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Oracle Drags Its Feet in the JavaScript Trademark Dispute
Oracle seeks to dismiss fraud claims in the JavaScript trademark dispute, delaying the case and avoiding questions about its right to the name.
This module is designed to make the DatumBox API available in Node.js. Its pretty inspired and ported from PHP Wrapper.
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.
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.
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);
// results is [] and have the output in same service format.
}
);
Services values that are available for batch should be within
'SentimentAnalysis', 'TwitterSentimentAnalysis', 'SubjectivityAnalysis',
'TopicClassification', 'SpamDetection', 'AdultContentDetection',
'ReadabilityAssessment', 'LanguageDetection', 'CommercialDetection',
'EducationalDetection', 'GenderDetection', 'TextExtraction',
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); // Remarks here.
});
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); // Remarks here.
});
Classifies Document as Subjective or Objective
datum.subjectivityAnalysis("TEXT_TO_FIND_HERE", function(err, data) {
if ( err )
return console.log(err);
console.log(data); // Remarks here.
});
Identifies the Topic of the Document
datum.topicClassification("TEXT_TO_FIND_HERE", function(err, data) {
if ( err )
return console.log(err);
console.log(data); // Remarks here.
});
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); // Remarks here.
});
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); // Remarks here.
});
Evaluates the Readability of the Document
datum.readabilityAssessment("TEXT_TO_FIND_HERE", function(err, data) {
if ( err )
return console.log(err);
console.log(data); // Remarks here.
});
Identifies the Language of the Document
datum.languageDetection("TEXT_TO_FIND_HERE", function(err, data) {
if ( err )
return console.log(err);
console.log(data); // Remarks here.
});
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); // Remarks here.
});
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); // Remarks here.
});
Gender Detection Service
datum.genderDetection("TEXT_TO_FIND_HERE", function(err, data) {
if ( err )
return console.log(err);
console.log(data); // Remarks here.
});
Extracts the clear text from Webpage
datum.textExtraction("TEXT_TO_FIND_HERE", function(err, data) {
if ( err )
return console.log(err);
console.log(data); // Remarks here.
});
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); // Remarks here.
});
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); // Remarks here.
});
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); // Remarks here.
});
Right now, the project is only getting developed by:
FAQs
DatumBox API Wrapper in Nodejs
The npm package datumbox receives a total of 6 weekly downloads. As such, datumbox popularity was classified as not popular.
We found that datumbox demonstrated a not healthy version release cadence and project activity because the last version was released a year ago. It has 1 open source maintainer collaborating on the project.
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Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
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