slides/keyword-break.html

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  47
  48 # Breaking keyword ciphers
  49
  50 a | b | c | d | e | f | g | h | i | j | k | l | m | n | o | p | q | r | s | t | u | v | w | x | y | z
  51 --|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|--
  52 k | e | y | w | o | r | d | a | b | c | f | g | h | i | j | l | m | n | p | q | s | t | u | v | x | z
  53
  54 ---
  55
  56 # Duplicate and extend your `affine_break()` function
  57
  58 * How to cycle through all the keys? What _are_ all the keys?
  59
  60 * Look at `words.txt`
  61
  62 ---
  63
  64 # Test it.
  65
  66 * `2013/4a.ciphertext`
  67 * `2013/4b.ciphertext`
  68
  69 This will take a while. Fire up a system monitor. What's wrong?
  70
  71 ---
  72
  73 # Python, threads, and the GIL
  74
  75 Thread-safe shared-memory code is hard.
  76
  77 Python's Global Interpreter Lock prevents shooting yourself in the foot.
  78
  79 Where you want true parallelism, need different threads (Python processes).
  80 * Thread-safe shared-memory code is hard.
  81
  82 The `multiprocessing` library makes this easier.
  83
  84 But before we get there, a couple of diversions...
  85
  86 ---
  87
  88 # map()
  89
  90 A common task is to apply a function to each item in a sequence, returning a sequence of the results.
  91
  92 ```python
  93 def double(x):
  94     return x * 2
  95
  96 >>> map(double, [1,2,3])
  97 [2,4,6]
  98 ```
  99
 100 * `map()` is a higher-order function: its first argument is the function that's applied.
 101
 102 How can we use this for keyword cipher breaking?
 103
 104 ---
 105
 106 # Mapping keyword decipherings
 107
 108 Define a function that takes a possible key (keyword and cipher type) and returns the key and its fitness.
 109
 110 * (Also pass in the message and the fitness function)
 111
 112 Use `map()` and `max()` to find the best key
 113
 114 ---
 115
 116 # Arity of print()
 117
 118 How many arguments does this take?
 119
 120 How do you write a function that takes this many arguments?
 121
 122 ---
 123
 124 # Function arguments
 125
 126 ## Positional, keyword
 127
 128 * Common or garden parameters, as you're used to.
 129 * `def keyword_encipher(message, keyword, wrap_alphabet=0):`
 130
 131 ## Excess positional
 132 * `def mean(x, *xs):`
 133
 134 First number goes in `x`, remaining go in the tuple `xs`
 135
 136 ## Excess keyword
 137
 138 * `def myfunc(arg1=0, **kwargs):`
 139
 140 `kwargs` will be a Dict of the remaining keywords (not `arg1`)
 141
 142 ---
 143
 144 # Back to `multiprocessing`
 145
 146 What does `Pool.starmap()` do?
 147
 148 ---
 149
 150 ```python
 151 from multiprocessing import Pool
 152
 153 def keyword_break_mp(message, wordlist=keywords, fitness=Pletters, chunksize=500):
 154     helper_args = [??? for word in wordlist] # One tuple for each possible key
 155     with Pool() as pool:
 156         breaks = pool.starmap(keyword_break_worker, helper_args, chunksize)
 157         return max(breaks, key=lambda k: k[1])
 158
 159 def keyword_break_worker(???):
 160     ???
 161     return (key, fitness)
 162 ```
 163
 164 * Gotcha: the function in `Pool.starmap()` must be defined at the top level
 165     * This is definitely a "feature"
 166
 167 ---
 168
 169 # Performance and chunksize
 170
 171 Try the multiprocessing keyword break. Is it using all the resources?
 172
 173 Setting `chunksize` is an art.
 174
 175 ## Map-reduce as a general pattern for multiprocessing
 176
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