A quick overview of the node.js streams interface with basic examples.
This is based on @brycebaril's presentation, Node.js Streams2 Demystified
Streams are a first-class construct in Node.js for handling data.
Think of them as as lazy evaluation applied to data.
Web fonts are pretty much all the rage. Using a CDN for font libraries, like TypeKit or Google Fonts, will be a great solution for many projects. For others, this is not an option. Especially when you are creating a custom icon library for your project.
Rails and the asset pipeline are great tools, but Rails has yet to get caught up in the custom web font craze.
As with all things Rails, there is more then one way to skin this cat. There is the recommended way, and then there are the other ways.
Here I will show how to update your Rails project so that you can use the asset pipeline appropriately and resource your files using the common Rails convention.
| # -*- coding: utf-8 -*- | |
| import codecs | |
| import cStringIO | |
| import csv | |
| import json | |
| import sys | |
| """ | |
| Convert Django json datadump fields into csv. |
| from flask import Flask, redirect, url_for, request | |
| app = Flask(__name__) | |
| is_maintenance_mode = True | |
| # Always throw a 503 during maintenance: http://is.gd/DksGDm | |
| @app.before_request | |
| def check_for_maintenance(): |
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
I was at Amazon for about six and a half years, and now I've been at Google for that long. One thing that struck me immediately about the two companies -- an impression that has been reinforced almost daily -- is that Amazon does everything wrong, and Google does everything right. Sure, it's a sweeping generalization, but a surprisingly accurate one. It's pretty crazy. There are probably a hundred or even two hundred different ways you can compare the two companies, and Google is superior in all but three of them, if I recall correctly. I actually did a spreadsheet at one point but Legal wouldn't let me show it to anyone, even though recruiting loved it.
I mean, just to give you a very brief taste: Amazon's recruiting process is fundamentally flawed by having teams hire for themselves, so their hiring bar is incredibly inconsistent across teams, despite various efforts they've made to level it out. And their operations are a mess; they don't real