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Amazon Kinesis Client Library for Python

This package provides an interface to the Amazon Kinesis Client Library (KCL) MultiLangDaemon, which is part of the Amazon KCL for Java. Developers can use the Amazon KCL to build distributed applications that process streaming data reliably at scale. The Amazon KCL takes care of many of the complex tasks associated with distributed computing, such as load-balancing across multiple instances, responding to instance failures, checkpointing processed records, and reacting to changes in stream volume. This interface manages the interaction with the MultiLangDaemon so that developers can focus on implementing their record processor executable. A record processor executable typically looks something like:

    #!env python
    from amazon_kclpy import kcl
    import json, base64

    class RecordProcessor(kcl.RecordProcessorBase):

        def initialize(self, initialiation_input):
            pass

        def process_records(self, process_records_input):
            pass

        def lease_lost(self, lease_lost_input):
            pass

        def shard_ended(self, shard_ended_input):
            pass

        def shutdown_requested(self, shutdown_requested_input):
            pass

    if __name__ == "__main__":
        kclprocess = kcl.KCLProcess(RecordProcessor())
        kclprocess.run()

Before You Get Started

Before running the samples, you'll want to make sure that your environment is configured to allow the samples to use your AWS Security Credentials.

By default the samples use the DefaultCredentialsProvider so you'll want to make your credentials available to one of the credentials providers in that provider chain. There are several ways to do this such as providing a ~/.aws/credentials file, or if you're running on EC2, you can associate an IAM role with your instance with appropriate access.

For questions regarding Amazon Kinesis Service and the client libraries please visit the Amazon Kinesis Forums

Running the Sample

Using the amazon_kclpy package requires the MultiLangDaemon which is provided by the Amazon KCL for Java. These jars will be downloaded automatically by the install command, but you can explicitly download them with the download_jars command. From the root of this repo, run:

python setup.py download_jars
python setup.py install

Now the amazon_kclpy and boto (used by the sample putter script) and required jars should be installed in your environment. To start the sample putter, run:

sample_kinesis_wordputter.py --stream words -w cat -w dog -w bird -w lobster

This will create an Amazon Kinesis stream called words and put the words specified by the -w options into the stream once each. Use -p SECONDS to indicate a period over which to repeatedly put these words.

Now we would like to run an Amazon KCL for Python application that reads records from the stream we just created, but first take a look in the samples directory, you'll find a file called sample.properties, cat that file:

cat samples/sample.properties

You'll see several properties defined there. executableName indicates the executable for the MultiLangDaemon to run, streamName is the Kinesis stream to read from, appName is the Amazon KCL application name to use which will be the name of an Amazon DynamoDB table that gets created by the Amazon KCL, initialPositionInStream tells the Amazon KCL how to start reading from shards upon a fresh startup. To run the sample application you can use a helper script included in this package. Note you must provide a path to java (version 1.7 or greater) to run the Amazon KCL.

amazon_kclpy_helper.py --print_command \
    --java <path-to-java> --properties samples/sample.properties

This will print the command needed to run the sample which you can copy paste, or surround the command with back ticks to run it.

`amazon_kclpy_helper.py --print_command \
    --java <path-to-java> --properties samples/sample.properties`

Alternatively, if you don't have the source on hand, but want to run the sample app you can use the --sample argument to indicate you'd like to get the sample.properties file from the installation location.

amazon_kclpy_helper.py --print_command --java <path-to-java> --sample

Running on EC2

Running on EC2 is simple. Assuming you are already logged into an EC2 instance running Amazon Linux, the following steps will prepare your environment for running the sample app. Note the version of java that ships with Amazon Linux can be found at /usr/bin/java and should be 1.7 or greater.

sudo yum install python-pip

sudo pip install virtualenv

virtualenv /tmp/kclpy-sample-env

source /tmp/kclpy-sample-env/bin/activate

pip install amazon_kclpy

Under the Hood - What You Should Know about Amazon KCL's MultiLangDaemon

Amazon KCL for Python uses Amazon KCL for Java internally. We have implemented a Java-based daemon, called the MultiLangDaemon that does all the heavy lifting. Our approach has the daemon spawn the user-defined record processor script/program as a sub-process. The MultiLangDaemon communicates with this sub-process over standard input/output using a simple protocol, and therefore the record processor script/program can be written in any language.

At runtime, there will always be a one-to-one correspondence between a record processor, a child process, and an Amazon Kinesis Shard. The MultiLangDaemon will make sure of that, without any need for the developer to intervene.

In this release, we have abstracted these implementation details away and exposed an interface that enables you to focus on writing record processing logic in Python. This approach enables Amazon KCL to be language agnostic, while providing identical features and similar parallel processing model across all languages.

See Also

Release Notes

Release 2.0.0 (January 15, 2019)

  • Introducing support for Enhanced Fan-Out
  • Updated to version 2.1.0 of the Amazon Kinesis Client for Java
    • Version 2.1.0 now defaults to using RegisterStreamConsumer Kinesis API, which provides dedicated throughput compared to GetRecords.
    • Version 2.1.0 now defaults to using SubscribeToShard Kinesis API, which provides lower latencies than GetRecords.
    • WARNING: RegisterStreamConsumer and SubscribeToShard are new APIs, and may require updating any explicit IAM policies
    • For more information about Enhaced Fan-Out and Polling with the KCL check out the announcement and developer documentation.
  • Introducing version 3 of the RecordProcessorBase which supports the new ShardRecordProcessor interface
    • The shutdown method from version 2 has been removed and replaced by leaseLost and shardEnded methods.
    • Introducing leaseLost method, which takes LeaseLostInput object and is invoked when a lease is lost.
    • Introducing shardEnded method, which takes ShardEndedInput object and is invoked when all records from a split/merge have been processed.
  • Updated AWS SDK version to 2.2.0
  • MultiLangDaemon now uses logging using logback
    • MultiLangDaemon supports custom logback.xml file via the --log-configuration option.
    • amazon_kclpy_helper script supports --log-configuration option for command generation.

Release 1.5.1 (January 2, 2019)

  • Updated to version 1.9.3 of the Amazon Kinesis Client Library for Java.
  • Changed to now download jars from Maven using https.
  • Changed to raise exception when downloading from Maven fails.

Release 1.5.0 (February 7, 2018)

  • Updated to version 1.9.0 of the Amazon Kinesis Client Library for Java
    • Version 1.9.0 now uses the ListShards Kinesis API, which provides a higher call rate than DescribeStream.
    • WARNING: ListShards is a new API, and may require updating any explicit IAM policies
    • PR #71

Release 1.4.5 (June 28, 2017)

  • Record processors can now be notified, and given a final opportunity to checkpoint, when the KCL is being shutdown.

    To use this feature the record processor must implement the shutdown_requested operation from the respective processor module. See v2/processor.py or kcl.py for the required API.

Release 1.4.4 (April 7, 2017)

  • PR #47: Update to release 1.7.5 of the Amazon Kinesis Client.
    • Additionally updated to version 1.11.115 of the AWS Java SDK.
    • Fixes Issue #43.
    • Fixes Issue #27.

Release 1.4.3 (January 3, 2017)

  • PR #39: Make record objects subscriptable for backwards compatibility.

Release 1.4.2 (November 21, 2016)

  • PR #35: Downloading JAR files now runs correctly.

Release 1.4.1 (November 18, 2016)

  • Installation of the library into a virtual environment on macOS, and Windows now correctly downloads the jar files.

Release 1.4.0 (November 9, 2016)

  • Added a new v2 record processor class that allows access to updated features.
    • Record processor initialization
      • The initialize method receives an InitializeInput object that provides shard id, and the starting sequence and sub sequence numbers.
    • Process records calls
      • The process_records calls now receives a ProcessRecordsInput object that, in addition to the records, now includes the millisBehindLatest for the batch of records
      • Records are now represented as a Record object that adds new data, and includes some convenience methods
        • Adds a binary_data method that handles the base 64 decode of the data.
        • Includes the sub sequence number of the record.
        • Includes the approximate arrival time stamp of the record.
    • Record processor shutdown
      • The method shutdown now receives a ShutdownInput object.
  • Checkpoint methods now accept a sub sequence number in addition to the sequence number.

Release 1.3.1

  • Version number increase to stay inline with PyPI.

Release 1.3.0

  • Updated dependency to Amazon KCL version 1.6.4

Release 1.2.0

  • Updated dependency to Amazon KCL version 1.6.1

Release 1.1.0 (January 27, 2015)

  • Python 3 support All Python files are compatible with Python 3

Release 1.0.0 (October 21, 2014)

  • amazon_kclpy module exposes an interface to allow implementation of record processor executables that are compatible with the MultiLangDaemon
  • samples module provides a sample putter application using boto and a sample processing app using amazon_kclpy

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