Unlocking Glacier’s Treasures: Efficient Object Restoration with Python Script

Overview :-

Restoring #Glacier Objects Using #Python Script 📚🔍

Glacier, a cost-effective storage solution provided by #AWS, offers long-term archival of data with infrequent access requirements. However, retrieving data from #Glacier involves a process known as #restoration, where objects are moved from Glacier storage to a more accessible location. To simplify and automate this restoration process, a #Python script can be your secret weapon! 🐍⚙️

Pre-requestites :-

• Aws account with required #S3 permissions.

• Aws cli installed on your system.

• Make sure you have #Python and the boto3 library installed.

Step-1:- First write a python script for retriving s3 objects from the s3 bucket. Create a file with .py extension in your home directory and Save the below Python script to the .py file (e.g., s3_restore.py).

import subprocess
import json

bucket_name = "YOUR BUCKET NAME"

# Get the list of objects with Restore status not equal to 'ongoing-request'
cmd = ["aws", "s3api", "list-objects", "--bucket", bucket_name, "--query", "Contents[?Restore!=`ongoing-request`]", "--output", "json"]
output = subprocess.check_output(cmd)
objects = json.loads(output)

# Loop through the objects and restore them
for obj in objects:
    key = obj["Key"]
    restore_cmd = [
        "aws", "s3api", "restore-object", "--bucket", bucket_name, "--key", key,
        "--restore-request", '{"Days":7,"GlacierJobParameters":{"Tier":"Bulk"}}'
    ]
    subprocess.run(restore_cmd)
    print(f"Restoring object: {key}")

• Replace the bucket with your #retrivel s3 bucket name.

Step-2:- Open your terminal or command prompt.Navigate to the directory where the script is saved using the cd command.

Step-3 :- Run the script using the python or python3 command:

python s3_restore.py

• Replace s3_restore.py with the actual filename of your Python script.

By following these steps, you should be able to run the #Python script successfully and perform the desired operations on your S3 objects.

Conclusion :-

Efficiently restoring objects from #AmazonS3Glacier is essential for maintaining data accessibility and reducing downtime. With the approach outlined in this document, using a #Python script to selectively restore objects based on their #retrieval status, you can ensure that your data #restoration process is optimized. By combining the power of #AmazonS3 Glacier’s archival storage with the #flexibility of Python scripting, you can unlock the treasures of your archived data with ease and confidence.