[ANN] MFP 0.01 (Music For Programmers, a graphical patching system)

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MFP -- Music For Programmers 

Release 0.01, "Mining For Participants" 

MFP is an environment for visually composing computer programs, with
an emphasis on music and real-time audio synthesis and analysis.  It's
very much inspired by Miller Puckette's Pure Data (pd) and Max/MSP,
with a bit of LabView and TouchOSC for good measure.  It is targeted
at musicians, recording engineers, and software developers who like
the "patching" dataflow metaphor for constructing audio synthesis,
processing, and analysis networks. 

MFP is a completely new code base, written in Python and C, with a
Clutter UI.  It has been under development by a solo developer (me!),
as a spare-time project for several years. 

Compared to Pure Data, its nearest relative, MFP is superficially
pretty similar but differs in a few key ways: 

 * MFP uses Python data natively.  Any literal data entered in the 
   UI is parsed by the Python evaluator, and any Python value is a 
   legitimate "message" on the dataflow network 
 
 * MFP provides fairly raw access to Python constructs if desired.  
   For example, the built-in read-eval-print console allows live 
   coding of Python functions as patch elements at runtime. 

 * Name resolution and namespacing are addressed more robustly, 
   with explicit support for lexical scoping 

 * The editing UI is largely keyboard-driven, with a modal input system 
   that feels a bit like vim.  The graphical presentation is a
   single-window style with layers rather than multiple windows.   

 * There is fairly deep integration of Open Sound Control (OSC), with 
   every patch element having an OSC address and the ability to learn
   any other desired address.  

The code is still in early days, but has reached a point in its
lifecycle where at least some interesting workflows are operational
and it can be used for a good number of things.  I think MFP is now
ripe for those with an experimental streak and/or development skills
to grab it, use it, and contribute to its design and development. 

The code and issue tracker are hosted on GitHub: 

    https://github.com/bgribble/mfp

You can find an introductory paper (submitted to LAC-2013) and
accompanying screenshots, some sample patches, and a few other bits of
documentation in the doc directory of the GitHub repo.  The README 
at the top level of the source tree contains dependency, build, 
and getting-started information.

Thanks,
Bill Gribble 




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