Episode 6 — Due Diligence Week
Programming with Python · Tutorial 06
The investor is finally in the shop, clipboard out, asking to see real numbers before Friday. Kevin proposes going “on vibes”; her expression does not change. So this week you stop hand-rolling arithmetic and reach for Python’s standard library: you’ll import math and statistics for professional-grade counts and averages, then use random to rehearse next week’s demand. You’ll also learn why a projection you can run twice, and get the same answer, is one an investor can trust. It’s also the first notebook where AI tools are allowed; the checks still only go green on code that actually runs.
Work on the notebook
Open in browser (recommended): runs entirely on your machine, in this tab: no account, no installation, and after it loads no internet is needed.
Your progress lives in this browser tab. If you reload the page (Cmd/Ctrl + R) your work is still there. But if you close the tab and open the link again later, you start from a clean notebook. There is no cross-device sync in the browser, and clearing browser data or private mode also wipes it.
So: download your .py before you leave (menu → Download → Download Python code). That download is the only guaranteed copy. Handing in files works exactly like this in the checkpoints, so you get to practice the motion every week. Note: a downloaded .py is for submission and backup. You can’t upload it back into the browser editor.
Open in molab: marimo’s free cloud (account required). Your copy saves to your account and reopens on any device. Choose this if you know you’ll switch computers or want to be certain nothing is lost. Optional: nothing graded ever requires it.