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Algorithms & data structures

Classic patterns — search, sort, stacks, queues, and practical complexity-aware code.

4 matches
Algorithms & data structures easy

Extract n largest elements from a large list using heapq

Uses heapq.nlargest to efficiently extract the top n largest numbers from a large list, even with millions of elements.

heapq heaps large-data
Python
import heapq
import random

def n_largest(numbers, n):
    """Return the n largest numbers from a list using heapq."""
    if n <= 0:
        return []
    return heapq.nlargest(n, numbers)

if __name__ == "__main__":
    # Create a large list with 1,000,000 random numbers
    large_list = [random.randint(1, 1_000_000…
14 0 Open
Algorithms & data structures medium

How to Find the n Smallest Items in a Large List with heapq in Python

This code demonstrates how to efficiently extract the n smallest items from a large list using Python's heapq module and a manual max-heap approach.

heapq heaps large data
Python
import heapq

def n_smallest_iterable(data, n):
    """Return the n smallest items without loading the whole list."""
    if n <= 0:
        return []
    return heapq.nsmallest(n, data)

def n_smallest_manual(data, n):
    """Return the n smallest using a heap, O(n log k) time."""
    if n <= 0:
        return []
   …
13 0 Open
Algorithms & data structures easy

How to Heapify a List into a Min Heap with heapq in Python

Convert any list into a valid min heap in-place using Python's heapq.heapify(), then pop the smallest element to verify heap order.

heapq min heap heapify
Python
import heapq

data = [5, 3, 8, 1, 9, 2, 7, 4, 6]
print("Original list:", data)

heapq.heapify(data)
print("Min heap:", data)

popped = heapq.heappop(data)
print("Smallest element popped:", popped)
print("Heap after pop:", data)
14 0 Open
Algorithms & data structures medium

Merge k sorted lists in Python using a heap

Merge k individually sorted lists into one sorted list in Python using a min-heap.

heapq merge sorted-list
Python
import heapq

def merge_k_sorted_lists(lists):
    heap = []
    # Push the first element of each list onto the heap
    for i, lst in enumerate(lists):
        if lst:
            heapq.heappush(heap, (lst[0], i, 0))
    
    result = []
    while heap:
        val, list_idx, elem_idx = heapq.heappop(heap)
        re…
15 0 Open

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