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Week 3: Functions, Files, and Reusable Formulas — Python For Entrepreneurs

Day 16 · ~11 min●

Every Monday you run the same MRR calculation by hand. What would it mean to name that logic and call it with one line?

Like a formula I save in a spreadsheet — except it runs on real data without me manually updating cells.

That's exactly what a function is. def compute_delta(this_week, last_week): is your formula name. The indented block is the formula body. Write it once, call it every Monday. This week you also learn to read a CSV string — the Stripe export you normally open in Excel — directly in Python without touching a file.

Wait — the CSV comes in as a string? I don't need to save a file first?

No file needed. The Pyodide runtime has no filesystem, so functions take the CSV text as an argument. That constraint is actually a gift — your functions become pure, testable, and composable. Five functions this week build the formatted report layer for the capstone investor update.

This week

Day 17 — write make_update_line with a docstring, named params, and return
Day 18 — add default args and return a tuple with summarize_plan
Day 19 — parse a CSV-formatted string into a list of customer dicts
Day 20 — use csv.DictReader + io.StringIO for robust CSV parsing
Day 21 — serialise customer data to JSON with json.dumps(indent=2)

Goal: by Friday your Monday MRR review is a single reusable function call.

Week 3

7 lessons this week

Day 16 · ~11 min●

Every Monday you run the same MRR calculation by hand. What would it mean to name that logic and call it with one line?

Like a formula I save in a spreadsheet — except it runs on real data without me manually updating cells.

Wait — the CSV comes in as a string? I don't need to save a file first?

This week

Day 17 — write make_update_line with a docstring, named params, and return
Day 18 — add default args and return a tuple with summarize_plan
Day 19 — parse a CSV-formatted string into a list of customer dicts
Day 20 — use csv.DictReader + io.StringIO for robust CSV parsing
Day 21 — serialise customer data to JSON with json.dumps(indent=2)

Goal: by Friday your Monday MRR review is a single reusable function call.

This week

Day 17 — write make_update_line with a docstring, named params, and return

Day 18 — add default args and return a tuple with summarize_plan

Day 19 — parse a CSV-formatted string into a list of customer dicts

Day 20 — use csv.DictReader + io.StringIO for robust CSV parsing

Day 21 — serialise customer data to JSON with json.dumps(indent=2)

Goal: by Friday your Monday MRR review is a single reusable function call.

This week

Day 17 — write make_update_line with a docstring, named params, and return

Day 18 — add default args and return a tuple with summarize_plan

Day 19 — parse a CSV-formatted string into a list of customer dicts

Day 20 — use csv.DictReader + io.StringIO for robust CSV parsing

Day 21 — serialise customer data to JSON with json.dumps(indent=2)

Goal: by Friday your Monday MRR review is a single reusable function call.