Powers of ten

Exponentiation can be useful in Hexagony, and powers of ten are particularly nice since multiplying a cell by ten can be accomplished by just using the 0 operator on the cell. Here is an exponentiation "subroutines" that can be called from the main IP with ], multiplying one cell adjacent to the cell it is called on n by 10**n:

        . . . . . / $ >
       . . . . . . > < $
      . . . . . . \ [ / .
     . . . . . . . . . . .
    . . . . . . . . . . . .
   . . . . . . . . . . . . .
  . . . . . . . . . . . . . .
 } 0 . \ . . . . . . . . . . .
  ( ' < . . . . . . . . . . .
   . . . . . . . . . . . . .
    . . . . . . . . . . . .
     . . . . . . . . . . .
      . . . . . . . . . .
       . . . . . . . . .
        . . . . . . . .

It can also become 100**n by adding an extra zero in the empty slot.

Data Structures

Like brainfuck, Hexagony is a registerless language where all data structures have to be built into memory from scratch. However, in contrast to brainfuck, moving through memory is arguably even more cumbersome, and cells can store arbitrarily large integers. Because of this, it is often feasible to store entire data structures in a single cell. Here is an example in Python 3 of what creating a stack stored entirely inside a single integer might look like.

class HexagonyStack:
 def __init__(self, size = 256):
  self.stack    = 0
  self.cellSize = size

 def push(self, val):
  self.stack = self.stack * self.cellSize + val 

 def pop(self):
  temp = self.stack % self.cellSize
  self.stack //= self.cellSize
  return temp

 def peek(self, index):     
  return self.stack // (self.cellSize ** index) % self.cellSize

HXS = HexagonyStack(100)
HXS.push(20)
HXS.push(30)
print(HXS.peek(1)) # 20
print(HXS.pop())   # 30
print(HXS.pop())   # 20
print(HXS.pop())   # 0

It is notable that this type of stack by default has an infinite number of zeroes at the bottom.

Cell sizes that are powers of ten are often the best for golf since multiplication by ten takes a single operator, and powers of two seem to aid performance.

Although data stored like this takes some math just to interface with it, it may often still be shorter than trying to manage the data pointer across a complex memory structure.

Wiki: Hexagony

Powers of ten

Data Structures