Using rvest to Scrape Multiple Job Listing pages - r

Question

I have read through multiple other similar questions and can't seem to find one that gives me the right answer.
I am trying to scrape all the current job titles on TeamWorkOnline.com.
This is the specific URL: https://www.teamworkonline.com/jobs-in-sports?employment_opportunity_search%5Bexclude_united_states_opportunities%5D=0&commit=Search
I have no problem starting the scraping process with this code:
listings <- data.frame(title=character(),
stringsAsFactors=FALSE)
{
url_ds <- paste0('https://www.teamworkonline.com/jobs-in-sports?employment_opportunity_search%5Bexclude_united_states_opportunities%5D=0&commit=Search',i)
var <- read_html(url_ds)
#job title
title <- var %>%
html_nodes('.margin-none') %>%
html_text() %>%
str_extract("(\\w+.+)+")
listings <- rbind(listings, as.data.frame(cbind(title)))
}
However, if you look at the site, there is 'numbered navigation' at the bottom to continue to other pages where more jobs are listed.
I cannot seem to figure out how to add the correct code to get rvest to automatically navigate to the other pages and scrape those jobs as well.
Any help would be greatly appreciated.

Answer 1

Try this:
library(rvest)
library(stringr)
listings <- character()
for (i in 1:25) {
url_ds <- paste0("https://www.teamworkonline.com/jobs-in-sports?employment_opportunity_search%5Bexclude_united_states_opportunities%5D=0&page=", i)
#job title
title <- read_html(url_ds) %>%
html_nodes('.margin-none') %>%
html_text() %>%
str_extract("(\\w+.+)+")
listings <- c(listings, title)
}
Simply loop through all pages to scrape and combine them.

Answer 2

There are 25 pages in the search results,
https://www.teamworkonline.com/jobs-in-sports?employment_opportunity_search%5Bexclude_united_states_opportunities%5D=0&page=25
when ever you clicking on the next button the number at the end of url is changing according to the navigation page number, if the above code working for the first page then you need to iterate through a range 1 to 25 and append your page number to the url and extract it.
I hope it works