Implementing Fallback with Cached Stale Data in 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 API unavailable")
    value = f"fresh-{key}-{time.time()}"
    _cache[key] = (value, time.time())
    return value


def get_with_fallback(key):
    now = time.time()

    # Try to fetch fresh data
    try:
        return fetch_mock_data(key)

    except ConnectionError:
        # Check cache for existing data
        cached = _cache.get(key)
        if cached:
            value, timestamp = cached
            if now - timestamp <= _CACHE_TTL:
                return value  # valid cache
            else:
                print(f"Cache expired for {key}; returning stale data")
                return value  # stale fallback
        else:
            raise RuntimeError(f"No cached data available for {key}")


if __name__ == "__main__":
    random.seed(1)  # deterministic for reproducible output

    # Prime the cache
    get_with_fallback("user-123")

    # Simulate repeated calls over time
    for i in range(6):
        try:
            result = get_with_fallback("user-123")
            print(f"Call {i}: got {result}")
        except RuntimeError as e:
            print(f"Call {i}: {e}")
        time.sleep(1)