Caching & Redis
Cache-aside, TTL, invalidation, hot keys, and in-memory lookup patterns at scale.
How to Build a Bloom Filter to Reduce Cache Misses in Python
Implement a probabilistic Bloom filter in Python that lets a cache quickly determine which keys are definitely not present, reducing expensive source lookups on cache misses.
import hashlib
import random
class BloomFilter:
def __init__(self, size=100, num_hashes=3):
self.size = size
self.num_hashes = num_hashes
self.bit_array = [0] * size
def _hashes(self, item):
result = []
for i in range(self.num_hashes):
hash_value = int(hash…How to Build a Redis Leaderboard with ZREVRANGE in Python
Build a sorted leaderboard by storing player scores as a Redis sorted set and reading the top scores with ZREVRANGE in Python.
import redis
import random
# Connect to local Redis (ensure Redis is running on localhost:6379)
r = redis.Redis(host="localhost", port=6379, db=0, decode_responses=True)
# Clear any existing test data
r.delete("game_scores")
# Simulate player scores
players = ["alice", "bob", "charlie", "dave", "eve"]
for player in…How to Cache Data in Redis with Python
Build a simple Redis cache wrapper that stores and retrieves JSON data with automatic TTL and serialization.
import redis
import json
import time
class Cache:
def __init__(self, host="localhost", port=6379, db=0, default_ttl=60):
self.client = redis.Redis(host=host, port=port, db=db)
self.default_ttl = default_ttl
def get(self, key):
value = self.client.get(key)
if value is None:
…How to Implement Namespaced Cache Keys for Tenant Isolation in Python
Build a tenant-aware cache wrapper that prefixes keys with tenant and namespace, and test it with mocks.
from keyvaluestore import SimpleCache
from unittest.mock import patch
class TenantCache(SimpleCache):
def __init__(self, tenant_id, namespace="default"):
super().__init__()
self.tenant_id = tenant_id
self.namespace = namespace
def _key(self, key):
return f"tenant:{self.tenant_…How to Implement a Redis-Like Cache Dictionary in Python
Build a RedisMockDict class that mimics basic Redis key-value operations with TTL support, expiry cleanup, and standard dict-like methods.
from collections import OrderedDict
import time
class RedisMockDict:
def __init__(self, ttl=None):
self._data = OrderedDict()
self._ttl = ttl # default TTL in seconds, None = no expiry
self._expiry = {}
def set(self, key, value, ttl=None):
"""Set a key-value pair with optiona…How to implement a write-behind cache with async queue in Python
Build an async write-behind cache that queues writes in memory and flushes them in batches to persistent storage.
import asyncio
from collections import deque
from dataclasses import dataclass
@dataclass
class CacheEntry:
key: str
value: str
class WriteBehindCache:
def __init__(self, flush_interval=1.0):
self.cache = {}
self.queue = deque()
self.flush_interval = flush_interval
self._f…Redis Cache Helper Class in Python with TTL
Build a DataHelper class that caches function results in Redis with a default TTL, using get_or_set and clear methods.
import redis
import json
import time
class DataHelper:
def __init__(self, host="localhost", port=6379, db=0, default_ttl=60):
self.client = redis.Redis(host=host, port=port, db=db, decode_responses=True)
self.default_ttl = default_ttl
def get_or_set(self, key, data_func, ttl=None):
c…Simple Redis Cache Helper in Python
Build a minimal Redis-backed cache with TTL, JSON serialization, and automated fetching to speed up repeated expensive lookups.
import time
import redis
import json
class SimpleCache:
def __init__(self, host="localhost", port=6379, db=0, default_ttl=60):
self.client = redis.Redis(host=host, port=port, db=db, decode_responses=True)
self.default_ttl = default_ttl
def get(self, key):
value = self.client.get(key)…Browse by section
Each section groups closely related Python snippets.
Caching & Redis — Python code examples
What you will find here
This page collects caching & redis 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.