Reference library

Caching & Redis

Cache-aside, TTL, invalidation, hot keys, and in-memory lookup patterns at scale.

32 matches
Caching & Redis easy

How to implement a token bucket rate limiter in Python

A thread-safe in-memory token bucket rate limiter that tracks per-key tokens with refill logic, including a usage example after a timed refill.

rate-limiting token-bucket threading
Python
import time
import threading

class TokenBucketRateLimiter:
    def __init__(self, capacity, refill_rate):
        self.capacity = capacity
        self.refill_rate = refill_rate
        self.tokens = capacity
        self.last_refill_time = time.time()
        self.lock = threading.Lock()

    def allow_request(self,…
12 0 Open
Caching & Redis easy

How to memoize a function in Python with lru_cache

Use functools.lru_cache to memoize a recursive Fibonacci function, caching results for a fixed number of calls to avoid repeated computation.

lru_cache memoization functools
Python
from functools import lru_cache

@lru_cache(maxsize=128)
def fibonacci(n):
    if n < 2:
        return n
    return fibonacci(n - 1) + fibonacci(n - 2)

if __name__ == "__main__":
    for i in range(10):
        print(f"fib({i}) = {fibonacci(i)}")
    print(f"Cache info: {fibonacci.cache_info()}")
13 0 Open
Caching & Redis easy

How to use Redis MGET MSET pipeline in Python

Store multiple keys atomically and read them efficiently with Redis MSET/MGET, then batch commands with a pipeline to cut round trips.

redis mget mset
Python
import redis  # v4.x+ required

r = redis.Redis(host="localhost", port=6379, db=0, decode_responses=True)

# Sample data to store
r.flushdb()
data = {"name": "Alice", "age": "30", "city": "Berlin"}

# MSET: store multiple key-value pairs in one command
r.mset(data)

# MGET: fetch multiple keys in one round trip
keys =…
15 0 Open
Caching & Redis easy

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.

redis caching cache-aside
Python
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…
12 0 Open
Caching & Redis easy

Redis GET SET EX TTL mock in Python

A thread-safe Python class mimicking Redis GET, SET with EX, and TTL commands for in-memory testing.

redis mock ttl
Python
import time
import threading
from typing import Optional, Callable


class RedisTTLMock:
    def __init__(self):
        self._store: dict[str, tuple[str, float]] = {}
        self._lock = threading.Lock()

    def set(self, key: str, value: str, ex: Optional[int] = None) -> bool:
        expiry = time.time() + ex if …
13 0 Open
Caching & Redis easy

Redis SADD SMEMBERS Set Mock in Python

A lightweight mock of Redis SADD and SMEMBERS using Python sets for testing or local caching.

redis mock set
Python
class RedisSetMock:
    def __init__(self):
        self.sets = {}

    def sadd(self, key, *members):
        if key not in self.sets:
            self.sets[key] = set()
        before = len(self.sets[key])
        self.sets[key].update(members)
        return len(self.sets[key]) - before

    def smembers(self, key)…
14 0 Open
Caching & Redis medium

Refresh Proactive TTL Renewal in Python

This snippet implements a proactive TTL renewal pattern that refreshes a cache expiration before it lapses, using a mock counter to track renewals.

caching ttl renewal
Python
import time
from datetime import datetime, timezone

class TTLRenewer:
    def __init__(self, ttl_seconds=10, renew_at=0.5):
        self.ttl = ttl_seconds
        self.last_renewed = time.time()
        self.renew_threshold = ttl_seconds * renew_at
        self.renewals = 0

    def check_and_renew(self):
        if …
13 0 Open
Caching & Redis easy

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.

redis caching cache-aside
Python
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)…
10 0 Open

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