crntaylor

  We only had 23 years of Python interpreter development,
  how would things look like when Python is 42, like C?

    1 / (10^n - 2) = 1/10^n * 1/(1 - 2/10^n)
                   = 1/10^n * (1 + 2/10^n + 2^2 /10^2n + 2^3 /10^3n + ...)

    2^k > 10^n   =>   k > n log(10) / log(2)

    x / (1 - x)^2 = x + 2x^2 + 3x^3 + 4x^4 + ...

    1/10^n + 2/10^2n + 3/10^3n + ...

    1 / 998001 = 0.000 001 002 003 004 005 006 007...

    1000 / 997002999 = 0.000 001 003 006 010 015 021 ...

    1 / 998999 = 0.000 001 001 002 003 005 008 013 021 ...

    1001000 / 997002999 = 0.001 004 009 016 025 036 049 ...

  more (portable and secure)

  (more portable) and secure

  sqrt n = loop x0 x1
   where
    loop x y = if converged x y
      then y
      else loop y (0.5 * (y + n/y))
    converged x y = abs (x/y - 1) < 1e-10
    x0 = 1.0;
    x1 = 0.5 * (1.0 + 1.0/n)

  sqrtGuesses n = go 1.0
   where
    go x = x : go (0.5 * (x + n/x))

   converge (x:y:rest) = if abs (x/y - 1) < 1e-10
     then y
     else converge (y:rest)

   sqrt n = converge (sqrtGuesses n)

  Actor–network theory is an approach to social theory and
  research, originating in the field of science studies, which treats
  objects as part of social networks. It can technically be described
  as a "material-semiotic" method. This means that it maps relations
  that are simultaneously material (between things) and semiotic 
  (between concepts). It assumes that many relations are both 
  material and semiotic.

  Broadly speaking, ANT is a constructivist approach in that it 
  avoids essentialist explanations of events or innovations (e.g. 
  explaining a successful theory by understanding the combinations 
  and interactions of elements that make it successful, rather than 
  saying it is “true” and the others are “false”). However, it is 
  distinguished from many other STS and sociological network theories 
  for its distinct material-semiotic approach.

  solve = do
    coin   <- choose (999/1000) fair biased
    tosses <- replicateM 10 coin
    condition (tosses == replicate 10 Head)
    nextToss <- coin
    return nextToss
   where
    fair   = choose (1/2) Head Tail
    biased = certainly Head