System design patterns
Sharding, load balancing, CAP tradeoffs, and scaling patterns — interview and production ready.
Create a Data Helper Class in Python
A reusable DataHelper class that saves and loads JSON and CSV files from a configurable base directory, with automatic header detection for CSV.
import json
import csv
from pathlib import Path
class DataHelper:
def __init__(self, base_path="."):
self.base_path = Path(base_path)
self.base_path.mkdir(exist_ok=True)
def save_json(self, data, filename):
path = self.base_path / filename
with open(path, "w") as f:
…How to Aggregate Mock API Routes by Method in Python
Groups mock API routes by path and method, collecting response bodies and counts into a nested dictionary structure.
from collections import defaultdict
def aggregate_mock_routes(routes):
"""Aggregate mock API routes by method and aggregate their response bodies."""
aggregated = defaultdict(lambda: defaultdict(list))
for route in routes:
method = route["method"]
path = route["path"]
response = …How to Build a Simple Service Discovery Registry in Python
A lightweight in-memory service registry class using a dict — register, deregister, and discover services with host, port, and version.
class ServiceRegistry:
def __init__(self):
self._services = {}
def register(self, name, host, port, version="1.0"):
self._services[name] = {
"host": host,
"port": port,
"version": version
}
def deregister(self, name):
return self._servic…How to Build a Weighted Random Load Balancer in Python
A Python load balancer mock that distributes requests across servers based on configurable weights using a cumulative weighted random selection algorithm.
import random
from collections import Counter
SERVERS = {
"server-a": 50,
"server-b": 30,
"server-c": 20,
}
def weighted_random_server(servers: dict[str, int]) -> str:
"""Select a server based on its weight (higher weight = more likely)."""
total_weight = sum(servers.values())
rand = random.…How to Build an MVP Presenter View Mock in Python
A minimal MVP (Model-View-Presenter) mock showing a Presenter controlling a SlideDeck model with slide navigation and typed state via dataclasses.
from dataclasses import dataclass, field
from typing import List
@dataclass
class SlideDeck:
title: str
slides: List[str] = field(default_factory=list)
current_index: int = 0
def next_slide(self) -> str:
if self.current_index < len(self.slides) - 1:
self.current_index += 1
…How to Implement the Repository Pattern in Python with an In-Memory Dict
Stores, retrieves, updates, and deletes user records in memory using a Repository abstraction over a plain dict, isolating data access from business logic.
class UserRepository:
def __init__(self):
self._storage = {}
self._next_id = 1
def create(self, name, email):
user_id = self._next_id
self._next_id += 1
self._storage[user_id] = {"id": user_id, "name": name, "email": email}
return self._storage[user_id]
def…How to Mock Hexagonal Architecture Ports and Adapters in Python
Mock an email adapter in a hexagonal architecture with unittest.mock to test business logic in isolation.
from unittest.mock import Mock
class EmailService:
def send(self, recipient, message):
raise NotImplementedError
class OrderProcessor:
def __init__(self, email_service):
self.email_service = email_service
def process_order(self, order_id, customer_email):
# Business logic
…How to Mock a Metrics Decorator in Python with unittest.mock
This code demonstrates a timing decorator that wraps a function to measure execution time and prints the duration, with a unit test using unittest.mock to patch the print function and assert it was called.
import time
from functools import wraps
from unittest.mock import patch
def add_metrics(func):
@wraps(func)
def wrapper(*args, **kwargs):
start = time.perf_counter()
result = func(*args, **kwargs)
elapsed = time.perf_counter() - start
print(f"{func.__name__} took {elapsed:.6f}s…How to Take Periodic Snapshots of Aggregate State in Python
Build a Python class that accumulates values and periodically captures immutable snapshots of total, count, and average for later analysis.
import time
import random
from collections import defaultdict
class SnapshotAggregator:
def __init__(self):
self.total = 0
self.count = 0
self.history = []
def add(self, value):
self.total += value
self.count += 1
def snapshot(self):
avg = self.total / se…How to mock the domain center in an onion architecture in Python
Define a repository interface and an in-memory mock to test domain services without touching infrastructure.
from abc import ABC, abstractmethod
from dataclasses import dataclass
from typing import Dict, List, Optional
@dataclass
class Order:
id: int
customer: str
items: List[str]
total: float
class OrderRepository(ABC):
@abstractmethod
def find_by_id(self, order_id: int) -> Optional[Order]:
…Idempotent Consumer: Store Processed IDs in Python
Implement an idempotent consumer that persists processed message IDs to a JSON file, skipping duplicates on restart.
import json
from pathlib import Path
class IdempotentStore:
def __init__(self, storage_path: str = "processed_ids.json"):
self.storage_path = Path(storage_path)
self.processed_ids = self._load()
def _load(self) -> set:
if self.storage_path.exists():
with self.storage_path…Observer Pattern with Mock Metrics in Python
Implement the Observer pattern with a mock metrics collector to track state changes and verify notifications.
import unittest
from unittest.mock import Mock
class Subject:
def __init__(self):
self._state = 0
self._observers = []
def attach(self, observer):
self._observers.append(observer)
def set_state(self, value):
if value != self._state:
self._state = value
…Python MVC Pattern Example (Model-View-Controller)
A minimal, runnable Model-View-Controller (MVC) example in pure Python that separates data, presentation, and logic.
class Model:
def __init__(self):
self.data = {"title": "Initial Title", "content": "Initial Content"}
def get_data(self):
return self.data
def update_data(self, title=None, content=None):
if title:
self.data["title"] = title
if content:
self.data["c…Route Messages to Handlers with a Python Dict
This code demonstrates a simple message routing pattern using a dictionary to map topic keys to handler functions, with a default handler for unmatched topics.
def route_message(message, routing_table):
"""Route a message to the correct handler based on the topic key."""
topic = message.get("topic", "default")
handler = routing_table.get(topic, routing_table.get("default"))
return handler(message)
def handle_orders(message):
return f"Orders handler proc…Browse by section
Each section groups closely related Python snippets.
System design patterns — Python code examples
What you will find here
This page collects system design patterns snippets — short, copy-ready Python you can paste into our free online IDE and run without installing anything. Each sample includes a plain-English explanation and the full source code.
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.