jueves, 22 de abril de 2010

How to install Ipython-zmq code ? (just for linux right now )

* c/c++ compiler (gcc)
* git client
* cython
* uuid-dev
* python-dev
* autotools (automake - autoconf - libtool)
* pkg-config

 install under debian/ubutu:
 #apt-get install  git g++ cython uuid-dev python-dev automake autoconf libtool
 # apt-get build-dep cython

install under redhat/fedora/OpenSuSE with yum:
 #yum install  git g++ cython uuid-dev automake autoconf libtool

 building  pyzmq:
 * download zmq libraries
     $git clone git://github.com/sustrik/zeromq2.git

  then run
     $cd zeromq2

     if you don`t have root permissions
     $./configure --prefix=your_favorite_installation_prefix
     $make install

     if you have root permissions
      #make install

      NOTE: I suggest you install like root

download pyzmq code:
     $git clone  http://github.com/ellisonbg/pyzmq.git
     $cd pyzmq
     edit setup.cfg
      example: setup.cfg

     if you don`t have  root permissions
      # Edit these to point to your installed zeromq library and header dirs.
      library_dirs = your_zeromq2_installation_prefix/lib
      include_dirs = your_zeromq2_installation_prefix/include

     if you have installed zeromq2 with root permission and default configuration
      # Edit these to point to your installed zeromq library and header dirs.
      library_dirs = /usr/local/lib
      include_dirs = /usr/local/include

     if you don`t have  root permissions
     $python setup.py  build
     $python setup.py install --prefix=your_favorite_ installation_prefix

     if you have root permissions
     #python setup.py install

   more info to install pyzmq in http://www.zeromq.org/bindings:python

Installing IPythonZmq.

Dowload with git
$git clone http://github.com:omazapa/ipython.git
$cd ipython
$python setup.py build
like root
#python setupegg.py develop


miércoles, 21 de abril de 2010

Possible future directions

I think one of the possible directions is to write a complex system to parallel processing with others modules like pympi, which let massive processing load, in different kernels with a system client/server comunication managed by zmq.
At this moment, ipython has wrote a system for parallel processing in mpi but using a twisted platform, the idea is to update iptyhon to  be supported by python3, with twisted this is no possible, so zeromq is the best way to do it.

Other feature zeromq has is the performance in data transmission and cython is writing support to python 3 code

lunes, 12 de abril de 2010

Porting IPython to a two process model using ZeroMQ


IPython's execution in a command-line environment will be ported to a two process model using the ZeroMQ library for inter-process communication. This will:

- prevent an interpreter crash from destroying the user session,
- allow multiple clients to interact simultaneously with a single interpreter
- allow IPython to reuse code for local execution and distributed computing (DC)
- give us a path for Python3 support, since ZeroMQ supports Python3 while Twisted (what we use today for DC) does not.


* A user-facing frontend that provides an environment like today's command-line IPython but running over two processes, with the code execution kernel living in a separate process and communicating with the frontend by using the ZeroMQ library.

* A kernel that supports IPython's features (tab-completion, code introspection, exception reporting with different levels of detail, etc), but listening to requests over a network port, and returning results as JSON-formatted messages over the network.

Project description

Currently IPython provides a command-line client that executes all code in a single process, and a set of tools for distributed and parallel computing that execute code in multiple processes (possibly but not necessarily on different hosts), using the Twisted asynchronous framework for communication between nodes. For a number of reasons, it is desirable to unify the architecture of the local execution with that of distributed computing, since ultimately many of the underlying abstractions are similar and should be reused. In particular, we would like to:

- Have even for a single user a 2-process model, so that the environment where code is being input runs in a different process from that which executes the code. This would prevent a crash of the Python interpreter executing code (because of a segmentation fault in a compiled extension or an improper access to a C library via ctypes, for example) from destroying the user session.

- Have the same kernel used for executing code locally be available over the network for distributed computing. Currently the Twisted-using IPython engines for distributed computing do not share any code with the command-line client, which means that many of the additional features of IPython (tab completion, object introspection, magic functions, etc) are not available while using the distributed computing system. Once the regular command-line environment is ported to allowing such a 2-process model, this newly decoupled kernel could form the core of a distributed computing IPython engine and all capabilities would be available throughout the system.

- Have a route to Python3 support. Twisted is a large and complex library that does currently not support Python3, and as indicated by the Twisted developers it may take a while before it is ported (http://stackoverflow.com/questions/172306/how-are-you-planning-on-handling-the-migration-to-python-3). For IPython, this means that while we could port the command-line environment, a large swath of IPython would be left 2.x-only, a highly undesirable situation. For this reason, the search for an alternative to Twisted has been active for a while, and recently we've identified the ZeroMQ (http://www.zeromq.org, zmq for short) library as a viable candidate. Zmq is a fast, simple messaging library written in C++, for which one of the IPython developers has written Python bindings using Cython (http://www.zeromq.org/bindings:python). Since Cython already knows how to generate Python3-compliant bindings with a simple command-line switch, zmq can be used with Python3 when needed.

As part of the Zmq Python bindings, the IPython developers have already developed a simple prototype of such a two-process kernel/frontend system (details below). I propose to start from this example and port today's IPython code to operate in a similar manner. IPython's command-line program (the main 'ipython' script) executes both user interaction and the user's code in the same process. This project will thus require breaking up IPython into the parts that correspond to the kernel and the parts that are meant to interact with the user, and making these two components communicate over the network using zmq instead of accessing local attributes and methods of a single global object.

Once this port is complete, the resulting tools will be the foundation (though as part of this proposal I do not expect to undertake either of these tasks) to allow the distributed computing parts of IPython to use the same code as the command-line client, and for the whole system to be ported to Python3. So while I do not intend to tackle here the removal of Twisted and the unification of the local and distributed parts of IPython, my proposal is a necessary step before those are possible.

Project Details

As part of the ZeroMQ bindings, the IPython developers have already developed a simple prototype example that provides a Python execution kernel (with none of IPython's code or features, just plain code execution) that listens on zmq sockets, and a frontend based on the InteractiveConsole class of the code.py module from the Python standard library. This example is capable of executing code, propagating errors, performing tab-completion over the network and having multiple frontends connect and disconnect simultaneously to a single kernel, with all inputs and outputs being made available to all connected clients (thanks to zqm's PUB sockets that provide multicasting capabilities for the kernel and to which the frontends subscribe via a SUB socket).

** we have all example code in

* http://github.com/ellisonbg/pyzmq/blob/completer/examples/kernel/kernel.py

* http://github.com/ellisonbg/pyzmq/blob/completer/examples/kernel/completer.py

* http://github.com/fperez/pyzmq/blob/completer/examples/kernel/frontend.py

All of this code already works, and can be seen in this example directory from the ZMQ python bindings:

* http://github.com/ellisonbg/pyzmq/blob/completer/examples/kernel

Based on this work, I expect to write a stable system for ipython kernel with ipython standards, error control,crash recovery system and general configuration options, also standardize defaults ports or auth system for remote connection etc.

The crash recovery system, is a ipython kernel module for when it fails unexpectedly, you can retrieve the information from the section, this will be based on a log and a lock file to indicate when the kernel was not closed in a proper way.


All work done will be tested and documented as it progresses, not after the fact.

* week 1,2

* Break up today's IPython monolithic object into kernel/frontend objects, while remaining in-process. This is the first step of the transition to a two process model but it will allow me to retain a functioning IPython during the transition. These objects will still make local python method calls and attribute accesses.
* Identify all the APIs that will require communication between kernel and frontend.

* week 3,4

* Modify the kernel/frontend objects to use messaging for all cross-object communication. This will be done using a local mock transport (no zmq dependency yet) but using JSON messages.

* week 5, 6

* Move kernel and client to separate processes and add the zmq transport to move the messages across the process boundary.

* week 7, 8

* Implement and test tab-completion and function tooltips across the process boundary, with support for multiple simultaneous clients. This is particularly tricky because these are asynchronous events that can happen while the kernel is busy executing code, so timeouts and multi-client support must be carefully thought out.

* week 9, 10

* Implement the configuration of kernel/frontend on the IPython configuration description system (which already exists).
* Slack time if any of the previous tasks took longer than originally planned.

Personal Information

I am a student of computer science at Universidad de Antioquia, Medellin - Colombia, and a system administrator in a research group, I have 6 years of experience as a programmer in different programming languages and in different areas of computing and I am passionate about GNU / Linux and open source community.

*Ipython and Me*

I really like ipython and projects that need to improve it, so I want to be part of this process of development and growth.

**Contact Info**

* e-mail: andresete.chaos@gmail.com
* website: http://ipython.scipy.org/moin/GSoC2010/IPythonZmq  for omore info

* My loved family and girlfriend that now also part of.

* Fernando Perez for making me part of this community and spend their time and patience to guide me.

* To Diego Restrepo and Jorge Zuluaga for supporting me in my education and my training as a scientist.