Your Python Application in the Cloud

cloudnumbers.com supports the interpreted, interactive, object-oriented and extensible programming language Python (http://www.python.org/). Python is a user-friendly open source programming language that is used in many areas. It has become really popular since many programmers consider it to be one of the easiest programming languages to study and work with.

cloudnumbers.com combines High-Performance Computing (HPC) and Python in order to provide a fully scalable platform for all your calculations. Combining Python´s ease-of-use with high performance computing means that ideas can more quickly become applications, increasing the productivity of developers, while overcoming any limitations.

HPC support for Python is provided with the following libraries:

• mpi4py (http://mpi4py.scipy.org/): This module provides the binding of the Message Passing Interface (MPI) standard to the Python programming language. It allows any Python program to exploit multiple processors.
• pp (http://www.parallelpython.com/):  This module provides mechanism for parallel execution of Python code on multicore machines and on computer clusters.

Python is a language being used for creating software applications. It is used in various sectors such as finance, social science or life – science. Among others, Python helps people like Biostatisticians, Biomechanics or Bioinformatics to perform clustering, run mathematical analysis techniques and that way work faster. Bioinformatics increase their productivity while lowering their costs due to the use of software packages like Python. At cloudnumbers.com you have the opportunity to use Python for your HPC calculations in the cloud. You can use the pre-installed modules SciPy (http://www.scipy.org/) or NumPy (http://numpy.scipy.org/) and you can build a cluster within minutes. As a scientist you will enjoy the benefits of flexibility, speed and scalability while using Python at cloudnumbers.com.

A simple example using Python at cloudnumbers.com:
This example shows you how to fit experimental data and plots the results using matplotlib. For more details and the code please check the SciPy / Cookbook dictonery.

To view the plot open your “Desktop” in the cloud.

An example for parallel computing with Python and mpi4py can be found in the “Sample Workspace” or execute this command from your cloudnumbers.com’s command line:
mpirun -np 4 -x PYTHONPATH python workspace/Python/helloworld.py

Please feel free to modivy the code examples and go on with your own code. If you have any question do not hesitat to contact us: info@cloudnumbers.com