vishnuatrai

God and Puma configuration

Add to Gemfile:

gem 'puma'
gem 'god'

Run in app folder:

bundle install

vishnuatrai

tmux shortcuts & cheatsheet

start new:

tmux

start new with session name:

tmux new -s myname

vishnuatrai

Note: these are pretty rough notes I made for my team on the fly as I was reading through some pages. Some could be mildly inaccurate but hopefully not terribly so. I might resort to convenient fiction & simplification sometimes.

My top contenders, mostly based on popularity / community etc:

• Angular
• Backbone
• React
• Ember

Mostly about MVC (or derivatives, MVP / MVVM).

vishnuatrai

Gerrit vs Github: for code review and codebase management

Sure, Github wins on the UI. Hands down. But, despite my initial annoyance with Gerrit when I first started using it almost a year ago, I am now a convert. Fully. Let me tell you why.

Note: This is an opinionated (on purpose) piece. I assume your preferences are like mine on certain ideas, such as:

• Fast-forward submits to the target branch are better than allowing merge commits to the target branch. The reason I personally prefer this is that, even if a non-conflicting merge to the target branch is possible, the fact that the review/pull request is not up to date with the latest on the target branch means feature branch test suite runs in the CI pipeline reporting on the review/PR may not be accurate. Another minor point is that forced merge commits are annoying as fuck (opinion) and clutter up Git log histories unnecessarily and I prefer clean histories.
• Atomic/related changes all in one commit is something worth striving for. Having your dev

vishnuatrai

var debug = process.env.NODE_ENV !== "production";
var webpack = require('webpack');

module.exports = {
  context: __dirname,
  devtool: debug ? "inline-sourcemap" : null,
  entry: "./js/scripts.js",
  output: {
    path: __dirname + "/js",
    filename: "scripts.min.js"

vishnuatrai

Latency numbers every programmer should know

L1 cache reference ......................... 0.5 ns
Branch mispredict ............................ 5 ns
L2 cache reference ........................... 7 ns
Mutex lock/unlock ........................... 25 ns
Main memory reference ...................... 100 ns             
Compress 1K bytes with Zippy ............. 3,000 ns  =   3 µs
Send 2K bytes over 1 Gbps network ....... 20,000 ns  =  20 µs
SSD random read ........................ 150,000 ns  = 150 µs

Read 1 MB sequentially from memory ..... 250,000 ns = 250 µs

vishnuatrai

rails runner "ApplicationController.allow_forgery_protection = false; s = ActionDispatch::Integration::Session.new(Rails.application); s.post('/login', user: {login: 'admin', password: 'password'}); s.get('/my'); puts s.response.body"

vishnuatrai

// Finds unused indexes in a mysql database

SELECT
  t.TABLE_SCHEMA,
  t.TABLE_NAME,
  s.INDEX_NAME,
  s.COLUMN_NAME,
  s.SEQ_IN_INDEX,
  ( SELECT MAX(SEQ_IN_INDEX)
    FROM INFORMATION_SCHEMA.STATISTICS s2

vishnuatrai

function keepTrying(otherArgs, promise) {
	promise = promise||new Promise();
	
	// try doing the important thing
	
	if(success) {
		promise.resolve(result);
	} else {
		setTimeout(function() {
			keepTrying(otherArgs, promise);

vishnuatrai

What is this?

Following this guide will set up a local Elasticsearch with Kibana and Marvel using Homebrew and Homebrew Cask

Prerequisites

If you already have Java installed on your system, skip steps Install Cask and Install Java

If you already have Java and Homebrew installed on your system, skip steps Prerequisites, start at Install Elasticsearch and Kibana after running $ brew update

Install Homebrew

• $ ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"