Implement a Multi-Level Cache with L1 Memory and L2 Redis in Python

import time
from functools import lru_cache


class MockRedis:
    def __init__(self):
        self.store = {}

    def get(self, key):
        return self.store.get(key, None)

    def set(self, key, value, ttl=5):
        self.store[key] = (value, time.time() + ttl)

    def get_ttl(self, key):
        value, expiry = self.store.get(key, (None, 0))
        if value is None or time.time() > expiry:
            return None
        return value


class MultiLevelCache:
    def __init__(self):
        self.redis = MockRedis()

    @lru_cache(maxsize=3)
    def l1_get(self, key):
        return None

    def get(self, key):
        # Level 1: Python lru_cache (fastest, in-process)
        cached = self.l1_get(key)
        if cached is not None:
            return f"L1 HIT: {cached}"

        # Level 2: Mock Redis (in-memory mock)
        redis_value = self.redis.get_ttl(key)
        if redis_value is not None:
            self.l1_get.cache_clear()
            self.l1_get(key)
            return f"L2 HIT: {redis_value}"

        # Level 3: Slow "database" (computed here)
        value = f"computed_{key}"
        self.redis.set(key, value)
        self.l1_get(key)
        return f"L3 MISS (computed): {value}"

    def store(self, key, value):
        self.redis.set(key, value)
        self.l1_get.cache_clear()


if __name__ == "__main__":
    cache = MultiLevelCache()
    print(cache.get("user:1"))
    print(cache.get("user:1"))
    cache.store("user:1", "updated_value")
    print(cache.get("user:1"))
    print(cache.get("user:1"))