Shehmeer Jiwani dragonai

Culture

What do you like best about working there?
What do you like least?
How would you describe this company's culture? engineering culture?
What causes the most conflict among employees here?
What would you change if you could?
How has the company changed in the past five years? How do you think it will change in the next five?
How long has the longest serving team member been there?
What's the average or median tenure?

Solarized Dark profile for Terminal.app on macOS High Sierra

Based on the excellent Solarized (Dark) created by Ethan Schoonover. For source code, check the main Solarized repository on GitHub.

Installation

Open and save Solarized Dark.terminal.

Import from the “Profiles” tab in the settings of Terminal.app or just double-click the file after downloading.

'Include' in Sequelize: The One Confusing Query That You Should Memorize

When querying your database in Sequelize, you'll often want data associated with a particular model which isn't in the model's table directly. This data is usually typically associated through join tables (e.g. a 'hasMany' or 'belongsToMany' association), or a foreign key (e.g. a 'hasOne' or 'belongsTo' association).

When you query, you'll receive just the rows you've looked for. With eager loading, you'll also get any associated data. For some reason, I can never remember the proper way to do eager loading when writing my Sequelize queries. I've seen others struggle with the same thing.

Eager loading is confusing because the 'include' that is uses has unfamiliar fields is set in an array rather than just an object.

So let's go through the one query that's worth memorizing to handle your eager loading.

The Basic Query

Server Price Breakdown: DigitalOcean, Amazon AWS LightSail, Vultr, Linode, OVH, Hetzner, Scaleway/Online.net:

Permalink: git.io/vps

$5/mo

Provider	Type	RAM	Cores	Storage	Transfer	Network	Price

Setting up a Raspberry Pi as a dashboard server with Dashing

Why the heck did I do this?

I wanted to set up one of my Raspberry Pi's as a data dashboard, pushing sensor data to a web interface that's easy to digest. I decided to use Shopify's Dashing framework. Dashing is based on Sinatra, and is pretty lightweight.

Dashing does require Ruby 1.9.3 to run. In addition, it makes use of the execjs gem, which needs to have a working Javascript interpreter available. Originally, I tried to get therubyracer working, but decided to switch over to Node.js when I ran into roadblocks compiling V8.

One warning: The RPi is a very slow system compared with modern multi-core x86-style systems. It's pretty robust, but compiling all this complex software taxes the system quite a bit. Expect that it's going to take at least half a day to get everything going.

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

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