Html ls。一些API在其文档中明确指定了每分钟的最大调用数。如果这一个不知道，可能值得联系API背后的人，看看他们是否知道（并将发布）这些信息。谢谢，@g-grothendieck。在推出我自己的解决方案/答案之前，我可能应该进一步研究一下easyPubMed

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ls。一些API在其文档中明确指定了每分钟的最大调用数。如果这一个不知道，可能值得联系API背后的人，看看他们是否知道（并将发布）这些信息。谢谢，@g-grothendieck。在推出我自己的解决方案/答案之前，我可能应该进一步研究一下

easyPubMed

函数。不幸的是，这是我最初尝试的（并在我的问题中指出），但此方法不包括CSV中包含的其他元数据。谢谢你给我推荐其他的套餐，我会考虑的。

library(httr)
library(jsonlite)
library(tidyverse)

# Search for "hello world"
search_url <- "https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi?db=pubmed&term=%22hello+world%22&format=json"

# Search for results
search_result <- GET(search_url)

# Extract the content
search_content <- content(search_result, 
                          type = "application/json",
                          simplifyVector = TRUE)

# search_content$esearchresult$idlist
# [1] "29725961" "28103545" "27567633" "25955529" "22999052" "19674957"

# Get a vector of the search result IDs
result_ids <- search_content$esearchresult$idlist

# Get a summary for id 29725961 (the first one).
summary_url <- "https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esummary.fcgi?db=pubmed&version=2.0&id=29725961&format=json" # 

summary_result <- GET(summary_url)

# Extract the content
summary_content <- content(summary_result, 
                          type = "application/json")

# Quickie cleanup (thanks to Tony ElHabr)
# https://www.r-bloggers.com/converting-nested-json-to-a-tidy-data-frame-with-r/
summary_untidy <- enframe(unlist(summary_content))

# Get rid of *some* of the fluff...
summary_tidy <- summary_untidy %>% 
  filter(grepl("result.29725961", name)) %>% 
  mutate(name = sub("result.29725961.", "", name))

# Convert the multiple author records into a single comma-separated string.
authors <- summary_tidy %>% 
  filter(grepl("^authors.name$", name)) %>% 
  summarize(pasted = paste(value, collapse = ", "))

# Begin to construct a data frame that has the same information as the downloadable CSV
summary_csv <- tibble(
  Title = summary_tidy %>% filter(name == "title") %>% pull(value),
  URL = sprintf("/pubmed/%s", summary_tidy %>% filter(name == "uid") %>% pull(value)),
  Description = pull(authors, pasted),
  Details = "... and so on, and so on, and so on... "
)

# Write the sample data frame to a csv.
write_csv(summary_csv, path = "just_like_the_search_page_csv.csv")

library(easyPubMed)
out <- batch_pubmed_download(pubmed_query_string = "hello world")
DF <- table_articles_byAuth(pubmed_data = out[1])
write.csv(DF, "helloworld.csv")