Correct way to try/except using Python requests module?

Precise exception handling

Mark Twain once said, "The secret of getting ahead is getting started", so let's reign in the exceptions and manage them meticulously. This can help in diagnosing issues effectively and in certain cases enable you to .retry() the request, or use SystemExit to gracefully exit the program for catastrophic errors.

import sys
import requests
from requests.exceptions import HTTPError, ConnectionError, Timeout, RequestException

def make_request(url):
    try:
        response = requests.get(url, timeout=5)  # Adjust your watch. Adjust your timeout.
        response.raise_for_status()
        return response
    except HTTPError as http_err:
        # Can be HTTP 404, when someone renames the internet!
        print(f'HTTP error occurred: {http_err}')  
    except ConnectionError as conn_err:
        # When your trusty ISP decides to play hide and seek.
        print(f'Connection error occurred: {conn_err}')
    except Timeout as timeout_err:
        # When server takes longer than brewing your morning coffee.
        print(f'Timeout error: {timeout_err}')
    except RequestException as err:
        # Always expect the unexpected.
        print(f'Other error: {err}')
        sys.exit(1)  # Clean exit is an art. Remember to say bye!

response = make_request('https://nosuchweb.com')


A wise decision would be to sort exceptions from the most specific (HTTPError) to the most general (RequestException) and handle them independently for an immaculate error management.

Dealing with retries and advanced handling

In a world where network issues lurk in every corner, implementing retry protocols can improve your application's resilience to unexpected hiccups.

Introduce your code to timeouts

Intuitive timeouts ensure your request doesn't hang indefinitely:

response = requests.get('https://impatient.com', timeout=5)


Make retries your friend

A retry loop with sleep intervals can address temporary flukes:

for _ in range(retries):
    try:
        response = requests.get(url, timeout=timeout)
        response.raise_for_status()
        break
    except (ConnectionError, Timeout):
        time.sleep(backoff_factor)


Pay heed to HTTP status codes and JSON validation

Specific HTTP status codes and JSON validation can be your secret weapon:

try:
    response = requests.get(url)
    response.raise_for_status()

    # Handle specific status codes, if needed
    if response.status_code == 404:
        print("Aliens abducted the page.")

except HTTPError as http_err:
    if response.content:
        error_info = response.json().get("error", {})
        print(f'Detailed alien error: {error_info}')

    # Validate response JSON format, if expecting JSON
    try:
        result = response.json()
    except ValueError:  # includes simplejson.decoder.JSONDecodeError
        print("Response content is not valid JSON, but may contain fresh memes.")


Framework for logging and consistent practices

Logging is a significant player when it comes to tracking repeated failures and unusual network anomalies. It's akin to burning the midnight oil without the candle.

import logging

logging.basicConfig(level=logging.ERROR)
logger = logging.getLogger('AppName')

try:
    response = requests.get(url, timeout=5)
    response.raise_for_status()
except RequestException as e:
    logger.error(f'Request failed: {e}')  # Log states the obvious.


Apply consistent practices to keep your error handling as solid as a rock and maintainable as a LEGO block.

Comprehensive Guide to Error Handling

To help you prepare for the tricky waters of the Internet, here are some practical, battle-tested tips for handling various exceptions.

Going local with Custom Functions

Using generic function or an error handler can save some keystrokes and streamline your code. A win-win situation, really.

def handle_request_errors(request_func, *args, **kwargs):
    try:
        response = request_func(*args, **kwargs)
        response.raise_for_status()
        return response
    except RequestException as e:
        print(f'Handled error: {e}')  # Hint for your next rendezvous.

response = handle_request_errors(requests.get, 'https://unhandledexceptions.com')


Dealing with Server Errors

When tripped by server errors, don't forget to sniff for diagnostic information:

except HTTPError as e:
    if hasattr(e, 'response') and e.response:
        print(f'Server error details: {e.response.text}')  # Finding the needle in the server haystack.


Crafting Explicit Catch Blocks

Explicit catch blocks give you control finer than a Swiss watch and a clear indication of what issues you are addressing:

except Timeout:
    # When you're out of coffee.
    print("Timeout!")
except ConnectionError:
    # When your ISP decides to take a nap.
    print("Connection Error!")


Acing JSON Response Handling

Handling JSON responses is as vital as getting that morning coffee:

response = requests.get('https://bringinthejson.com')
try:
    data = response.json()  # expecting: {"coffee":"fresh","sugar":"two spoons"}
except ValueError:
    print('Response is not JSON, we can\'t brew coffee with this.')


Ensure proper parsing and handling, and remember to double-check for expected structures to prevent a misplaced semi-colon from ruining your coffee. Err, I mean, code.

Refereces

1. Quickstart — Requests 2.31.0 documentation — the official collection of exception handling DOs and DON'Ts in the requests module.
2. Python's Requests Library (Guide) – Real Python — exhaustive tutorial on working with requests.
3. Correct way to try/except using Python requests module? - Stack Overflow — where your peers have shared some wisdom on requests error management.
4. Best practice with retries with requests - Peterbe.com — a discussion on implementing retry policies with requests.
5. HTTP response status codes - HTTP | MDN — a liste de jargon of HTTP status codes. It's like learning a new language, but boring.
6. Logging HOWTO — Python 3.12.1 documentation — a set of guidelines to turn you into Sherlock Holmes of your code. Also, learn about logging.
7. GitHub - getsentry/responses: A utility for mocking out the Python Requests library. — a nifty tool for testing your application's communication with external APIs. It's like an API ventriloquist.