lukaszx0

# Usage:
# 1) Ctr+S downloads page to ~/Desktop/books.html
# 2) Run script
# 3) Find your books in /tmp/humble_books
# 4) Read them
# 5) Profit
cat ~/Desktop/books.html |
  grep "https://dl.humble.com" |
  sed -n -E 's/.data-web\=\"(https://dl.humble.com/([.]+).([a-z]+)?["]+)./\1 \2 \3/p' |
  sed 's/&/&/g' > /tmp/humble_books_list && cat /tmp/humble_books_list |

pathikrit

/**
 * Solves the n-Queen puzzle in O(n!)
 * Let p[r] be the column of the queen on the rth row (must be exactly 1 queen per row)
 * There also must be exactly 1 queen per column and hence p must be a permuation of (0 until n)
 * There must be n distinct (col + diag) and n distinct (col - diag) for each queen (else bishop attacks)
 * @return returns a Iterator of solutions 
 *     Each solution is an array p of length n such that p[i] is the column of the queen on the ith row
 */
def nQueens(n: Int): Iterator[Seq[Int]] = 
  (0 until n)

staltz

The introduction to Reactive Programming you've been missing

(by @andrestaltz)

---

This tutorial as a series of videos

If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.

---

georg

IT'S SHOWTIME

HEY CHRISTMAS TREE isLessThan100
YOU SET US UP @NO PROBLEMO
HEY CHRISTMAS TREE n
YOU SET US UP 0
HEY CHRISTMAS TREE multiple
YOU SET US UP @NO PROBLEMO

STICK AROUND isLessThan100

seboudry

Latency numbers every programmer should know

L1 cache reference ......................... 0.5 ns
Branch mispredict ............................ 5 ns                     on recent CPU
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 µs
Send 2K bytes over 1 Gbps network ....... 20,000 ns  =  20 µs
SSD random read ........................ 150,000 ns  = 150 µs

Read 1 MB sequentially from memory ..... 250,000 ns = 250 µs 4X memory

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

wsargent

303 See Other

Location: https://github.com/wsargent/docker-cheat-sheet

Hi there!

The docker cheat sheet has moved to a Github project under https://github.com/wsargent/docker-cheat-sheet.

Please click on the link above to go to the cheat sheet.

aras-p

// Just before switching jobs:
// Add one of these.
// Preferably into the same commit where you do a large merge.
//
// This started as a tweet with a joke of "C++ pro-tip: #define private public",
// and then it quickly escalated into more and more evil suggestions.
// I've tried to capture interesting suggestions here.
//
// Contributors: @r2d2rigo, @joeldevahl, @msinilo, @_Humus_,
// @YuriyODonnell, @rygorous, @cmuratori, @mike_acton, @grumpygiant,

ndarville

Business Models

Advertising

Models	Examples
Display ads	Yahoo!
Search ads	Google

olasitarska

# -*- coding: utf-8 -*-
"""
Builds epub book out of Paul Graham's essays: http://paulgraham.com/articles.html

Author: Ola Sitarska <ola@sitarska.com>
Copyright: Licensed under the GPL-3 (http://www.gnu.org/licenses/gpl-3.0.html)

This script requires python-epub-library: http://code.google.com/p/python-epub-builder/
"""