kmatt

#! /usr/bin/env python

import redis
import random
import sys

r = redis.Redis(host = 'localhost', port = 6389)

REDIS_SETGET = False
REDIS_HSET = False

kmatt

# I am a scientist who has been using R for about 2 years. Today I achieved a measure of enlightenment into
# the zen of R, and I want to share it with you.

# I was simulating a set of independent random walks, which are formed by a multiplicative process. Here is
# the code I had built up over a few months of working on it and modifying it on and off as research
# questions changed:

TimeSteps <- 1000
Walks <- 100
ErrorMagnitude <- 0.03

kmatt

# http://openmymind.net/Paging-And-Ranking-With-Large-Offsets-MongoDB-vs-Redis-vs-Postgresql/

lids = ['4fe907f1210b2e9e3080f001', '4fe907f1210b2e9e3080f002', '4fe907f1210b2e9e3080f003', '4fe907f1210b2e9e3080f004', '4fe907f1210b2e9e3080f005']
 
 insert the data
 open('data.csv', 'w') do |f| 
   6000000.times do |i| 
        f.puts "#{lids.sample},user_#{i},#{(rand() * 10000000).to_i}"
      end 
  end

kmatt

# .png with Windows GDI versus .png with cairographics

doInstall <- TRUE  # Change to FALSE if you don't want packages installed.
toInstall <- c("ggplot2", "RColorBrewer", "Cairo")
if(doInstall){install.packages(toInstall, repos = "http://cran.us.r-project.org")}
lapply(toInstall, library, character.only = TRUE)

# Generate some data
nn <- 100
myData <- data.frame(X = rnorm(nn),

kmatt

#!/broad/software/free/Linux/redhat_5_x86_64/pkgs/r_3.0.2/bin/Rscript

# Eric Vallabh Minikel
# CureFFI.org
# 2014-01-14
# example of how to use optparse in R scripts

# usage: ./exampleRScript1.r -a thisisa -b hiagain
#        ./exampleRScript1.r --avar thisisa --bvar hiagain

kmatt

#!/bin/sh
### BEGIN INIT INFO
# Provides:
# Required-Start:    $remote_fs $syslog $zookeeper
# Required-Stop:     $remote_fs $syslog
# Default-Start:     2 3 4 5
# Default-Stop:      0 1 6
# Short-Description: Start daemon at boot time
# Description:       Enable service provided by daemon.
### END INIT INFO

kmatt

vimdiff cheat sheet

##git mergetool

In the middle file (future merged file), you can navigate between conflicts with ]c and [c.

Choose which version you want to keep with :diffget //2 or :diffget //3 (the //2 and //3 are unique identifiers for the target/master copy and the merge/branch copy file names).

:diffupdate (to remove leftover spacing issues)

:only (once you’re done reviewing all conflicts, this shows only the middle/merged file)

kmatt

display.cell <- function(x, bgcol="#DAE6F2", ...) {
  opar <- par(bg=bgcol, mar=rep(0,4))
  plot(c(0,1), c(0,1), type="n", axes=FALSE, xlab="", ylab="")
  text(.5, .5, as.character(x), ...)
  lines(c(-0.1,1.1), c(0,0))
  par(opar)
}

format.digits <- function(x) as.character(paste("$", as.character(x), sep="   "))

kmatt

import mimetypes
import sys
from collections import OrderedDict

filename = sys.argv[1]

def file_type(filename):
    type = mimetypes.guess_type(filename)
    return type

kmatt

#!/usr/bin/env python
#
# Very basic example of using Python and IMAP to iterate over emails in a
# gmail folder/label.  This code is released into the public domain.
#
# RKI July 2013
# http://www.voidynullness.net/blog/2013/07/25/gmail-email-with-python-via-imap/
#
import sys
import imaplib