{"id":15995,"date":"2022-10-13T20:25:26","date_gmt":"2022-10-13T14:55:26","guid":{"rendered":"https:\/\/jassweb.com\/solved\/solved-improving-my-r-code-advice-wanted-on-better-way-of-coding-closed\/"},"modified":"2022-10-13T20:25:26","modified_gmt":"2022-10-13T14:55:26","slug":"solved-improving-my-r-code-advice-wanted-on-better-way-of-coding-closed","status":"publish","type":"post","link":"https:\/\/jassweb.com\/solved\/solved-improving-my-r-code-advice-wanted-on-better-way-of-coding-closed\/","title":{"rendered":"[Solved] Improving my R code – advice wanted on better way of coding? [closed]"},"content":{"rendered":"

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You could try using purrr<\/code> instead of the loop as follows:<\/p>\n

require(rvest)\nrequire(purrr)\nrequire(tibble)\n\nURLs %>% \n  map(read_html) %>% \n  map(html_nodes, \"#yw1 .spielprofil_tooltip\") %>% \n  map_df(~tibble(Player = html_text(.), P_URL = html_attr(., \"href\")))\n<\/code><\/pre>\n
Timing:<\/p>\n
   user  system elapsed \n  2.939   2.746   5.699 \n<\/code><\/pre>\n
The step that take the most time is the crawling via map(read_html)<\/code>.
\nTo paralyze that you can use e.g. the parallel backend of plyr<\/code> as follows:<\/p>\n
require(httr)\ndoMC::registerDoMC(cores=3) # cores depending on your system\nplyr::llply(URLs, GET, .parallel = TRUE) %>% \n  map(read_html) %>% \n  map(html_nodes, \"#yw1 .spielprofil_tooltip\") %>% \n  map_df(~tibble(Player = html_text(.), P_URL = html_attr(., \"href\")))\n<\/code><\/pre>\n
Somehow my Rstudio crashed using plyr::llply(URLs, read_html, .parallel = TRUE)<\/code> thats why i use the underlying httr::GET<\/code> and parse the result in the next step via map(read_html)<\/code>. So the scraping is done in parallel but the parsing of the response is done sequentially.<\/p>\n
Timing:<\/p>\n
   user  system elapsed \n  2.505   0.337   2.940 \n<\/code><\/pre>\n
In both cases the result looks as follows:<\/p>\n
# A tibble: 1,036 \u00d7 2\n          Player                                P_URL\n           <chr>                                <chr>\n1   David de Gea   \/david-de-gea\/profil\/spieler\/59377\n2      D. de Gea   \/david-de-gea\/profil\/spieler\/59377\n3  Sergio Romero  \/sergio-romero\/profil\/spieler\/30690\n4      S. Romero  \/sergio-romero\/profil\/spieler\/30690\n5  Sam Johnstone \/sam-johnstone\/profil\/spieler\/110864\n6   S. Johnstone \/sam-johnstone\/profil\/spieler\/110864\n7    Daley Blind    \/daley-blind\/profil\/spieler\/12282\n8       D. Blind    \/daley-blind\/profil\/spieler\/12282\n9    Eric Bailly   \/eric-bailly\/profil\/spieler\/286384\n10     E. Bailly   \/eric-bailly\/profil\/spieler\/286384\n# ... with 1,026 more rows\n<\/code><\/pre>\n<\/p><\/div>\n
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            2<\/span> <\/p><\/div>\n<\/div>\n
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solved Improving my R code – advice wanted on better way of coding? [closed] <\/p>\n","protected":false},"excerpt":{"rendered":"
[ad_1] You could try using purrr instead of the loop as follows: require(rvest) require(purrr) require(tibble) URLs %>% map(read_html) %>% map(html_nodes, “#yw1 .spielprofil_tooltip”) %>% map_df(~tibble(Player = html_text(.), P_URL = html_attr(., “href”))) Timing: user system elapsed 2.939 2.746 5.699 The step that take the most time is the crawling via map(read_html). To paralyze that you can use … Read more<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[320],"tags":[321],"class_list":["post-15995","post","type-post","status-publish","format-standard","hentry","category-solved","tag-r"],"yoast_head":"\n[Solved] Improving my R code - advice wanted on better way of coding? 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