[Python] Sum of products of columns in polars

I have a dataset, part of which looks like this:

customer product

price​

quantity​

sale_time
C060235 P0204

6.99​

2​

2024-03-11 08:24:11
C045298 P0167

14.99​

1​

2024-03-11 08:35:06
...
C039877 P0024

126.95​

1​

2024-09-30 21:18:45

What I want is a list of unique customer, product pairs with the total sales, so something like:

customer product

total​

C0000105 P0168

643.78​

C0000105 P0204

76.88​

...
C1029871 P1680

435.44​

Here's my attempt at constructing this. This gives me the grand total of all sales, which isn't what I want. What's a correct approach?

import polars as pl

db.select(
(
pl.col('customer'),
pl.col('product'),
pl.col('quantity').mul(pl.col('price')).alias('total')
)
).group_by(('customer', 'product'))

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