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Trends in programming language development and adoption point to Python as the high-level systems integration language of choice. Python leverages a vast developer-base external to the Neuroscience community, and promises leaps in simulation complexity and maintainability to any neural simulator which adopts it. As more and more simulators support Python, model development times can be drastically reduced by promoting code sharing and reuse across simulator communities. As a result, modellers can devote their software development time to innovating new simulation tools such as network topology databases, stimulus programming, analysis and visualisation tools, and simulation accounting, to name a few.

Today I finally plugged-in the Yahoo Boss Mashup Framework into the Google App Engine environment. Google App Engine (GAE) provides a pretty sweet yet simple platform for executing Python applications on Google's infrastructure. The Boss Mashup Framework (BMF) provides Python API's for accessing Yahoo's Search API's as well remixing data a la SQL constructs. Running BMF on top of GAE is a seemingly natural progression, and quite arguably the easiest way to deploy Boss - so I spent today porting BMF to the GAE platform. See also http://bossy.appspot.com/qa?query=who+is+brad+pitt+married+to

I have written a wrapper to expose openlibrary.org api data as RDF. It is written in Python and deployed on Google App Engine. It is only an illustration of Linked Data publication, and in order to get a first feedback, so do not rely on it in your application since the URL or the content will change in the future.

GUESS is an exploratory data analysis and visualization tool for graphs and networks. The system contains a domain-specific embedded language called Gython (an extension of Python, or more specifically Jython) which supports the operators and syntactic sugar necessary for working on graph structures in an intuitive manner. An interactive interpreter binds the text that you type in the interpreter to the objects being visualized for more useful integration. GUESS also offers a visualization front end that supports the export of static images and dynamic movies.

The goal of this project is to develop a Python tool to make an in-depth quantitative analysis about Wikipedia, generating graphics and statistical results for each language version of Wikipedia.

SWAML, pronounced [swæml], is a research project around the semantic web technologies to publish the mailing lists' archives into a RDF format. It has been developed by the CTIC Foundation and the WESO-RG at University of Oviedo (Spain). You can visit the project page at BerliOS for more details. SWAML process description SWAML reads a collection of email messages stored in a mailbox (from a mailing list compatible with RFC 4155) and generates a RDF description. It is written in Python using SIOC as the main ontology to represent in RDF a mailing list.