isobar python pattern library
One of the nicest things about the SuperCollider language is the Patterns library, which is a very elegant way of doing generative music and other stuff where you need to generate event-patterns.
Dan Jones made a kind of copy of the Patterns library but for Python, called "isobar", and I've been meaning to try it out. So here are some initial notes from me trying it for the first time - there may be more blog articles to come, this is just first impressions.
OK so here's one difference straight away: in SuperCollider a Pattern is not a thing that generates values, it's a thing that generates Streams, which then generate values. In isobar, it's not like that: you create a pattern such as a PSeq (e.g. one to yield a sequence of values 6, 8, 7, 9, ...) and immediately you can call .next on it to return the values. Fine, cutting out the middle-man, but I'm not sure what we're meant to do if we want to generate multiple similar streams of data all coming from the same "cookie cutter".
For example in SuperCollider:
p = Pseq([4, 5, 6, 7]);
q = p.asStream;
r = p.asStream;
r.next; // outputs 4
r.next; // outputs 5
q.next; // outputs 4
q.next; // outputs 5
and in isobar it looks like we'd have to do:
q = PSeq([4, 5, 6, 7])
r = PSeq([4, 5, 6, 7])
r.next() # outputs 4
r.next() # outputs 5
q.next() # outputs 4
q.next() # outputs 5
Note how I have to instantiate two "parent" patterns. (I could have cached the list in a variable, of course.) It looks pointless with such a simple example, who cares which of the two we do. But I wonder if this will inhibit the pattern-composition fun in isobar, that you can do in SuperCollider by putting patterns in patterns in patterns... who can say. Will dabble.
The other thing that was missing is Pbind, the bit of magic that constructs SuperCollider's "Event"s (similar to Python "dict"s).
As a quick test of whether I understood Dan's code I added a PDict class. It seems to work:
from isobar import *
p = PDict({'parp': PSeq([4,5,6,7]), 'prep': PSeq(['a','b'])})
p.next() # outputs {'prep': 'a', 'parp': 4}
p.next() # outputs {'prep': 'b', 'parp': 5}
p.next() # outputs {'prep': 'a', 'parp': 6}
p.next() # outputs {'prep': 'b', 'parp': 7}
p.next() # outputs {'prep': 'a', 'parp': 4}
This should make things go further - as in SuperCollider, you should be able to use this to construct sequences with various parameters (pitch, filter cutoff, duration) all changing together, according to whatever patterns you give them.
There's loads of stuff not done; for example in SuperCollider there's Pkey() which lets you cross the beams - you can use the current value of 'prep' to decide the value of 'parp' by looking up its current value in the dict, whereas here I'm not sure if that's even going to be possible.
Anyway my fork of Dan's code, specifically the branch with PDict added, is at:
https://github.com/danstowell/isobar/tree/PDict
Syndicated 2012-01-08 16:20:12 (Updated 2012-01-08 16:25:02) from Dan Stowell
