How to correctly identify html node - html

Question

I want to scrape the price of a product on a webshop, but I struggle to correctly allocate the correct nodes to the price i want to scrape.
The relevant part of my code looks like this:
"https://www.surfdeal.ch/produkt/2019-aqua-marina-fusion-orange/"%>%
read_html()%>%
html_nodes('span.woocommerce-Price-amount.amount')%>%
html_text()
When executing this code, I do get prices as a result, but not the ones i want (it shows the prices of other produts that are listed beneath.
How can I now correctly identify the node to the price of the product itself (375.-)

Answer 1

First: I don't know R.
This page uses JavaScript to add this price in HTML
but I don't know if rvest can run JavaScript.
But I found this value in <form data-product_variations="..."> as JSON
and I could display prices for all options:
data <- "https://www.surfdeal.ch/produkt/2019-aqua-marina-fusion-orange/" %>%
read_html() %>%
html_nodes('form.variations_form.cart') %>%
html_attr('data-product_variations') %>%
fromJSON
data$display_price
data$regular_price
data$image$title
Result:
> data$display_price
[1] 479 375 439 479 479
> data$display_regular_price
[1] 699 549 629 699 699
> data$image$title
[1] "aqua marina fusion bamboo padddel"
[2] "aqua marina fusion aluminium padddel"
[3] "aqua marina fusion carbon padddel"
[4] "aqua marina fusion hibi padddel"
[5] "aqua marina fusion silver padddel"
> colnames(data)
[1] "attributes" "availability_html" "backorders_allowed"
[4] "dimensions" "dimensions_html" "display_price"
[7] "display_regular_price" "image" "image_id"
[10] "is_downloadable" "is_in_stock" "is_purchasable"
[13] "is_sold_individually" "is_virtual" "max_qty"
[16] "min_qty" "price_html" "sku"
[19] "variation_description" "variation_id" "variation_is_active"
[22] "variation_is_visible" "weight" "weight_html"
[25] "is_bookable" "number_of_dates" "your_discount"
[28] "gtin" "your_delivery"
EDIT:
To work with page which uses JavaScript you may need other tools - like phantomjs
How to Scrape Data from a JavaScript Website with R | R-bloggers