mdang

Ruby on Rails Cheatsheet

Architecture

Create a new application

Install the Rails gem if you haven't done so before

jeonghwan-kim

module.exports = {
  up: function (queryInterface, Sequelize) {
    return [
      queryInterface.addColumn('User', 'name', {
        type: Sequelize.STRING
      }),
      queryInterface.addColumn('User', 'nickname', {
        type: Sequelize.STRING,
      })
    ];

GilLevi

Gil Levi and Tal Hassner, Emotion Recognition in the Wild via Convolutional Neural Networks and Mapped Binary Patterns

Convolutional neural networks for emotion classification from facial images as described in the following work:

Gil Levi and Tal Hassner, Emotion Recognition in the Wild via Convolutional Neural Networks and Mapped Binary Patterns, Proc. ACM International Conference on Multimodal Interaction (ICMI), Seattle, Nov. 2015

Project page: http://www.openu.ac.il/home/hassner/projects/cnn_emotions/

If you find our models useful, please add suitable reference to our paper in your work.

rwarbelow

1. Add gem 'rails_12factor' to your Gemfile. This will add error logging and the ability for your app to serve static assets.
2. bundle
3. Run RAILS_ENV=production rake db:create db:migrate db:seed
4. Run rake secret and copy the output
5. From the command line: export SECRET_KEY_BASE=output-of-rake-secret
6. To precompile your assets, run rake assets:precompile. This will create a folder public/assets that contains all of your assets.
7. Run RAILS_ENV=production rails s and you should see your app.

Remember to clobber your assets (rake assets:clobber) and re-precompile (rake assets:precompile) if you make changes.

marcellodesales

######
# Author: Marcello de Sales ([email protected])
# Description: Create Create Environment Variables in EC2 Hosts from EC2 Host Tags
# 
### Requirements:  
# * Install jq library (sudo apt-get install -y jq)
# * Install the EC2 Instance Metadata Query Tool (http://aws.amazon.com/code/1825)
#
### Installation:
# * Add the Policy EC2:DescribeTags to a User

ilyaigpetrov

Meteor Alternatives Per Feature

This table was created in 2015 so may be quite outdated today.

Feature	Meteor Solution	Alternative Solutions	Description
Live DB Sync	[livequery][lq] ([mongo-oplog]), [ddp]	RethinkDB, Redis, ShareDB, [npm:mongo-oplog], [firebase], etc.	Push DB updates to client/server.
Latency Compensation, Optimistic UI	[minimongo][mm]	[RethinkDB][lcr], [mWater/minimongo] (fork, not ws but http, browserify)	Imitate successful db query on client before it is done.
Isomorphic Code	[isobuild] & isopacks	browserify	Write one code for server/client/mobile.
Isomorphic Packaging	[isobuild], atmosphere		No more separate packages for server & client. Get bower + npm + mobile.

paulirish

What forces layout / reflow

All of the below properties or methods, when requested/called in JavaScript, will trigger the browser to synchronously calculate the style and layout*. This is also called reflow or layout thrashing, and is common performance bottleneck.

Generally, all APIs that synchronously provide layout metrics will trigger forced reflow / layout. Read on for additional cases and details.

Element APIs

Getting box metrics

• elem.offsetLeft, elem.offsetTop, elem.offsetWidth, elem.offsetHeight, elem.offsetParent

01.configure

2015-08-24 20:19:09 +0530

./configure
--prefix=/usr/local/Cellar/python/2.7.10_2
--enable-ipv6
--datarootdir=/usr/local/Cellar/python/2.7.10_2/share
--datadir=/usr/local/Cellar/python/2.7.10_2/share
--enable-framework=/usr/local/Cellar/python/2.7.10_2/Frameworks
--without-ensurepip
--without-gcc

01.configure

2015-08-24 19:34:15 +0530

./configure
--prefix=/usr/local/Cellar/sqlite/3.8.11.1
--disable-dependency-tracking
--enable-dynamic-extensions

checking for a BSD-compatible install... /usr/bin/install -c
checking whether build environment is sane... yes
checking for a thread-safe mkdir -p... ./install-sh -c -d

karpathy

"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np

# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)