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18 changes: 14 additions & 4 deletions heaps/heap_sort.py
Original file line number Diff line number Diff line change
@@ -1,8 +1,18 @@

from heaps.min_heap import MinHeap

def heap_sort(list):
""" This method uses a heap to sort an array.
Time Complexity: ?
Space Complexity: ?
Time Complexity: O(n log n)
Space Complexity: O(n)
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"""
pass

heap = MinHeap()
for element in list:
heap.add(element)

index = 0
while not heap.empty():
list[index] = heap.remove()
index += 1

return list
82 changes: 62 additions & 20 deletions heaps/min_heap.py
Original file line number Diff line number Diff line change
@@ -1,5 +1,5 @@
class HeapNode:

def __init__(self, key, value):
self.key = key
self.value = value
Expand All @@ -15,39 +15,63 @@ class MinHeap:
def __init__(self):
self.store = []

# helpers
def parent_index(self, index):
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💖 Love these!

return (index - 1) // 2

def left_child_index(self, index):
return (2 * index) + 1

def right_child_index(self, index):
return (2 * index) + 2


def add(self, key, value = None):
""" This method adds a HeapNode instance to the heap
If value == None the new node's value should be set to key
Time Complexity: ?
Space Complexity: ?
Time Complexity: O(log n)
Space Complexity: O(1)
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✨ Because of the recursive call stack of heap_up, space complexity is O(log n)

"""
pass

if value is None:
value = key

new_node = HeapNode(key, value)
self.store.append(new_node)
self.heap_up(len(self.store) - 1)


def remove(self):
""" This method removes and returns an element from the heap
maintaining the heap structure
Time Complexity: ?
Space Complexity: ?
Time Complexity: O(log n)
Space Complexity: O(1)
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✨ Because of the recursive call stack of heap_down space complexity is O(log n)

"""
pass

if len(self.store) == 0:
return

self.swap(0, len(self.store) - 1)
min = self.store.pop()
self.heap_down(0)

return min.value



def __str__(self):
""" This method lets you print the heap, when you're testing your app.
"""
""" This method lets you print the heap, when you're testing your app."""

if len(self.store) == 0:
return "[]"
return f"[{', '.join([str(element) for element in self.store])}]"


def empty(self):
""" This method returns true if the heap is empty
Time complexity: ?
Space complexity: ?
Time complexity: O(1)
Space complexity: O(1)
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"""
pass
return len(self.store) == 0


def heap_up(self, index):
Expand All @@ -57,25 +81,43 @@ def heap_up(self, index):
property is reestablished.

This could be **very** helpful for the add method.
Time complexity: ?
Space complexity: ?
Time complexity: O(log n)
Space complexity: O(1)
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✨ However because of the recursive call stack, space complexity is O(log n)

"""
pass

if index == 0:
return

if self.store[self.parent_index(index)].key > self.store[index].key:
self.swap(self.parent_index(index), index)
self.heap_up(self.parent_index(index))


def heap_down(self, index):
""" This helper method takes an index and
moves the corresponding element down the heap if it's
larger than either of its children and continues until
the heap property is reestablished.
"""
pass

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if self.left_child_index(index) < len(self.store):
if self.right_child_index(index) < len(self.store):
if self.store[self.left_child_index(index)].key < self.store[self.right_child_index(index)].key:
smaller_node = self.left_child_index(index)
else:
smaller_node = self.right_child_index(index)
else:
smaller_node = self.left_child_index(index)
if self.store[index].key > self.store[smaller_node].key:
self.swap(index, smaller_node)
self.heap_down(smaller_node)


def swap(self, index_1, index_2):
""" Swaps two elements in self.store
at index_1 and index_2
used for heap_up & heap_down
"""
temp = self.store[index_1]
self.store[index_1] = self.store[index_2]
self.store[index_2] = temp

self.store[index_1], self.store[index_2] = self.store[index_2], self.store[index_1]
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💫 Very concise