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@codaco/network-exporters

v2.0.0-alpha.1

Published

Utility for exporting a network canvas network

Downloads

23

Readme

@codaco/network-exporters Build Status

Utility for exporting a Network Canvas interview session in either CSV or GraphML format.

Notes

  • Include typing: [see here]https://www.typescriptlang.org/docs/handbook/declaration-files/templates/module-class-d-ts.html
  • Move filesystem stuff to a separate package. Perhaps a monorepo?
  • removed tempDataPath and userDataPath, and appPath so we can drop Electron dependency. These can be provided by consumer.
  • need to create an abstracted filesystem interface that can be passed to this module, with separate cordova and electron instances.
  • remove archive functionality - defer to the consumer to decide what to do with encoded files. We will now return a list of paths
  • Need to document events and options

Usage

Designed to be used in a nodejs environment (not browser!). The intended scenario for Network Canvas use is:

  • ** Interviewer ** - Consumed by backend (node) Electron context, with functionality exposed via IPC. Filesystem provided will be a shim over fs or fs-extra.
  • ** Fresco ** - Consumed by API server (node) context, with functionality exposed via HTTP. Filesystem provided will be a shim over fs or fs-extra.

Sample use

Something like this:

const FileExportManager = require('@codaco/network-exporters');
const Filesystem = require('./node-filesystem-shim');

const fileExportManager = new FileExportManager(Filesystem);

// Provides helper method to generate text that can be used in UI.
const infoForUser = fileExportManager.getSupportedFormats();

// Bind event handlers to the emitter
fieExportManager.on('progress', (progress) => {
 console.log(progress);
});

const job = fileExportManager.prepareExportJob(
 sessions, // Collection of NC session objects
 protocols, // Collection of NC protocol objects
 formats, // Array of onr or more of 'csv' or 'graphml'
 options, // Export options object, including things such as temp path, user path, etc.
);

await job.run();