JoergWMittag

{"businesses":[
    {"address1":"466 Haight St",
     "city":"San Francisco",
     "mobile_url":"http://mobile.yelp.com/biz/yyqwqfgn1ZmbQYNbl7s5sQ",
     "name":"Nickies",
     "address2":"",
     "avg_rating":4,
     "latitude":37.772201,
     "zip":"94117",
     "address3":"",

canton7

How to have local versions of tracked config files in git

This is a fairly common question, and there isn't a One True Answer.

These are the most common techniques:

If you can modify your application

schlamar

import os
import sys
import traceback
from functools import wraps
from multiprocessing import Process, Queue


def processify(func):
    '''Decorator to run a function as a process.
    Be sure that every argument and the return value

hellerbarde

Latency numbers every programmer should know

L1 cache reference ......................... 0.5 ns
Branch mispredict ............................ 5 ns
L2 cache reference ........................... 7 ns
Mutex lock/unlock ........................... 25 ns
Main memory reference ...................... 100 ns             
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

1wErt3r

;SMBDIS.ASM - A COMPREHENSIVE SUPER MARIO BROS. DISASSEMBLY
;by doppelganger (doppelheathen@gmail.com)

;This file is provided for your own use as-is.  It will require the character rom data
;and an iNES file header to get it to work.

;There are so many people I have to thank for this, that taking all the credit for
;myself would be an unforgivable act of arrogance. Without their help this would
;probably not be possible.  So I thank all the peeps in the nesdev scene whose insight into
;the 6502 and the NES helped me learn how it works (you guys know who you are, there's no 

ssylvan

#define USE_ROBIN_HOOD_HASH 1
#define USE_SEPARATE_HASH_ARRAY 1

template<class Key, class Value>
class hash_table
{
  static const int INITIAL_SIZE = 256;
	static const int LOAD_FACTOR_PERCENT = 90;

	struct elem

shawndumas

[mergetool]
    prompt = false
    keepBackup = false
    keepTemporaries = false

[merge]
    tool = winmerge

[mergetool "winmerge"]
    name = WinMerge

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

wrouesnel

# this is an rsync-excludes format list of files to exclude.

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.

---