Learn vocabulary faster using flashcards
This is an Electron application based on the Electron Quick Start Guide.
A basic Electron application files:
package.json- Points to the app's main file and lists its details and dependencies.main.js- Starts the app and creates a browser window to render HTML. This is the app's main process.
To clone and run this repository you'll need Git and Node.js (which comes with npm) installed on your computer. From your command line:
# Clone this repository
git clone https://github.com/malik-aliyev-94/memo_cards
# Go into the repository
cd memo_cards
# Install dependencies
npm install
# Run the app
npm start
# Run the dist
npm distAfter running npm dist you can run memo_cards.app (on MacOS). This will also run nodejs server (:4200), you can open http://localhost:4200 on browser too.
Browser extensions for Chrome (chrome-ext) and Safari (VocaExt.safariextension) are also available. These extensions needed to easily add new words from translate.google.com
Once you have translated the word, you can click the extension button on toolbar and save the new word to your vocabulary.
You can also run only web app (without electron).
node ./server.js or nodemon ./server.js
To run Node.js server file automatically after launching Electron App,
require('./server'); and mainWindow.loadURL('http://localhost:4200')
lines are added to main.js electron app file.
As a database SQLITE have been used. You can read more about how to use sqlite with nodejs from here
Give attntion to the database connection in server.js file
// Database connection
var db = new sqlite3.Database(path.join(__dirname, 'app.db').replace('/app.asar', ''), (err) => {
if (err) {
return console.error(err.message);
}
console.log('database: Connected');
});path.join(__dirname, 'app.db').replace('/app.asar', '') have been used to solve db-file is not found within app.asar problem (Electron sqlite3 issue after packaging app).
As a front-end framework materialize have been used.
You can scrap content from vocabulary.com after new word have been added.
Read more about Web Scraping with NodeJS --> Parsing HTML with Cheerio.js