nu7hatch

...

module Helpers
  # Replace standard input with faked one StringIO. 
  def fake_stdin(*args)
    begin
      $stdin = StringIO.new
      $stdin.puts(args.shift) until args.empty?
      $stdin.rewind
      yield

cgrand

; http://groups.google.com/group/clojure/browse_thread/thread/974e2c7f89e27231/5f4bff3e58dfa36f
; output images http://i.imgur.com/gSASS.png (square maze)
;               http://i.imgur.com/uEqaq.png (hex maze)

;; generic Wilson's algorithm implementation
(defn maze 
 "Returns a random maze carved out of walls; walls is a set of
  2-item sets #{a b} where a and b are locations.
  The returned maze is a set of the remaining walls."
 [walls]

jboner

Latency Comparison Numbers (~2012)
----------------------------------
L1 cache reference                           0.5 ns
Branch mispredict                            5   ns
L2 cache reference                           7   ns                      14x L1 cache
Mutex lock/unlock                           25   ns
Main memory reference                      100   ns                      20x L2 cache, 200x L1 cache
Compress 1K bytes with Zippy             3,000   ns        3 us
Send 1K bytes over 1 Gbps network       10,000   ns       10 us
Read 4K randomly from SSD*             150,000   ns      150 us          ~1GB/sec SSD

piscisaureus

Locate the section for your github remote in the .git/config file. It looks like this:

[remote "origin"]
	fetch = +refs/heads/*:refs/remotes/origin/*
	url = git@github.com:joyent/node.git

Now add the line fetch = +refs/pull/*/head:refs/remotes/origin/pr/* to this section. Obviously, change the github url to match your project's URL. It ends up looking like this:

joshed-io

cd $HOME/.rbenv/plugins/ruby-build
git pull
rbenv install 2.0.0-p0
rbenv local 2.0.0-p0
gem install bundler -v 1.3.0.pre.8

cd /path/to/ruby/app

# Necessary if not already 600
chmod 600 $HOME/.gem/credentials

glucero

#!/usr/bin/env ruby

class RubyArchive

  require 'rubygems/package'
  require 'zlib'

  attr_reader :path

  class Archive

debasishg

General Background and Overview

1. Probabilistic Data Structures for Web Analytics and Data Mining : A great overview of the space of probabilistic data structures and how they are used in approximation algorithm implementation.
2. Models and Issues in Data Stream Systems
3. Philippe Flajolet’s contribution to streaming algorithms : A presentation by Jérémie Lumbroso that visits some of the hostorical perspectives and how it all began with Flajolet
4. Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
5. [Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep=rep1&t

jxcl

This is free and unencumbered software released into the public domain.

Anyone is free to copy, modify, publish, use, compile, sell, or
distribute this software, either in source code form or as a compiled
binary, for any purpose, commercial or non-commercial, and by any
means.

In jurisdictions that recognize copyright laws, the author or authors
of this software dedicate any and all copyright interest in the
software to the public domain. We make this dedication for the benefit

barn

#!/bin/bash
#
# This.
# Is.
# Awful.

# write that file as:
# round=<0|1|2>
# oldpass=1234
# newpass=4321

bishboria

These links no longer work. Springer have pulled the free plug.

Graduate texts in mathematics

duplicates = multiple editions

A Classical Introduction to Modern Number Theory, Kenneth Ireland Michael Rosen

A Classical Introduction to Modern Number Theory, Kenneth Ireland Michael Rosen