docs_bulk_prep(
  x,
  index,
  path,
  type = NULL,
  chunk_size = 1000,
  doc_ids = NULL,
  quiet = FALSE,
  digits = NA
)

## Not run: 
# From a data.frame
ff <- tempfile(fileext = ".json")
docs_bulk_prep(mtcars, index = "hello", path = ff)
readLines(ff)

## field names cannot contain dots
names(iris) <- gsub("\\.", "_", names(iris))
docs_bulk_prep(iris, "iris", path = tempfile(fileext = ".json"))

## type can be missing, but index can not
docs_bulk_prep(iris, "flowers", path = tempfile(fileext = ".json"))

# From a list
docs_bulk_prep(apply(iris, 1, as.list), index="iris",
   path = tempfile(fileext = ".json"))
docs_bulk_prep(apply(USArrests, 1, as.list), index="arrests",
   path = tempfile(fileext = ".json"))

# when chunking
## multiple files created, one for each chunk
bigiris <- do.call("rbind", replicate(30, iris, FALSE))
docs_bulk_prep(bigiris, index = "big", path = tempfile(fileext = ".json"))

# When using in a loop
## We internally get last _id counter to know where to start on next bulk
## insert but you need to sleep in between docs_bulk_prep calls, longer the
## bigger the data is
files <- c(system.file("examples", "test1.csv", package = "elastic"),
           system.file("examples", "test2.csv", package = "elastic"),
           system.file("examples", "test3.csv", package = "elastic"))
paths <- vector("list", length = length(files))
for (i in seq_along(files)) {
  d <- read.csv(files[[i]])
  paths[i] <- docs_bulk_prep(d, index = "stuff",
     path = tempfile(fileext = ".json"))
}
unlist(paths)

# You can include your own document id numbers
## Either pass in as an argument
files <- c(system.file("examples", "test1.csv", package = "elastic"),
           system.file("examples", "test2.csv", package = "elastic"),
           system.file("examples", "test3.csv", package = "elastic"))
tt <- vapply(files, function(z) NROW(read.csv(z)), numeric(1))
ids <- list(1:tt[1],
           (tt[1] + 1):(tt[1] + tt[2]),
           (tt[1] + tt[2] + 1):sum(tt))
paths <- vector("list", length = length(files))
for (i in seq_along(files)) {
  d <- read.csv(files[[i]])
  paths[i] <- docs_bulk_prep(d, index = "testes",
    doc_ids = ids[[i]], path = tempfile(fileext = ".json"))
}
unlist(paths)

## or include in the input data
### from data.frame's
files <- c(system.file("examples", "test1_id.csv", package = "elastic"),
           system.file("examples", "test2_id.csv", package = "elastic"),
           system.file("examples", "test3_id.csv", package = "elastic"))
paths <- vector("list", length = length(files))
for (i in seq_along(files)) {
  d <- read.csv(files[[i]])
  paths[i] <- docs_bulk_prep(d, index = "testes",
     path = tempfile(fileext = ".json"))
}
unlist(paths)

### from lists via file inputs
paths <- vector("list", length = length(files))
for (i in seq_along(files)) {
  d <- read.csv(files[[i]])
  d <- apply(d, 1, as.list)
  paths[i] <- docs_bulk_prep(d, index = "testes",
      path = tempfile(fileext = ".json"))
}
unlist(paths)


# A mix of actions
## make sure you use a column named 'es_action' or this won't work
## if you need to delete or update you need document IDs
if (index_exists(x, "baz")) index_delete(x, "baz")
df <- data.frame(a = 1:5, b = 6:10, c = letters[1:5], stringsAsFactors = FALSE) 
f <- tempfile(fileext = ".json")
invisible(docs_bulk_prep(df, "baz", f))
cat(readLines(f), sep = "\n")
docs_bulk(x, f)
Sys.sleep(2)
(res <- Search(x, 'baz', asdf=TRUE)$hits$hits)

df[1, "a"] <- 99
df[1, "c"] <- "aa"
df[3, "c"] <- 33
df[3, "c"] <- "cc"
df$es_action <- c('update', 'delete', 'update', 'delete', 'delete')
df$id <- res$`_id`
df
f <- tempfile(fileext = ".json")
invisible(docs_bulk_prep(df, "baz", path = f, doc_ids = df$id))
cat(readLines(f), sep = "\n")
docs_bulk(x, f)


# suppress progress bar
docs_bulk_prep(mtcars, index = "hello",
  path = tempfile(fileext = ".json"), quiet = TRUE)
## vs. 
docs_bulk_prep(mtcars, index = "hello",
  path = tempfile(fileext = ".json"), quiet = FALSE)

## End(Not run)