Algorithms & data structures
Classic patterns — search, sort, stacks, queues, and practical complexity-aware code.
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 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 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 Flatten List of Dict Values in Python
This code flattens the values of a list of dictionaries into a single list, handling both list values and scalar values.
def flatten_dict_values(dicts):
flattened = []
for d in dicts:
for value in d.values():
if isinstance(value, list):
flattened.extend(value)
else:
flattened.append(value)
return flattened
if __name__ == "__main__":
data = [
{"a": …How to Generate Fibonacci Sequence in Python
Generate the first n Fibonacci numbers as a list using a simple iterative loop.
def fibonacci(n):
"""Generate the first n terms of the Fibonacci sequence."""
if n <= 0:
return []
seq = [0, 1]
while len(seq) < n:
seq.append(seq[-1] + seq[-2])
return seq[:n]
if __name__ == "__main__":
n = 10
result = fibonacci(n)
print(result)How to Generate Permutations of Length r in Python
Generate and print all r-length permutations of a list using Python's itertools.permutations.
from itertools import permutations
def show_permutations(items, r):
result = list(permutations(items, r))
for perm in result:
print(perm)
print(f"Total: {len(result)}")
if __name__ == "__main__":
data = ["A", "B", "C"]
show_permutations(data, 2)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 an Arithmetic Progression List in Python
Generates a list of terms in an arithmetic progression using a list comprehension.
def generate_ap(start, difference, count):
"""Generate a list of n terms in an arithmetic progression."""
return [start + i * difference for i in range(count)]
if __name__ == "__main__":
ap = generate_ap(3, 5, 6)
print(ap)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 Get the Breadth-First Traversal Order of a Graph in Python
Performs a breadth-first search on an adjacency list and returns the order nodes are visited, using a deque for efficient queue operations.
from collections import deque
def bfs_order(adjacency, start=0):
"""Return the order nodes are visited in a breadth-first traversal."""
visited = set()
order = []
queue = deque([start])
visited.add(start)
while queue:
node = queue.popleft()
order.append(node)
for neig…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.
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)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 Map Strings to Uppercase in Python
Loops through a list of strings and builds a new list with each string converted to uppercase.
strings = ["hello", "world", "python", "skillset"]
uppercased = []
for s in strings:
uppercased.append(s.upper())
print(uppercased)How to Remove Banned Values from a List in Python
Filters a list by removing elements present in a banned set, preserving the original order.
def remove_banned(values, banned):
banned_set = set(banned)
return [item for item in values if item not in banned_set]
if __name__ == "__main__":
values = [1, 2, 3, 4, 5, 2, 6, 3, 7]
banned = [2, 3]
result = remove_banned(values, banned)
print(result)Browse by section
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