Implement exercise binary-search-tree (#773)

This commit is contained in:
Rodrigo Oliveira
2017-11-13 19:09:54 -02:00
committed by Nathan Parsons
parent 16ba6f52d1
commit f236ea1ff6
5 changed files with 218 additions and 0 deletions

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"reactive_programming" "reactive_programming"
] ]
}, },
{
"uuid": "6f196341-0ffc-9780-a7ca-1f817508247161cbcd9",
"slug": "binary-search-tree",
"core": false,
"unlocked_by": null,
"difficulty": 4,
"topics":[
"recursion",
"classes",
"trees",
"searching",
"object_oriented_programming"
]
},
{ {
"uuid": "e7351e8e-d3ff-4621-b818-cd55cf05bffd", "uuid": "e7351e8e-d3ff-4621-b818-cd55cf05bffd",
"slug": "accumulate", "slug": "accumulate",

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# Binary Search Tree
Insert and search for numbers in a binary tree.
When we need to represent sorted data, an array does not make a good
data structure.
Say we have the array `[1, 3, 4, 5]`, and we add 2 to it so it becomes
`[1, 3, 4, 5, 2]` now we must sort the entire array again! We can
improve on this by realizing that we only need to make space for the new
item `[1, nil, 3, 4, 5]`, and then adding the item in the space we
added. But this still requires us to shift many elements down by one.
Binary Search Trees, however, can operate on sorted data much more
efficiently.
A binary search tree consists of a series of connected nodes. Each node
contains a piece of data (e.g. the number 3), a variable named `left`,
and a variable named `right`. The `left` and `right` variables point at
`nil`, or other nodes. Since these other nodes in turn have other nodes
beneath them, we say that the left and right variables are pointing at
subtrees. All data in the left subtree is less than or equal to the
current node's data, and all data in the right subtree is greater than
the current node's data.
For example, if we had a node containing the data 4, and we added the
data 2, our tree would look like this:
4
/
2
If we then added 6, it would look like this:
4
/ \
2 6
If we then added 3, it would look like this
4
/ \
2 6
\
3
And if we then added 1, 5, and 7, it would look like this
4
/ \
/ \
2 6
/ \ / \
1 3 5 7
## Submitting Exercises
Note that, when trying to submit an exercise, make sure the solution is in the `exercism/python/<exerciseName>` directory.
For example, if you're submitting `bob.py` for the Bob exercise, the submit command would be something like `exercism submit <path_to_exercism_dir>/python/bob/bob.py`.
For more detailed information about running tests, code style and linting,
please see the [help page](http://exercism.io/languages/python).
## Source
Wikipedia [https://en.wikipedia.org/wiki/Binary_search_tree](https://en.wikipedia.org/wiki/Binary_search_tree)
## Submitting Incomplete Solutions
It's possible to submit an incomplete solution so you can see how others have completed the exercise.

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class TreeNode(object):
def __init__(self, value):
self.value = value
class BinarySearchTree(object):
def __init__(self):
pass
def add(self, value):
pass
def search(self, value):
pass

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import unittest
from binary_search_tree import BinarySearchTree
class BinarySearchTreeTests(unittest.TestCase):
def test_add_integer_numbers(self):
bst = BinarySearchTree()
bst.add(1)
bst.add(8)
bst.add(3)
bst.add(5)
bst.add(2)
self.assertEqual(list(bst.list()), [1, 2, 3, 5, 8])
def test_add_float_numbers(self):
bst = BinarySearchTree()
bst.add(7.5)
bst.add(5.3)
bst.add(5.5)
bst.add(6.0)
bst.add(7.7)
self.assertEqual(list(bst.list()), [5.3, 5.5, 6.0, 7.5, 7.7])
def test_add_mixed_numbers(self):
bst = BinarySearchTree()
bst.add(1)
bst.add(8)
bst.add(7.5)
bst.add(5.3)
self.assertEqual(list(bst.list()), [1, 5.3, 7.5, 8])
def test_add_duplicated_numbers(self):
bst = BinarySearchTree()
bst.add(1)
bst.add(1)
bst.add(7.5)
bst.add(5.3)
self.assertEqual(list(bst.list()), [1, 1, 5.3, 7.5])
def test_search_existent_numbers(self):
bst = BinarySearchTree()
bst.add(1)
bst.add(7.5)
self.assertEqual(bst.search(1).value, 1)
self.assertEqual(bst.search(7.5).value, 7.5)
def test_search_nonexistent_numbers(self):
bst = BinarySearchTree()
bst.add(1)
bst.add(7.5)
self.assertIs(bst.search(6), None)
self.assertIs(bst.search(8.8), None)
if __name__ == '__main__':
unittest.main()

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from collections import deque
class TreeNode(object):
def __init__(self, value):
self.value = value
self.left_node = None
self.right_node = None
def __str__(self):
return str(self.value)
class BinarySearchTree(object):
def __init__(self):
self.root = None
def add(self, value):
if(self.root is None):
self.root = TreeNode(value)
else:
inserted = False
cur_node = self.root
while not inserted:
if(value <= cur_node.value):
if(cur_node.left_node):
cur_node = cur_node.left_node
else:
cur_node.left_node = TreeNode(value)
inserted = True
elif(value > cur_node.value):
if(cur_node.right_node):
cur_node = cur_node.right_node
else:
cur_node.right_node = TreeNode(value)
inserted = True
def search(self, value):
cur_node = self.root
found = False
while not found:
if(cur_node is None):
return None
elif(value < cur_node.value):
cur_node = cur_node.left_node
elif(value > cur_node.value):
cur_node = cur_node.right_node
elif(value == cur_node.value):
return cur_node
def list(self):
elements = deque()
self.trav_inorder(self.root, elements)
return elements
def trav_inorder(self, node, elements):
if(node is not None):
self.trav_inorder(node.left_node, elements)
elements.append(node.value)
self.trav_inorder(node.right_node, elements)