Python/data_structures/heap/heap.py

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from __future__ import annotations
from abc import abstractmethod
from collections.abc import Iterable
from typing import Generic, Protocol, TypeVar
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class Comparable(Protocol):
@abstractmethod
def __lt__(self: T, other: T) -> bool:
pass
@abstractmethod
def __gt__(self: T, other: T) -> bool:
pass
@abstractmethod
def __eq__(self: T, other: object) -> bool:
pass
T = TypeVar("T", bound=Comparable)
class Heap(Generic[T]):
"""A Max Heap Implementation
>>> unsorted = [103, 9, 1, 7, 11, 15, 25, 201, 209, 107, 5]
>>> h = Heap()
>>> h.build_max_heap(unsorted)
>>> h
[209, 201, 25, 103, 107, 15, 1, 9, 7, 11, 5]
>>>
>>> h.extract_max()
209
>>> h
[201, 107, 25, 103, 11, 15, 1, 9, 7, 5]
>>>
>>> h.insert(100)
>>> h
[201, 107, 25, 103, 100, 15, 1, 9, 7, 5, 11]
>>>
>>> h.heap_sort()
>>> h
[1, 5, 7, 9, 11, 15, 25, 100, 103, 107, 201]
"""
def __init__(self) -> None:
self.h: list[T] = []
self.heap_size: int = 0
def __repr__(self) -> str:
return str(self.h)
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def parent_index(self, child_idx: int) -> int | None:
"""return the parent index of given child"""
if child_idx > 0:
return (child_idx - 1) // 2
return None
def left_child_idx(self, parent_idx: int) -> int | None:
"""
return the left child index if the left child exists.
if not, return None.
"""
left_child_index = 2 * parent_idx + 1
if left_child_index < self.heap_size:
return left_child_index
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return None
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def right_child_idx(self, parent_idx: int) -> int | None:
"""
return the right child index if the right child exists.
if not, return None.
"""
right_child_index = 2 * parent_idx + 2
if right_child_index < self.heap_size:
return right_child_index
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return None
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def max_heapify(self, index: int) -> None:
"""
correct a single violation of the heap property in a subtree's root.
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It is the function that is responsible for restoring the property
of Max heap i.e the maximum element is always at top.
"""
if index < self.heap_size:
violation: int = index
left_child = self.left_child_idx(index)
right_child = self.right_child_idx(index)
# check which child is larger than its parent
if left_child is not None and self.h[left_child] > self.h[violation]:
violation = left_child
if right_child is not None and self.h[right_child] > self.h[violation]:
violation = right_child
# if violation indeed exists
if violation != index:
# swap to fix the violation
self.h[violation], self.h[index] = self.h[index], self.h[violation]
# fix the subsequent violation recursively if any
self.max_heapify(violation)
def build_max_heap(self, collection: Iterable[T]) -> None:
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"""
build max heap from an unsorted array
>>> h = Heap()
>>> h.build_max_heap([20,40,50,20,10])
>>> h
[50, 40, 20, 20, 10]
>>> h = Heap()
>>> h.build_max_heap([1,2,3,4,5,6,7,8,9,0])
>>> h
[9, 8, 7, 4, 5, 6, 3, 2, 1, 0]
>>> h = Heap()
>>> h.build_max_heap([514,5,61,57,8,99,105])
>>> h
[514, 57, 105, 5, 8, 99, 61]
>>> h = Heap()
>>> h.build_max_heap([514,5,61.6,57,8,9.9,105])
>>> h
[514, 57, 105, 5, 8, 9.9, 61.6]
"""
self.h = list(collection)
self.heap_size = len(self.h)
if self.heap_size > 1:
# max_heapify from right to left but exclude leaves (last level)
for i in range(self.heap_size // 2 - 1, -1, -1):
self.max_heapify(i)
def extract_max(self) -> T:
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"""
get and remove max from heap
>>> h = Heap()
>>> h.build_max_heap([20,40,50,20,10])
>>> h.extract_max()
50
>>> h = Heap()
>>> h.build_max_heap([514,5,61,57,8,99,105])
>>> h.extract_max()
514
>>> h = Heap()
>>> h.build_max_heap([1,2,3,4,5,6,7,8,9,0])
>>> h.extract_max()
9
"""
if self.heap_size >= 2:
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me = self.h[0]
self.h[0] = self.h.pop(-1)
self.heap_size -= 1
self.max_heapify(0)
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return me
elif self.heap_size == 1:
self.heap_size -= 1
return self.h.pop(-1)
else:
raise Exception("Empty heap")
def insert(self, value: T) -> None:
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"""
insert a new value into the max heap
>>> h = Heap()
>>> h.insert(10)
>>> h
[10]
>>> h = Heap()
>>> h.insert(10)
>>> h.insert(10)
>>> h
[10, 10]
>>> h = Heap()
>>> h.insert(10)
>>> h.insert(10.1)
>>> h
[10.1, 10]
>>> h = Heap()
>>> h.insert(0.1)
>>> h.insert(0)
>>> h.insert(9)
>>> h.insert(5)
>>> h
[9, 5, 0.1, 0]
"""
self.h.append(value)
idx = (self.heap_size - 1) // 2
self.heap_size += 1
while idx >= 0:
self.max_heapify(idx)
idx = (idx - 1) // 2
def heap_sort(self) -> None:
size = self.heap_size
for j in range(size - 1, 0, -1):
self.h[0], self.h[j] = self.h[j], self.h[0]
self.heap_size -= 1
self.max_heapify(0)
self.heap_size = size
if __name__ == "__main__":
import doctest
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# run doc test
doctest.testmod()
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# demo
for unsorted in [
[0],
[2],
[3, 5],
[5, 3],
[5, 5],
[0, 0, 0, 0],
[1, 1, 1, 1],
[2, 2, 3, 5],
[0, 2, 2, 3, 5],
[2, 5, 3, 0, 2, 3, 0, 3],
[6, 1, 2, 7, 9, 3, 4, 5, 10, 8],
[103, 9, 1, 7, 11, 15, 25, 201, 209, 107, 5],
[-45, -2, -5],
]:
print(f"unsorted array: {unsorted}")
heap: Heap[int] = Heap()
heap.build_max_heap(unsorted)
print(f"after build heap: {heap}")
print(f"max value: {heap.extract_max()}")
print(f"after max value removed: {heap}")
heap.insert(100)
print(f"after new value 100 inserted: {heap}")
heap.heap_sort()
print(f"heap-sorted array: {heap}\n")