Compare Avalanche vs Snowball debt repayment strategies. No signup, no data stored.
"You could be debt-free 14 months sooner and save $2,847 in interest. But that requires discipline, which is how you got here."
| Feature | Description |
|---|---|
| 📊 Strategy Comparison | Side-by-side Avalanche vs Snowball with interactive charts |
| 🔄 Balance Transfer Analysis | Model multiple transfers to low-APR cards |
| 📈 Sensitivity Analysis | Impact of paying $50–$500 more per month |
| 📅 Bi-Weekly Payments | Toggle to see how 13 annual payments saves interest |
| 🏷️ Promo APR Support | Model 0% intro rates with expiry dates |
| Warns when payments can't keep up with interest | |
| 💬 Plain English Summary | What each strategy actually means for you |
| 🎴 Customizable Summary Card | Themed, with toggleable content and payment plan breakdown |
| 📋 CSV Export | Download your month-by-month payment plan |
Or run locally:
git clone https://github.com/DrKenReid/Debt-Payoff-Simulator.git
cd Debt-Payoff-Simulator
pip install -r requirements.txt
streamlit run app.pyThe engine is deliberately simple and its assumptions are explicit:
- Interest compounds monthly at APR ÷ 12, applied before each payment.
- The simulator assumes everything left after expenses goes toward debt each month — minimum payments first, the remainder to the strategy's priority debt. "Extra Monthly Payment" adds on top of that budget.
- Bi-weekly mode models the classic trick: 26 half-payments = 13 full payments per year, i.e. your monthly debt budget × 13/12.
- Promo APRs apply until their end date, then revert to the standard APR. Balance transfers add the fee to the transferred balance and start a 0% promo window.
- Simulations cap at 600 months; if total debt grows three months in a row, the plan is flagged as never paying off.
⚠️ For educational purposes only — this is a simplified model, not financial advice.
pip install -r requirements-dev.txt
pytestPRs welcome! See CONTRIBUTING.md.
- Steam Stats Visualized — Spotify Wrapped for your Steam library
- Letterboxd Roasted — Spotify Wrapped for your Letterboxd
Ken Reid — Data Scientist, photographer, and avid reader.
- kenreid.co.uk — Portfolio & blog
- @kenreid.co.uk — Bluesky
- @DrKenReid — GitHub