Algorithms & data structures
Classic patterns — search, sort, stacks, queues, and practical complexity-aware code.
Bucket Numbers into Histogram Bin Counts in Python
Partition a list of numbers into equal-width histogram bins and count how many fall into each bin using only the Python standard library.
from collections import Counter
def histogram_bins(numbers, num_bins):
"""Bucket numbers into histogram bin counts."""
if not numbers:
return []
min_val = min(numbers)
max_val = max(numbers)
bin_width = (max_val - min_val) / num_bins
# Handle edge case where all values are id…
Count Smaller Elements to the Right in Python
Return a list where each index counts how many elements to its right are smaller than that element using a clean O(n²) nested-loop approach.
def count_smaller_elements(arr):
"""
Return a list where result[i] is the number of elements
to the right of arr[i] that are smaller than arr[i].
"""
result = []
for i in range(len(arr)):
count = 0
for j in range(i + 1, len(arr)):
if arr[j] < arr[i]:
…
How to Add Two Lists Elementwise in Python
Add two equal-length lists element by element using a list comprehension with zip, returning a new list of summed values.
def elementwise_add(list1, list2):
return [a + b for a, b in zip(list1, list2)]
if __name__ == "__main__":
list_a = [1, 2, 3, 4]
list_b = [10, 20, 30, 40]
result = elementwise_add(list_a, list_b)
print(result)
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 Build a Coordinate Grid with Nested Loops in Python
Generate a 2D list of (row, col) coordinate pairs using nested loops and return the grid structure.
def build_coordinate_grid(rows, cols):
"""Build a 2D grid of (row, col) coordinates using nested loops."""
grid = []
for r in range(rows):
row = []
for c in range(cols):
row.append((r, c))
grid.append(row)
return grid
if __name__ == "__main__":
grid = build_coo…
How to Combine filter and map with a List Comprehension in Python
This Python code demonstrates how to combine filtering and mapping in a single list comprehension and shows the equivalent filter() and map() approach.
def square(x):
return x * x
def is_even(x):
return x % 2 == 0
numbers = [1, 2, 3, 4, 5, 6, 7, 8]
result = [square(x) for x in numbers if is_even(x)]
print(f"Original numbers: {numbers}")
print(f"Squares of even numbers: {result}")
# Combined filter + map equivalent
filtered = filter(is_even, numbers)
mapp…
How to Compare Two Lists Elementwise for Greater Flags in Python
Compare two equal-length lists element by element and return a list of booleans marking where list_a values are greater than list_b values.
def compare_lists_greater(list_a, list_b):
"""
Compare two lists elementwise and return a list of booleans
indicating whether each element in list_a is greater than the
corresponding element in list_b.
"""
if len(list_a) != len(list_b):
raise ValueError("Lists must have the same length"…
How to Compute Cosine Similarity Between Two Vectors in Python
This code calculates the cosine similarity between two numeric vectors using the dot product and Euclidean norms, returning a value between -1 and 1.
import math
def cosine_similarity(vec_a, vec_b):
if len(vec_a) != len(vec_b):
raise ValueError("Vectors must have the same length")
dot_product = sum(a * b for a, b in zip(vec_a, vec_b))
norm_a = math.sqrt(sum(a * a for a in vec_a))
norm_b = math.sqrt(sum(b * b for b in vec_b))
i…
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 Compute the Cartesian Product of Two Lists in Python
Generates all ordered pairs from two lists using itertools.product and prints each combination.
from itertools import product
# Two small input lists
list_a = [1, 2, 3]
list_b = ["x", "y"]
# Compute the Cartesian product
result = list(product(list_a, list_b))
# Display the result
print("Cartesian product of", list_a, "and", list_b, "is:")
for pair in result:
print(pair)
How to Compute the Dot Product of Two Lists in Python
Compute the dot product of two equal-length numeric lists using a generator expression with zip and sum.
def dot_product(list1, list2):
"""
Compute the dot product of two numeric lists.
The lists must have the same length.
"""
if len(list1) != len(list2):
raise ValueError("Lists must have the same length")
return sum(a * b for a, b in zip(list1, list2))
if __name__ == "__main__":
…
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 Count Occurrences of Each Value in Python
Count how many times each value appears in a list using Python's Counter from the collections module.
from collections import Counter
def count_occurrences(values):
"""Return a dictionary mapping each value to its count."""
return dict(Counter(values))
if __name__ == "__main__":
sample_data = ["apple", "banana", "apple", "cherry", "banana", "apple"]
result = count_occurrences(sample_data)
print(r…
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 Detect Hardcoded Secrets in Python Source Code
A Python utility that scans source code for common hardcoded secrets like API keys, passwords, tokens, and AWS credentials using regex patterns.
import re
def detect_secrets(text):
"""Detect potential hardcoded secrets in source code."""
patterns = {
'api_key': r'(?i)(api[_-]?key|apikey)\s*[=:]\s*["\']([^"\']+)["\']',
'password': r'(?i)(password|passwd)\s*[=:]\s*["\']([^"\']+)["\']',
'token': r'(?i)(\b(token|secret)\b)\s*[=:]\s…
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 Find Four Sum Quadruplets in Python (Sorted Demo)
Find all unique quadruplets in a sorted array that sum to a target, with duplicate skipping.
def four_sum(nums, target):
nums.sort()
result = []
n = len(nums)
for i in range(n - 3):
if i > 0 and nums[i] == nums[i - 1]:
continue
for j in range(i + 1, n - 2):
if j > i + 1 and nums[j] == nums[j - 1]:
continue
left, right = j + 1…
How to Find Gaps Between Sorted Intervals in Python
This code finds gap ranges between sorted intervals using pairwise iteration, returning ranges where no interval covers.
from itertools import pairwise
def find_gaps(intervals):
intervals = sorted(intervals)
gaps = []
for prev, curr in pairwise(intervals):
if prev[1] < curr[0]:
gaps.append((prev[1] + 1, curr[0] - 1))
return gaps
if __name__ == "__main__":
intervals = [(1, 3), (5, 7), (10, 12), (…
How to Find Intersection of Two Sorted Interval Lists in Python
A two-pointer algorithm that finds all overlapping intervals between two sorted lists of intervals.
def interval_intersection(list1, list2):
i = j = 0
result = []
while i < len(list1) and j < len(list2):
# Find the overlap between current intervals
lo = max(list1[i][0], list2[j][0])
hi = min(list1[i][1], list2[j][1])
# If there's an overlap, add it to result
…
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.
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]:
…
How to Find the Nearest Value to a Target in a Sorted List in Python
Use bisect to binary-search a sorted list and return the element closest to a target value.
import bisect
def nearest_value(sorted_list, target):
if not sorted_list:
return None
pos = bisect.bisect_left(sorted_list, target)
if pos == 0:
return sorted_list[0]
if pos == len(sorted_list):
return sorted_list[-1]
before = sorted_list[pos - 1]
after = sorted_list[po…
How to Find the Next Greater Element for Each List Item in Python
Use a monotonic stack to find the next greater element to the right for every item in a list, in O(n) time.
def next_greater_element(nums):
result = [-1] * len(nums)
stack = []
for i in range(len(nums) - 1, -1, -1):
while stack and stack[-1] <= nums[i]:
stack.pop()
result[i] = stack[-1] if stack else -1
stack.append(nums[i])
return result
if __name__ == "__main…
How to Find the Previous Smaller Element in Python
Use a monotonic stack to find the nearest smaller element to the left of each item in a list, returning -1 when none exists.
from collections import deque
def previous_smaller_elements(arr):
stack = deque()
result = [-1] * len(arr)
for i in range(len(arr)):
while stack and arr[stack[-1]] >= arr[i]:
stack.pop()
if stack:
result[i] = arr[stack[-1]]
stack.append(i)
return resul…
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.
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 []
…
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