blam23

Toribash Scripting Tutorial

What is this tutorial about?

This tutorial is about using and creating 'scripts' in Toribash. In this first tutorial I will be covering what scripts are, how to use them, how they are made and what tools you will need to make them.

There is a very simple exercise at the end of the tutorial that will test what you have learned.

The proceeding tutorials will then go into detail about how to make scripts, including going over the basics of programming.

These tutorials are created for people with no experience in programming, but are also recommended for people who know programming but are not sure in how to create scripts specifically for Toribash

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,

konklone

# Basically the nginx configuration I use at konklone.com. 
# I check it using https://www.ssllabs.com/ssltest/analyze.html?d=konklone.com
# 
# To provide feedback, please tweet at @konklone or email [email protected].
# Comments on gists don't notify the author. 
# 
# Thanks to WubTheCaptain (https://wubthecaptain.eu) for his help and ciphersuites.
# Thanks to Ilya Grigorik (https://www.igvita.com) for constant inspiration.

server {

plentz

# to generate your dhparam.pem file, run in the terminal
openssl dhparam -out /etc/nginx/ssl/dhparam.pem 2048

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

sehe

all:consumer producer

CPPFLAGS+=-std=c++03 -Wall -pedantic
CPPFLAGS+=-g -O0
CPPFLAGS+=-isystem ~/custom/boost/

LDFLAGS+=-L ~/custom/boost/stage/lib/ -Wl,-rpath,/home/sehe/custom/boost/stage/lib
LDFLAGS+=-lboost_system -lrt -lpthread

%:%.cpp

rcnly

#!/usr/bin/env python

from os.path import isfile
from sys import argv
from time import sleep

import commands
import select

suffix = argv[1] if len(argv) > 1 else ""

justecorruptio

M[16],X=16,W,k;main(){T(system("stty cbreak")
);puts(W&1?"WIN":"LOSE");}K[]={2,3,1};s(f,d,i
,j,l,P){for(i=4;i--;)for(j=k=l=0;k<4;)j<4?P=M
[w(d,i,j++)],W|=P>>11,l*P&&(f?M[w(d,i,k)]=l<<
(l==P):0,k++),l=l?P?l-P?P:0:l:P:(f?M[w(d,i,k)
]=l:0,++k,W|=2*!l,l=0);}w(d,i,j){return d?w(d
-1,j,3-i):4*i+j;}T(i){for(i=X+rand()%X;M[i%X]
*i;i--);i?M[i%X]=2<<rand()%2:0;for(W=i=0;i<4;
)s(0,i++);for(i=X,puts("\e[2J\e[H");i--;i%4||
puts(""))printf(M[i]?"%4d|":"    |",M[i]);W-2

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.

---

jeregrine

def index(conn, %{"event" => "true"}) do                                                                       
  conn = conn                                                                                                  
          |> put_resp_content_type("text/event-stream")                                                        
          |> send_chunked(200)                                                                                 
  {:ok, conn} = chunk(conn, ["data: ", JSON.encode!(Thermostat.Data.get()), "\n\n"])                           
  Phoenix.Topic.subscribe self, "data"                                                                         
  data_updated(conn)                                                                                           
end 

defp data_updated(conn) do