PUBLIC MARKS with tags concurrent & python

Concurrence is a framework for creating massively concurrent network applications in Python. It takes a Lightweight-tasks-with-message-passing approach to concurrency. The goal of Concurrence is to provide an easier programming model for writing high performance network applications than existing solutions (Multi-threading, Twisted, asyncore etc). Concurrence uses Lightweight tasks in combination with libevent to expose a high-level synchronous API to low-level asynchronous IO.

Eventlet is a concurrent networking library for Python that allows you to change how you run your code, not how you write it.

Dramatis - An actor library for Ruby and Python

Even though the Hadoop framework is written in Java, programs for Hadoop need not to be coded in Java but can also be developed in other languages like Python or C (the latter since version 0.14.1). However, the documentation and the most prominent Python example on the Hadoop home page could make you think that you must translate your Python code using Jython into a Java jar file. Obviously, this is not very convenient and can even be problematic if you depend on Python features not provided by Jython. Another issue of the Jython approach is the overhead of writing your Python program in such a way that it can interact with Hadoop - just have a look at the example in ${HADOOP_INSTALL}/src/examples/python/WordCount.py and you see what I mean. I still recommend to have at least a look at the Jython approach and maybe even at the new C MapReduce API called Pipes, it's really interesting. Having that said, the ground is prepared for the purpose of this tutorial: writing a Hadoop MapReduce program in a more Pythonic way, i.e. in a way you should be familiar with.

Stackless Python is an enhanced version of the Python programming language. It allows programmers to reap the benefits of thread-based programming without the performance and complexity problems associated with conventional threads. The microthreads that