[Python] Pandas group by - maximum row for a subset

I have a dataframe with weekly product sales

product_id week_number sales
A1 1 1000
A1 2 2000
A1 3 3000
A2 1 8000
A2 2 4000
A2 3 2000

I want to add a column that identifies rows where the total sales were the highest for the given product:

product_id week_number sales product_max
A1 1 1000 FALSE
A1 2 2000 FALSE
A1 3 3000 TRUE
A2 1 8000 TRUE
A2 2 4000 FALSE
A2 3 2000 FALSE

Since A1 had its highest sales on week 3, that row is tagged as True. But week 3 wasn't the highest for A2. (And so for A2, week 1 is tagged as True.)

I know I could write a loop to do this and cycle through each of the product IDs one by one, but I am wondering if there is a way to do this with a different function - possibly Pandas Groupby?

Thank you!

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