@graphistry/node-api: Graphistry's Node.js client API

Automatically upload and visualize datasets using node, powered by Graphistry's GPU graph visualization infrastructure

Install

npm install @graphistry/node-api

Standard native esm imports

import { EdgeFile, NodeFile, Dataset, Client } from '@graphistry/node-api';

Still transitioning to esm?

• You may need "type": "module" in your package.json
• Transpiling should preserve esm import syntax. Ex: "babel": { "presets": [ ["@babel/preset-env", {"modules": false}] ] }

The node-api-test sample project shares an example of a native node project. Please contact the team for additional format support.

Usage

The many options

The API is split between the client wrapper and the JSON configuration payloads:

• @graphistry/node-api API docs: Overall Node.js client llibrary
• Graphistry REST API docs: JSON payload options around configuring file formats and visualization settings

Ex: JavaScript with async/await

import { EdgeFile, NodeFile, Dataset, Client } from '@graphistry/node-api';

//defaults: 'https', 'hub.graphistry.com', 'https://hub.graphistry.com'
const client = new Client('my_username', 'my_password');

//columnar data is fastest; column per attribute; reuse across datasets
const edgesFile = new EdgeFile({'s': ['a1', 'b2'], 'd': ['b2', 'c3']});
const nodesFile = new NodeFile({'n': ['a1', 'b2', 'c3'], 'a1': ['x', 'y', 'z']});

const dataset = new Dataset({
    node_encodings: { bindings: { node: 'n' } },
    edge_encodings: { bindings: { source: 's', destination: 'd' } },
    metadata: {},
    name: 'testdata',
}, edgesFile, nodesFile);

await dataset.upload(client);
console.info(`View at ${dataset.datasetID} at ${dataset.datasetURL}`);

Ex: TypeScript with async/await

Exactly the same!

Ex: Using promises

import { EdgeFile, NodeFile, Dataset, Client } from '@graphistry/node-api';

//defaults: 'https', 'hub.graphistry.com', 'https://hub.graphistry.com'
const client = new Client(user, password);

//columnar data is fastest; column per attribute; reuse across datasets
const edgesFile = new EdgeFile({'s': ['a1', 'b2'], 'd': ['b2', 'c3']});
const nodesFile = new NodeFile({'n': ['a1', 'b2', 'c3'], 'a1': ['x', 'y', 'z']});

(new Dataset({
        node_encodings: { bindings: { node: 'n' } },
        edge_encodings: { bindings: { source: 's', destination: 'd' } },
        metadata: {},
        name: 'testdata',
    }, edgesFile, nodesFile))
.upload(client)
.then(dataset => {
    console.info(`View at ${dataset.datasetID} at ${dataset.datasetURL}`);
})
.catch(err => {
    console.error('Oops', err);
})

Ex: Apache Arrow uploads

We recommend uploading Apache Arrow format data in most scenarios due to the speed and reliability guarantees:

import { tableFromArrays, tableToIPC, Table } from 'apache-arrow';
import { EdgeFile } from '@graphistry/node-api';

//columnar data is fastest; column per attribute; reuse across datasets
const edgesJSON = {'s': ['a1', 'b2'], 'd': ['b2', 'c3']};
const edgesTable: Table = tableFromArrays(edgesJSON);
const edgesUint8: Uint8Array = tableToIPC(edgesArr, 'file');
const edgesFile = new EdgeFile(edgesUint8, 'arrow');

Ex: Using an organization

You can log into an organization instead of a personal account

import { Client } from '@graphistry/node-api';
const c = new Client('my_user', 'my_pass', 'my_org');

Ex: Custom token

If you already have a JWT token, you can pass it in

import { Client } from '@graphistry/node-api';
const c = new Client();
c.setToken('Bearer 123abc');

Ex: Custom server

You can switch which server to use for uploads and for downloads, which is useful for self-hosted servers and advanced enterprise network configurations

import { Client } from '@graphistry/node-api';
const c = new Client(
    'my_user', 'my_pass', 'optional_my_org',
    'https', //upload protcol
    'hub.graphistry.com', //upload server
    'https://hub.graphistry.com' //url to use in browsers
)

Using API Options

• Set parsing options for different File formats and shapes

• Configure Dataset nodes & edges to use data-driven colors, sizes, icons, and badges using simple and complex encodings, including both continuous and categorical mappings

• Theme with custom branding around background & foreground colors, images, logos, titles, and more

const client = new Client(user, password, org, protocol, host);

// Row-oriented data slower to upload but often convenient
const edgesRows = [
    { 's': 'a', 'd': 'b', 'v': 'e1' },
    { 's': 'b', 'd': 'c', 'v': 'e2' },
    { 's': 'c', 'd': 'a', 'v': 'e3' }
];
const nodesRows = [
    { 'n': 'a', 'vv': 10, 't': 'person' },
    { 'n': 'b', 'vv': 20, 't': 'person' },
    { 'n': 'c', 'vv': 30 , 't': 'car' }
];

const edgesFile = new EdgeFile(
    edgesRows, 'json', 'my_edges',
    // Also: file_compression, sql_transforms, ...
    // https://hub.graphistry.com/docs/api/2/rest/files/
    {
        // JSON parsing options:
        // - https://hub.graphistry.com/docs/api/2/rest/upload/data/#uploadjson2
        // - https://pandas.pydata.org/docs/reference/api/pandas.read_json.html
        parser_options: {
            orient: 'records'  // Row-oriented: Array of objects
        }                      // Default: to columnar json - Object of arrays
    }
);

// Node files are optional, mainly for properties
const nodesFile = new NodeFile(nodesRows);

const dataset = new Dataset(
    {

        // Also: color, size, title, icon, badge, axis
        // - https://hub.graphistry.com/docs/api/2/rest/upload/colors
        // - https://hub.graphistry.com/docs/api/2/rest/upload/complex/
        node_encodings: {
            bindings: {
                node: 'n', // id (required)
                node_title: 'vv'
            },
            complex: {
                default: {
                    pointColorEncoding: {
                        graphType: "point",
                        encodingType: "color",
                        attribute: "vv",
                        variation: "continuous",
                        colors: ["blue", "yellow", "red"]
                    },
                    pointIconEncoding: {
                        graphType: "point",
                        encodingType: "icon",
                        attribute: "t",
                        variation: "categorical",
                        mapping: {
                            categorical: {
                                fixed: {
                                    "person": "user",
                                    "car": "car"
                                },
                                other: "question"
                            }
                        }
                    }
                }
            }
        },

        //Also: color, weight, icon, badge, title
        // - https://hub.graphistry.com/docs/api/2/rest/upload/colors
        // - https://hub.graphistry.com/docs/api/2/rest/upload/complex/
        edge_encodings: {
            bindings: {
                source: 's', destination: 'd'
            },
            complex: { }
        },

        // Brand & theme: Background, foreground, logo, page metadata
        // https://hub.graphistry.com/docs/api/2/rest/upload/metadata/
        metadata: {
            bg: {
                color: 'silver'
            },
            logo: {
                "url": "http://a.com/logo.png",
            }
        },
        name: 'testdata',
    },
    edgesFile,
    nodesFile,

    // Visual and layout settings
    // https://hub.graphistry.com/docs/api/1/rest/url/#urloptions
    {
        strongGravity: true,
        edgeCurvature: 0.5
    }
);

await dataset.upload(client);

console.info(`View dataset ${dataset.datasetID} at ${dataset.datasetURL}`);
console.info(`Dataset using node file ${nodesFile.fileID}, edge file ${edgesFile.fileID}`);

Underlying REST API

For further information about authentication, files, and datasets, see the Graphistry REST API docs.

TypeScript

Types are already automatically bundled with this module

For source maps, you may want to add NODE_OPTIONS=--enable-source-maps to your environment or run node as node --enable-source-maps.