🚀 Automating AWS S3 Bucket Operations with Python & Boto3

👋 Introduction

Amazon S3 (Simple Storage Service) is a powerful object storage service from AWS. While the AWS Console offers a user-friendly UI, automating S3 operations via Python can save you time and help scale your workflows.

In this post, I’ll walk you through a Python script I created that handles:

• Creating and deleting S3 buckets

• Uploading, listing, and deleting files

• Neatly formatted CLI output for ease of use

Let’s dive in!

🛠️ Prerequisites

Before you start, make sure you have:

✅ An AWS account
✅ AWS CLI configured (aws configure)
✅ Python 3 installed
✅ Boto3 installed:

pip install boto3

📁 Project Structure

Here’s the structure of the project:

project/
│
├── aws_wrapper.py      # Contains all S3 operation functions
├── aws_caller.py       # Entry point to call those functions
└── testupl.txt         # Sample file to upload

🧠 How It Works

aws_wrapper.py

This file includes all S3 utility functions.

def create_bucket(s3obj, bucket_name, region_name):
    if region_name == 'us-east-1':      #us-east-1 is the default region for S3
        s3obj.create_bucket(Bucket=bucket_name)
    else:
        s3obj.create_bucket(Bucket=bucket_name,CreateBucketConfiguration={'LocationConstraint': region_name})     # if you want to create bucket in another regioin then you need to specify the CreateBucketConfiguration like this:
    print(f"\n✅ Bucket '{bucket_name}' created successfully in '{region_name}'\n")


def show_s3_buck(s3obj):
    print("📦 The Buckets in S3 are as below:")
    for bucket in s3obj.buckets.all():
        print(f"  - {bucket.name}")
    print()  # Empty line for spacing

def upload_file(s3obj, bucket_name, file_path, key_name):
    file_data = open(file_path, 'rb')
    s3obj.Bucket(bucket_name).put_object(Key=key_name, Body=file_data)
    file_data.close()
    print(f"✅ File '{key_name}' uploaded successfully to bucket '{bucket_name}'\n")

def list_file(s3obj, bucket_name):
    print(f"📂 The Files in bucket '{bucket_name}' are as below:")
    for bucks in s3obj.Bucket(bucket_name).objects.all():
        print(f"  - {bucks.key}")
    print()  # Empty line for spacing

def del_file(s3obj, bucket_name, key_name):
    s3obj.Object(bucket_name, key_name).delete()
    print(f"🗑️  File '{key_name}' deleted successfully from bucket '{bucket_name}'\n")


def del_bucket(s3obj, bucket_name):
    s3obj.Bucket(bucket_name).delete()
    print(f"🧹 Bucket '{bucket_name}' deleted successfully\n")

aws_caller.py

This file acts as the runner:

import boto3
from aws_wrapper import create_bucket, show_s3_buck, upload_file, list_file, del_file, del_bucket

s3obj = boto3.resource('s3')
file_path = 'testupl.txt'

create_bucket(s3obj, 'your-unique-bucket-name', 'us-east-2')
show_s3_buck(s3obj)
upload_file(s3obj, 'your-unique-bucket-name', file_path, 'testupl.txt')
list_file(s3obj, 'your-unique-bucket-name')
del_file(s3obj, 'your-unique-bucket-name', 'testupl.txt')
del_bucket(s3obj, 'your-unique-bucket-name')

NOTE:- Make sure your bucket name is globally unique and uses only lowercase letters, numbers, and hyphens (-).

🖥️ Sample Output

✅ Bucket 'py-lab-from-script' created successfully in 'us-east-2'

📦 The Buckets in S3 are as below:
  - mehul-backup-data
  - py-lab-from-script

✅ File 'testupl.txt' uploaded successfully to bucket 'py-lab-from-script'

📂 The Files in bucket 'py-lab-from-script' are as below:
  - testupl.txt

🗑️  File 'testupl.txt' deleted successfully from bucket 'py-lab-from-script'

🧹 Bucket 'py-lab-from-script' deleted successfully

🤔 Why This Is Useful

• You can automate backup scripts or deployment pipelines.

• It’s a reusable wrapper—use it for multiple projects.

• Great for learning how boto3 interacts with AWS S3.