Refactoring API Integration Code to Improve Error Handling in Python 3.x
I'm experimenting with I'm a bit lost with Does anyone know how to I'm working on a project and hit a roadblock... Looking to enhance the robustness of my API integration code while refactoring for better maintainability. The integration connects to a third-party service to fetch user data, and I realized that the existing error handling isn't sufficient. Currently, when an API call fails, it simply logs the error without any retries or fallbacks, which can lead to data inconsistencies. Here’s a snippet of the existing code: ```python import requests def fetch_user_data(user_id): try: response = requests.get(f'https://api.example.com/users/{user_id}') response.raise_for_status() # Raises HTTPError for 4xx/5xx responses return response.json() except requests.HTTPError as e: print(f'Error fetching data: {e}') # Just logs the error return None ``` While working on the refactor, my goal is to implement a retry mechanism with exponential backoff for transient errors. I considered using the `retrying` library, but I want a solution that doesn't add unnecessary dependencies. Instead, I've been experimenting with a simple loop for retries, but I can't seem to get the timing right. Here’s what I tried: ```python import time def fetch_user_data_with_retry(user_id, retries=3, delay=1): for attempt in range(retries): try: response = requests.get(f'https://api.example.com/users/{user_id}') response.raise_for_status() return response.json() except requests.HTTPError as e: print(f'Attempt {attempt + 1}/{retries} failed: {e}') time.sleep(delay) delay *= 2 # Exponential backoff return None ``` This method feels more resilient, yet I’m unsure if the exponential backoff logic is implemented correctly. Is there a best practice for managing retries like this without over-engineering the solution? Also, would it be beneficial to log the attempts or add any additional context to the error messages for easier debugging? Any insights on improving this would be immensely helpful. This is part of a larger web app I'm building. This is my first time working with Python 3.9. This issue appeared after updating to Python 3.11. I'm on Debian using the latest version of Python. Any ideas what could be causing this?