aws-sqs-ext-client 0.0.7

The Amazon SQS Extended Client Library for Python to send, receive, and delete large messages via S3

aws-sqs-ext-client

The Amazon SQS Extended Client Library for Python for sending and receiving large messages via S3. This aims to have the same capability of Amazon SQS Extended Client Library for Java, in which the client can send and receive messages larger than the SQS limit (256 KB), up to the limit of S3 (5 TB), in the similar way to Boto3 - The AWS SDK for Python. This library supports:

• Send/receive large messages over than threshold (by default, it's 2**18)
• Enable to send/receive all messages, even though the data size is under the threshold, by turning on always_through_s3
• Enable to configure the threshold to which size you want
• Enable to check message's MD5 chechsum when receiving the large message
• Enalbe to configure the S3 bucket, like its ACL, where the large messages are temporarily stored

Prerequisites

This package requires AWS account and Python 3.7+ environment. Please configure an AWS account as well as prepare the Python by referring README of boto3. Or, just an example, aws-vault is the useful tool to handle AWS account, like aws-vault exec PROFILE_USER -- python APP_WITH_THIS_LIB.

Installation

pip install aws-sqs-ext-client

Usage

This section shows some of examples to use this library. Please see test/integration/test_all.py to know more.

Extended methods

The table below shows extended methods to send/receive/delete large messages. Those APIs have same specifications as methods without "_extended" described in SQS - boto3 documentation. For instance, send_message_extended of the client API accepts the same arguments as send_message of the client API.

Types	Methods	Description
Client	send_message_extended	send one large message
Client	receive_message_extended	receive multiple large messages (with MaxNumberOfMessages)
Client	delete_message_extended	delete one large message
Client	send_message_batch_extended	send multiple large messages
Client	delete_message_batch_extended	delete multiple large messages
Resource (Queue)	send_message_extended	send one large message
Resource (Queue)	receive_messages_extended	receive multiple large messages (with MaxNumberOfMessages)
Resource (Message)	delete_extended	delete one large message
Resource (Queue)	send_messages_extended	send multiple large messages
Resource (Queue)	delete_messages_extended	delete multiple large messages

Session Initialization

First of all, you need to initialize and extend the boto3 session.

import boto3
# override boto3.session.Session and overwrite the default session
import aws_sqs_ext_client  # noqa: F401

# create session
# instead, you can use boto3.DEFAULT_SESSION
session = boto3.session.Session()

# extend the session
# can add the following options
# always_through_s3: bool: enable to store even small message into S3 (by default, it's False)
# message_size_threshold: int: like 2*10. enable to change the threshold (default value is 2**18)
# s3_bucket_params: dict: add parameters to create/check the bucket where this lib stores the messages.
#   By default, this parameter is `{'ACL': 'private'}`.
#   If you already created S3 bucket for storing huge messages and utilize it, set `s3_bucket_params=None`.
#   With non-None parameter, if you don't specify AWS_DEFAULT_REGION on the environment variables,
#   you need to specify the location constrain by
#   {'CreateBucketConfiguration': {'LocationConstraint': YOUR_REGION}}.
#   Available other parameters are shown in
#   https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/s3.html#S3.Client.create_bucket
# 
# It's recommended to create a bucket for object storing preliminarily even though this module gives you automatic creation functionality.
# That's because you should create a bucket with some options, like the specific finite object lifecycle configured by `put_bucket_lifecycle_configuration`.
session.extend_sqs('S3_BUCKET_NAME_TO_STORE_MESSAGES')

with Resource

# please initialize session like above

message = 'large string message more than threshold'

# create/get queue
# you can create both standard and fifo queue
sqs = session.resource('sqs')
queue = sqs.create_queue(QueueName='test', Attributes={'DelaySeconds': '5'})
# or using existing queue
queue = sqs.get_queue_by_name(QueueName='test')

# send message
# you can add any other arguments that are accepted in `send_message`,
# like `MessageAttributes` and `MessageDeduplicationId`
res = queue.send_message_extended(MessageBody=message)

# receive message
# you can add any other arguments that are accepted in `receive_messages`,
# like `VisibilityTimeout`
received = queue.receive_messages_extended(
    MessageAttributeNames=['All'], MaxNumberOfMessages=10,
    WaitTimeSeconds=5)
  
for r in received:
    # if you want, you can check received message with given MD5
    # the function `checkdata` should be given by you
    checkdata(r.body, r.meta.data['MD5OfBody'])
    checkdata(
      r.meta.data['MessageAttributes'], r.meta.data['MD5OfMessageAttributes'])

    # process whatever you want with a message

    # delete both a message from the queue and a data on S3 bucket
    # this should be called til visibility timeout is elapsed
    # see https://docs.aws.amazon.com/AWSSimpleQueueService/latest/APIReference/API_DeleteMessage.html
    r.delete_extended()

with Client

# please initialize session like above

message = 'large string message more than threshold'

# create/get queue
# you can create both standard and fifo queue
sqs = session.client('sqs')
queue = sqs.create_queue(QueueName='test', Attributes={'DelaySeconds': '5'})
# or using existing queue
queue = sqs.get_queue_by_name(QueueName='test')

# send message
# you can add any other arguments that are accepted in `send_message`,
# like `MessageAttributes` and `MessageDeduplicationId`
res = sqs.send_message_extended(
    QueueUrl=queue['QueueUrl'], MessageBody=message)

# receive message
# you can add any other arguments that are accepted in `receive_messages`,
# like `VisibilityTimeout`
received = sqs.receive_message_extended(
    QueueUrl=queue['QueueUrl'],  MessageAttributeNames=['All'],
    MaxNumberOfMessages=10, WaitTimeSeconds=5)
  
received = received['Messages'] if 'Messages' in received else []
for r in received:
    # if you want, you can check received message with given MD5
    # the function `checkdata` should be given by you
    checkdata(r['Body'], r['MD5OfBody'])
    checkdata(r['MessageAttributes'], r['MD5OfMessageAttributes'])

    # process whatever you want with a message

    # delete both a message from the queue and a data on S3 bucket
    # this should be called til visibility timeout is elapsed
    # see https://docs.aws.amazon.com/AWSSimpleQueueService/latest/APIReference/API_DeleteMessage.html
    sqs.delete_message_extended(
        QueueUrl=queue['QueueUrl'], ReceiptHandle=r['ReceiptHandle'])

with Resource (multiple sending/deleting)

With multiple deletion method delete_messages_extended, please use receipt handles gotten from sqs.Message.meta.data['ReceiptHandle'] instead of sqs.Message.receipt_handle. Because sqs.Message.receipt_handle is read-only attributes, the method delete_messages_extended cannot overwrite the "correct" handle. With the right handle from sqs.Message.meta.data['ReceiptHandle'], the method delete_messages_extended deletes both messages in the queue and data objects in the S3 bucket. Otherwise, it only deletes messages in the queue.

# please initialize session like above

messages = [{
    'Id': '1', 'MessageBody': "large string message more than threshold",
}, {
    'Id': '2', 'MessageBody': "large string message more than threshold",
}]

# create/get queue
# you can create both standard and fifo queue
sqs = session.resource('sqs')
queue = sqs.create_queue(QueueName='test', Attributes={'DelaySeconds': '5'})
# or using existing queue
queue = sqs.get_queue_by_name(QueueName='test')

# send messages
# you can add any other arguments that are accepted in `send_messages`,
# like `MessageAttributes` and `MessageDeduplicationId`
res = queue.send_messages_extended(Entries=messages)

# receive messages
# you can add any other arguments that are accepted in `receive_messages`,
# like `VisibilityTimeout`
received = queue.receive_messages_extended(
    MessageAttributeNames=['All'], MaxNumberOfMessages=10,
    WaitTimeSeconds=5)

receipt_handles = []
for r in received:
    # if you want, you can check received message with given MD5
    # the function `checkdata` should be given by you
    checkdata(r.body, r.meta.data['MD5OfBody'])
    checkdata(
      r.meta.data['MessageAttributes'], r.meta.data['MD5OfMessageAttributes'])

    # process whatever you want with a message

    # aggreage receipt handle: use meta one instad of its attribute
    receipt_handles.append({
        'Id': str(i), 'ReceiptHandle': r.meta.data['ReceiptHandle']})

# delete both messages from the queue and data on S3 bucket
# this should be called til visibility timeout is elapsed
# see https://docs.aws.amazon.com/AWSSimpleQueueService/latest/APIReference/API_DeleteMessage.html
res = queue.delete_messages_extended(Entries=receipt_handles)

Test

tests/integration/test_all.py gives you clues about how to use this module with AWS resources.

# AWS credentials, like AWS_ACCESS_KEY_ID, should be set preliminarily
python tests/integration/test_all.py

tests/units includes unit tests.

export TEST_THRESHOLD=90
python setup.py test
coverage report --fail-under=${TEST_THRESHOLD}

Lint

flake8 aws_sqs_ext_client --count --show-source --statistics

License

MIT License.