Algorithms & data structures
Classic patterns — search, sort, stacks, queues, and practical complexity-aware code.
Binary Search on Answer in Python: Koko Eating Bananas
Find the minimum eating speed so Koko finishes all banana piles within a given hour limit using binary search on the answer.
import math
def min_eating_speed(piles, h):
"""Return minimum integer eating speed K so Koko finishes within h hours."""
def hours_needed(speed):
return sum(math.ceil(p / speed) for p in piles)
low, high = 1, max(piles)
while low < high:
mid = (low + high) // 2
if hours_needed…Drop Elements From Start While Condition Is True in Python
This generator function drops elements from the beginning of an iterable while a predicate returns true, then yields the rest.
def drop_while(predicate, iterable):
"""Drop elements from the start while predicate is true."""
it = iter(iterable)
for item in it:
if not predicate(item):
yield item
break
yield from it
if __name__ == "__main__":
numbers = [1, 2, 3, 4, 1, 2, 5]
result = list(d…Find Elements Appearing More Than n/3 Times in Python
Return all elements that occur more than len(array)/3 times using a simple dictionary counter.
def majority_third(arr):
"""Return elements appearing more than len(arr)/3 times."""
cutoff = len(arr) / 3
counts = {}
for x in arr:
counts[x] = counts.get(x, 0) + 1
return [x for x, c in counts.items() if c > cutoff]
if __name__ == "__main__":
test1 = [3, 2, 3]
test2 = [1, 1, 1, …Find Maximum Distance Between Identical Elements in Python
Compute the maximum index distance between any two identical elements in a list using a dictionary to track first occurrences.
from collections import defaultdict
def max_distance_between_identical(nums):
first_occurrence = {}
max_dist = 0
for i, num in enumerate(nums):
if num in first_occurrence:
dist = i - first_occurrence[num]
max_dist = max(max_dist, dist)
else:
first_occur…Find Median of Two Sorted Arrays in Python
Merges two sorted arrays with a two-pointer walk and returns the median of the combined sorted sequence.
def median_of_two_sorted_arrays(nums1, nums2):
merged = []
i = j = 0
while i < len(nums1) and j < len(nums2):
if nums1[i] <= nums2[j]:
merged.append(nums1[i])
i += 1
else:
merged.append(nums2[j])
j += 1
merged.extend(nums1[i:])
merged.…Find Missing Number in Python Sequence 1 to N
Find the missing number from a list containing numbers 1 to N using the arithmetic sum formula.
def find_missing_number(nums, n):
expected_sum = n * (n + 1) // 2
actual_sum = sum(nums)
return expected_sum - actual_sum
if __name__ == "__main__":
n = 10
numbers = [1, 2, 3, 4, 5, 6, 7, 9, 10]
missing = find_missing_number(numbers, n)
print(f"The missing number is: {missing}")Find Missing Numbers, Duplicates, and Ranges in Python
Analyze a list to identify missing numbers, duplicate values, and contiguous ranges using sets and the Counter class.
def find_missing_duplicates_ranges(numbers):
"""Find missing numbers, duplicates, and ranges in a list."""
from collections import Counter
if not numbers:
return {"missing": [], "duplicates": [], "ranges": []}
full_range = set(range(min(numbers), max(numbers) + 1))
present = set(n…Find the Duplicate Number in Python Using Floyd's Cycle Detection
Detects the duplicate integer in an array of n+1 numbers (values 1 to n) in O(n) time and O(1) space using Floyd's cycle detection algorithm applied to a linked-list model.
def find_duplicate(nums):
slow = nums[0]
fast = nums[0]
# Phase 1: Find intersection point of the cycle
while True:
slow = nums[slow]
fast = nums[nums[fast]]
if slow == fast:
break
# Phase 2: Find the start of the cycle (the duplicate)
slow = nums[0…Find the Last Index Where a Condition Is True in Python
This code scans a sequence from the end and returns the index of the last element that satisfies a given condition, or -1 if none do.
def last_index_where(sequence, condition):
"""Return the index of the last element in sequence that satisfies condition."""
for i in range(len(sequence) - 1, -1, -1):
if condition(sequence[i]):
return i
return -1
if __name__ == "__main__":
numbers = [1, 4, 7, 2, 9, 5, 8, 3]
is_…Game of Life Next State Grid in Python
Compute the next generation of Conway's Game of Life from a 2D grid using the standard three rules with neighbor counting.
def next_state(grid):
m, n = len(grid), len(grid[0])
new = [[0] * n for _ in range(m)]
for r in range(m):
for c in range(n):
total = 0
for dr in (-1, 0, 1):
for dc in (-1, 0, 1):
if dr == 0 and dc == 0:
continue
…Generate Pascal's Triangle Rows in Python
Builds Pascal's triangle as a list of rows, where each inner value is the sum of the two values above it.
def generate_pascals_triangle(rows):
triangle = []
for row_num in range(rows):
row = [1] * (row_num + 1)
for col in range(1, row_num):
row[col] = triangle[row_num - 1][col - 1] + triangle[row_num - 1][col]
triangle.append(row)
return triangle
if __name__ == "__main__":
…How to Apply a Function to Sliding Window Slices in Python
This Python code applies a given function to every contiguous window of a specified size in a list, returning a list of results.
def apply_to_sliding_windows(data, window_size, func):
return [func(data[i:i + window_size]) for i in range(len(data) - window_size + 1)]
if __name__ == "__main__":
numbers = [1, 2, 3, 4, 5, 6]
window_size = 3
results = apply_to_sliding_windows(numbers, window_size, sum)
print(results)
results…How to Compute Jaccard Similarity in Python
Compute the Jaccard similarity between two lists by converting them to sets and dividing the intersection size by the union size.
def jaccard_similarity(list1, list2):
set1 = set(list1)
set2 = set(list2)
intersection = set1 & set2
union = set1 | set2
if not union:
return 0.0
return len(intersection) / len(union)
if __name__ == "__main__":
a = [1, 2, 3, 4, 5]
b = [3, 4, 5, 6, 7]
pri…How to Count Distinct Elements in a List in Python
Count the number of unique items in a list by converting it to a set and returning its length.
def count_distinct_elements(items):
return len(set(items))
if __name__ == "__main__":
sample = [1, 2, 3, 2, 1, 4, 3, 5, 4, 6]
result = count_distinct_elements(sample)
print(result)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.
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…How to Evaluate RPN Expressions in Python
Use a stack to evaluate Reverse Polish Notation token lists with a dictionary of operator lambdas, truncating division toward zero.
def eval_rpn(tokens):
stack = []
ops = {
'+': lambda a, b: a + b,
'-': lambda a, b: a - b,
'*': lambda a, b: a * b,
'/': lambda a, b: int(a / b) # truncate toward zero
}
for token in tokens:
if token in ops:
b = stack.pop()
a = stack.pop(…How to Generate a Geometric Progression List in Python
This Python function builds a list of n terms in a geometric progression, starting with a given first term and multiplying by a constant ratio at each step.
def geometric_progression(first_term, ratio, count):
"""
Generate a list of 'count' terms in a geometric progression
starting with 'first_term' and multiplied by 'ratio' each step.
"""
progression = []
current = first_term
for _ in range(count):
progression.append(current)
c…How to Generate a Power Set in Python with Bitmasks
Generate the power set of a small list using a bitmask approach, producing all possible subsets.
def power_set(items):
"""Generate the power set of a list using bitmask approach."""
n = len(items)
result = []
for mask in range(1 << n):
subset = []
for i in range(n):
if mask & (1 << i):
subset.append(items[i])
result.append(subset)
r…How to Get All Combinations of a List in Python
Generate and display all combinations of a given length from a list using Python's itertools.combinations.
from itertools import combinations
def list_combinations(items, r):
"""Return all combinations of length r from a list."""
return list(combinations(items, r))
if __name__ == "__main__":
fruits = ["apple", "banana", "cherry", "date"]
pick = 2
result = list_combinations(fruits, pick)
print…How to Implement a Moving Average from a Data Stream in Python
Implement a MovingAverage class using a deque and running sum to compute the average of the last k values from a continuous data stream.
from collections import deque
class MovingAverage:
def __init__(self, size):
self.size = size
self.queue = deque()
self.window_sum = 0
def next(self, val):
self.queue.append(val)
self.window_sum += val
if len(self.queue) > self.size:
self.window_su…How to Implement a Recent Counter with a Deque in Python
Implements a RecentCounter class that uses a deque to count ping requests within the last 3000 milliseconds.
from collections import deque
import time
class RecentCounter:
def __init__(self):
self.hits = deque()
def ping(self, t: int) -> int:
self.hits.append(t)
while self.hits and self.hits[0] < t - 3000:
self.hits.popleft()
return len(self.hits)
if __name__ == "__mai…How to Remove Duplicates in Python Preserving Order
Removes duplicate items from a list while keeping the first occurrence order intact using a set for fast membership checks.
def remove_duplicates_preserving_order(items):
seen = set()
result = []
for item in items:
if item not in seen:
seen.add(item)
result.append(item)
return result
if __name__ == "__main__":
sample = [3, 1, 2, 1, 3, 4, 2, 5]
unique_items = remove_duplicates_preserv…How to Rotate an Array by k Steps in Python
This code rotates a list to the right by k positions using modulo arithmetic to handle k larger than the list length.
def rotate_array(nums, k):
if not nums:
return []
n = len(nums)
k = k % n
return nums[-k:] + nums[:-k] if k else nums[:]
if __name__ == "__main__":
arr = [1, 2, 3, 4, 5, 6]
k = 2
result = rotate_array(arr, k)
print(f"Original: {arr}")
print(f"Rotated by {k}: {result}")How to Sample Random Items Without Replacement in Python
Select k random unique items from a sequence using random.sample for uniform, non-repeating selection.
import random
def sample_without_replacement(population, k):
"""Return k random items from population without replacement."""
if k > len(population):
raise ValueError("k cannot exceed population size")
# Use random.sample for O(k) time, no mutation of the original
return random.sample(populati…Browse by section
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