subudeepak

WebSockets - An Introduction

WebSockets is a modern HTML5 standard which makes communication between client and server a lot more simpler than ever. We are all familiar with the technology of sockets. Sockets have been fundamental to network communication for a long time but usually the communication over the browser has been restricted. The general restrictions

• The server used to have a permanent listener while the client (aka browser) was not designated any fixed listener for a more long term connection. Hence, every communication was restricted to the client demanding and the server responding.
• This meant that unless the client requested for a particular resource, the server was unable to push such a resource to the client.
• This was detrimental since the client is then forced to check with the server at regular intervals. This meant a lot of libraries focused on optimizing asynchronous calls and identifying the response of asynchronous calls. Notably t

dgeb

import Orbit from 'orbit';
import { RecordNotFoundException, RecordAlreadyExistsException } from 'orbit_common/lib/exceptions';
import attr from 'ember_orbit/attr';
import Context from 'ember_orbit/context';
import Store from 'ember_orbit/store';
import Model from 'ember_orbit/model';
import { createStore } from 'test_helper';

var get = Ember.get,
    set = Ember.set;

domderen

#!/bin/sh
 
# installation of Oracle Java JDK.
sudo apt-get -y update
sudo apt-get -y install python-software-properties
sudo add-apt-repository -y ppa:webupd8team/java
sudo apt-get -y update
sudo apt-get -y install oracle-java7-installer

# Installation of commonly used python scipy tools

wagenet

app.registry.add('css', 'broccoli-compass', 'scss', {
  toTree: function(tree, inputPath, outputPath, options) {
    // broccoli-compass doesn't like leading slashes
    if (inputPath[0] === '/') { inputPath = inputPath.slice(1); }

    tree = mergeTrees([
      tree,
      'public'
    ], {
      description: 'TreeMerger (stylesAndVendorAndPublic)'

staltz

The introduction to Reactive Programming you've been missing

(by @andrestaltz)

---

This tutorial as a series of videos

If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.

---

samselikoff

This post is also on my blog, since Gist doesn't support @ notifications.

---

Components are taking center stage in Ember 2.0. Here are some things you can do today to make the transition as smooth as possible:

• Use Ember CLI
• In general, replace views + controllers with components
• Only use controllers at the top-level for receiving data from the route, and use Ember.Controller instead of Ember.ArrayController or Ember.ObjectController
• Fetch data in your route, and set it as normal properties on your top-level controller. Export an Ember.Controller, otherwise a proxy will be generated. You can use Ember.RSVP.hash to simulate setting normal props on your controller.

code0100fun

// app/controllers/sign-in.js
import Ember from 'ember';

export default Ember.Controller.extend({
  actions: {
    signIn(){
      this.set('errors', null);
      var params = { identification: this.get('email'), password: this.get('password') };
      // Redirects to index route on success (configurable in config/environment.js)
      this.get('session').authenticate('simple-auth-authenticator:oauth2-password-grant', params);

beci

sudo add-apt-repository ppa:ubuntu-toolchain-r/test
sudo apt-get update
sudo apt-get install gcc-5 g++-5

sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-5 60 --slave /usr/bin/g++ g++ /usr/bin/g++-5

shagunsodhani

A Few Useful Things to Know about Machine Learning

The paper presents some key lessons and "folk wisdom" that machine learning researchers and practitioners have learnt from experience and which are hard to find in textbooks.

1. Learning = Representation + Evaluation + Optimization

All machine learning algorithms have three components:

• Representation for a learner is the set if classifiers/functions that can be possibly learnt. This set is called hypothesis space. If a function is not in hypothesis space, it can not be learnt.
• Evaluation function tells how good the machine learning model is.
• Optimisation is the method to search for the most optimal learning model.

bjorndown

use std::fmt;

#[derive(Copy,Clone)]
enum CellState { Dead, Alive }

impl fmt::Display for CellState {
    fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
        let printable = match *self {
            CellState::Alive => 'x',
            CellState::Dead => ' ',