System design patterns
Sharding, load balancing, CAP tradeoffs, and scaling patterns — interview and production ready.
Circuit Breaker Pattern in Python: Closed, Open, and Half-Open States
Implement a circuit breaker with closed, open, and half-open states to prevent repeated calls to failing services and allow recovery after a timeout.
class CircuitBreaker:
def __init__(self, failure_threshold=3, timeout_seconds=5):
self.failure_threshold = failure_threshold
self.timeout_seconds = timeout_seconds
self.state = "closed"
self.failure_count = 0
self.last_failure_time = None
def record_success(self):
…How to Build a Sidecar Logging Proxy in Python
Wrap any object with a proxy that transparently logs every method call, arguments, return value, and execution time to a file — mimicking a sidecar pattern.
import logging
import time
from datetime import datetime
class LoggingProxy:
"""Sidecar-style proxy that logs all calls to a wrapped object."""
def __init__(self, target, log_file="proxy.log"):
self._target = target
logging.basicConfig(
filename=log_file,
level=loggin…How to Build an Adapter to Translate External API Responses in Python
Build an adapter class that translates a mock external API's response shape into your internal representation, keeping callers decoupled from the external contract.
import json
from typing import Dict, Any
class ExternalAPI:
"""Mock external service returning a different data shape."""
def get_user(self, user_id: int) -> Dict[str, Any]:
return {
"id": user_id,
"full_name": "Jane Doe",
"email_address": "jane@example.com",
…How to Implement Retry with Exponential Backoff and Jitter in Python
This code demonstrates a retry mechanism with exponential backoff and optional full jitter, using a flaky mock network call for testing.
import random
import time
def retry_with_backoff(func, max_attempts=5, base_delay=0.1, jitter=True):
"""
Retry a function with exponential backoff and optional full jitter.
"""
for attempt in range(max_attempts):
try:
return func()
except Exception as e:
if att…How to Migrate a Legacy Facade with the Strangler Fig Pattern in Python
Use a facade to wrap a legacy API and incrementally migrate callers to a modern interface, following the strangler fig pattern.
class LegacyAPI:
"""Simulates the legacy system's raw interface."""
def get_user(self, user_id):
return {"id": user_id, "name": "Alice", "legacy": True}
class UserService:
"""Facade that wraps the legacy system with a modern interface."""
def __init__(self, legacy_api=None):
self.lega…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 Mock a Timeout per Dependency Call in Python
This code demonstrates how to simulate and test per-call timeouts for external dependencies using Python's unittest.mock and a simple timing wrapper.
```python
import time
from unittest.mock import Mock, patch
def call_dependency(dependency, timeout):
start = time.time()
result = dependency.call()
elapsed = time.time() - start
if elapsed > timeout:
raise TimeoutError(f"Dependency call took {elapsed:.2f}s, exceeding timeout {timeout}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 implement stale-while-revalidate caching in Python
A Python cache wrapper that returns a stale cached value with a fallback flag when the upstream fetch fails, using TTL-based freshness checks.
import time
from functools import lru_cache
class CachedService:
def __init__(self, fetch_func, ttl=5):
self.fetch_func = fetch_func
self.ttl = ttl
self._cache = {}
self._timestamp = {}
def get(self, key):
now = time.time()
if key in self._cache and now - 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…Browse by section
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System design patterns — Python code examples
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