↗ PYTHON TO PROFIT

Foundations · Free guide

Write Python functions that stay understandable

Functions are not just a way to avoid repeated typing. They create boundaries. A good boundary gives one part of the program a clear job, makes assumptions visible, and creates a place where a test can prove behavior.

Name the result

Prefer calculate_invoice_total over process_data. A concrete verb and noun tell the next reader what the function promises.

Pass inputs explicitly

Hidden global state makes a function harder to reuse and test. Pass the values it needs and return the result.

Keep one level of responsibility

Calculating a total and sending an email are different jobs. Separate pure calculation from external effects such as files, networks, and databases.

Validate at the boundary

Reject impossible values close to where they enter the system. A ValueError with a precise message is better than a mysterious result later.

Working example

from decimal import Decimal

def calculate_invoice_total(
    subtotal: Decimal,
    tax_rate: Decimal,
    discount: Decimal = Decimal("0"),
) -> Decimal:
    if subtotal < 0:
        raise ValueError("subtotal cannot be negative")
    if not Decimal("0") <= tax_rate <= Decimal("1"):
        raise ValueError("tax_rate must be between 0 and 1")
    if not Decimal("0") <= discount <= subtotal:
        raise ValueError("discount must be between 0 and subtotal")

    taxable = subtotal - discount
    return (taxable * (Decimal("1") + tax_rate)).quantize(Decimal("0.01"))
Remember: A good function is a small promise with explicit inputs and a predictable result.
Ready to connect the code to a real product?

Python to Profit teaches the technical and commercial loop: choose a problem, validate it, build the thin path, test it, deploy it, and learn from customers.

Explore the curriculum
← All free guides