RSelenium may end up being the way to go. However, if you can insert some judicious waits, or chunk your requests, so server isn't swamped with requests, you can use rvest and make the same requests the page does.
You first need to generate all the combinations of province and comune (filtering out unwanted values); this can be done by making xmlhttp requests, using the value attribute for the options within the select for province, to gather back the comune dropdown options and their associated values.
You then make further requests, for each combination pair, to get the page content, which you would get when making selections from each of those dropdowns manually and pushing CERCA.
Pauses are needed as there are 10,389 valid combinations, by my reckoning, and, if you attempt to make all those requests one after the other, following the initial requests as well, the server will cut-off the connection.
Another option would be to chunk up combined into smaller dataframes and make requests for those at timed intervals and then combine the results.
library(rvest)
library(dplyr)
library(purrr)
get_provincias <- function(link) {
nodes <- read_html(link) %>%
html_nodes('[name="provincia"] > option:not([selected]):not(:contains("-")):not(:contains("\u0085"))')
df <- data.frame(
Provincia = nodes %>% html_text(trim = T),
id0 = nodes %>% html_attr("value")
)
return(df)
}
get_comunes <- function(id) {
link <- sprintf(
"https://www.solferinoesanmartino.it/db-torelli/_get_comuni.php?id0=%s&id1=0&_=%i",
id,
as.numeric(as.POSIXct(Sys.Date(), format = "%Y-%m-%d"))
)
# print(link)
nodes <- read_html(link) %>% html_nodes('option:not([value="0"])')
df <- data.frame(
id0 = id, # id1
Comune = nodes %>% html_text(trim = T),
id3 = nodes %>% html_attr("value")
)
return(df)
}
get_page <- function(prov_id, com_id) {
link <- sprintf(
"https://www.solferinoesanmartino.it/db-torelli/_get_soldati.php?id0=1&id1=&id2=%s&id3=%s&_=%i",
prov_id,
com_id,
as.numeric(as.POSIXct(Sys.Date(), format = "%Y-%m-%d"))
)
page <- read_html(link)
# print(page %>% html_node(".listing_name") %>% html_text(trim = T))
# print(tibble(id3 = com_id, page = page))
return(tibble(id3 = com_id, page = page))
}
provincias <- get_provincias("https://www.solferinoesanmartino.it/progetto-torelli/progetto-torelli-risultati")
comunes <- map_df(provincias$id0, get_comunes) %>% filter(Comune != "-")
combined <- dplyr::right_join(provincias, comunes, by = "id0")
# length(combined$Comune) -> 10389
results <- map2_dfr(combined$id0, combined$id3, .f = get_page)
final <- dplyr::inner_join(combined, results, by = "id3")
Below is a longer version, with the additional info you requested, where I played around with adding pauses. I still found that I could run up to, and including
combined <- dplyr::right_join(provincias, comunes, by = "id0")
in one go. But after that I needed to chunk requests into about 2000 requests batches with 20-30 minutes in between. You can try tweaking the timings below. I ended up using the commented out section to run each batch and then left a pause of 30 mins in between.
Some things to consider:
It seems that you can have comunes values like ... which still return listings. With that in mind you may wish to remove the :not parts of this:
html_nodes('[name="provincia"] > option:not([selected]):not(:contains("-")):not(:contains("\u0085"))')
as I assumed that was filtering out invalid results.
Next, you might consider writing a helper function with httr and retry,
to make the requests with backoff/retry, rather than use pauses.
Such a function might look like this:
httr::RETRY(
"GET",
<request url>,
times = 3,
pause_min = 20*60,
pause_base = 20*60)
Anyway, those are some ideas. Even without the server cutting the connection, via uses of waits, I still found it started to throttle requests, meaning some requests took quite a long time to complete. Optimizing this could potentially take a lot of time and effort. I spent a good few days playing around looking at chunk size and waits.
library(rvest)
library(dplyr)
library(purrr)
get_provincias <- function(link) {
nodes <- read_html(link) %>%
html_nodes('[name="provincia"] > option:not([selected]):not(:contains("-")):not(:contains("\u0085"))')
df <- data.frame(
Provincia = nodes %>% html_text(trim = T),
id0 = nodes %>% html_attr("value")
)
return(df)
}
get_comunes <- function(id) {
link <- sprintf(
"https://www.solferinoesanmartino.it/db-torelli/_get_comuni.php?id0=%s&id1=0&_=%i",
id,
as.numeric(as.POSIXct(Sys.Date(), format = "%Y-%m-%d"))
)
# print(link)
nodes <- read_html(link) %>% html_nodes('option:not([value="0"])')
df <- data.frame(
id0 = id, # id1
Comune = nodes %>% html_text(trim = T),
id3 = nodes %>% html_attr("value")
)
return(df)
}
get_data <- function(prov_id, com_id) {
link <- sprintf(
"https://www.solferinoesanmartino.it/db-torelli/_get_soldati.php?id0=1&id1=&id2=%s&id3=%s&_=%i",
prov_id,
com_id,
as.numeric(as.POSIXct(Sys.Date(), format = "%Y-%m-%d"))
)
# print(link)
page <- read_html(link)
df <- data.frame(
cognome = page %>% html_nodes(".listing_name") %>% html_text(trim = T),
livello = page %>% html_nodes(".listing_level") %>% html_text(trim = T),
id3 = com_id,# for later join back on comune
id0 = prov_id
)
Sys.sleep(.25) # pause for . sec
return(df)
}
get_chunks <- function(df, chunk_size) { # adapted from @BenBolker https://stackoverflow.com/a/7060331
n <- nrow(df)
r <- rep(1:ceiling(n / chunk_size), each = chunk_size)[1:n]
d <- split(df, r)
return(d)
}
write_rows <- function(df, filename) {
flag <- file.exists(filename)
df2 <- purrr::map2_dfr(df$id0, df$id3, .f = get_data)
write.table(df2,
file = filename, sep = ",",
append = flag,
quote = F, col.names = !flag,
row.names = F
)
Sys.sleep(60*10)
}
provincias <- get_provincias("https://www.solferinoesanmartino.it/progetto-torelli/progetto-torelli-risultati")
Sys.sleep(60*5)
comunes <- map_df(provincias$id0, get_comunes) %>% filter(Comune != "-")
Sys.sleep(60*10)
combined <- dplyr::right_join(provincias, comunes, by = "id0")
Sys.sleep(60*10)
chunked <- get_chunks(combined, 2000) # https://stackoverflow.com/questions/7060272/split-up-a-dataframe-by-number-of-rows
filename <- "prov_com_cog_liv.csv"
map(chunked, ~ write_rows(.x, filename))
## #### test case #####################
# df <- chunked[[6]]
#
# flag <- file.exists(filename)
#
# df2 <- map2_dfr(df$id0, df$id3, .f = get_data)
#
# write.table(df2,
# file = filename, sep = ",",
# append = flag,
# quote = F, col.names = !flag,
# row.names = F
# )
####################################
results <- read.csv(filename)
final <- dplyr::right_join(combined, results, by = "id3")
