The main reason is development velocity and productivity clearly established by Python.

Additional justifications...

• Ease of access to all Java library packages. Thus, no vias such as thrift are required.

• For long running programs, Python on the JVM is performant.

• Jython can leverage existing CPython modules.

• Script, test, script, test... no long compiles and builds required.

Drop me a line if you find any of this useful, or if you have any constructive comments or insights.

## Contents

* jython-shell-script/ * Jython shell scripts that make it easy to include various BigData eco-system jars. * Simplify access to HBase.

• lib/

  • Libraries to access HDFS, HBase, Elasticsearch, etc.

• conf/

  • Configuration file examples.

• tests/

  • Run tests for the lib/ modules.

• examples/

  • Working example Jython code.

## Features.

* Boon JSON processor

• HBase

• HDFS

• Properties Configuration Object

• Worker Threads Model

## Planned...

* more examples/...

• lib/Tachyon.py

• lib/0mq.py

Thanks,
-dsidlo