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

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