Python Code
Samples
Copy-ready Python snippets by topic and difficulty — short, focused, and runnable in the browser editor.
How to implement a Facade class to simplify subsystem calls in Python
Use a Facade class to wrap complex subsystem interactions behind a simple start() method, hiding the details and providing a clean interface.
class CPU:
def freeze(self):
print("CPU: freezing")
def jump(self, position):
print(f"CPU: jumping to {position}")
def execute(self):
print("CPU: executing")
class Memory:
def load(self, position, data):
print(f"Memory: loading '{data}' at {position}")
class HardDr…Implement the Strategy Pattern with Interchangeable Algorithm Classes in Python
Uses abstract base classes to define a SortStrategy interface, then swaps between BubbleSort and QuickSort at runtime.
from abc import ABC, abstractmethod
from typing import List
class SortStrategy(ABC):
@abstractmethod
def sort(self, data: List[int]) -> List[int]:
pass
class BubbleSort(SortStrategy):
def sort(self, data: List[int]) -> List[int]:
result = data[:]
n = len(result)
for i in…Memento Pattern in Python: Save and Restore Object State
Implement the Memento design pattern to snapshot and restore an object's state, demonstrated with a text editor undo feature.
class TextEditor:
def __init__(self, text="", cursor_pos=0):
self.text = text
self.cursor_pos = cursor_pos
def type_text(self, new_text):
self.text += new_text
self.cursor_pos += len(new_text)
def move_cursor(self, pos):
self.cursor_pos = max(0, min(pos, len(self.t…Observer Pattern in Python: Notify Listeners
Implement the Observer design pattern in Python with a Subject class that manages listeners and notifies them with messages.
class Subject:
def __init__(self):
self._observers = []
def attach(self, observer):
self._observers.append(observer)
def detach(self, observer):
self._observers.remove(observer)
def notify(self, message):
for observer in self._observers:
observer.update(me…Python Adapter Class: Wrap Legacy Interface
Convert a legacy system's interface into a modern one using the Adapter pattern in Python, translating method calls and data formats.
class LegacySystem:
"""Legacy interface - old method names and parameter format."""
def query_employee_info(self, emp_id, emp_name):
return f"Legacy: {emp_id} - {emp_name}"
def update_employee_department(self, emp_id, department_code):
return f"Legacy: Updated {emp_id} to dept {department_…Python Factory Method: Create Shapes by Type String
A factory method that maps a type string to a concrete shape class and returns an instance, with runtime error handling.
class Shape:
def draw(self):
raise NotImplementedError
class Circle(Shape):
def draw(self):
return "Drawing a circle"
class Square(Shape):
def draw(self):
return "Drawing a square"
class Triangle(Shape):
def draw(self):
return "Drawing a triangle"
class ShapeFact…Template Method Pattern in Python: Define Base Class with Algorithm Steps
Create a template method base class using ABC that defines the skeleton of an algorithm while letting subclasses implement specific steps.
from abc import ABC, abstractmethod
class DataProcessor(ABC):
"""Template method that defines the skeleton of an algorithm."""
def process(self):
"""Template method - defines the sequence of steps."""
self.load_data()
self.clean_data()
self.transform_data()
self.s…Unit of Work Pattern: Track Changes, Commit, and Rollback in Python
This code defines a UnitOfWork class that tracks operations (add) and supports commit to apply changes and rollback to revert them, using a dataclass-based logger.
from dataclasses import dataclass, field
from typing import Any, Callable, List, Tuple
@dataclass
class UnitOfWork:
log: List[Tuple[str, Callable, tuple, dict]] = field(default_factory=list)
def track(self, operation: str, fn: Callable, *args, **kwargs):
self.log.append((operation, fn, args, kwargs)…Visitor Pattern in Python: Double Dispatch Demo
Demonstrates the Visitor design pattern with double dispatch so operations on Dog and Cat objects are selected at runtime without modifying their classes.
class Animal:
def accept(self, visitor):
visitor.visit(self)
class Dog(Animal):
def speak(self):
return "Woof!"
class Cat(Animal):
def speak(self):
return "Meow!"
class SoundVisitor:
def visit(self, animal):
if isinstance(animal, Dog):
return self.visit_do…How to Decode a String with Repeated Brackets in Python
Decodes strings with patterns like '3[a]2[bc]' by using a stack to handle nested and repeated bracket groups.
def decode_string(s: str) -> str:
stack = []
current_num = 0
current_str = ""
for ch in s:
if ch.isdigit():
current_num = current_num * 10 + int(ch)
elif ch == "[":
stack.append((current_str, current_num))
current_str = ""
current_num = 0…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 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 Generate Cartesian Product Combinations in Python
Use itertools.product to generate every combination across multiple iterables, a pattern common for product variant generation.
from itertools import product
def generate_cartesian_combinations(*iterables):
"""Generate all Cartesian product combinations of given iterables."""
return list(product(*iterables))
if __name__ == "__main__":
colors = ["red", "green", "blue"]
sizes = ["S", "M", "L"]
styles = ["t-shirt", "hoodie"]…Normalize Data in Python with Comprehensions and Generators
Clean a list by dropping None values with a comprehension, then min-max normalize it using a lazy generator expression — a beginner-friendly data preparation pattern.
import statistics
# Sample raw data including missing and outlier-ish values
raw = [22, 18, None, 25, 30, 19, 22, 17, None, 28, 24]
# Clean the data: drop None values using a list comprehension
clean = [x for x in raw if x is not None]
# Normalize using min-max scaling with a generator expression
min_val = min(clea…Circuit Breaker Pattern in Python for LLM API Calls
Implements a circuit breaker class that wraps LLM client calls to fail fast when the service is degrading, then recover automatically after a timeout.
import time
class CircuitBreaker:
def __init__(self, failure_threshold=3, recovery_timeout=5):
self.failure_threshold = failure_threshold
self.recovery_timeout = recovery_timeout
self.failure_count = 0
self.state = "closed"
self.last_failure_time = None
def call(self, …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 implement exponential backoff for LLM API calls in Python
A decorator that retries flaky LLM API calls with exponential delay, using a mock client to demonstrate the pattern.
import time
import random
class MockLLM:
def call(self, prompt):
if random.random() < 0.7: # 70% chance of transient failure
raise ConnectionError("API unavailable")
return f"LLM response for: {prompt}"
def with_exponential_backoff(max_retries=5, base_delay=0.1):
def decorator(fu…Build a Python Tool to Find All API Endpoints on a Website
A Python script that crawls a website, searches for common API endpoint patterns in HTML and JavaScript, and returns all discovered public API URLs.
import re
import requests
from urllib.parse import urljoin, urlparse
from collections import deque
def find_api_endpoints(base_url, max_pages=10):
visited = set()
queue = deque([base_url])
api_endpoints = set()
api_patterns = [
r'/api/[a-zA-Z0-9_/-]+',
r'/v[0-9]+/[a-zA-Z0-9_/-]+',…Create a Local Search Engine to Instantly Find Files on Your Computer in Python
Build a local file search engine in Python that indexes files by name, extension, and glob pattern for instant retrieval.
import os
import sys
import time
from pathlib import Path
import fnmatch
class LocalSearchEngine:
def __init__(self, root_directory="."):
self.root_directory = Path(root_directory)
self.file_index = {}
def build_index(self):
"""Build a complete index of files in the root direc…How to Kill Zombie Processes Matching a Name in Python
Scans running processes with ps, finds zombies whose command name matches a pattern, and attempts to kill them with SIGKILL.
import subprocess
import re
import signal
def find_zombies(name_pattern):
"""Find PIDs of zombie processes matching the given pattern."""
result = subprocess.run(["ps", "-eo", "pid,stat,comm"], capture_output=True, text=True)
zombies = []
for line in result.stdout.splitlines()[1:]: # Skip header
…Fan Out Records to Multiple Sinks in Python
Distribute the same records across multiple target sinks (database, API, queue, etc.) using a defaultdict-based fan-out pattern.
import json
from collections import defaultdict
SINKS = ["database", "api", "message_queue", "data_lake", "monitoring"]
def fan_out(records, *sinks):
dist = defaultdict(list)
for record in records:
for sink in sinks:
dist[sink].append(record)
return dict(dist)
if __name__ == "__main_…How to Deduplicate Events with At-Least-Once Delivery in Python
Implements an exactly-once processing pattern for at-least-once event delivery by tracking seen event IDs in a set, skipping duplicates.
seen_ids = set()
def process_event(event_id: str, payload: dict) -> dict:
"""Process an event exactly once, ignoring duplicates."""
if event_id in seen_ids:
return {"status": "duplicate", "event_id": event_id}
seen_ids.add(event_id)
return {"status": "processed", "event_id": event_id, **payloa…How to Generate Git LFS Extension Patterns in Python
This script builds mock Git LFS file patterns for common geospatial extensions and filters them based on compression suffixes.
import itertools
import re
LFS_EXTENSIONS = {".csv", ".geojson", ".tif", ".shp", ".gpkg"}
def build_mock_lfs_pattern(base_name="data_usgs_lidar"):
patterns = []
for ext in sorted(LFS_EXTENSIONS):
for variant in (("", ".lz4"), (".compressed",), (".b", ".a"), ("_v1", ".zip")):
full_pattern …How to detect secrets in git history with Python
Scan a git history export file for common secret patterns using regex and Python.
import re
from pathlib import Path
def scan_history_for_secrets(history_file: str) -> list:
"""Scan a git history export for potential secrets using regex patterns."""
patterns = {
"AWS Access Key": r"AKIA[0-9A-Z]{16}",
"GitHub Token": r"gh[pousr]_[0-9A-Za-z]{36,255}",
"Private Key": …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.