[LAD] [ANN] MFP 0.02 (Music For Programmers, a graphical patching system)

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Date: Wednesday, March 13, 2013 - 3:34 pm

MFP -- Music For Programmers

Release 0.02, "Making Fine Progress"

I'm pleased to announce an updated release of MFP, containing many
fixes and improvements. It is still not anywhere near a "production"
level, but is becoming more and more usable. Your interest and
participation are invited!

A summary of changes is below. Please see the GitHub issue tracker
for complete details:

https://github.com/bgribble/mfp

Changes since initial release v0.01:
----------------------------------------

* #30: Fix RMS calculation in [ampl~]

* #37: Add [s~], [r~] and different via graphics for signals

* #41: Clean up SSE vs non-SSE, add tests for non-SSE build

* #42: Make parameter setting non-locking; add mfp_alloc thread
for non-blocking memory allocation; in general, clean up
RT components of operation

* #43: Refactor color name usage to avoid API breakage with
different versions of Clutter python bindings

* #44: Fix broken tests

* #46: Add ability to load .so extension libraries with new DSP types

* #47: Handle JACK block size changes at runtime

* #48: Add [latency] object to report JACK input and output latency
changes to patches

About MFP:
----------------------------------------

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 Python 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 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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