Copying playlists and songs between iTunes libraries

My home computer infrastructure is currently in a state of transition, in which my recently-purchased MacBook Pro laptop is slowly taking over all of the tasks once handled by my aging (or ageing?) iMac desktop machine. 

I'm now finally confronting the inevitability of transitioning my iTunes onto the MacBook. This presents a particular headache since, for the time being at least, the iMac will remain the primary seat of home internet connectivity and is thus the natural place to, ahem, "acquire" new music. So what I need is a reasonably painless way to copy recently added tracks from the iMac iTunes library to the MacBook one, in order to keep the latter up to date with ongoing additions. I'd also like to be able to copy playlists (those painstakingly crafted distillations of listenable tracks tailored to specific moods and musical contexts).

Thanks partly to the fact that my iMac iTunes Library lives on an external hard-drive (due to lack of space on the main drive), it turns out that both tasks can be quite easily accomplished, using essentially the same procedure.

To copy songs:

1. In the "source" iTunes (the iMac) sort tracks by "Date Added" and create a new playlist containing all tracks added since the most recently-added track on the "destination" iTunes (the MacBook Pro).

2. Export this playlist (File > Library > Export Playlist...) --- I don't think the format matters, but I chose Unicode and that works.

3. Close the source iTunes, disconnect the external hard-drive from the source machine, and plug it into the destination machine.

4. In the destination iTunes, import the playlist from step 2 (you need to have copied it across or be remotely connected to the source machine). Now here's the cool thing: in the playlist, the location of the song file is given; since this is somewhere on the external drive, iTunes can find it and copy it across to its library.

To copy playlists containing songs already in both iTunes libraries:

Follow the same procedure, but this time, in step 4, iTunes is smart enough to see that it has copies of the songs already, so it simply recreates the playlist using these.

So all in all, not too much of a headache. I could try to be clever and write some AppleScripts to automate this process even further but that would be taking it too far...

Brewster's Millions (1984)

Silly but fun Richard Pryor flick from the early 80s. The premise is about as contrived as it gets: washed-up baseball player Pryor discovers that he is the sole heir to a fortune from a distant relative. However, there's a catch: in order to instil good spending habits, the dying relative has placed a rather sadistic catch on the inheritance: Pryor must spend $30 million in 30 days, legitimately (i.e. he can't just give to charity). If he succeeds, he will then inherit $300 million; if he fails he gets nothing. Alternatively, he can take a "wimp out" clause and pocket $1 million. About the only the only other thing I need to add is that the accountant charged with ensuring that spends every penny is the love interest (played by Lorette McKee) who is not in on the "game" and despairs at watching Pryor spending like there's no tomorrow.

Electric Dreams (1984)

Rather silly rom com from the early 80s. Dorky guy buys a home computer system (featuring one of those old-school classic acoustically coupled modems) that somehow becomes sentient after he pours champagne into it (don't ask) and then vies with him for the affections of the cello-playing love interest from the floor above (aside: she is played by a young Virginia Madsen, who more recently played the love interest of geeky wine connoisseur and writer Miles in Sideways). The highlight, and main legacy of the film, is probably the song "Together In Electric Dreams" by Giorgio Moroder (who also has a brief cameo).

Platoon (1986)

Recently re-watched this great Vietnam film from the 80s (back when Oliver Stone made good movies). It holds up well: the lead performances from Willem Defoe, Tom Berenger and (a young and rather scrawny) Charlie Sheen are all excellent, while the message of the futility of America's military activities in foreign lands is probably even more relevant now than it was back then.

It was amusing to see some of the supporting cast who went to bigger things: a young Johnny Depp; a very boyish Kevin Dillon (Matt's younger brother), who has recently hit the big time as Johnny Drama in Entourage; and Forest Whitaker, who in the same year also had a small but great role as a pool hustler in The Color of Money.

Lies, damn lies, and statistics

At 11:30 this morning, a red headline flashed up on my Bloomberg terminal, trumpeting the breaking news that "AUSTRALIAN EMPLOYMENT FELL 9,700 IN AUG.". The market and currency immediately responded to this negative news by promptly dropping by more than 0.5%.

Barely a day goes without an economic "number" of some sort being released, and each one is closely watched with morbid anticipation by the markets. In this sea of instant information, however, no one seems to pay attention to the fine print. One of the first things you learn in the study of any science is the importance of attaching meaning to all measurements via statistical error bounds. Although often seen as dry and tedious, this process is absolutely vital to establishing the meaningfulness of experimental results.

So, with my developing sense of skeptical for just about everything to do with economics, I thought I'd take a closer look at these numbers. On the website of the Australian Bureau of Statistics you can access their complete press release. Scrolling down a bit, you find a table containing the numbers and their corresponding "95% confidence interval" (this is a bound within which, statistically speaking, the "true" number has a 95% chance of lying; if this bound doesn't include zero, then the measured number can be regarded as "statistically significant" -- i.e. meaningfully different from zero).

Here are the numbers and C.I.s:

Total Employment change: -9 700 (-64 300 to 44 900)

Total Unemployment: 18 400 (-12 600 to 49 400)

Unemployment rate: 0.1% (-0.1% to 0.3%)

Participation rate: 0.0% (-0.4% to 0.4%)


It can be seen that not a one of these is statistically different from zero. Based on these numbers, all we can say with any conviction is that total employment changed by somewhere between -64k and +45k. It is simply meaningless to say that it fell -- the numbers just don't allow us to draw this conclusion.

To make this point perhaps even more clear: if the ABS were to re-run their survey on a different random sample, the above results suggest that there is a decent chance they would observe a reduction, rather than increase, in unemployment.

So why do the markets jerk around like puppets on a string in response to this non-information? My guess is that it's a classic case of people trying to second-guess how other (possibly stupider) people are going to react. In this game, the quality of the underlying information is of little relevance: all that counts is that some people out there will believe it and trade accordingly.

Who's to blame for this madness? The ABS, for not making the limitations of their numbers sufficiently clear (perhaps, but in their defence at least they make the information on confidence intervals freely available on their website if you choose to look)? The media, for seizing on any soundbite-sized piece of information and over-analysing it to death? Or us, for continuing to pay attention? I suspect it's a good dose of each.

Less Than Zero (1987)

Quite enjoyed this adaptation of Brett Easton Ellis' 1985 debut novel, which deals with drug addiction and nihilism in the lives of rich white kids in LA during the 80s. Stars Robert Downey Jr (who would subsequently go on to explore the above-mentioned issues in his off-screen life), James Spader (one of my favourite supporting actors), Jamie Gertz (the girlfriend from Lost Boys who slipped into obscurity after her 15 minutes in the 80s), and Andrew Mcarthy (a fringe brat-packer whose 15 minutes went by almost as a quickly as Jamie's).