To begin with, this question is not a dup of this one, but builds on it.
Taking the tree in that question as an example,
1
/ \\
2 3
/
Sounds like breadth-first traversal to me.
Breadth-first traversal is implemented with a queue. Here, simply insert in the queue a special token that indicate that a newline must be printed. Each time the token is found, print a newline and re-insert the token in the queue (at the end -- that's the definition of a queue).
Start the algorithm with a queue containing the root followed by the special newline token.
Just build one level at a time, e.g.:
class Node(object):
def __init__(self, value, left=None, right=None):
self.value = value
self.left = left
self.right = right
def traverse(rootnode):
thislevel = [rootnode]
while thislevel:
nextlevel = list()
for n in thislevel:
print n.value,
if n.left: nextlevel.append(n.left)
if n.right: nextlevel.append(n.right)
print
thislevel = nextlevel
t = Node(1, Node(2, Node(4, Node(7))), Node(3, Node(5), Node(6)))
traverse(t)
Edit: if you're keen to get a small saving in maximum consumed "auxiliary" memory (never having simultaneously all this level and the next level in such "auxiliary" memory), you can of course use collection.deque
instead of list
, and consume the current level as you go (via popleft
) instead of simply looping. The idea of creating one level at a time (as you consume --or iterate on-- the previous one) remains intact -- when you do need to distinguish levels, it's just more direct than using a single big deque plus auxiliary information (such as depth, or number of nodes remaining in a given level).
However, a list that is only appended to (and looped on, rather than "consumed") is quite a bit more efficient than a deque (and if you're after C++ solutions, quite similarly, a std::vector using just push_back
for building it, and a loop for then using it, is more efficient than a std::deque). Since all the producing happens first, then all the iteration (or consuming), an interesting alternative if memory is tightly constrained might be to use a list anyway to represent each level, then .reverse
it before you start consuming it (with .pop
calls) -- I don't have large trees around to check by measurement, but I suspect that this approach would still be faster (and actually less memory-consuming) than deque
(assuming that the underlying implementation of list [[or std::vector]] actually does recycle memory after a few calls to pop
[[or pop_back
]] -- and with the same assumption for deque, of course;-).
For those who are simply interested in visualizing binary trees (and not so much in the theory behind breadth-first search), there is a show
function in the binarytree package. Applied to the example given in the question,
from binarytree import Node, show
root = Node(1)
root.left = Node(2)
root.right = Node(3)
root.left.left = Node(4)
root.right.left = Node(5)
root.right.right = Node(6)
show(root)
which prints
1
/ \
2 3
/ / \
4 5 6