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Python Code Samples

Copy-ready Python snippets by topic and difficulty — short, focused, and runnable in the browser editor.

299 matches
Lists & loops easy

Rotate List Left by k Positions in Python

Rotates a list left by k positions using slicing and modulo arithmetic to handle large k safely.

list rotation slicing
Python
def rotate_left(lst, k):
    if not lst:
        return []
    k = k % len(lst)
    return lst[k:] + lst[:k]

if __name__ == "__main__":
    my_list = [1, 2, 3, 4, 5]
    k = 2
    result = rotate_left(my_list, k)
    print(f"Original: {my_list}")
    print(f"After rotating left by {k}: {result}")
13 0 Open
Lists & loops easy

Truncate List Keeping Last N Elements in Python

Return a new list containing only the last N elements from a sequence, handling edge cases like zero or oversized counts.

list slicing sequence
Python
def truncate(seq, keep_last_n):
    """Return a new list keeping only the last n elements."""
    if keep_last_n <= 0:
        return []
    return list(seq)[-keep_last_n:]


if __name__ == "__main__":
    data = [10, 20, 30, 40, 50, 60]
    print(truncate(data, 3))
    print(truncate(data, 0))
    print(truncate(data…
12 0 Open
Functions & basics easy

Benchmark list append vs comprehension in Python

This micro-benchmark compares the speed of building a list with a for loop and append versus a list comprehension, using the timeit module to get precise timings.

timeit benchmark performance
Python
import timeit

# Build a list of the first 1,000,000 integers using append in a loop
def append_loop(n=1_000_000):
    result = []
    for i in range(n):
        result.append(i)
    return result

# Build the same list using a list comprehension
def comprehension(n=1_000_000):
    return [i for i in range(n)]

if __n…
14 0 Open
Functions & basics easy

Create a retry decorator with max attempts in Python

A decorator that retries a function up to a specified number of times when it raises an exception, with an optional delay between attempts.

decorator retry error-handling
Python
import functools
import time


def retry(max_attempts, delay=0.1):
    """Retry a function up to max_attempts times on exception."""
    def decorator(func):
        @functools.wraps(func)
        def wrapper(*args, **kwargs):
            for attempt in range(1, max_attempts + 1):
                try:
                …
12 0 Open
Functions & basics easy

How to Create Generator Functions with yield in Python

Create a memory-efficient generator function using yield to produce a Fibonacci sequence up to a limit.

generator yield fibonacci
Python
def fibonacci_sequence(limit):
    """Generate Fibonacci numbers up to a given limit."""
    a, b = 0, 1
    while a <= limit:
        yield a
        a, b = b, a + b


if __name__ == "__main__":
    fib_gen = fibonacci_sequence(100)
    
    for number in fib_gen:
        print(number, end=" ")
    print()
11 0 Open
Functions & basics easy

How to Group a List into Chunks in Python

Split a list into smaller groups of a fixed size using a reusable function with a default parameter.

list slicing functions
Python
def make_groups(numbers, group_size=2):
    """Splits a list into smaller groups of a given size."""
    groups = []
    for i in range(0, len(numbers), group_size):
        groups.append(numbers[i:i + group_size])
    return groups


if __name__ == "__main__":
    data = [1, 2, 3, 4, 5, 6, 7]

    print("Default size…
15 0 Open
Functions & basics easy

How to Implement Memoized Fibonacci in Python with functools.cache

Use functools.cache to memoize a recursive Fibonacci function, avoiding repeated computation and dramatically speeding up the calculation.

fibonacci memoization functools
Python
from functools import cache

@cache
def fibonacci(n: int) -> int:
    """Return the n-th Fibonacci number (0-indexed)."""
    if n < 2:
        return n
    return fibonacci(n - 1) + fibonacci(n - 2)

if __name__ == "__main__":
    for i in range(10):
        print(f"fibonacci({i}) = {fibonacci(i)}")
    print(f"Cache…
15 0 Open
Functions & basics easy

How to Validate CLI Integer Option Within a Range in Python

Use argparse with integer type and bounds checking to validate a command-line option falls within a specified min-max range.

argparse cli validation
Python
import argparse

def main():
    parser = argparse.ArgumentParser(description="Validate an integer within a range.")
    parser.add_argument("--value", type=int, required=True, help="Integer to validate")
    parser.add_argument("--min", type=int, default=0, help="Minimum allowed value")
    parser.add_argument("--max…
13 0 Open
Functions & basics easy

Sort a List of Dictionaries by Key in Python

Uses a lambda function with sorted() to order a list of dictionaries by a specified key, like price.

lambda sorting list
Python
def get_items():
    return [
        {"name": "apple", "price": 3},
        {"name": "banana", "price": 1},
        {"name": "cherry", "price": 2},
    ]

if __name__ == "__main__":
    items = get_items()
    sorted_items = sorted(items, key=lambda item: item["price"])
    for item in sorted_items:
        print(f"{…
12 0 Open
Errors & debugging medium

How to Re-raise Exceptions with 'raise from' in Python

Shows how to re-raise an exception with explicit context chaining using the 'raise ... from ...' syntax, so the original cause is preserved for debugging.

exceptions raise-from error-handling
Python
def divide_with_chain(a, b):
    try:
        result = a / b
        return result
    except ZeroDivisionError as original_error:
        # Re-raise with explicit chaining context
        raise ValueError("Cannot divide by zero") from original_error

def explain_chain():
    try:
        divide_with_chain(10, 0)
    …
12 0 Open
Errors & debugging medium

How to Simulate Timeout with Custom TimeoutError in Python

Run a function in a daemon thread and raise a custom TimeoutError if it exceeds a specified time limit.

timeout threading exceptions
Python
import time
from typing import Callable, TypeVar

T = TypeVar("T")


class TimeoutError(Exception):
    """Raised when an operation exceeds its time limit."""

    def __init__(self, message: str = "Operation timed out"):
        self.message = message
        super().__init__(self.message)


def run_with_timeout(func…
12 0 Open
Errors & debugging easy

How to Test Exceptions in Python with pytest.raises

Learn the pytest.raises pattern to assert that specific exceptions are raised and validate their messages.

pytest testing exceptions
Python
import pytest


def divide(a: int, b: int) -> float:
    if b == 0:
        raise ValueError("Cannot divide by zero")
    return a / b


def test_divide_by_zero_raises():
    with pytest.raises(ValueError, match="Cannot divide by zero"):
        divide(10, 0)


def test_divide_by_zero_raises_exact_match():
    with py…
15 0 Open
Errors & debugging easy

How to Validate an Email Address and Raise ValueError in Python

This code defines a validate_email function that checks an email address against a regex pattern and several rules, raising ValueError with a specific reason when invalid.

validation regex errors
Python
import re

def validate_email(email: str) -> str:
    """Validate an email address and return it if valid, otherwise raise ValueError."""
    if not isinstance(email, str):
        raise ValueError("Email must be a string")
    if len(email) > 254:
        raise ValueError("Email length exceeds 254 characters")

    #…
14 0 Open
Errors & debugging easy

How to check for None and raise helpful errors in Python

A defensive function that explicitly validates data, keys, and values — raising descriptive ValueError and KeyError exceptions before returning a result.

none error-handling validation
Python
def get_value(data, key):
    if data is None:
        raise ValueError("data cannot be None")
    if key not in data:
        raise KeyError(f"key '{key}' not found in data")
    result = data[key]
    if result is None:
        raise ValueError(f"value for key '{key}' is None")
    return result


if __name__ == "__…
15 0 Open
Errors & debugging easy

How to define an exception hierarchy for domain errors in Python

Create a custom exception hierarchy with a base DomainError class and specific subclasses to handle validation, not-found, permission, and concurrency errors cleanly in Python apps.

exceptions domain-errors error-handling
Python
class DomainError(Exception):
    """Base class for all domain errors."""
    pass

class ValidationError(DomainError):
    """Raised when input data fails validation rules."""
    pass

class NotFoundError(DomainError):
    """Raised when a requested entity does not exist."""
    pass

class PermissionDeniedError(Dom…
14 0 Open
Errors & debugging easy

Implement a Context Manager That Suppresses Exceptions in Python

Shows how to write a custom context manager that catches specified exceptions and optionally re-raises others, plus the stdlib contextlib.suppress alternative.

context-manager exception-handling with-statement
Python
import contextlib

class SuppressExceptions:
    def __init__(self, *exceptions):
        self.exceptions = exceptions

    def __enter__(self):
        return self

    def __exit__(self, exc_type, exc_val, exc_tb):
        if exc_type is None:
            return False
        if not self.exceptions or exc_type in se…
11 0 Open
Errors & debugging medium

Implement circuit breaker open after failures demo in Python

A minimal CircuitBreaker class that calls a function and automatically 'opens' after a set number of consecutive failures, blocking further calls with a RuntimeError.

circuit-breaker resilience error-handling
Python
import time
from datetime import datetime


class CircuitBreaker:
    def __init__(self, threshold=3):
        self.threshold = threshold
        self.failure_count = 0
        self.is_open = False

    def call(self, func, *args, **kwargs):
        if self.is_open:
            raise RuntimeError("Circuit is OPEN")
  …
13 0 Open
Files & data medium

Convert Image to ASCII Art in Python

Convert any image to ASCII art by resizing, converting to grayscale, and mapping pixel brightness to characters using Pillow.

image ascii-art pillow
Python
from PIL import Image
import sys

ASCII_CHARS = "@%#*+=-:. "

def resize_image(image, new_width=100):
    """Resize image maintaining aspect ratio."""
    width, height = image.size
    ratio = height / width
    new_height = int(new_width * ratio * 0.55)  # 0.55 adjusts for font aspect ratio
    return image.resize((…
51 0 Open
Files & data easy

Extract a Single Member from a ZIP Archive in Python

Extract one specific file from a ZIP archive to an output directory using the standard zipfile and pathlib modules.

zipfile zip extraction
Python
import zipfile
from pathlib import Path

def extract_single_member(zip_path: str, member_name: str, output_dir: str = ".") -> Path:
    """Extract a single member from a zip archive to the output directory."""
    with zipfile.ZipFile(zip_path, "r") as archive:
        archive.extract(member_name, output_dir)
    retu…
20 0 Open
Files & data easy

How to Archive Old Files by Age in Python

Move files older than a specified number of days from a source directory to an archive directory using Python's pathlib and shutil modules.

file-archiving pathlib shutil
Python
import os
import shutil
import time
from pathlib import Path

def archive_old_files(source_dir: str, archive_dir: str, days_old: int) -> None:
    cutoff_time = time.time() - (days_old * 86400)  # 86400 seconds in a day
    archive_path = Path(archive_dir)
    archive_path.mkdir(parents=True, exist_ok=True)

    for i…
48 0 Open
Files & data easy

How to Group Files by Extension in Python

Group file names by their file extension using a dictionary and pathlib, producing a simple clear mapping for beginners.

pathlib grouping filesystem
Python
from pathlib import Path


def group_data_by_extension(files: list[Path]) -> dict[str, list[str]]:
    """Group file names by their extension."""
    grouped: dict[str, list[str]] = {}
    for file in files:
        ext = file.suffix.lower()
        grouped.setdefault(ext, []).append(file.name)
    return grouped


if…
14 0 Open
Files & data medium

How to Load Pickle Files Safely in Python

This code demonstrates how to load pickle files safely in Python by using a restricted unpickler that only allows specific, trusted classes, preventing arbitrary code execution from untrusted pickles.

pickle security serialization
Python
import pickle

# Default pickle.load is unsafe: it executes arbitrary code when unpickling.
class Unsafe:
    def __reduce__(self):
        return (eval, ("open('/tmp/pickle_demo.txt', 'w').write('pwned')",))

# Create a malicious payload (simulating untrusted source)
malicious_data = pickle.dumps(Unsafe())

# Safe ap…
14 0 Open
Files & data medium

How to Memory Map Large Files Read-Only in Python

This code demonstrates reading only the tail of a large file using a read-only memory map (mmap) to avoid loading the entire file into memory.

mmap file-io memory-efficient
Python
import mmap
import os

def read_tail_with_mmap(filepath, bytes_from_end=64):
    """Read the last bytes of a large file using a read-only mmap."""
    file_size = os.path.getsize(filepath)
    start = max(0, file_size - bytes_from_end)

    with open(filepath, "rb") as f:
        with mmap.mmap(f.fileno(), length=0, a…
12 0 Open
Files & data easy

How to Merge Environment-Specific Config JSON in Python

Loads a base JSON config and overlays environment-specific overrides, merging the two dictionaries into one final config.

json config pathlib
Python
import json
import pathlib


def load_config(base_path: pathlib.Path, env: str) -> dict:
    base_config = json.loads(base_path.read_text())
    env_path = base_path.with_name(f"config.{env}.json")
    if env_path.exists():
        env_config = json.loads(env_path.read_text())
        return {**base_config, **env_conf…
14 0 Open

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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

  1. Pick a topic section — strings, lists, files, functions, and more
  2. Open a sample, read How it works, and copy the code block
  3. 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.