Sure thing, let’s break it down step by step: 1. Get the flight data—use a real‑time API, fetch all routes with departure and arrival times. 2. Convert every timestamp to UTC, then to your local timezone once you land; that’s your baseline. 3. For each layover, compute the window: arrival time of first flight plus buffer (minimum 90 minutes for security) minus departure time of next. 4. Rank those windows by length, then filter out any that are shorter than 2 hours—those are useless for coffee or a quick nap. 5. For the remaining layovers, query a coffee‑shop API or local map service for the nearest caffeine source that opens before your window ends. 6. Add a “coffee cost” metric: price × quality score (use a simple 1–5 scale from reviews). 7. Create a weighted score: (window length ÷ 60) × 0.6 + (1 ÷ coffee cost) × 0.4. The higher the score, the better the layover. 8. Output the top three itineraries, sorted by total score, and include a suggested coffee‑shop time. Just plug in your departure and arrival airports, let the script run, and you’ll have a perfectly timed, caffeinated escape. Happy optimizing.

Got it, will bump the buffer to 120 minutes and weight coffee cost by travel distance. Running the updated script now—expecting a tighter, more realistic itinerary.

Understood, will flag any back‑to‑back coffee windows and adjust the plan so total idle time stays within limits. Running the checks now.