This tutorial was created by Shopify for internal purposes. We've created a public version of it since we think it's useful to anyone creating a GraphQL API.
It's based on lessons learned from creating and evolving production schemas at Shopify over almost 3 years. The tutorial has evolved and will continue to change in the future so nothing is set in stone.
| import random | |
| import time | |
| import json | |
| import threading | |
| import click | |
| def send_message(msg, async=True): | |
| """Logs the msg (presumably a JSON object) to firehose |
| require "rubygems" | |
| require "twitter" | |
| # get these from apps.twitter.com | |
| CONSUMER_KEY = "foo" | |
| CONSUMER_SECRET = "bar" | |
| OAUTH_TOKEN = "blee" | |
| OAUTH_TOKEN_SECRET = "baz" | |
| TWITTER_USER = "your_username" # needs to be the one associated with keys above |
| ! Atom One Light theme | |
| xterm*background: #f9f9f9 | |
| xterm*foreground: #383a42 | |
| xterm*cursorColor: #d0d0d0 | |
| xterm*color0: #000000 | |
| xterm*color1: #E45649 | |
| xterm*color2: #50A14F | |
| xterm*color3: #986801 | |
| xterm*color4: #4078F2 | |
| xterm*color5: #A626A4 |
This document: https://goo.gl/AqGoE8
By far the most annoying part of getting started with messing with ML is installing researcher-made code and turning it into something fun to play with.
Before doing any of these, please install Miniconda. If you don't have it installed already, here's how:
For OSX, this is:
Disclaimer: This piece is written anonymously. The names of a few particular companies are mentioned, but as common examples only.
This is a short write-up on things that I wish I'd known and considered before joining a private company (aka startup, aka unicorn in some cases). I'm not trying to make the case that you should never join a private company, but the power imbalance between founder and employee is extreme, and that potential candidates would
