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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 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 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 Solve the Trapping Rain Water Problem in Python
Compute the total water trapped between elevation bars using a two-pointer O(n) algorithm.
def trap(height):
if not height:
return 0
left, right = 0, len(height) - 1
left_max, right_max = 0, 0
water = 0
while left < right:
if height[left] < height[right]:
if height[left] >= left_max:
left_max = height[left]
else:
…How to Sort Colors (Dutch National Flag) in Python
In-place sorting of a list of 0s, 1s, and 2s using the Dutch National Flag algorithm with O(n) time and O(1) space.
def sort_colors(nums):
low, mid, high = 0, 0, len(nums) - 1
while mid <= high:
if nums[mid] == 0:
nums[low], nums[mid] = nums[mid], nums[low]
low += 1
mid += 1
elif nums[mid] == 1:
mid += 1
else: # nums[mid] == 2
nums[mid], n…Implement Insert Delete GetRandom O(1) in Python
Build a RandomizedSet class that supports insert, delete, and get_random in average O(1) time using a list and a dictionary mapping values to indices.
import random
class RandomizedSet:
def __init__(self):
self.values = []
self.index_map = {}
def insert(self, val):
if val in self.index_map:
return False
self.index_map[val] = len(self.values)
self.values.append(val)
return True
def delete(self…Product of Array Except Self in Python Without Division
Compute the product of all array elements except the current one in O(n) time using prefix and suffix products, without using division.
from math import prod
def product_except_self(nums):
n = len(nums)
result = [1] * n
left_product = 1
for i in range(n):
result[i] = left_product
left_product *= nums[i]
right_product = 1
for i in range(n - 1, -1, -1):
result[i] *= right_product
right_product *…Quickselect in Python: Find the kth Smallest Element
Python implementation of the Quickselect algorithm to find the kth smallest element in an unsorted list with average O(n) time complexity.
def quickselect(arr, k):
"""
Returns the k-th smallest element (0-indexed) using Quickselect.
Average: O(n), Worst: O(n^2)
"""
if len(arr) == 1:
return arr[0]
pivot = arr[-1]
left = [x for x in arr[:-1] if x <= pivot]
right = [x for x in arr[:-1] if x > pivot]
if k < len(l…Split Array Largest Sum in Python (Minimize Largest Subarray Sum)
Binary search + greedy check to split an array into k subarrays while minimizing the largest subarray sum.
def can_split(nums, k, max_sum):
subarrays = 1
current_sum = 0
for num in nums:
if current_sum + num <= max_sum:
current_sum += num
else:
subarrays += 1
current_sum = num
if subarrays > k:
return False
return True
def spli…Validate Sudoku Board Rows Columns and Boxes in Python
Validate a 9x9 Sudoku board by checking that each row, column, and 3x3 box contains the numbers 1 through 9 exactly once.
def validate_sudoku(board):
def is_valid_group(group):
return sorted(group) == list(range(1, 10))
def get_columns():
return [[board[r][c] for r in range(9)] for c in range(9)]
def get_boxes():
boxes = []
for box_row in range(0, 9, 3):
for box_col in range(0, 9,…Build a Generator Pipeline in Python: Filter Then Map
Create a lazy data pipeline by chaining generator functions that read, filter, map, and write data step by step.
def read_data():
return ["a", "bb", "ccc", "dd", "eeeee", "f"]
def filter_short(words):
return (word for word in words if len(word) >= 2)
def map_to_upper(words):
return (word.upper() for word in words)
def write_data(words):
for word in words:
print(word)
if __name__ == "__main__":
…How to Build a Backpressure Generator Pause Producer Demo in Python
Demonstrates a producer–consumer pattern with a fixed-size buffer that pauses production when full, simulating backpressure.
import time
import collections
def producer(buffer, max_size, items):
"""Adds items to the buffer until full, then pauses."""
for item in items:
while len(buffer) >= max_size:
print(f"Buffer full ({len(buffer)}/{max_size}) — producer paused")
time.sleep(0.1)
buffer.appe…How to Create a Generator Context Manager in Python with contextlib
Create a custom context manager with the @contextlib.contextmanager decorator to manage resources using a generator function.
import contextlib
@contextlib.contextmanager
def temporary_directory():
"""Yield a string and clean up after the block exits."""
print("Creating temp directory...")
dir_name = "/tmp/example"
try:
yield dir_name
finally:
print(f"Removing {dir_name}...")
if __name__ == "__main__":
…How to Generate Primes with a Generator in Python
Generate prime numbers up to a limit using the Sieve of Eratosthenes wrapped in a generator expression for lazy evaluation.
def prime_generator(limit):
sieve = [True] * (limit + 1)
sieve[0] = sieve[1] = False
for i in range(2, int(limit ** 0.5) + 1):
if sieve[i]:
for j in range(i * i, limit + 1, i):
sieve[j] = False
return (num for num, is_prime in enumerate(sieve) if is_prime)
if __n…How to Throw an Exception into a Python Generator
This code demonstrates how to use the .throw() method on a generator to inject an exception at its current yield point and let it recover gracefully.
def demo_throw_into_generator():
"""Demonstrate throwing an exception into a running generator."""
def counter():
"""Generator that counts until interrupted."""
try:
i = 0
while True:
yield i
i += 1
except ValueError as e:
…How to filter a generator with a predicate function in Python
This code defines a generator function that yields only items from an iterable that satisfy a given predicate, then tests it with even and positive number filters.
def filter_gen(predicate, iterable):
for item in iterable:
if predicate(item):
yield item
def is_even(num):
return num % 2 == 0
def is_positive(num):
return num > 0
if __name__ == "__main__":
numbers = range(-5, 10)
even_numbers = list(filter_gen(is_even, numbers))
p…How to Build a Data Helper for LLM Prompts in Python
A beginner-friendly helper class that flattens nested dictionaries, formats prompt templates, and safely parses JSON for AI/LLM pipelines.
import json
from typing import Any, Dict, List, Optional
class DataHelper:
"""Simple helper class for working with data in AI/LLM pipelines."""
def __init__(self, data: Optional[Dict[str, Any]] = None) -> None:
self.data = data or {}
def flatten(self, prefix: str = "") -> Dict[str, Any]…How to Detect Prompt Injection in Python
Implements a regex-based heuristic in Python to flag common prompt injection attempts before sending input to an LLM.
import re
def contains_prompt_injection(user_input: str) -> bool:
# Directives to ignore previous instructions or act as system
ignore_patterns = [
r"\bignore\s+(all\s+)?previous\s+instructions\b",
r"\bdisregard\s+(all\s+)?previous\s+instructions\b",
r"\bdon'?t\s+follow\s+(any\s+)?inst…How to Retry LLM Calls on Rate Limit Errors in Python
Implement a retry mechanism with exponential backoff for LLM API calls that raises a custom RateLimitError, using a mock function to demonstrate the pattern.
import time
import random
def mock_llm_call():
"""Simulates an LLM API call that may raise a rate limit error."""
if random.random() < 0.4: # 40% chance of rate limit
raise RateLimitError("Rate limit exceeded. Try again later.")
return {"response": "Hello world from mock LLM"}
class RateLimitE…How to cache embeddings with a Python dict to avoid recomputation
Caches embeddings computed from text in a dictionary keyed by SHA-256 hash, returning cached results for repeated calls.
import hashlib
import time
class EmbeddingCache:
def __init__(self):
self.cache = {}
def _hash_text(self, text):
return hashlib.sha256(text.encode()).hexdigest()
def get_embedding(self, text, compute_func):
key = self._hash_text(text)
if key not in self.cache:
…How to parallel map embeddings with a thread pool in Python
Run embedding computations in parallel using ThreadPoolExecutor, collect results into a dict keyed by the original item.
import threading
from concurrent.futures import ThreadPoolExecutor
import time
def compute_embedding(item: int) -> tuple[int, int]:
time.sleep(0.05) # Simulate embedding work
return item, item * 10
def parallel_map_embed(items, max_workers=3):
results = {}
with ThreadPoolExecutor(max_workers=max_w…Parse ReAct Logs into Thought Action Observation Steps in Python
Parse a ReAct agent's textual log into structured steps with thought, action, and observation using regex and named tuples.
import re
from collections import namedtuple
ReActStep = namedtuple("ReActStep", ["thought", "action", "observation"])
def parse_react_log(log: str) -> list[ReActStep]:
"""Parse a ReAct log into structured thought/action/observation steps."""
pattern = re.compile(
r"Thought:\s*(?P<thought>.+?)\s*"
…Track GitHub Repository Growth in Python
A Python dashboard that fetches and displays GitHub repository statistics including stars, forks, creation date, and recent star activity using the GitHub API.
import requests
import json
from datetime import datetime, timedelta
def track_repo_growth(owner, repo):
url = f"https://api.github.com/repos/{owner}/{repo}"
headers = {"Accept": "application/vnd.github.v3+json"}
response = requests.get(url, headers=headers)
data = response.json()
name = data…Browse by section
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