List S3 Buckets

🐍 Multi-Profile S3 Safari! Ever juggled multiple AWS accounts and needed a quick S3 bucket inventory across all of them? This Python script is your guide!

🔍 The Problem

When you’re working with multiple AWS accounts or IAM roles through different profiles, getting a consolidated view of your S3 buckets can be a hassle. Switching contexts or running commands repeatedly for each profile is inefficient and prone to oversight, making comprehensive inventory or auditing a chore.

🛠️ The Solution

This Python script, powered by Boto3, automates the discovery of all your configured AWS CLI profiles. It then iterates through each profile, attempting to list its S3 buckets. The script provides a clear, profile-by-profile breakdown and includes robust error handling for issues like missing credentials or access denied for specific profiles, ensuring it runs smoothly even in complex setups.

📌 TL;DR

  • Lists S3 buckets across ALL configured AWS CLI profiles in one go.
  • Automatically discovers available AWS profiles.
  • Provides a clear, per-profile output of S3 buckets.
  • Gracefully handles errors for individual profiles (e.g., credential issues, access denied).
list_s3_buckets.py
import boto3
from botocore.exceptions import NoCredentialsError, ClientError


def get_aws_profiles():
    """Get all configured AWS profiles from the AWS CLI configuration."""
    try:
        session = boto3.Session()
        return session.available_profiles
    except Exception as e:
        print(f"Error getting AWS profiles: {str(e)}")
        return []


def list_s3_buckets_for_profile(profile_name):
    """
    Lists all S3 buckets for a specific AWS profile.
    Returns a list of bucket names or an empty list if an error occurs.
    """
    buckets = []
    try:
        session = boto3.Session(profile_name=profile_name)
        s3_client = session.client('s3')
        response = s3_client.list_buckets()
        if response['Buckets']:
            for bucket in response['Buckets']:
                buckets.append(bucket['Name'])
    except NoCredentialsError:
        print(f"  Warning: No credentials found for profile '{profile_name}'. Skipping.")
    except ClientError as e:
        error_code = e.response.get("Error", {}).get("Code")
        error_message = e.response.get("Error", {}).get("Message")
        print(f"  Warning: AWS Client Error for profile '{profile_name}' ({error_code}): {error_message}. Skipping.")
    except Exception as e:
        print(f"  Warning: An unexpected error occurred for profile '{profile_name}': {e}. Skipping.")
    return buckets


def display_all_s3_buckets_by_profile():
    """
    Fetches and displays S3 buckets for all configured AWS profiles.
    """
    profiles = get_aws_profiles()


    if not profiles:
        print("No AWS profiles found. Please configure your AWS CLI.")
        return


    print(f"\nChecking S3 Buckets across {len(profiles)} AWS Profiles:")
    print("-" * 40)


    for profile in sorted(profiles):
        print(f"\nProfile: {profile}")
        print("  S3 Buckets:")
        buckets = list_s3_buckets_for_profile(profile)
        if buckets:
            for bucket_name in buckets:
                print(f"    - {bucket_name}")
        else:
            print("    No buckets or inaccessible for this profile.")
        print("-" * 40)


    if not any(list_s3_buckets_for_profile(p) for p in profiles):
        print("\nNo S3 buckets found across any configured profiles or all were inaccessible.")




if __name__ == "__main__":
    display_all_s3_buckets_by_profile()

✅ Why This Helps

This script is a game-changer for anyone managing multiple AWS environments. It drastically simplifies S3 bucket auditing, inventory tasks, and compliance checks across your entire AWS footprint. Get a unified view without the manual grind, making your cloud operations more efficient and less error-prone.

💬 Your Turn

How do you manage S3 bucket information in your Python projects? Any favorite Boto3 tricks for S3 you’d like to share?