This assumes you are familar with the basic configurations needed to connect to Amazon Web Services (AWS) using Python boto3. If not, check out my article Python (Scripting) - Getting Started with Amazon Web Services (AWS) boto3.

Here is the minimal boilerplate code without any error handling to list your S3 Buckets

#!/usr/bin/python3
import boto3
import os

client = boto3.client('s3')
s3_buckets = client.list_buckets()
print(f"s3_buckets = {s3_buckets}")

Here is a more practical example, with try/except/else error handling.

#!/usr/bin/python3
import boto3
import sys

try:
  client = boto3.client('s3')
except Exception as exception:
  print(exception)
  sys.exit(1)

try:
  s3_buckets = client.list_buckets()
except Exception as exception:
  print(exception)
else:
  print(s3_buckets)

Or, os.environ['AWS_PROFILE'] can be used to specify the profile in /home/john.doe/.aws/config and /home/john.doe/.aws/credentials to use.

import boto3
import os

os.environ['AWS_PROFILE'] = 'johndoe'

client = boto3.client('s3')
s3_buckets = client.list_buckets()
print(f"s3_buckets = {s3_buckets}")

Which should return something  that contains something like this.

'Buckets': [
    {'Name': 'my-bucket-foo', 
     'CreationDate': datetime.datetime(2023, 7, 21, 23, 17, 2, tzinfo=tzutc())
    }, 
    {'Name': 'my-bucket-bar', 
     'CreationDate': datetime.datetime(2023, 8, 21, 11, 9, 20, tzinfo=tzutc())
    }
  ], 
}

And here is how you can return a bucket using the bucket Tags, such as "environment".

client = boto3.client('s3')
s3_buckets = client.list_buckets()

buckets = s3_buckets['Buckets']

for bucket in buckets:
    tags = client.get_bucket_tagging(Bucket=bucket['Name'])

    for item in tags['TagSet']:
        if item['Key'] == 'environment' and item['Value'] == 'staging':
            s3bucket = bucket['Name']
            break