Simple Merkle tree implementation.

MerkleTree.py

from hashlib import md5

def groupn(lst, n):
  return [lst[i:i+n] for i in range(0, len(lst), n)]


class Node(object):
  def __init__(self, _hash):
    self._hash = _hash
    self.childrens = []
  
  def hash(self):
    return self._hash

class Leaf(object):
  def __init__(self, data):
    self.data = data
  
  def hash(self):
    _hash = md5()
    _hash.update(self.data.encode('utf-8'))
    return _hash.hexdigest()


def merge_build(nodes):
  if len(nodes) == 1:
    return nodes[0]
  
  result_nodes = []
  has_even_nodes = len(nodes) % 2 == 0
  remaining_nodes = []

  if not has_even_nodes:
    remaining_nodes.append(nodes.pop())
  
  for n1, n2 in groupn(nodes, 2):
    result_hash = md5()
    h1 = n1.hash()
    h2 = n2.hash()
    result_hash.update(h1.encode('utf-8'))
    result_hash.update(h2.encode('utf-8'))
    hash_str = result_hash.hexdigest()
    pnode = Node(hash_str)
    pnode.childrens = [n1, n2]
    result_nodes.append(pnode)
  
  for n1 in remaining_nodes:
    result_hash = md5()
    result_hash.update(n1.hash().encode('utf-8'))
    hash_str = result_hash.hexdigest()
    pnode = Node(hash_str)
    pnode.childrens = [n1]
    result_nodes.append(pnode)
  return merge_build(result_nodes)


class MerkleTree(object):

  def __init__(self, tree):
    self.tree = tree

  @classmethod
  def build_from(cls, leafs):
    leaf_nodes = []
    for leaf in leafs:
      leaf_nodes.append(Leaf(leaf))
    root = merge_build(leaf_nodes)
    return cls(root)



merkle = MerkleTree.build_from(["a", "b", "c", "d", "e"])
print(merkle.tree.hash())