Jason Sigal therewasaguy

"Encouraging the Nonstandard" 2018 Resources

Author

Melody Loveless
Website: melodyloveless.com
Soundcloud: https://soundcloud.com/melody-loveless
Instagram: @melodycodes
(But really you should follow my band Codie at @hi_codie on Instagram and Twitter)

Started for the Music Education Hackathon (Fall 2018). Updated for the Bates Digital Music Symposium. This page has collection of resources for people to explore nonstandard frameworks of music making with an emphasis in music technology. This list does aim or claim to be complete or completley reprsentational of what's out there - but it's a start ╘[◉﹃◉]╕

Falsehoods programmers believe about time

This is a compiled list of falsehoods programmers tend to believe about working with time.

Don't re-invent a date time library yourself. If you think you understand everything about time, you're probably doing it wrong.

Falsehoods

There are always 24 hours in a day.
February is always 28 days long.
Any 24-hour period will always begin and end in the same day (or week, or month).

#Make-A-Twitter-Bot Workshop

Session led by Allison Parrish

##Some of my bots

Power Vocab Tweet (markov chains)
Library of Emoji (context-free grammars)
Egress Methods (CMU pronouncing dictionary)
Eventually Bot

Session Management in an Autoscaling Environment

Problem Statement

User sessions in J2EE and LAMP stacks have traditionally been handled in memory by the application server handling the user request. Because of that, load balancers have been configured to use sticky sessions. By sticky sessions we mean that once the user has visited the site, they will be assigned an app server and will return to that server for subsequent requests. The load balancers typically handle that by referencing the users session cookie.

Elastic cloud environments differ from traditional server configurations in that they have a variable number of servers based on traffic loads whereas traditional configurations had a fixed number of servers. When traffic volumes decline it is necessary to vaporize servers. In doing so, we would lose user sessions (essentially forcing a logout) unless we come up with a new strategy for session management.

A new approach

After much research, it is clear that the best

	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

	All actions are performed in Terminal.app.

	1. Install Homebrew http://brew.sh/

	2. Install Jack (route audio tool) http://jackaudio.org/. Current stable version from official website doesn't work with
	MacOS Sierra (I use 10.12.3) so you need to download beta version from there https://yadi.sk/d/JwT10b7v3Dm5yy.
	After installing reboot your computer.

	3. Install Darkice (audio streamer) via brew.

	var request = require('request');
	var fs = require('fs');
	var sox = require('sox');
	var spawn = require('child_process').spawn;

	var WATSON_USER = '';
	var WATSON_PASS = '';
	var url = 'https://stream.watsonplatform.net/speech-to-text/api/v1/recognize';

	# You don't need Fog in Ruby or some other library to upload to S3 -- shell works perfectly fine
	# This is how I upload my new Sol Trader builds (http://soltrader.net)
	# Based on a modified script from here: http://tmont.com/blargh/2014/1/uploading-to-s3-in-bash

	S3KEY="my aws key"
	S3SECRET="my aws secret" # pass these in

	function putS3
	{
	path=$1

	I
	MISS
	HIM
	HURRY
	UP
	THURSDAY
	OR
	FRIDAY
	ITS
	NOT

	import numpy as np
	import sklearn
	from sklearn.tree import *
	from sklearn.datasets import *

	iris = load_iris()

	X = iris.data
	y = iris.target