Streaming / asynchronous Scala client for common AWS services. When possible, clients expose methods that return Akka Stream's Sources / Flows / Sinks to provide streaming facilities.

Clients use a pool of threads managed internally and optimized for blocking IO operations.

This library makes heavy use of our extension library for Akka Stream MfgLabs/akka-stream-extensions.

resolvers ++= Seq(
  Resolver.bintrayRepo("mfglabs", "maven")
)

Three packages are available :

libraryDependencies += "com.mfglabs" %% "commons-aws-cloudwatch" % "0.12.2"
libraryDependencies += "com.mfglabs" %% "commons-aws-s3" % "0.12.2"
libraryDependencies += "com.mfglabs" %% "commons-aws-sqs" % "0.12.2"

Changelog here

Scaladoc is available there

import com.mfglabs.commons.aws.s3._

val client = AmazonS3Client()()) // client with un-materialized composable Source / Flow / Sink

val fileStream: Source[ByteString, Unit] = client.getFileAsStream(bucket, key)

val multipartfileStream: Source[ByteString, Unit] = client.getMultipartFileAsStream(bucket, prefix)

someBinaryStream.via(
  client.uploadStreamAsFile(bucket, key, chunkUploadConcurrency = 2)
)

someBinaryStream.via(
  client.uploadStreamAsMultipartFile(
    bucket,
    prefix,
    nbChunkPerFile = 10000,
    chunkUploadConcurrency = 2
  )
)

val ops = client.materialized(flowMaterializer) // client with added materialized methods

val file: Future[ByteString] = ops.getFile(bucket, key)

// More methods, check the source code

Please remark that you don't need any implicit scala.concurrent.ExecutionContext as it's directly provided and managed by [[AmazonS3Client]] itself.

There are also smart AmazonS3Client constructors that can be provided with custom. java.util.concurrent.ExecutorService if you want to manage your pools of threads.

import com.mfglabs.commons.aws.sqs._

val sqs = AmazonSQSClient()()

val sender: Flow[String, SendMessageResult, Unit] =
  Flow[String].map { body =>
    val req = new SendMessageRequest()
    req.setMessageBody(body)
    req.setQueueUrl(queueUrl)
    req
  }
  .via(sqs.sendMessageAsStream())

val receiver: Source[Message, Unit] = sqs.receiveMessageAsStream(queueUrl, autoAck = false)

Please remark that you don't need any implicit scala.concurrent.ExecutionContext as it's directly provided and managed by [[AmazonSQSClient]] itself.

There are also smart AmazonSQSClient constructors that can be provided with custom. java.util.concurrent.ExecutorService if you want to manage your pools of threads.

In your code:

import com.mfglabs.commons.aws.cloudwatch
import cloudwatch._ // brings implicit extensions

// Create the client
val CW = cloudwatch.AmazonCloudwatchClient()()

// Use it
for {
  metrics  <- CW.listMetrics()
} yield (metrics)

Please remark that you don't need any implicit scala.concurrent.ExecutionContext as it's directly provided and managed by [[AmazonCloudwatchClient]] itself.

There are also smart AmazonCloudwatchClient constructors that can be provided with custom. java.util.concurrent.ExecutorService if you want to manage your pools of threads.

This software is licensed under the Apache 2 license, quoted below.

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.