I finally got this ‘AZ Pisces Forecast’ monitoring system off the ground. Man, it was a messy ride, but sometimes the dumbest projects teach you the most. I started this whole thing because I was absolutely sick of those clickbait finance sites. Every month, same deal: some guru claiming the stars were aligning for a massive wealth bump if you were a Pisces, or they’d tell you to hedge everything if you were a Virgo. I knew it was junk, but I kept clicking.
The Genesis and Scrape
I decided enough was enough. My practice here was simple: build a script that went out and grabbed the data from all the main ‘AZ’ astrology/finance sites I used to waste time on. I wanted to see if the predictions had any actual correlation to the market performance of my low-cap portfolio. Purely for kicks, you know?
I jumped straight into Python. I’ve got this old dusty setup of requests and Beautiful Soup. I spun up a virtual environment and started coding the initial scraper. Getting the main text block was easy enough—it was just some heavily nested paragraph tags. But then the headache started. These sites are a total hack job; they used four different DIV structures for the actual ‘Money Guide’ part across the five different sources I targeted. It wasn’t uniform HTML at all. I spent three afternoons just writing different selectors for each source.
I had to implement serious error handling. If the scraper failed on one site, I didn’t want the whole thing to crash. I wrapped each site’s scraping logic in its own try/except block, which felt like building five different tools, not one cohesive system. I outputted the results into a basic JSON file that just held the date, the forecast text summary (like ‘major profit’ or ‘extreme caution’), and the market open/close for my selected index on that day. My goal was to eventually automate the ‘correlation’ check, but step one was just getting the data in one spot.
The Ugly Visualization Stage
Once I had the JSON, I needed to see the patterns. I hate front-end work. Absolutely hate it. So I dredged up some ancient JavaScript charting library I used way back in college. I wrote a terrible, spaghetti-code JS script that just consumed the local JSON file and plotted the forecast severity (I manually assigned a value of 1 to 5 for the bullishness of the forecast) against the daily percentage change of my index.
The result? A chart that looked like a toddler’s scribble. Zero correlation. Nada. The ‘extreme profit’ forecast often lined up with a 1.5% drop. The ‘exercise caution’ warning happened on days the market shot up 2%. The data I had spent days fighting to collect was, technically and empirically, worthless garbage. A complete waste of time.
Why I Even Bothered with this Nonsense
You’re probably reading this thinking, “Why the hell did this dude invest three weeks of his life proving something everyone already knew?” Fair question. It comes down to a really painful lesson I learned a few years ago. You see, this whole practice wasn’t about proving the forecast wrong. It was about proving my own desperation wrong.
A few years back, before I got into building my own systems, I trusted a ‘sure thing’ tip. It was from a guy who used to work at my old firm, a seeming genius. I pulled nearly all my non-retirement savings out and poured every last penny into this one micro-cap stock he was raving about. I woke up one Monday morning and saw the news: the CEO was under investigation for fraud. The stock tanked. I watched my account bleed down to maybe 3% of its original value within 48 hours. I panicked and sold what little was left just to stop the pain. I was absolutely screwed.
I spent the next six months living on canned beans, just trying to figure out how I’d made such a monumentally stupid, trusting mistake. I scoured the internet for comfort, for answers, for any sign that the universe had a plan for my ruined financial life. I drank cold coffee and chain-smoked while scrolling through every article, every blog, every weird niche theory. That’s when I stumbled into the ‘AZ Pisces Forecast’ world. I read it, and it was so ludicrously vague and non-committal—just random happy talk—that it snapped me out of it.
I realized the desperation had made me stupid, trusting someone else’s ‘guide’ or the stars’ advice instead of building my own knowledge. My current practice, the whole scraper and visualization tool, exists purely as a monument to that desperate time. The tool sits on my local machine. It still runs every Sunday night, scrapes the data, and plots the graph. And every week, I open the ridiculous chart with its zero correlation, and it reminds me of the cold, hard fact: if you’re looking for a ‘Money Guide’ anywhere but inside your own research and disciplined system, you’re already lost.
The system is useless, but the process solidified my resolve not to be an idiot again. And that, friends, is the only money guide that actually matters.
