phones, video and synthetic programming

A quick Pythonic burst before I depart for IBC later this week.

Video
In my spare time I’ve been tinkering around with Final Cut Pro’s XML capabilities and FCP’s interesting Apple Event support with the goal of automating the production of some channel elements. Python’s great libraries and the community behind their production is one of its strengths. For this work I have employed Appscript from HAS to allow me to send Apple Events to FCP. For the XML processing Fredrik Lundh’s elementtree was the natural choice. I used the Python Imaging Library (PIL) for a similar project several years ago for the automated production of id boards.
Once I’ve cleaned things up I’ll publish my FCP Apple Event class as an example of using Appscript.

Phones
Python for s60 mobile platform went gold last month. I need to dust off my PC to install some Windows only software that’s required to create a developer certificate. The dev cert allows you to get at the tastier capabilities of the phone.

Synthetic Programming
Corepy is a Python package for creating applications targeted at the IBM’s PowerPC and Cell architectures.

“Synthetic programming was developed to provide a new approach to high-performance and multi-core computing using scripting languages. The design of the synthetic programming environment encourages developers to experiment with different approaches for mapping algorithms to processing resources and generating optimized code sequences.

Synthetic programming itself is a methodology for building applications that combines high-level language code with user generated machine code. The synthetic programming environment exposes the underlying processor instructions as first-class functions in the host language and provides components for building and executing instruction sequences built using the instruction interfaces. The instruction sequences, called synthetic programs, can contain any instruction available for the processor, allowing developers to create highly optimized kernels for high-performance tasks. An application can contain many synthetic programs, all of which can be executed an arbitrary number of times synchronously or asynchronously, allowing the application to make full use of data and processing resources.” - Mueller C., Synthetic Programming: User-directed Run-time Code Synthesis for High Performance Computing

So the ease of use and elegance of Python is employed to create high performance machine code, making “assembly fun again”.

This is one of those times when having an older machine has its advantages as copepy will only run on PPC Macintoshes, so time available I’ll be able to load it up on the trusty PowerBook. Probably of more interest to those in scientific programming, such bioinformatics.