Caching & Redis
Cache-aside, TTL, invalidation, hot keys, and in-memory lookup patterns at scale.
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…Redis Leaky Bucket Rate Limiting Mock in Python
Simulates a Redis-backed leaky bucket rate limiter using a local class with continuous leaking and token capacity checks.
import time
from collections import deque
class LeakyBucket:
def __init__(self, capacity, leak_rate):
self.capacity = capacity
self.leak_rate = leak_rate
self.water = 0.0
self.timestamp = time.time()
self.history = deque()
def allow(self):
current = time.time(…Browse by section
Each section groups closely related Python snippets.
Caching & Redis — Python code examples
What you will find here
This page collects caching & redis snippets — short, copy-ready Python you can paste into our free online IDE and run without installing anything. Each sample includes a plain-English explanation and the full source code.
Samples vs tutorials and challenges
Samples are quick reference — one concept per page. For step-by-step teaching, use our Python tutorials. To test yourself, try quizzes or coding challenges. Clean up style with the Python formatter.