I'm currently working on a website for a music company, which includes a full blown web application that will be accessible to members and assist in music distribution.
In order to make this happen, I have to be able to organize the tracks by genre. But keep in mind, this is a music company... they won't have anything but a huge library of music, so doing it manually is simply out of the question. Here's the other problem: Not all mp3s have ID3 tags (the tags that cause track details to appear on your player's display), and those that do may or may not fit in perfectly with your pre-defined items.
I wrote this in Python, so I wanted to share how I worked around this problem with calculating string similarity, rather than attempting to match strings or perform complex regular expressions to produce a possibly mediocre result.
In order to make this happen, I have to be able to organize the tracks by genre. But keep in mind, this is a music company... they won't have anything but a huge library of music, so doing it manually is simply out of the question. Here's the other problem: Not all mp3s have ID3 tags (the tags that cause track details to appear on your player's display), and those that do may or may not fit in perfectly with your pre-defined items.
I wrote this in Python, so I wanted to share how I worked around this problem with calculating string similarity, rather than attempting to match strings or perform complex regular expressions to produce a possibly mediocre result.
