Alright folks, let me tell you about the time I wrestled with the “fightsong lyrics” thing. It was a trip, lemme tell ya.
First off, why even bother? Well, I was messing around with a little project, trying to build a simple app that could maybe, someday, identify songs from snippets of lyrics. Ambitious, I know. But you gotta start somewhere, right? So, naturally, I figured step one: get some lyrics.
I started dead simple. Just googled “fightsong lyrics.” Scraped a few websites, copy-pasted into a text file. Real caveman stuff. But quickly realized that was a dead end. The formatting was all over the place, some sites had ads jammed in the middle of the lyrics, just a total mess.
Next up: APIs. I figured someone, somewhere, had to have a decent lyrics API. Spent a couple of hours digging. Found a few that looked promising, signed up for some free trials. Most were either crazy expensive for the number of requests I’d need, or the data quality was… questionable. Like, completely wrong lyrics for popular songs. One even gave me German lyrics when I asked for an English song. Go figure.
So, scraping it is! Okay, back to scraping, but this time, I decided to be smarter about it. Found a few lyrics websites that seemed reasonably consistent in their formatting. Wrote a little Python script using Beautiful Soup to target specific HTML elements. It was a pain in the butt. Websites change their layouts all the time, so the script kept breaking. I’d fix it, and then a week later, bam, broken again. Cat and mouse game.
Cleaning up the mess. Even with the scraper, the lyrics were still pretty rough. Lots of extra whitespace, weird characters, HTML tags that slipped through the cracks. Wrote another Python script to clean things up. Used regular expressions to strip out the junk, convert to lowercase, remove punctuation. Still wasn’t perfect, but way better.
- Step 1: Googled, copy-pasted. (Failed miserably)
- Step 2: API hunt. (Expensive and unreliable)
- Step 3: Web scraping with Beautiful Soup. (Painful, but workable)
- Step 4: Data cleaning with regex. (Less painful, but still tedious)
The “fightsong” problem specifically. The thing about fightsongs is they’re often super specific to a particular school or team. So, just getting “a fightsong” isn’t enough. I needed to be able to associate the lyrics with the right school. This meant going back to the websites and trying to extract that information too. More scraping, more regex, more headaches.
The “copyright” headache. And then, the big one: copyright. I’m not trying to get sued here! I made sure to only use the lyrics for non-commercial purposes, and to give credit to the original sources. Still makes me nervous, though. Lyrics are tricky territory.
What I learned: This whole “fightsong lyrics” adventure was way more complicated than I thought it would be. Scraping is never as easy as it looks, data cleaning is a never-ending process, and copyright law is scary. But, hey, I learned a lot about web scraping, regular expressions, and the surprising diversity of college fight songs. And now I can probably recognize half a dozen fight songs just from the lyrics alone. So, you know, progress?
