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.