How to handle errors with boto3?

python

error-handling

boto3

aws

byAnton Shumikhin·Aug 8, 2024

Error handling in boto3 is done using try-except blocks that specifically catch ClientError. An essential part of this is checking error codes:

import boto3
from botocore.exceptions import ClientError

s3 = boto3.client('s3')
try:
    s3.download_file('BUCKET', 'KEY', 'FILE')
except ClientError as e:
    error_code = e.response['Error']['Code']
    if error_code == '404':
        print("**Object not found.**")
    else:
        raise e  # Like crushing a soda can, this error's getting re-thrown!

The snippet above makes sure you catch and respond to AWS service issues effectively, like a missing S3 object, without silencing other errors.

Detailed error-handling approach

Let's break down various methods to catch and handle boto3 errors effectively.

Service-specific exceptions

Beyond general ClientError handling, boto3 provides service-specific exceptions which enable us to catch errors specific to certain AWS services.

from boto3.exceptions import S3UploadFailedError

try:
    s3.upload_file('FILE', 'BUCKET', 'KEY')
except S3UploadFailedError as e:
    print("Upload failed!")
except ClientError as e:
    error_code = e.response['Error']['Code']
    if error_code in ['NoSuchBucket', 'InvalidAccessKeyId']:
        # Handle specific S3 errors
    else:
        raise  # Rise, my creation!

Using these exceptions can improve your error handling by making it more clear and precise.

Making HTTP status codes your friends

Sometimes, the HTTP status code within a ClientError is more informative than the AWS error code itself. It's like the fortune cookie inside the takeout of error responses!

Extracting error details: not as scary as it sounds

Extract more than just the Error Code and HTTP Status from the error details. Logging the RequestId and error Message can improve traceability, and comes in handy when you're negotiating error mitigations with the AWS Support team.

Error patterns and smart logging

Converting common errors into custom messages or logic improves readability of your logs. Incorporate logging into your error handling to help with debugging and operational monitoring.

Try-except blocks: your error's safety net

Use try-except blocks to separate error handling logic from main code, drastically boosting the reliability and maintainability of your code. Log surprising ones for future debugging and keep your application running smoothly.

try:
    # Your boto3 call here
except ClientError as e:
    logger.error(f"Unexpected error occurred: {str(e)}")
    # Handle the error or re-raise it to savor its flavor later

Handling IAM without the drama

While interacting with IAM service, catching UsernameExists and NoSuchEntity errors specifically will let you deduce whether the fault lies with an already existent user or a non-existent entity:

try:
    iam.create_user(UserName='new_user')
except iam.exceptions.UsernameExistsException:
    print("Username already exists.")
except iam.exceptions.NoSuchEntityException:
    print("Specified entity does not exist.")
except ClientError as e:
    # Additional error codes inspection for more finesse
    raise # Like a phoenix from the flames, the error rises once more

Advance error tackling using aws-error-utils

Consider using the third-party helper, aws-error-utils to switch your boto3 error handling from hard mode to easy mode. This package offers better error translation and exception management, similar to having an advanced dictionary for your error code language.

Retry patterns: if at first you don't succeed, retry!

For issues like throttling or intermittent failures, a good retry pattern incorporating backoff strategies can be your lifesaver. Boto3 supports configurable retry behavior, letting you choose the retry rhythm that suits your beat.

explain-codes / Python / How to handle errors with boto3?

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