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https://github.com/krahets/hello-algo.git
synced 2025-11-02 21:24:53 +08:00
Unify the comment style of python codes
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@ -24,7 +24,7 @@ def test_pop(heap: list, flag: int = 1) -> None:
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print_heap([flag * val for val in heap])
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""" Driver Code """
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"""Driver Code"""
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if __name__ == "__main__":
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# 初始化小顶堆
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min_heap, flag = [], 1
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@ -35,33 +35,34 @@ if __name__ == "__main__":
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# Python 的 heapq 模块默认实现小顶堆
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# 考虑将“元素取负”后再入堆,这样就可以将大小关系颠倒,从而实现大顶堆
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# 在本示例中,flag = 1 时对应小顶堆,flag = -1 时对应大顶堆
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""" 元素入堆 """
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# 元素入堆
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test_push(max_heap, 1, flag)
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test_push(max_heap, 3, flag)
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test_push(max_heap, 2, flag)
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test_push(max_heap, 5, flag)
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test_push(max_heap, 4, flag)
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""" 获取堆顶元素 """
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# 获取堆顶元素
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peek: int = flag * max_heap[0]
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print(f"\n堆顶元素为 {peek}")
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""" 堆顶元素出堆 """
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# 堆顶元素出堆
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test_pop(max_heap, flag)
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test_pop(max_heap, flag)
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test_pop(max_heap, flag)
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test_pop(max_heap, flag)
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test_pop(max_heap, flag)
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""" 获取堆大小 """
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# 获取堆大小
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size: int = len(max_heap)
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print(f"\n堆元素数量为 {size}")
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""" 判断堆是否为空 """
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# 判断堆是否为空
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is_empty: bool = not max_heap
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print(f"\n堆是否为空 {is_empty}")
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""" 输入列表并建堆 """
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# 输入列表并建堆
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# 时间复杂度为 O(n) ,而非 O(nlogn)
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min_heap: list[int] = [1, 3, 2, 5, 4]
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heapq.heapify(min_heap)
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@ -105,7 +105,7 @@ class MaxHeap:
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print_heap(self.max_heap)
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""" Driver Code """
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"""Driver Code"""
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if __name__ == "__main__":
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# 初始化大顶堆
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max_heap = MaxHeap([9, 8, 6, 6, 7, 5, 2, 1, 4, 3, 6, 2])
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