Turn an rmd to a df, extracting the knitr chunks and caches.

rmd_to_df

# remotes::install_github('muschellij2/knitr')
library(knitr)

rmd_to_df = function(file) {
  x = xfun::read_utf8(file)
  on.exit(knitr::knit_code$restore(), add = TRUE)
  res = knitr:::split_file(x, patterns = knitr::all_patterns$md)
  classes = sapply(res, attr, "class")
  blocks = res[classes %in% "block"]
  params = lapply(blocks, function(el) {
    if (attr(el, "class") %in% "block") {
      knitr:::block_params(el, verbose = FALSE)
    } else {
      NULL
    }
  })
  df = lapply(params, function(x) {
    if (!is.null(x)) {
      keep_names = c("eval", "echo", "engine", 
                     "label", "code", "hash", "cache",
                     "cache.path", "cache.vars", 
                     "error",
                     "cache.lazy", "fig.path", "fig.ext",
                     "fig.env", "error", "warning", "message",
                     "include", "params.src", "purl")
      x$code = paste(x$code, collapse = "\n")
      x = lapply(keep_names, function(r) {
        xx = x[[r]]
        if (is.null(xx)) {
          xx = NA
        }
        xx
      })
      names(x) = keep_names
      as.data.frame(x[keep_names])
    } else {
      NULL
    }
  })
  df = do.call("rbind", df)
  return(df)
}
tfile = tempfile(fileext = ".Rmd")
curl::curl_download(
  "https://raw.githubusercontent.com/muschellij2/neuroc/master/brain_extraction/index.Rmd",
  destfile = tfile)

res = rmd_to_df(tfile)
head(res, 10)