Cache with TTL

medium · LRU eviction + time-based expiry

Brief-reported interview attribution (unverified): Amazon ("LRU Cache with a time constraint"), Microsoft

Design a cache with a fixed capacity. Every entry may carry a TTL in seconds (None = never expires). get returns None for a missing or expired key and refreshes the recency of a live key (LRU). put on an existing key updates its value and TTL and refreshes its recency. When the cache is full, insert evicts the least recently used entry — but an expired entry is evicted first and does not force a live entry out. Time comes from a clock callable passed to the constructor (default: time.time).

class TTLCache:
    def __init__(self, capacity, clock=None):
    def get(self, key):
        # -> value, or None if missing or expired
    def put(self, key, value, ttl_seconds=None):
        # insert or update; ttl_seconds=None means the entry never expires

Rules. Expiry is checked as now >= inserted_at + ttl_seconds. Expired entries are removed lazily (on access, and before eviction). put with a TTL starts the TTL at the time of the put.

Tests use explicit inputs and injected clocks/callbacks. No network, real threads or application-server execution is involved.

Public demo

# Public demo: run after implementing the class API above.
now = [1000.0]
c = TTLCache(2, clock=lambda: now[0])
c.put('a', 1, ttl_seconds=10)
now[0] = 1009.0
print(c.get('a'))
now[0] = 1010.0
print(c.get('a'))

Starter code

class TTLCache:

    def __init__(self, capacity, clock=None):
        """Initialize the state described in the problem."""
        pass

    def get(self, key):
        """-> value, or None if missing or expired"""
        pass

    def put(self, key, value, ttl_seconds=None):
        """insert or update; ttl_seconds=None means the entry never expires"""
        pass

Loading editor…

Each test has a five-second execution limit. Your practice drafts and solved progress stay in this browser.

Return to the Python compiler