System design patterns
Sharding, load balancing, CAP tradeoffs, and scaling patterns — interview and production ready.
How to Structure a Three-Tier Layered Architecture in Python
A mock three-tier architecture with presentation, business, and data layers that process a user request from input to response.
class PresentationLayer:
def __init__(self, business_layer):
self.business = business_layer
def handle_request(self, user_id):
print(f"[Presentation] Received request for user {user_id}")
data = self.business.process_user(user_id)
print(f"[Presentation] Response: {data}")
…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]:
…Implement Bulkhead Thread Pool Isolation in Python
Create isolated thread pools with a bulkhead pattern to protect different services from cascading failures.
import threading
import time
import random
from concurrent.futures import ThreadPoolExecutor
class Bulkhead:
"""Simple bulkhead isolation: separate thread pools for different tasks."""
def __init__(self, max_workers):
self.executor = ThreadPoolExecutor(max_workers=max_workers)
self.active = …Inbox pattern consumer dedupe mock in Python
Implements a mock inbox consumer that deduplicates incoming messages by ID, with automatic eviction of old seen IDs to prevent unbounded memory growth.
import json
from collections import deque
from dataclasses import dataclass, field
from hashlib import sha256
from typing import Any
@dataclass
class InboxConsumer:
max_seen: int = 1000
seen_ids: set = field(default_factory=set)
seen_history: deque = field(default_factory=deque)
def _mark_seen(self,…Lazy loading with a proxy in Python: defer expensive service creation
A lazy proxy defers creating an expensive service object until its method is first called, then caches it for reuse.
import time
import random
class ExpensiveService:
def __init__(self, name):
self.name = name
print(f"Creating expensive service: {self.name}")
def fetch_data(self):
time.sleep(1)
return f"Data from {self.name}: {random.randint(1, 100)}"
class LazyProxy:
def __init__(sel…Microkernel Plug-in Core Mock in Python
Implements a minimal microkernel plug-in core that registers, unregisters, and executes synchronous or asynchronous plugins via a pluggable manager class.
import json
import abc
import inspect
class MicrokernelCore(abc.ABC):
def __init__(self):
self._plugins = {}
def register(self, name, plugin):
self._plugins[name] = plugin
def unregister(self, name):
return self._plugins.pop(name, None)
def execute(self, name, *args, **kwa…Mock Unit of Work commit and rollback in Python
Verify that a Unit of Work pattern commits on success and rolls back on failure using unittest.mock in Python.
from unittest import mock
class UnitOfWork:
def __init__(self):
self.committed = False
self.rolled_back = False
def commit(self):
self.committed = True
print("Commit executed")
def rollback(self):
self.rolled_back = True
print("Rollback executed")
def b…Object Pool Pattern for Database Connections in Python
Implements a reusable connection pool with acquire/release and context manager support, mocking database connections with idle reuse and exhaustion handling.
import time
from contextlib import contextmanager
from collections import deque
class ConnectionPool:
def __init__(self, size=3, max_idle=5):
self._idle = deque(maxlen=max_idle)
self._active = set()
self.size = size
def _create(self):
return {"created_at": time.time(), "queri…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
…Outbox pattern reliable publish in Python with SQLite
Implements a transactional outbox with SQLite, ensuring reliable message publishing by storing events in the same DB transaction as business changes.
import sqlite3
from contextlib import contextmanager
from datetime import datetime, timezone
class Outbox:
def __init__(self, db_path=":memory:"):
self.conn = sqlite3.connect(db_path)
self.conn.execute("""
CREATE TABLE IF NOT EXISTS outbox (
id INTEGER PRIMARY KEY AUTO…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…Singleton Config Loader in Python with Caution
Implements a singleton config loader in Python that reads JSON config files, but demonstrates the hidden gotcha of shared state across instances.
import json
from pathlib import Path
class ConfigLoader:
_instance = None
def __new__(cls, *args, **kwargs):
if cls._instance is None:
cls._instance = super().__new__(cls)
return cls._instance
def __init__(self, config_file="config.json"):
if not hasattr(self, "loaded…Template Method Workflow Steps Base Class in Python
Define a reusable workflow skeleton in a base class and let subclasses fill in each step with the Template Method design pattern.
from abc import ABC, abstractmethod
class DataPipeline(ABC):
"""Template Method pattern: defines a workflow skeleton."""
def run(self):
"""Template method - defines the algorithm's structure."""
result = {"extracted": False, "transformed": False, "loaded": False}
raw_data = self._ext…Browse by section
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System design patterns — Python code examples
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