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Algorithms & data structures

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

4 matches
Algorithms & data structures medium

Find Longest Consecutive Sequence in Python

Find the length of the longest consecutive elements sequence in an unsorted array using a set for O(n) lookups.

set longest-sequence hash-table
Python
def longest_consecutive_length(nums):
    num_set = set(nums)
    longest = 0
    
    for num in num_set:
        if num - 1 not in num_set:
            current = num
            current_streak = 1
            
            while current + 1 in num_set:
                current += 1
                current_streak += 1
…
13 0 Open
Algorithms & data structures medium

How to Decode a String with Repeated Brackets in Python

Decodes strings with patterns like '3[a]2[bc]' by using a stack to handle nested and repeated bracket groups.

stack string-decoding algorithms
Python
def decode_string(s: str) -> str:
    stack = []
    current_num = 0
    current_str = ""

    for ch in s:
        if ch.isdigit():
            current_num = current_num * 10 + int(ch)
        elif ch == "[":
            stack.append((current_str, current_num))
            current_str = ""
            current_num = 0…
13 0 Open
Algorithms & data structures medium

How to Find Minimum Swaps to Sort an Array in Python

Calculate the minimum number of adjacent-free swaps needed to sort a permutation array using cycle detection in Python.

sorting cycles greedy
Python
def min_swaps_to_sort(arr):
    n = len(arr)
    arr_pos = sorted((val, idx) for idx, val in enumerate(arr))
    visited = [False] * n
    swaps = 0

    for i in range(n):
        if visited[i] or arr_pos[i][1] == i:
            continue

        cycle_size = 0
        j = i
        while not visited[j]:
            …
13 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

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