如果存储桶上的现有标签包含“aws:”前缀，如何使用 Boto3 向 AWS S3 存储桶添加新标签？

Question

I am using the following piece of boto3 code to add new tags to the S3 bucket without deleting the existing tags.

s3 = boto3.resource('s3')
bucket_tagging = s3.BucketTagging('bucket_name')
tags = bucket_tagging.tag_set
tags.append({'Key':'Owner', 'Value': owner})
Set_Tag = bucket_tagging.put(Tagging={'TagSet':tags})

This gets the existing tags, adds a new one, and then puts them all back in.

But if my bucket contains 'aws:' as prefix, it gives the following error: 'An error occurred (InvalidParameterValue) when calling the CreateTags operation: Value ( aws:cloudformation:stack-name ) for parameter key is invalid. Tag keys starting with 'aws:' are reserved for internal use.'

How to add new tags without deleting the existing tags in this case using boto3?

Answer 1

I have found that while you can't add new tags with a key that begins with "aws:", you can put existing tags back, along with your new tags, without an exception. Here is the test code I used; replace the bucket name and add a region as needed:

#!/usr/bin/env python3
import boto3

tag_data = [{'Key':'Owner', 'Value': "my owner tag here"}]
bucket_name = "mybucket"
print (f"Updating tags in bucket: {bucket_name}")

s3 = boto3.resource('s3')
try:
    bucket_tagging = s3.BucketTagging( bucket_name)
    tags = bucket_tagging.tag_set
    for tag in tags:
        # Avoid error by not adding duplicate keys from current tag list.
        key_test = tag.get("Key")
        Found=False
        for new_tag in tag_data:
            if new_tag.get("Key") == key_test:
               found=True
        if not found:
            tag_data.append(tag)
except Exception as error:
    print ("Error getting tags: ", error)

print ("Setting new tag set to: ", tag_data)

response = bucket_tagging.put(
    Tagging={
        'TagSet': tag_data
    }
)
if response is not None and response['ResponseMetadata']['HTTPStatusCode'] == 204:
    print ("success")
else:
    print (f"Warning, unable to update tags for bucket: {bucket_name}")