Python Code
Samples
Copy-ready Python snippets by topic and difficulty — short, focused, and runnable in the browser editor.
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…Rearrange array alternately max min in Python
Rearranges a sorted list so its elements alternate between the current maximum and current minimum using two pointers in O(n) time.
def rearrange_alternately(arr):
"""
Rearrange sorted array so elements alternate: max, min, next max, next min...
Returns a new list in O(n) time using O(n) space.
"""
n = len(arr)
result = []
left, right = 0, n - 1
while left <= right:
if left == right:
result.appen…Remove item at index without pop in Python
Remove an item at a given index from a list without using pop by slicing the list around the index.
def remove_at_index(lst, index):
"""Remove item at index and return the new list."""
if index < 0 or index >= len(lst):
raise IndexError("Index out of range")
return lst[:index] + lst[index + 1:]
if __name__ == "__main__":
items = [10, 20, 30, 40, 50]
result = remove_at_index(items, 2)
…Reorder a List by Odd Even Indices in Python
Splits a list into two sublists based on 1-based index parity, then concatenates odd-indexed elements before even-indexed ones.
def reorder_by_odd_even(items):
"""Reorders a list so that elements at odd indices come first,
followed by elements at even indices (1-based).
Example: [0,1,2,3,4,5,6] -> [1,3,5,0,2,4,6]
"""
odds = [items[i] for i in range(1, len(items), 2)]
evens = [items[i] for i in range(0, len(items), …Segregate Negative Numbers Before Positives in Python
Reorders a list so all negative numbers appear before non-negative numbers while preserving the original relative order of elements.
def segregate_negatives(numbers):
"""Segregate negatives before positives without altering relative order."""
negatives = [n for n in numbers if n < 0]
positives = [n for n in numbers if n >= 0]
return negatives + positives
if __name__ == "__main__":
sample = [3, -1, 4, -5, 2, -9, 0]
result =…Set Matrix Zeroes in Python: Markers List Grid Demo
Given a matrix, this code finds all rows and columns that contain a zero and sets every element in those rows and columns to zero, using boolean marker arrays.
def set_zeroes(matrix):
rows, cols = len(matrix), len(matrix[0])
row_markers = [False] * rows
col_markers = [False] * cols
# First pass: record which rows and columns contain zeros
for i in range(rows):
for j in range(cols):
if matrix[i][j] == 0:
row_markers[i] …Simplify a File Path in Python with a Stack
Uses a stack to normalize an absolute Unix path by handling '.', '..', and duplicate slashes.
from pathlib import PurePosixPath
def simplify_path(path: str) -> str:
tokens = path.split('/')
stack = []
for token in tokens:
if not token or token == '.':
continue
if token == '..':
if stack:
stack.pop()
else:
stack.append…Sort Unique Values by Frequency in Python
Count element frequencies with Counter and sort unique values by descending frequency, breaking ties alphabetically.
from collections import Counter
def sort_unique_by_frequency(values):
counts = Counter(values)
return sorted(counts.keys(), key=lambda x: (-counts[x], x))
if __name__ == "__main__":
data = [4, 2, 2, 8, 3, 3, 1, 3, 5, 5, 5, 5, 1]
result = sort_unique_by_frequency(data)
print(f"Sorted unique values…Sort list by multiple keys with tuple ordering in Python
Sort a list of dictionaries by multiple criteria — surname, age, then score descending — using a tuple key and negation.
def sort_multi_key(data):
# Sorts by surname, then age, then score descending
return sorted(
data,
key=lambda person: (
person['surname'].lower(),
person['age'],
-person['score'] # negative to reverse sort by score
)
)
if __name__ == "__main__"…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…Split a String into Multiple Lines by Width in Python
Demonstrates a word-wrap algorithm that splits a message into rows without exceeding a maximum width.
def split_message(text, max_width):
words = text.split()
rows = []
current_row = []
for word in words:
if len(" ".join(current_row + [word])) > max_width:
rows.append(" ".join(current_row))
current_row = [word]
else:
current_row.append(word)
if …Stable merge two lists by custom comparator in Python
Merge two lists into one sorted output using a custom comparator while maintaining the original order of equal elements.
from functools import cmp_to_key
def compare(x, y):
# Custom comparator: sorts by length first, then by original index for stability
if len(x) != len(y):
return len(x) - len(y)
return 0 # Equal keys preserve original order (stable)
def merge_stable(left, right, cmp_func):
result = []
i =…Stable sort preserving equal order demo in Python
Demonstrates Python's stable sort, showing that elements with equal sort keys retain their original relative order.
from operator import itemgetter
def stable_sort_demo():
data = [(3, "first"), (1, "second"), (3, "third"), (1, "fourth"), (2, "fifth")]
print("Original:", data)
# Sort by first element (the tuple's first value), keeping relative order of equal items
sorted_data = sorted(data, key=itemgetter(0))
…Take While Predicate True From Start in Python
Create a custom take_while function that collects elements from an iterable until a predicate returns False, then stops.
def take_while(predicate, iterable):
"""Return elements from iterable until the predicate becomes False."""
result = []
for item in iterable:
if predicate(item):
result.append(item)
else:
break
return result
if __name__ == "__main__":
numbers = [2, 4, 6, 7,…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,…Batch Rows in Chunks with a Generator in Python
Group a list of row dicts into fixed-size chunks using a generator that yields one slice per call.
from typing import Iterator, List
def batch_rows(rows: List[dict], batch_size: int) -> Iterator[List[dict]]:
for i in range(0, len(rows), batch_size):
yield rows[i:i + batch_size]
if __name__ == "__main__":
sample_rows = [
{"id": 1, "name": "Alice"},
{"id": 2, "name": "Bob"},
…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__":
…Build a lazy generator to read file lines in Python
Create a generator function that yields file lines one at a time, avoiding loading the entire file into memory, and demonstrate its lazy processing.
def lazy_lines(filepath):
"""Yield lines from a file one at a time without loading the whole file into memory."""
with open(filepath, 'r', encoding='utf-8') as file:
for line in file:
yield line.rstrip('\n')
if __name__ == "__main__":
# Create a sample file to demonstrate
sample_c…Chunk an Iterable into Batches with a Generator in Python
Yield fixed-size batches from any iterable lazily using itertools.islice inside a generator function.
from itertools import islice
def chunked(iterable, size):
iterator = iter(iterable)
while True:
batch = list(islice(iterator, size))
if not batch:
break
yield batch
if __name__ == "__main__":
data = range(10)
for batch in chunked(data, 3):
print(batch)Convert Data in Python with Comprehensions and Generators
Convert mixed data to integers, filter and transform numbers, and extract fields from dicts using list comprehensions and generator expressions.
def convert_numbers(data):
"""Convert a list of mixed values into integers using a comprehension."""
return [int(item) for item in data if item is not None]
def double_even_numbers(numbers):
"""Double only even numbers using a generator expression."""
return (n * 2 for n in numbers if n % 2 == 0)
d…Count Data in Python with Comprehensions and Generators
Count list items with a dict comprehension and generate squares lazily with a generator expression, printing both results.
from collections import Counter
data = ["apple", "banana", "apple", "cherry", "banana", "apple"]
counts = {item: data.count(item) for item in set(data)}
square_gen = (x * x for x in range(5))
squares = list(square_gen)
if __name__ == "__main__":
print("Manual count:", counts)
print("Counter:", dict(Counter…Cycle an iterable forever in Python
Define a generator that repeatedly yields items from an iterable, cycling back to the beginning infinitely.
def cycle_generator(iterable):
"""Yield items from iterable forever, cycling back to the start."""
items = list(iterable) # Convert to list so it can restart
index = 0
while True:
yield items[index]
index = (index + 1) % len(items)
if __name__ == "__main__":
colors = ["red", "gre…Dict Comprehension to Map Keys to Lengths in Python
Build a dictionary that maps each word to its character count using a dictionary comprehension.
words = ["apple", "banana", "cherry", "date", "elderberry"]
word_lengths = {word: len(word) for word in words}
print(word_lengths)Enumerate a Generator With a Running Total in Python
A generator that yields each element with its index and a cumulative sum, letting you track a running total as you iterate.
def running_total_enum(iterable):
"""Yields (index, item, running_total) for each element."""
total = 0
for index, item in enumerate(iterable):
total += item
yield index, item, total
if __name__ == "__main__":
numbers = [10, 20, 30, 40, 50]
for idx, value, running_sum in running_to…Browse by section
Each section groups closely related Python snippets.
Guide: free Python code samples library
Copy-ready Python snippets for learners and developers
PythonSkillset code samples are short, focused examples organised by topic and difficulty. Every snippet is server-rendered HTML — readable by search engines and easy to copy. Open any sample, read the notes, copy the code, then press Try in editor to run it in the browser with Pyodide.
How to use this library
- Pick a topic section — strings, lists, files, functions, and more
- Open a sample, read How it works, and copy the code block
- Run it in the IDE, tweak values, then take a related quiz or tutorial lesson
Samples vs tutorials and challenges
Samples are quick reference — one concept per page. For step-by-step teaching, use our Python tutorials. To test yourself, try quizzes or coding challenges. Clean up style with the Python formatter.