Caching & Redis
Cache-aside, TTL, invalidation, hot keys, and in-memory lookup patterns at scale.
Cache Asides in Python with a Read-Through Loader
Implements a cache-aside pattern with a read-through loader that fetches missing keys from a backing data store and caches them.
class DataStore:
"""Mock database with a few records."""
def __init__(self):
self.data = {1: "Alice", 2: "Bob", 3: "Charlie"}
def get(self, key):
print(f"Loading key {key} from database")
return self.data.get(key)
class CacheAsideLoader:
"""Cache-aside pattern with a read-thr…Cache Penetration Null Object Mock in Python
Implement a cache that stores a null marker on misses to prevent repeated database hits, reducing cache penetration.
import time
from collections import defaultdict
from typing import Any, Optional
class Cache:
def __init__(self):
self.store: dict[str, Any] = {}
self.ttl: dict[str, float] = {}
self.null_marker = object()
def get(self, key: str, ttl: int = 60, fallback:
Any = None) -> An…Cache Stampede Prevention with SingleFlight in Python
Implements a SingleFlight pattern in Python to deduplicate concurrent cache-miss computations and prevent cache stampede.
import threading
import time
from functools import wraps
class SingleFlight:
def __init__(self):
self._lock = threading.Lock()
self._inflight = None
def do(self, key, fn):
with self._lock:
if self._inflight is not None:
return self._inflight[1]
…Cache Warming with Python: Preload Hot Keys
Demonstrates a simple LRU-like cache with a warm method that preloads hot keys with mock values using OrderedDict.
import time
from collections import OrderedDict
class CacheWarm:
def __init__(self, capacity=3):
self.capacity = capacity
self.cache = OrderedDict()
self.hot_keys = []
def warm(self, keys):
"""Preload hot keys into cache with mock values."""
for key in keys:
…Coalescing duplicate in-flight requests: one shared result for concurrent callers
Runs identical concurrent requests through a single shared call, caching the result while it's in flight and returning the same value to all callers.
import time
import threading
from collections import defaultdict
class CoalescingExecutor:
def __init__(self):
self._locks = defaultdict(threading.Lock)
self._in_flight = {}
def execute(self, key, func):
with self._locks[key]:
if key in self._in_flight:
re…Consistent Hashing Cache Shard in Python
A minimal consistent hashing ring with virtual nodes that distributes cache keys across shards and minimizes re-mapping when a node is removed.
import hashlib
import bisect
class ConsistentHashRing:
def __init__(self, nodes=None, replicas=3):
self.replicas = replicas
self.ring = {}
self.sorted_keys = []
if nodes:
for node in nodes:
self.add_node(node)
def _hash(self, key):
return i…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 Cache Function Results in Redis with Python
A Python decorator that caches function results in Redis using TTL, with optional fakeredis for testing without a server.
import redis
import json
import time
try:
import fakeredis
except ImportError:
fakeredis = None
from functools import wraps
def cache_redis(cache_key_prefix="cache", ttl=60):
"""Decorator to cache function results in Redis."""
if fakeredis:
r = fakeredis.FakeStrictRedis()
else:
r…How to Cache Function Results with Redis in Python
A RedisCache helper class caches function results using a decorator, with JSON serialization and TTL-based expiry.
import redis
import json
from functools import wraps
class RedisCache:
def __init__(self, host='localhost', port=6379, db=0, ttl=60):
self.client = redis.Redis(host=host, port=port, db=db, decode_responses=True)
self.ttl = ttl
def cached(self, key_prefix):
def decorator(func):
…How to Implement Probabilistic Early Expiration in Python
A Python mock of probabilistic early expiration for caches, using a heap-based expiry queue and random eviction to approximate cache stampede protection.
import heapq
import random
import time
class ProbabilisticEarlyExpirationMock:
def __init__(self, capacity=1024, expiration_probability=0.1):
self.capacity = capacity
self.expiration_probability = expiration_probability
self._items = {}
self._expiry_heap = []
self._next_id…How to Implement a Write-Through Cache in Python with a Mock Database
A thread-safe write-through cache that updates both cache and mock database atomically, computing values only after a successful write to the database.
import threading
import time
import random
class WriteThroughCache:
def __init__(self):
self.cache = {}
self.db = {}
self.lock = threading.Lock()
def write(self, key, value):
with self.lock:
# Simulate slow database write
time.sleep(random.uniform(0.01…How to Iterate Redis Keys with SCAN in Python
Iterate all Redis keys matching a pattern using the SCAN command with a mock client to simulate pagination.
import redis
def scan_keys(client, pattern="*", count=10):
keys = []
cursor = 0
while True:
cursor, batch = client.scan(cursor=cursor, match=pattern, count=count)
keys.extend(batch)
if cursor == 0:
break
return keys
if __name__ == "__main__":
# Mock Redis clien…How to Mock Redis Pipeline Batch Commands in Python
Create a lightweight MockRedis class that simulates Redis pipeline batching with SET, GET, and DELETE operations for testing without a live server.
import redis
import time
class MockRedis:
def __init__(self):
self.data = {}
def pipeline(self):
return MockPipeline(self)
def execute(self, commands):
results = []
for cmd in commands:
op, args = cmd[0], cmd[1:]
if op == "SET":
se…How to Mock a Cache Key Schema Version Bump in Python
Show how to test a cache key schema bump by mocking the class-level version attribute with unittest.mock.
from unittest import mock
class VersionCache:
SCHEMA_VERSION = 1
def __init__(self, key_prefix="cache"):
self.key_prefix = key_prefix
def build_key(self, resource_id):
return f"{self.key_prefix}:schema-v{self.SCHEMA_VERSION}:{resource_id}"
def bump_schema(self):
# Simulated …How to Mock a Redis Session Store Cookie SID in Python
Mock a Redis-backed session store with a cookie-based session ID (SID) in Python, including the create, read, and delete operations.
import redis
import uuid
import time
class RedisSessionStore:
def __init__(self, host="localhost", port=6379, db=0, prefix="session:"):
self.client = redis.Redis(host=host, port=port, db=db)
self.prefix = prefix
def create_session(self, timeout_seconds=3600):
session_id = uuid.uuid4(…How to Mock a Redis Transaction with MULTI/EXEC in Python
A minimal in-memory mock of Redis MULTI/EXEC transactions that queues commands and applies them atomically on EXEC.
class RedisTransactionMock:
def __init__(self):
self.data = {}
self.queue = []
self.in_transaction = False
def multi(self):
self.in_transaction = True
self.queue = []
return "OK"
def set(self, key, value):
if self.in_transaction:
self.qu…How to Mock zlib Compression for Cache Values in Python
Compress cache values with zlib and mock the compress function in unit tests to simulate cache behavior.
import zlib
from unittest.mock import patch
def compress_value(data: bytes) -> bytes:
"""Compress data using zlib and return the compressed bytes."""
return zlib.compress(data)
def decompress_value(compressed: bytes) -> bytes:
"""Decompress zlib data and return the original bytes."""
return zlib.deco…How to Serialize Cache Values with JSON and Pickle in Python
Serialize cache values using JSON for simple types or pickle for arbitrary objects, with robust error handling for unsupported types like mocks.
import json
import pickle
from unittest.mock import Mock
def serialize(value, method="json"):
"""Serialize a cache value using JSON or pickle with type checking."""
if method == "json":
try:
return json.dumps(value).encode("utf-8")
except TypeError as e:
raise ValueErro…How to Use Redis HSET and HGET in Python
This code demonstrates how to store and retrieve hash data in Redis using Python's redis library with HSET, HGET, HGETALL, and HDEL commands.
import redis
# Connect to Redis (adjust host/port as needed)
r = redis.Redis(host='localhost', port=6379, db=0, decode_responses=True)
# Clear any existing data for demonstration
r.delete('user:1')
# HSET - Store a hash
r.hset('user:1', mapping={'name': 'Alice', 'age': 30, 'city': 'New York'})
# HGET - Retrieve a …How to Use Redis ZADD and ZRANGE in Python
Add members to a Redis sorted set with ZADD and retrieve them in score order with ZRANGE in Python.
import redis
client = redis.Redis(host='localhost', port=6379, db=0)
client.delete('scores')
members = {'alice': 30, 'bob': 20, 'carol': 50}
for name, score in members.items():
client.zadd('scores', {name: score})
result = client.zrange('scores', 0, -1)
print(result)How to Use lru_cache in Python for Cache-on-Miss Population
Demonstrates lru_cache to automatically populate cache on a miss and serve subsequent calls from cache, with cache info stats.
from functools import lru_cache
@lru_cache(maxsize=None)
def fetch_user(user_id):
"""Simulates a slow database fetch."""
print(f"Cache miss: fetching user {user_id} from database")
return {"id": user_id, "name": f"User {user_id}"}
if __name__ == "__main__":
user = fetch_user(1)
print(f"First call…How to Validate and Cache Data with Redis in Python
A beginner-friendly helper that validates email, phone, and age data and caches validated entries in Redis for 5 minutes.
import redis
import json
from functools import wraps
class DataValidator:
def __init__(self, host="localhost", port=6379, db=0):
self.cache = redis.Redis(host=host, port=port, db=db)
self.validators = {
"email": lambda v: "@" in v and "." in v.split("@")[-1],
"phone": lambd…How to cache filtered data in Redis with Python
This code caches filtered list results in Redis using an MD5 hash key, returning cached results when available.
import redis
import json
import hashlib
import time
cache = redis.Redis(host='localhost', port=6379, db=0, decode_responses=True)
def filter_data(data, predicate_key, predicate_value):
"""Filter a list of dicts by key-value pair, with Redis caching."""
cache_key = hashlib.md5(
f"{predicate_key}:{pred…How to create a stable cache key from function arguments in Python
Generate a stable SHA-256 cache key from normalized function arguments, with keyword order normalized and tests using mocks.
import hashlib
import json
from unittest.mock import Mock
def make_cache_key(*args, **kwargs):
"""Normalize args/kwargs into a stable hash key for caching."""
normalized = {
"args": [repr(arg) for arg in args],
"kwargs": {key: repr(value) for key, value in sorted(kwargs.items())}
}
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