killercup

/*
 * I add this to html files generated with pandoc.
 */

html {
  font-size: 100%;
  overflow-y: scroll;
  -webkit-text-size-adjust: 100%;
  -ms-text-size-adjust: 100%;
}

Vessy

# Plotting networks in R 
# An example how to use R and rgexf package to create a .gexf file for network visualization in Gephi

############################################################################################
# Clear workspace 
rm(list = ls())

# Load libraries
library("igraph")
library("plyr")

noamross

throttle = new.env(parent = emptyenv())
throttle$recent = data.frame(domain =  character(), last_visit = character())

#' A throttled version of GET
#' 
#' This uses \code{httr::GET} to fetch a web page, but throttles based on domains.
#' 
#' \code{slowGET} keeps a list of domains recently accessed by itself in a 
#' separate environment.  If a domain has been accessed since \code{pause}
#' seconds ago, it will delay execution until that time has passed

sebsto

sudo wget http://repos.fedorapeople.org/repos/dchen/apache-maven/epel-apache-maven.repo -O /etc/yum.repos.d/epel-apache-maven.repo
sudo sed -i s/\$releasever/6/g /etc/yum.repos.d/epel-apache-maven.repo
sudo yum install -y apache-maven
mvn --version

seanorama

Create a local Vagrant base box from an existing VirtualBox VM

What

• Setting up a new development VM should be as easy as 2 commands. And it is:
  • vagrant init; vagrant up
• In this example we are converting the HDP Sandbox to be used in this way. But the howto will work with any existing VM.

Why

conormm

R to python data wrangling snippets

The dplyr package in R makes data wrangling significantly easier. The beauty of dplyr is that, by design, the options available are limited. Specifically, a set of key verbs form the core of the package. Using these verbs you can solve a wide range of data problems effectively in a shorter timeframe. Whilse transitioning to Python I have greatly missed the ease with which I can think through and solve problems using dplyr in R. The purpose of this document is to demonstrate how to execute the key dplyr verbs when manipulating data using Python (with the pandas package).

dplyr is organised around six key verbs:

zonca

ser www-data;
worker_processes 4;
pid /run/nginx.pid;

events {
  worker_connections 1024;
}

http {

cosmincatalin

#!/bin/bash

# These variables can be overwritten using the arguments below
VERSION="1.1.463"
# drwho is listed as user in YARN's Resource Manager UI.
USER="drwho"
# Depending on where the EMR cluster lives, you might have to change this to avoid security issues.
# To change the default password (and user), use the arguments bellow.
# If the cluster is not visible on the Internet, you can just leave the defaults for convenience.
PASS="tardis"

mattiaslundberg

Ansible playbook to setup HTTPS using Let's encrypt on nginx.

The Ansible playbook installs everything needed to serve static files from a nginx server over HTTPS.
The server pass A rating on [SSL Labs](https://www.ssllabs.com/).

To use:
 1. Install [Ansible](https://www.ansible.com/)
 2. Setup an Ubuntu 16.04 server accessible over ssh
 3. Create `/etc/ansible/hosts` according to template below and change example.com to your domain
 4. Copy the rest of the files to an empty directory (`playbook.yml` in the root of that folder and the rest in the `templates` subfolder)

tomz

#!/bin/bash
set -x -e

# AWS EMR bootstrap script 
# for installing open-source R (www.r-project.org) with RHadoop packages and RStudio on AWS EMR
#
# tested with AMI 4.0.0 (hadoop 2.6.0)
#
# schmidbe@amazon.de
# 24. September 2014