The aforementioned tool is in the correct direction, but doesn't facilitate the song-grabbing, doesn't support enough system versions, and only works on the same machine.
I realized I needed to define my problem more broadly, as well as better document what was at my disposal.
Really, the idea is that I need to be able to choose "fresh" music from my media library, and have said "fresh" music be weighted towards music I enjoy more.
What I am trying right now is a smart playlist in iTunes (+shuffle) that chooses songs that:
*Have not been played in time period X *Have not been skipped in time period X+Y *Is limited to 2x the size of the shuffle, based on highest play count
Shuffle chooses songs randomly from said playlist, but with a prevalence towards higher-rated songs (though I currently do not have a mechanism for re-rating).
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The aforementioned tool is in the correct direction, but doesn't facilitate the song-grabbing, doesn't support enough system versions, and only works on the same machine.
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As for the other half, I'd do a search at http://code.google.com or http://search.cpan.org (or I suppose you could see if there's an (ugh) Python solution).
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Really, the idea is that I need to be able to choose "fresh" music from my media library, and have said "fresh" music be weighted towards music I enjoy more.
What I am trying right now is a smart playlist in iTunes (+shuffle) that chooses songs that:
*Have not been played in time period X
*Have not been skipped in time period X+Y
*Is limited to 2x the size of the shuffle, based on highest play count
Shuffle chooses songs randomly from said playlist, but with a prevalence towards higher-rated songs (though I currently do not have a mechanism for re-rating).
Reply
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