DatumBox API for Node.js
DatumBox
This module is designed to make the DatumBox API available in Node.js. Its pretty inspired and ported from PHP Wrapper.
What is the Datumbox API?
The Datumbox is a web service which allows you to use our tools from your website, software or mobile application. The API gives you access to all of the supported functions of our service. In this page you will find all the information that you need in order to use our API, fully implemented code samples and the latest API Documentation.
Our Web Service uses "REST-Like" RPC-style operations over HTTP POST requests with parameters URL encoded into the request and its response is encoded in JSON. It is designed to be easy to use and you can implement it in any model computer language that allows you generating web requests.
How to use the API Client?
All you need to do is download the sample code, edit example.php and place your API Key. To get an API Key sign up to datumbox.com service and visit the API Access panel in your profile.
Getting Started
Initialize the module with your api key.
var datum = require('datumbox').factory("API_KEY_HERE");
This big blast we added in version 1.0.1
is, you can now make asynchronous
parallel service request from DatumBox
on your text. How?
datum.parallel(
"So, do you dare to find different sentiments of me in one request?",
['SentimentAnalysis', 'TwitterSentimentAnalysis', 'GenderDetection'],
function(err, results) {
if ( err )
return console.error(err);
}
);
Services values that are available for batch should be within
'SentimentAnalysis', 'TwitterSentimentAnalysis', 'SubjectivityAnalysis',
'TopicClassification', 'SpamDetection', 'AdultContentDetection',
'ReadabilityAssessment', 'LanguageDetection', 'CommercialDetection',
'EducationalDetection', 'GenderDetection', 'TextExtraction',
Sentiment Analysis
Identifies the Sentiment of the Document
datum.sentimentAnalysis("Can you find my sentiments please?", function(err, data) {
if ( err )
return console.log(err);
console.log(data);
});
Identifies the Sentiment of Twitter Messages
datum.twitterSentimentAnalysis("Can you find my #sentiments #please?", function(err, data) {
if ( err )
return console.log(err);
console.log(data);
});
Subjectivity Analysis
Classifies Document as Subjective or Objective
datum.subjectivityAnalysis("TEXT_TO_FIND_HERE", function(err, data) {
if ( err )
return console.log(err);
console.log(data);
});
Topic Classification
Identifies the Topic of the Document
datum.topicClassification("TEXT_TO_FIND_HERE", function(err, data) {
if ( err )
return console.log(err);
console.log(data);
});
Spam Detection
Classifies the Document as spam or nospam
datum.spamDetection("TEXT_TO_FIND_HERE", function(err, data) {
if ( err )
return console.log(err);
console.log(data);
});
Adult Content Detection
Classifies the Document as adult or noadult
datum.adultContentDetection("TEXT_TO_FIND_HERE", function(err, data) {
if ( err )
return console.log(err);
console.log(data);
});
Readability Assessment
Evaluates the Readability of the Document
datum.readabilityAssessment("TEXT_TO_FIND_HERE", function(err, data) {
if ( err )
return console.log(err);
console.log(data);
});
Language Detection
Identifies the Language of the Document
datum.languageDetection("TEXT_TO_FIND_HERE", function(err, data) {
if ( err )
return console.log(err);
console.log(data);
});
Commercial Detection
Classifies the Document as commercial or nocommercial
datum.commercialDetection("TEXT_TO_FIND_HERE", function(err, data) {
if ( err )
return console.log(err);
console.log(data);
});
Educational Detection
Classifies the Document as educational or noeducational
datum.educationalDetection("TEXT_TO_FIND_HERE", function(err, data) {
if ( err )
return console.log(err);
console.log(data);
});
Gender Detection
Gender Detection Service
datum.genderDetection("TEXT_TO_FIND_HERE", function(err, data) {
if ( err )
return console.log(err);
console.log(data);
});
Extracts the clear text from Webpage
datum.textExtraction("TEXT_TO_FIND_HERE", function(err, data) {
if ( err )
return console.log(err);
console.log(data);
});
Extracts the Keywords of the Document
datum.keywordExtraction("TEXT_TO_FIND_HERE", "n", function(err, data) {
if ( err )
return console.log(err);
console.log(data);
});
Document Similarity
Estimates the similarity between 2 Documents
datum.documentSimilarity("DOCUMENT_CONTENT_1", "DOCUMENT_CONTENT_2",, function(err, data) {
if ( err )
return console.log(err);
console.log(data);
});
Magic Caller
Get the sentiments of DatumService via magic by defining service on the fly.
datum.magic("SentimentAnalysis", "TEXT_TO_FIND_HERE", function(err, data) {
if ( err )
return console.log(err);
console.log(data);
});
Contributors
Right now, the project is only getting developed by: