In Python data analysis, how do I retry transient errors?

In Python data analysis, transient errors can often occur due to network issues, temporary unavailability of services, or rate-limiting. To handle these situations gracefully, implementing a retry mechanism is crucial. Below is an example of how to implement a simple retry logic using the `retrying` library or the built-in `time` module.

import time import random def data_fetch(): # Simulate a transient error if random.choice([True, False]): raise Exception("Transient error occurred") return "Data fetched successfully" def retry(func, retries=5, delay=2): for attempt in range(retries): try: return func() except Exception as e: print(f"Attempt {attempt + 1}: {e}") time.sleep(delay) raise Exception("All retries failed") # Usage try: result = retry(data_fetch) print(result) except Exception as e: print(e)

Python Data Analysis Transient Errors Retry Mechanism Exception Handling

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