": 0.022372}, {"tag": "nature", "confidence_score": 0.013477}, {"tag": "lifestyle", "confidence_score": 0.006467}, {"tag": "automobile", "confidence_score": 0.001161}, {"tag": "personal care", "confidence_score": 0.000275}]}

>>> ner( "Narendra Modi is the prime minister of India" )
{"entities": [
	{
		"category": "name",
		"name": "Narendra Modi",
		"confidence_score": 0.951439
	},
	{
		"category": "place",
		"name": "India",
		"confidence_score": 0.9263
	}
]}

>>> keywords( "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." )
[{"relevance_score": 4, "keyword": "Prime Minister Narendra Modi"}, {"relevance_score": 1, "keyword": "link"}, {"relevance_score": 3, "keyword": "speech Human Resource"}, {"relevance_score": 1, "keyword": "Smriti"}, {"relevance_score": 1, "keyword": "Lok"}]

>>> emotion("Did you hear the latest Porcupine Tree song ? It\'s rocking !")
{"emotion": "other", "probabilities": {"angry": 0.010629, "other": 0.453988, "sad": 0.028748, "excited": 0.2596, "happy": 0.247035}

>>> intent("Finance ministry calls banks to discuss new facility to drain cash")
{"probabilities": {"news": 0.946028, "other": 0.015853, "query": 0.000412, "feedback/opinion": 0.014115, "spam": 0.023591}}

>>> multilang("Me encanta jugar al baloncesto", "es")	# The text is encoded in the function
{"sentiment": "positive", "confidence_score": 1.0}

>>> abuse("you f**king a$$hole")
{"sentence_type": "Abusive", "confidence_score": 0.953125}

>>> sentiment_social("I left my camera at home")
{"probabilities": {"positive": 0.040374, "neutral": 0.491032, "negative": 0.468594}}

>>> custom_classifier( TEXT, ID )
Get your custom classifier id by loggin to your [dashboard](https://user.apis.paralleldots.com/login) and publishing your categories.
{ "taxonomy": [ { "tag": tag1, "confidence_score": score1 }, { "tag": tag2, "confidence_score": score2 }, ... ] }

>>> usage()
{
"emotion": 100,
"sentiment": 100,
"similarity": 100,
"taxonomy": 100,
"abuse": 100,
"intent": 100,
"keywords": 100,
"ner": 100,
"multilang": 100,
"sentiment_social": 100
}