eligrey

/*
 * object.watch polyfill
 *
 * 2012-04-03
 *
 * By Eli Grey, http://eligrey.com
 * Public Domain.
 * NO WARRANTY EXPRESSED OR IMPLIED. USE AT YOUR OWN RISK.
 */

branneman

Better local require() paths for Node.js

Problem

When the directory structure of your Node.js application (not library!) has some depth, you end up with a lot of annoying relative paths in your require calls like:

const Article = require('../../../../app/models/article');

Those suck for maintenance and they're ugly.

Possible solutions

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

gianrubio

machine: 
  services:
    - docker
  post:
    - wget https://gist.githubusercontent.com/gianrubio/dce37ee9b9c024937832d776597e2603/raw/4cdb30e5075e8e6064ac48a258e05f518f8c88c0/circleci-tunnel.sh ~/ && chmod +x ~/circleci-tunnel.sh
    - ~/circleci-tunnel.sh start:
        background: true

CMCDragonkai

History Data Structures

For stateful applications, there are 5 different ways of managing the history of state:

• No History - Living in the moment. - Examples: Any stateful application that doesn't discards all previous states upon mutation.
• Ad Hoc Snapshotting - Allows restoration to manually saved snapshots. - Examples: Memento Pattern.
• Singleton - Only remembers the previous snapshot, where undoing the undo is just another undo. - Examples: Xerox PARC Bravo.
• 1 Stack - Allows linear undo. - Examples: AtariWriter.
• 2 Stack - Allows linear undo and redo. - Examples: Browser History, Microsoft Word, Adobe Photoshop.

galpratama

104.16.119.221 boards.4chan.org
104.16.59.249 i.4cdn.org

jdrew1303

Introduction

The computer driven markets for instruments like stocks and exchange traded stock options, have transformed finance and the flow of capital. These markets are enabled by order matching engines (and the infrastructure that supports this software). Before computer trading networks and matching engines, stocks where traded on cavernous exchange floors and transaction costs where high. When electronic trading fully matured, floor traders were a fading anachronism and transaction costs had been reduced to pennies a share in many cases. Electronic trading could not exist without advanced network infrastructure, but without the software matching engines no shares would change hands. The computer trading networks, the matching engine software has also created a concentrated nexus of potential failure. Failures in these systems have increased as the frequency and volume on the electronic networks has increased. The position of order matching engines in the trading infrastructure makes these systems o