waylonflinn

#!/usr/bin/python3

# Usage:
#lh.py on
#lh.py off
# with no arguments, state will be toggled (off -> on, on -> off)
#lh.py

from bluepy import btle
import sys

waylonflinn

New (and Unimproved?)

Lake Murray / Ardmore

South on I-35, 2 hours

• Ski Jump Campground (unimproved), $14 / night

info | map

waylonflinn

# How to Edit Gameplay Footage

## Identify the Narratives

There will likely be at least four narratives going on at any one time.

1. Channel/life narrative
	a. Who are you as a person?
	b. What's this channel about?
2. Personal/life narrative (more temporally local than the channel narrative)

waylonflinn

Authentic Al Pastor, Crockpot Style

Ingredients

• 1 pineapple

• 1 bottle of beer

• 1/4 cup vinegar

• 2 pounds of pork (loin, shoulder or butt)

• 1/2 cup onion

waylonflinn

import bcolz
import bquery

data_path = '/some/place/with/bcolz/data'

c_table = bquery.ctable(rootdir=data_path)

## Filter

# create the criteria

waylonflinn

Why node.js?

Assumptions:

• three things matter: developer productivity, production performance, infrastructure cost

  • developer productivity: prototyping, productionifying, maintenance
  • production performance: latency, concurrency
  • infrastructure cost: hardware baseline, hardware scaling, operations (dev-ops) overhead

• same code on client and server (developer productivity)

  • no context switch

waylonflinn

#!/usr/bin/bash
# pass in a single argument with the name of the project

mkdir git
mkdir git/$1

mkdir apps
mkdir apps/$1

mkdir deployments

waylonflinn

# First run the python data science script: https://gist.github.com/waylonflinn/506f563573600d944923

# cuda
# wget http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1404/x86_64/cuda-repo-ubuntu1404_6.5-14_amd64.deb
# dpkg -i cuda-repo-ubuntu1404_6.5-14_amd64.deb
# sudo apt-get update
# sudo apt-get install -y cuda
# pushd installs
# wget https://github.com/BVLC/caffe/archive/v0.9999.tar.gz
# tar -xvf v0.9999.tar.gz

waylonflinn

#! /usr/bin/env python
# this script filters output from ipython notebooks, for use in git repos
# http://stackoverflow.com/questions/18734739/using-ipython-notebooks-under-version-control
#
# put this file in a `bin` directory in your home directory, then run the following commands:
#
# chmod a+x ~/bin/ipynb_output_filter.py
# echo -e "*.ipynb \t filter=dropoutput_ipynb" >> ~/.gitattributes
# git config --global core.attributesfile ~/.gitattributes
# git config --global filter.dropoutput_ipynb.clean ~/bin/ipynb_output_filter.py

waylonflinn

#!/usr/bin/env bash

## create an ubuntu 14.04 hvm instance, then from your home directory:

# 1. download this script
# wget https://gist.githubusercontent.com/waylonflinn/506f563573600d944923/raw/install-python-data-science.sh

# 2. make it executable
# chmod a+x install-python-data-science.sh