跨多个页面的 R 网络抓取

R web scraping across multiple pages

我正在开发一个网络抓取程序来搜索特定的葡萄酒和 return 该品种的当地葡萄酒列表。我遇到的问题是多页结果。下面的代码是我正在使用的基本示例

url2 <- "http://www.winemag.com/?s=washington+merlot&search_type=reviews"
htmlpage2 <- read_html(url2)
names2 <- html_nodes(htmlpage2, ".review-listing .title")
Wines2 <- html_text(names2)

对于这个特定的搜索,有 39 页的结果。我知道 url 更改为 http://www.winemag.com/?s=washington%20merlot&drink_type=wine&page=2,但是是否有一种简单的方法可以让代码循环遍历所有 returned 页面并将所有 39 页的结果编译到一个列表中?我知道我可以手动完成所有 urls,但这似乎有点矫枉过正。

您可以 lapply 跨越 URL 的矢量,您可以通过将基数 URL 粘贴到一个序列来制作它:

library(rvest)

wines <- lapply(paste0('http://www.winemag.com/?s=washington%20merlot&drink_type=wine&page=', 1:39),
                function(url){
                    url %>% read_html() %>% 
                        html_nodes(".review-listing .title") %>% 
                        html_text()
                })

结果将在列表中返回,每个页面都有一个元素。

如果您希望所有信息都作为 data.frame:

,您也可以对 purrr::map_df() 执行类似的操作
library(rvest)
library(purrr)

url_base <- "http://www.winemag.com/?s=washington merlot&drink_type=wine&page=%d"

map_df(1:39, function(i) {

  # simple but effective progress indicator
  cat(".")

  pg <- read_html(sprintf(url_base, i))

  data.frame(wine=html_text(html_nodes(pg, ".review-listing .title")),
             excerpt=html_text(html_nodes(pg, "div.excerpt")),
             rating=gsub(" Points", "", html_text(html_nodes(pg, "span.rating"))),
             appellation=html_text(html_nodes(pg, "span.appellation")),
             price=gsub("\$", "", html_text(html_nodes(pg, "span.price"))),
             stringsAsFactors=FALSE)

}) -> wines

dplyr::glimpse(wines)
## Observations: 1,170
## Variables: 5
## $ wine        (chr) "Charles Smith 2012 Royal City Syrah (Columbia Valley (WA)...
## $ excerpt     (chr) "Green olive, green stem and fresh herb aromas are at the ...
## $ rating      (chr) "96", "95", "94", "93", "93", "93", "93", "93", "93", "93"...
## $ appellation (chr) "Columbia Valley", "Columbia Valley", "Columbia Valley", "...
## $ price       (chr) "140", "70", "70", "20", "70", "40", "135", "50", "60", "3...