Day 74 of 100 Days Coding Challenge: Python
Today, I stitched everything together like a quilter finishing the last patch on a very geeky blanket. The goal? Use all the functions I’ve built over the past weeks to create a final recommendation system. In short: should I add more shares or just sit tight? My app only deals with the stocks I’m already tracking—no wild goose chase across the market. I did toy with the idea of building a “stock-hunting” feature, but that’s a whole different adventure, so I shelved it for another program.
My portfolio is more of a carefully balanced meal than a buffet. I keep a 30/70, 40/60, or 50/50 mix between bonds/fixed income and stocks, adjusting when it feels right. Bonds are split across short- and long-term, while stocks get divided across sectors. Truth be told, half my holdings still cluster around a few sectors, but that’s the nature of my investing style. I’m not a daily trader. I just invest systematically every week and let time do the heavy lifting.
Every function in this app was designed to reflect my method—slow, steady, and structured. Today marks the final “core” function. Tomorrow, I’ll wrap up with one last extra flourish before calling this project done.
Today’s Motivation / Challenge
Think of this function as the “gut check” before you hit the buy button. Instead of relying on hunches, it gathers what I’ve already built—momentum, RSI, moving averages—and asks: “Does this stock deserve more of your money?” It’s like having your own personal investment butler who politely says, “Perhaps not today, sir.”
Purpose of the Code (Object)
This function pulls together signals from multiple indicators and summarizes them into a simple recommendation. No complex trading strategy here—just a handy way to see whether your portfolio needs a nudge or if you’re better off staying put.
AI Prompt
Create a summary of multiple indicators and create a simple recommendation.
Functions & Features
- Combines RSI, moving average, and momentum signals.
- Generates a simple “buy/hold” style recommendation.
- Focuses only on stocks already in your portfolio.
Requirements / Setup
pip install yfinance pandas matplotlib numpy
Minimal Code Sample
def buy_suggestion():
rsi = show_rsi_status()
ma = moving_average_tracker()
mom = show_momentum_score()
# Combine indicators → final suggestion
print(“Recommendation: adjust or hold?”)
It just compiles all the signals into one place, like a referee calling the final play.
Notes / Lessons Learned
Adding this wasn’t actually difficult—the hard work was already done in the earlier functions. This was like putting the roof on a house after weeks of hammering walls together. I was pleasantly surprised by how satisfying it felt to see the app give me a neat, cohesive recommendation. It reminded me of my other homemade projects—whether yogurt, kombucha, or bread, you know exactly what went into it, and you can trust the result. That same sense of control made this feature feel “just right.”
Optional Ideas for Expansion
- Add a “stock scout” function to suggest new tickers to track.
- Layer in news headlines for context with the numbers.
- Export recommendations to a CSV for record-keeping.