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## Capture the Flag - Cypto Beginners - Basic Cypher 
#  authors: Nauman (recluze) / Sohail 
#  Effat University, Jeddah, KSA 


#  Information availble to perform cryptanalysis: 
#  - Message is in the English language 
#  - Message is approximately (but not exactly) 10 words long

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asodjflasdjfsdf

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defmodule Fib do 
  def fib(0) do 0 end
  def fib(1) do 1 end
  def fib(n) do fib(n-1) + fib(n-2) end
end

IO.puts Fib.fib(10)

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printNumber(int num) { 
  print("The number is: ${num}!!"); 

}

void main() {
  for (int i = 0; i < 5; i++) {
    print('hello ${i + 1}');
  }

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First, update and upgrade all packages: 
sudo apt-get update 
sudo apt-get upgrade 

sudo -i # Change to root 
cd /usr/local/src 


Main docs: 
https://wiki.asterisk.org/wiki/display/AST/Installing+Asterisk+From+Source

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Transforming Code into Beautiful, Idiomatic Python

Notes from Raymond Hettinger's talk at pycon US 2013 video, slides.

The code examples and direct quotes are all from Raymond's talk. I've reproduced them here for my own edification and the hopes that others will find them as handy as I have!

Looping over a range of numbers

for i in [0, 1, 2, 3, 4, 5]:

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# searchAgents.py
# ---------------
# Licensing Information:  You are free to use or extend these projects for
# educational purposes provided that (1) you do not distribute or publish
# solutions, (2) you retain this notice, and (3) you provide clear
# attribution to UC Berkeley, including a link to http://ai.berkeley.edu.
# 
# Attribution Information: The Pacman AI projects were developed at UC Berkeley.
# The core projects and autograders were primarily created by John DeNero
# (denero@cs.berkeley.edu) and Dan Klein (klein@cs.berkeley.edu).

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# multiAgents.py
# --------------
# Licensing Information:  You are free to use or extend these projects for
# educational purposes provided that (1) you do not distribute or publish
# solutions, (2) you retain this notice, and (3) you provide clear
# attribution to UC Berkeley, including a link to http://ai.berkeley.edu.
# 
# Attribution Information: The Pacman AI projects were developed at UC Berkeley.
# The core projects and autograders were primarily created by John DeNero
# (denero@cs.berkeley.edu) and Dan Klein (klein@cs.berkeley.edu).

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# multiAgents.py
# --------------
# Licensing Information:  You are free to use or extend these projects for
# educational purposes provided that (1) you do not distribute or publish
# solutions, (2) you retain this notice, and (3) you provide clear
# attribution to UC Berkeley, including a link to http://ai.berkeley.edu.
# 
# Attribution Information: The Pacman AI projects were developed at UC Berkeley.
# The core projects and autograders were primarily created by John DeNero
# (denero@cs.berkeley.edu) and Dan Klein (klein@cs.berkeley.edu).

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model = Model()
with model:
  beta = Uniform('beta', lower=-10, upper=10, shape=(1, n_predictors))
  
  p = tinvlogit(sum(beta * predictors, 1))
  Y_obs = Bernoulli('Y_obs', p=p, observed=Y)
  
  start = find_MAP()
  step = NUTS(scaling=start)
  trace = sample(mcmc_training_sample_size, step, start)