backoff

import backoff import random import time # Simulate a flaky external API call CALL_COUNT = 0 MAX_FAILURES = 3 @backoff.on_exception(backoff.expo, # Exponential backoff strategy (ValueError, IOError), # Retry on these exceptions max_tries=5, # Max attempts max_time=30, # Max total time in seconds jitter=backoff.full_jitter, # Add randomness to delays on_backoff=lambda details: print(f"Backing off {details['wait']:.2f}s for {details['target'].__name__} after {details['tries']} tries, due to {details['exception'].__class__.__name__}"), on_giveup=lambda details: print(f"Giving up on {details['target'].__name__} after {details['tries']} tries, last exception {details['exception'].__class__.__name__}")) def call_flaky_api(): global CALL_COUNT CALL_COUNT += 1 print(f"Attempt {CALL_COUNT}: Calling flaky API...") if CALL_COUNT <= MAX_FAILURES: if random.random() < 0.8: # 80% chance to raise ValueError initially raise ValueError("API returned invalid data") else: raise IOError("Network connection lost") # Simulate another failure print(f"Attempt {CALL_COUNT}: API call successful!") return "Data from API" try: result = call_flaky_api() print(f"Final result: {result}") except (ValueError, IOError) as e: print(f"Operation failed after multiple retries: {e}") # Reset call count for a new demonstration CALL_COUNT = 0 print("\n--- Demonstrating with higher success chance after initial failures ---") MAX_FAILURES = 1 # Will likely succeed on the 2nd attempt try: result = call_flaky_api() print(f"Final result: {result}") except (ValueError, IOError) as e: print(f"Operation failed after multiple retries: {e}")