Algorithm-a-Day : Day 12 : Binary Search Tree

Our first tree structure. Hurray!
Trees are important because a lot of things are implemented with them. Not of all of them act like BS Trees, but it's easy so we're starting with it.
Also, make sure to check out the section below on how Trees are printed. This causes a lot of people trouble, and I found a good solution.

Github :: Binary Search Tree

ABOUT BINARY SEARCH TREE
------------------------
  A handy tree structure built for fast look-ups!
Our versions here today aren't self-balancing, meaning that if your root
sucks you could end up with a very lopsided tree.
Many built-in data structures in modern languages are implemented with trees,
so it's importaant to know what they are and how they work.
This included knowing how the following things are done:

-- Recursion. 
-- Queues.
-- Depth-first searches.
-- Breadth-first searches.
(But for a binary search tree we don't have to worry about those types
of searches)

ABOUT PRINTING TREE STRUCTURES
------------------------------
  This causes so much unnecessary suffering, so I created a slick recursive
way to print out tree structures opening out to the right. Each leaf gets
its own line, and everything is indented properly. It's quite easy to read. 
Check out both the py_test.py file and the C unit test to see what 
I'm talking about. 

C
-
  Here we had to introduce some new structs. Allocating memory for them is
standard run-of-the-mill stuff. Don't forget to check for NULL pointers
everywhere possible. I'll be there with an "I told you so" when a Segfault 
cracks your computer in half.
  Insertion and checking for containment is all done with recursion. These 
things can be done iteratively too, but it can get silly.
  Printing here, unlike the Python and Haskell versions, is done without
any string creation, and instead prints right in the functions itself.
  There is a **unit test** file, so make sure to check that out too.

PYTHON
------
  Shorter and sweeter than the C version, but all around the same.
Just as we've had in other Python versions of algorithms thus far, we get
to specify 'special functions' that allow us to use keywords on our Tree.
    print(tree)
    if 5 in tree: ...
    etc.
  For printing, here we're gradually building up a list of strings of the 
leaves, then concatinating it all at the end in the __str__ function.
Remember that in Python, str.join() is always better than str + str.

HASKELL
-------
  God functional programming rocks. Here we start by defining instances
of typeclasses for the Tree type, allowing us to (via Functor) map functions
across our Tree, and (via Foldable) use folds across it as well.
  While it may look a little different, the function showTree produces 
the same result as the print functions in the C and Python versions. Once
again, a victory for recursion. showTree is called by 'show', as is standard.
  Everything else is essentially the same, but with the Haskell twist.
Even so, its over half as short as the C version (and that's with all our
instance definitions included!).
  In conclusion, Haskell continues to impress me with its power of 
expressiveness.