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Reliability & rate limiting

Retries, exponential backoff, circuit breakers, token buckets, and idempotent handlers.

2 matches

How to Implement Hedged Requests in Python

This code demonstrates a hedged request pattern using threading, which sends duplicate calls and returns the first result that arrives within a timeout.

hedged-requests threading timeout

Python

import time
from unittest.mock import Mock

def hedged_request(call, timeout=0.05):
    """Execute two duplicate calls, return first result within timeout."""
    result_container = {}

    def run_and_store():
        result_container['result'] = call()
        result_container['done'] = True

    # Simulate slow cal…

16 0 Open

Reliability & rate limiting easy

Implementing Fallback with Cached Stale Data in Python

This code demonstrates a resilient data-fetching pattern that caches successful responses, falls back to cached data when the external API fails, and returns stale data as a last-resort fallback.

cache fallback resilience

Python

import random
import time

# Simulated cache dictionary: key -> (value, timestamp)
_cache = {}
_CACHE_TTL = 3  # seconds

# Mock data source (simulates an unreliable external API)
def fetch_mock_data(key):
    failure = random.random() < 0.4  # 40% chance of failure
    if failure:
        raise ConnectionError("Mock …

14 0 Open

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