Algorithms & data structures
Classic patterns — search, sort, stacks, queues, and practical complexity-aware code.
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 []
…
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 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 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)
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…
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