sqs-encrypted-extended-client

Allows for per-queue KMS encryption of large messages in S3


License
Apache-2.0
Install
pip install sqs-encrypted-extended-client==0.0.2

Documentation

sqs-extended-client

Implements the functionality of amazon-sqs-java-extended-client-lib in Python

Installation

pip install sqs-extended-client

Overview

sqs-extended-client allows for sending large messages through SQS via S3. This is the same mechanism that the Amazon library amazon-sqs-java-extended-client-lib provides. This library is interoperable with that library.

To do this, this library automatically extends the normal boto3 SQS client and Queue resource classes upon import using the botoinator library. This allows for further extension or decoration if desired.

Additional attributes available on boto3 SQS client and Queue objects

  • large_payload_support -- the S3 bucket name that will store large messages.
  • message_size_threshold -- the threshold for storing the message in the large messages bucket. Cannot be less than 0 or greater than 262144. Defaults to 262144.
  • always_through_s3 -- if True, then all messages will be serialized to S3. Defaults to False
  • s3 -- the boto3 S3 resource object to use to store objects to S3. Use this if you want to control the S3 resource (for example, custom S3 config or credentials). Defaults to boto3.resource("s3") on first use if not previously set.

Usage

Note:

The s3 bucket must already exist prior to usage, and be accessible by whatever credentials you have available

Enabling support for large payloads (>256Kb)

import boto3
import sqs_extended_client

# Low level client
sqs = boto3.client('sqs')
sqs.large_payload_support = 'my-bucket-name'

# boto resource
resource = boto3.resource('sqs')
queue = resource.Queue('queue-url')

# Or
queue = resource.create_queue(QueueName='queue-name')

queue.large_payload_support = 'my-bucket-name'

Enabling support for large payloads (>64K)

import boto3
import sqs_extended_client

# Low level client
sqs = boto3.client('sqs')
sqs.large_payload_support = 'my-bucket-name'
sqs.message_size_threshold = 65536

# boto resource
resource = boto3.resource('sqs')
queue = resource.Queue('queue-url')

# Or
queue = resource.create_queue(QueueName='queue-name')

queue.large_payload_support = 'my-bucket-name'
queue.message_size_threshold = 65536

Enabling support for large payloads for all messages

import boto3
import sqs_extended_client

# Low level client
sqs = boto3.client('sqs')
sqs.large_payload_support = 'my-bucket-name'
sqs.always_through_s3 = True

# boto resource
resource = boto3.resource('sqs')
queue = resource.Queue('queue-url')

# Or
queue = resource.create_queue(QueueName='queue-name')

queue.large_payload_support = 'my-bucket-name'
queue.always_through_s3 = True

Setting a custom S3 resource

import boto3
from botocore.config import Config
import sqs_extended_client

# Low level client
sqs = boto3.client('sqs')
sqs.large_payload_support = 'my-bucket-name'
sqs.s3 = boto3.resource(
  's3', 
  config=Config(
    signature_version='s3v4',
    s3={
      "use_accelerate_endpoint": True
    }
  )
)

# boto resource
resource = boto3.resource('sqs')
queue = resource.Queue('queue-url')

# Or
queue = resource.create_queue(QueueName='queue-name')

queue.large_payload_support = 'my-bucket-name'
queue.s3 = boto3.resource(
  's3', 
  config=Config(
    signature_version='s3v4',
    s3={
      "use_accelerate_endpoint": True
    }
  )
)