在R中向量化for循环

Question

Oh, man. I am so terrible at removing for-loops from my code because I find them so intuitive and I first learned C++. Below, I am fetching IDs for a search (copd in this case) and using that ID to retrieve its full XML file and from that save its location into a vector. I do not know how to speed this up, and it took about 5 minutes to run on 700 IDs, whereas most searches have 70,000+ IDs. Thank you for any and all guidance.

library(rentrez)
library(XML)

# number of articles for term copd
count <- entrez_search(db = "pubmed", term = "copd")$count

# set max to count
id <- entrez_search(db = "pubmed", term = "copd", retmax = count)$ids

# empty vector that will soon contain locations
location <- character()

# get all location data 
for (i in 1:count)
{
  # get ID of each search
  test <- entrez_fetch(db = "pubmed", id = id[i], rettype = "XML")

  # convert to XML
  test_list <- XML::xmlToList(test)

  # retrieve location
  location <- c(location, test_list$PubmedArticle$MedlineCitation$Article$AuthorList$Author$AffiliationInfo$Affiliation)
}

Answer 1

This may give you a start - it seems to be possible to pull down multiple at once.

library(rentrez)
library(xml2)

# number of articles for term copd
count <- entrez_search(db = "pubmed", term = "copd")$count

# set max to count
id_search <- entrez_search(db = "pubmed", term = "copd", retmax = count, use_history = T)

# get all
document <- entrez_fetch(db = "pubmed", rettype = "XML", web_history = id_search$web_history)

document_list <- as_list(read_xml(document))

Problem is that this is still time consuming because there are a large number of documents. Its also curious that it returns exactly 10,000 articles when I've tried this - there may be a limit to what you can return at once.

You can then use something like the purrr package to start extracting the information you want.