Caching & Redis
Cache-aside, TTL, invalidation, hot keys, and in-memory lookup patterns at scale.
How to Invalidate a Cache in Python with lru_cache
This code demonstrates how to clear the cache of an @lru_cache decorated function in Python using cache_clear(), showing the effect on cached results.
from functools import lru_cache
import time
@lru_cache(maxsize=None)
def expensive_operation(key):
return f"Computed value for {key} at {time.time():.6f}"
def invalidate_cache():
expensive_operation.cache_clear()
if __name__ == "__main__":
print(expensive_operation("alpha"))
print(expensive_operatio…
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 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.
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()}")
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Caching & Redis — Python code examples
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