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RDS - JS

WARNING: THIS PROJECT IS IN EARLY DEVELOPMENT STAGE. CONTENT OR CODE SHOULD ONLY BE USED FOR TESTING OR EVALUATION PURPOSES.

npm npm bundle size Travis (.com) branch Coveralls github branch GitHub Snyk Vulnerabilities for GitHub Repo semantic-release code style: prettier

Checkout our awesome examples/showcases repo.

Start using the sdk with our stackblitz template


Rich Data Services (or RDS) is a suite of REST APIs designed by Metadata Technology North America (MTNA) to meet various needs for data engineers, managers, custodians, and consumers. RDS provides a range of services including data profiling, mapping, transformation, validation, ingestion, and dissemination. For more information about each of these APIs and how you can incorporate or consume them as part of your work flow please visit the MTNA website.

RDS-JS is TypeScript/JavaScript library to simplify and faciliate interacting with any given RDS API. By using this SDK you will add to your project the benefit of strong types and easy to use helper functions that directly reflect the RDS API.

Make RDS queries easy. Write strongly typed code. Use RDS-JS.

References

RDS SDK Documentation RDS API Documentation Examples Contributing Developer Documentation Changelog

Quick start

Using NPM

Install the sdk into your project.

npm install @rds/sdk

The setup

import { RdsServer, RdsCatalog, RdsDataProduct } from '@rds/sdk';

// Instantiate a new server to define where the RDS API is hosted.
const server = new RdsServer('https://covid19.richdataservices.com/rds');
// Instantiate a catalog that exists on the server
const catalog = new RdsCatalog(server, 'int');
// Instantiate a data product that exists on the catalog
const dataProduct = new RdsDataProduct(catalog, 'jhu_country');

These are the basic, foundational building blocks of the RDS SDK. From here, we can explore what catalogs/data products exist on the server, details about them, subset the data through various queries, and downloading customized data packages.

See the documentation for the full SDK API.


RdsServer

Represents a single RDS API server, provides methods to query server-level information.

Get the root catalog on the server

import { RdsServer } from '@rds/sdk';
const server = new RdsServer('https://covid19.richdataservices.com/rds');
server.getRootCatalog().then(res => console.log(`There are ${res.parsedBody.catalogs.length} catalogs on this server!`));

RdsCatalog

Represents a single catalog on a server, provides methods to query catalog related information.

Resolve properties about the catalog

import { RdsCatalog } from '@rds/sdk';
// Given a previously instantiated server, like in the examples above
const catalog = new RdsCatalog(server, 'int');
catalog
  .resolve()
  .then(()=>
    catalog.name; // Name of catalog
    catalog.description; // Catalog description
    catalog.dataProducts; // All the data products on this catalog
    // See the docs for all the possible properties
  );

RdsDataProduct

Represents a single data product within a catalog, provides methods to query data product related information.

Run a select query to get record level microdata.

import { AmchartsDataSet, HttpResponse, RdsDataProduct, RdsSelectParameters } from '@rds/sdk';

// Given the catalog from the above examples
const dataProduct = new RdsDataProduct(catalog, 'jhu_country');
// Specify some parameters
const params: RdsSelectParameters = {
  cols: 'date_stamp,cnt_confirmed,cnt_death,cnt_recovered',
  where: '(iso3166_1=US)',
  metadata: true,
  limit: 5000,
  format: 'amcharts'
};

dataProduct.select<AmchartsDataSet>(params).then((res: HttpResponse<AmchartsDataSet>) => {
  /* Make a cool visualization */
});

Run a tabulation to get aggregate level data about the dimensions and measures specified.

import { PlotlyDataSet, HttpResponse, RdsDataProduct, RdsTabulateParameters } from '@rds/sdk';

// Given the catalog from the above examples
const dataProduct = new RdsDataProduct(catalog, 'jhu_country');
// Specify some parameters
const params: RdsTabulateParameters = {
  dims: 'date_stamp,iso3166_1',
  measure: 'cnt_confirmed:SUM(cnt_confirmed)',
  where: '(year_stamp=2020) AND (iso3166_1=US OR iso3166_1=CA OR iso3166_1=ES OR iso3166_1=IT OR iso3166_1=CN)',
  orderby: 'date_stamp ASC,iso3166_1 ASC',
  metadata: true,
  inject: true,
  totals: true,
  format: 'plotly_heatmap'
};

dataProduct.tabulate<PlotlyDataSet>(params).then((res: HttpResponse<PlotlyDataSet>) => {
  /* Make a cool visualization */
});

Contribute

Putting this product together and maintaining the repository takes time and resources. We welcome your support in any shape or form, in particular:

  • Fork/clone, and contribute to the package
  • Let us know is you find any discrepancy or have suggestions towards enhancing the content or quality of the library
  • Buy us a beer/coffee! Donations are appreciated and can be made through PayPal
  • Consider using RDS or any of our data/metadata services, products, or expertise