endlessm/eos-knowledge-electron-boilerplate

Name: eos-knowledge-electron-boilerplate

Owner: endlessm

Description: Skeleton application to build knowledge apps using Electron

Created: 2017-03-17 22:14:00.0

Updated: 2017-03-20 10:19:41.0

Pushed: 2017-03-20 10:19:57.0

Homepage: null

Size: 1651

Language: JavaScript

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README

eos-knowledge-electron-boilerplate

This is an application boilerplate which should set you up writing EndlessOS knowledge content application powered by and electron frontend. This boilerplate sets up all the tricky bits of application packaging, content initialization and global search integration so you can focus on writing the UI for you application.

Note: the frontend code here is practically non-existent. For a more complete example of some actual app UI using this boilerplate, check out the react branch.

Dependencies

First you will need node and npm installed. The com.endlessm.ElectronKnowledgeDevApp flatpak app is a good way to get access to these tools.

Then you will need electron-forge installed globally

install -g electron-forge
Building

To install npm dependencies and pre-load content…

install
run download

To develop and test the application the application…

start

Finally, to build the flatpak app…

run make

which will build the flatpak in the out/make directory.

Installing

Once you have built the flatpak, just install with

pak --user install --bundle out/make/com.endlessm.electron.myths.en_master_x86_64.flatpak
pak run com.endlessm.electron.myths.en
Templating

You may want to power multiple knowledge apps with the same frontend code built from this boilerplate. This boilerplate uses the eos-knowledge-downloader tool to seed content for the application.

You can use it to download different app.json manifests and load in different content. Or you can use the

mplate [app json path or uri]

script in the base of this repo to quickly build a lot of flatpaks with the same frontend code.


This work is supported by the National Institutes of Health's National Center for Advancing Translational Sciences, Grant Number U24TR002306. This work is solely the responsibility of the creators and does not necessarily represent the official views of the National Institutes of Health.