diff --git a/DESCRIPTION b/DESCRIPTION
index 6e584f6..fd14462 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -74,4 +74,4 @@ URL: https://inseefrlab.github.io/rtauargus,
 BugReports: https://github.com/inseefrlab/rtauargus/issues
 Roxygen: list(markdown = TRUE)
 StagedInstall: no
-Config/roxygen2/version: 8.0.0
+Config/roxygen2/version: 8.1.0
diff --git a/NAMESPACE b/NAMESPACE
index 5fdf8a9..9b39347 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -28,6 +28,7 @@ export(run_arb)
 export(sp_format)
 export(split_dataframe)
 export(split_in_clusters)
+export(summarize_secret)
 export(tab_arb)
 export(tab_multi_manager)
 export(tab_rda)
@@ -46,19 +47,24 @@ importFrom(dplyr,across)
 importFrom(dplyr,all_of)
 importFrom(dplyr,arrange)
 importFrom(dplyr,bind_rows)
+importFrom(dplyr,case_when)
 importFrom(dplyr,distinct)
 importFrom(dplyr,everything)
 importFrom(dplyr,filter)
 importFrom(dplyr,group_by)
+importFrom(dplyr,last_col)
 importFrom(dplyr,left_join)
 importFrom(dplyr,mutate)
+importFrom(dplyr,n)
 importFrom(dplyr,n_distinct)
 importFrom(dplyr,pull)
 importFrom(dplyr,rename)
+importFrom(dplyr,rename_with)
 importFrom(dplyr,row_number)
 importFrom(dplyr,rowwise)
 importFrom(dplyr,select)
 importFrom(dplyr,summarise)
+importFrom(dplyr,tibble)
 importFrom(dplyr,ungroup)
 importFrom(dplyr,where)
 importFrom(igraph,graph_from_data_frame)
@@ -68,6 +74,7 @@ importFrom(lifecycle,deprecated)
 importFrom(purrr,compact)
 importFrom(purrr,discard)
 importFrom(purrr,imap_dfr)
+importFrom(purrr,list_c)
 importFrom(purrr,map)
 importFrom(purrr,map2)
 importFrom(purrr,map_at)
diff --git a/R/globals.R b/R/globals.R
index 7fdf7ed..6f53a3c 100644
--- a/R/globals.R
+++ b/R/globals.R
@@ -6,5 +6,6 @@ utils::globalVariables(
     "starts_with","spanning_name","hrc_spanning_name","eq_indicator","rhs","total","term_number",
     "eq_name","unit","var","n_total","total_alt","group","initial_indicator","spanning_new",
     "spanning_key","all_sides","side","sides_manquants","table_name_combined","var_mapped",
-    "totcode","all_combinations","covered_sides",".")
+    "totcode","all_combinations","covered_sides","VALUE", "status", "nb_cells",
+    "value",".")
 )
diff --git a/R/multitable.R b/R/multitable.R
index 3e7e3fd..a945bd1 100644
--- a/R/multitable.R
+++ b/R/multitable.R
@@ -122,6 +122,7 @@ tab_multi_manager <- function(
     ip_start = 10,
     ip_end = 0,
     num_iter_max = 10,
+    summary_secret = FALSE,
     split_tab = FALSE,
     nb_tab_option = "smart",
     limit = 14700,
@@ -506,24 +507,10 @@ tab_multi_manager <- function(
       )
     }
   )
-  last_secret <- paste0("is_secret_", num_iter_all)
 
-  stats <- purrr::imap_dfr(
-    liste_tbx_res,
-    function(tab, name){
-      tab$primary_secret <- tab[[secret_var]]
-      tab$total_secret <- tab[[last_secret]]
-      tab$secondary_secret <- tab$total_secret & !tab$primary_secret
-      tab$valid_cells <- !tab$total_secret
-      res <- data.frame(
-        tab_name = name,
-        primary_secret = sum(tab$primary_secret),
-        secondary_secret = sum(tab$secondary_secret),
-        total_secret = sum(tab$total_secret),
-        valid_cells = sum(tab$valid_cells)
-      )
-    }
-  )
+  stats_out <- summarize_secret(liste_tbx_res, var = value, secret_var = secret_var)
+
+  last_secret <- paste0("is_secret_", num_iter_all)
 
   purrr::iwalk(
     num_iter_par_tab,
@@ -539,15 +526,15 @@ tab_multi_manager <- function(
   journal_add_break_line(journal)
   journal_add_line(journal, "Secreted cells counts per table")
   journal_add_break_line(journal)
-  purrr::walk(
-    noms_tbx,
-    function(tab){
+  purrr::iwalk(
+    stats_out,
+    function(tab_stats, tab_name){
       journal_add_line(
         journal,
-        "---TAB ", tab, " ---"
+        "---TAB ", tab_name, " ---"
       )
-      df <- t(stats[stats$tab_name == tab,-1,drop=FALSE])
-      suppressWarnings(gdata::write.fwf(df, rownames = TRUE, colnames = FALSE, file = journal, append = TRUE))
+      # df <- t(stats[stats$tab_name == tab,-1,drop=FALSE])
+      suppressWarnings(gdata::write.fwf(tab_stats, rownames = TRUE, colnames = TRUE, file = journal, append = TRUE))
       journal_add_break_line(journal)
     }
   )
@@ -560,5 +547,14 @@ tab_multi_manager <- function(
   journal_add_line(journal, "End time: ", format(Sys.time(), "%Y-%m-%d  %H:%M:%S"))
   journal_add_break_line(journal)
 
-  return(liste_tbx_res)
+
+  if(summary_secret){
+
+    return( append(liste_tbx_res, list(stats = stats_out)) )
+
+  }else{
+
+    return(liste_tbx_res)
+  }
+
 }
diff --git a/R/summarize_secret.R b/R/summarize_secret.R
new file mode 100644
index 0000000..fa41681
--- /dev/null
+++ b/R/summarize_secret.R
@@ -0,0 +1,125 @@
+#' Provide the summary of the suppression pattern from a rtauargus result
+#'
+#' @param res_tau either the data.frame resulting from tab_rtauargus run or
+#' the list of data.frame resulting from tab_multimanager run
+#' @param var the quantitative variable name to use for values stats of suppression
+#' (default to `NULL` that is the stats are only computed depending on the number of cells )
+#' @param secret_var the name of the variable indicating the primary suppressed cells
+#' @returns data.frame or list of data.frames
+#' @export
+#'
+#' @examples
+#'\dontrun{
+#' library(dplyr)
+#' data(turnover_act_size)
+#'
+#' # Prepare data with primary secret ----
+#' turnover_act_size <- turnover_act_size %>%
+#'   mutate(
+#'     is_secret_freq = N_OBS > 0 & N_OBS < 3,
+#'     is_secret_dom = ifelse(MAX == 0, FALSE, MAX/TOT>0.85),
+#'     is_secret_prim = is_secret_freq | is_secret_dom
+#'   )
+#'
+#' # Make hrc file of business sectors ----
+#' data(activity_corr_table)
+#' hrc_file_activity <- activity_corr_table %>%
+#'   write_hrc2(file_name = "hrc/activity")
+#'
+#' # Compute the secondary secret ----
+#' options(
+#'   rtauargus.tauargus_exe =
+#'     "Y:/Logiciels/TauArgus/TauArgus4.2.3/TauArgus.exe"
+#' )
+#'
+#' res <- tab_rtauargus(
+#'   tabular = turnover_act_size,
+#'   files_name = "turn_act_size",
+#'   dir_name = "tauargus_files",
+#'   explanatory_vars = c("ACTIVITY", "SIZE"),
+#'   hrc = c(ACTIVITY = hrc_file_activity),
+#'   totcode = c(ACTIVITY = "Total", SIZE = "Total"),
+#'   secret_var = "is_secret_prim",
+#'   value = "TOT",
+#'   freq = "N_OBS",
+#'   verbose = FALSE
+#' )
+#'
+#' summarize_secret(res, "TOT")
+#' summarize_secret(res)
+#' }
+#' @importFrom dplyr case_when
+#' @importFrom dplyr last_col
+#' @importFrom dplyr tibble
+#' @importFrom dplyr rename_with
+#' @importFrom dplyr n
+#' @importFrom purrr list_c
+summarize_secret <- function(res_tau, var = NULL, secret_var = "is_secret_prim"){
+
+  if( is.data.frame(res_tau) ) {
+
+    if( !is.null(var)  &&  ! var %in% names(res_tau) ){
+
+      stop("The variable has to be present in the data.frame")
+
+    }
+
+    if( ! secret_var %in% names(res_tau) ){
+
+      stop("The primary secret variable has to be present in the data.frame")
+
+    }
+
+    tab_mod <- res_tau %>%
+      {if( ! is.null(var) ) dplyr::rename_with(., ~"VALUE", all_of(var)) else .} |>
+      dplyr::rename_with(~"final_status_ta", last_col()) |>
+      dplyr::rename_with(~"is_secret_prim", all_of(secret_var)) |>
+      dplyr::mutate(
+        status = case_when(
+          is_secret_prim  ~ "primary suppr.",
+          final_status_ta != "V" ~ "secondary suppr.",
+          TRUE ~ "published"
+        )) |>
+      dplyr::mutate(status = factor(
+        status,
+        levels = c("primary suppr.", "secondary suppr.", "published", "total"),
+        ordered = TRUE)
+      )
+
+    stats <- tab_mod |>
+      group_by(status) %>%
+      {if( ! is.null(var) ) dplyr::summarise(., nb_cells = n(), value = sum(VALUE) ) else dplyr::summarise(., nb_cells = n()) } |>
+      dplyr::bind_rows(
+        dplyr::tibble(
+          status = "total",
+          tab_mod %>% {if( ! is.null(var) ) dplyr::summarise(., nb_cells = n(), value = sum(VALUE)) else dplyr::summarise(., nb_cells = n()) }
+        )
+      ) |>
+      mutate(pourc_cells = round( nb_cells/nb_cells[status == "total"]*100, 2 ) ) %>%
+      {if( ! is.null(var) ) dplyr::mutate(., round( pourc_value = value/value[status == "total"]*100, 2 ) ) else . }
+
+    return(stats)
+
+  }else if( any(! purrr::map(res_tau, is.data.frame) |> purrr::list_c()) ){
+
+    stop("res_tau has to be a data.frame or a list of data.frames")
+
+  }else{
+
+    if( !( is.null(var) ) & any(! purrr::map(res_tau, \(t) var %in% names(t)) |> purrr::list_c()) ){
+
+      stop("The variable has to be present in each of the dataframes")
+
+    }
+
+    if( any(! purrr::map(res_tau, \(t) secret_var %in% names(t)) |> purrr::list_c()) ){
+
+      stop("The primary secret variable has to be present in the data.frame")
+
+    }
+
+    return( purrr::map(res_tau, summarize_secret, var = var) )
+
+  }
+
+}
diff --git a/R/tab_rtauargus.R b/R/tab_rtauargus.R
index 89ffaa4..c129f8b 100644
--- a/R/tab_rtauargus.R
+++ b/R/tab_rtauargus.R
@@ -11,6 +11,7 @@
 #' All files will have the same name, only their extension will be different.
 #' @param dir_name string indicated the path of the directory in which to save
 #' all the files (.rda, .hst, .txt, .arb, .csv) generated by the function.
+#' @param summary_secret If `TRUE`, a statistical summary of the suppression is provided along with the masked data.
 #' @param unif_labels boolean, if explanatory variables have to be standardized
 #' @param split_tab `r lifecycle::badge("experimental")` boolean,
 #' whether to reduce dimension to 3 while treating a table of dimension 4 or 5
@@ -31,12 +32,16 @@
 #' for the treatment of tabular.
 #'
 #' @return
-#' If output_type equals to 4 and split_tab = FALSE,
+#' If output_type equals to 4 and summary_secret = FALSE and split_tab = FALSE,
 #' then the original tabular is returned with a new
 #' column called Status, indicating the status of the cell coming from Tau-Argus :
 #' "A" for a primary secret due to frequency rule, "B" for a primary secret due
 #' to dominance rule, "D" for secondary secret and "V" for no secret cell.
 #'
+#' If summary_secret = TRUE,
+#' then the function returns a list of two data.frames,
+#' including the masked data (`mask`) and the stats data (`stats`).
+#'
 #' If split_tab = TRUE,
 #' then the original tabular is returned with some new columns which are boolean
 #' variables indicating the status of a cell at each iteration of the protection
@@ -45,7 +50,8 @@
 #' final status of the suppression process of the original table.
 #'
 #' If `split_tab = FALSE` and  `output_type` doesn't equal to `4`,
-#' then the raw result from tau-argus is returned.
+#' then the raw result from tau-argus is written as a csv file in `dir_name`
+#' directory and `NULL` is returned to R.
 #'
 #' @section Standardization of explanatory variables and hierarchies:
 #'
@@ -127,6 +133,7 @@ tab_rtauargus <- function(
     maxscore = NULL,
     suppress = "MOD(1,5,1,0,0)",
     safety_rules = paste0("MAN(",ip,")"),
+    summary_secret = FALSE,
     show_batch_console = FALSE,
     output_type = 4,
     output_options = "",
@@ -289,7 +296,7 @@ and the process may take longer.")
   param_run$show_batch_console <- show_batch_console
 
   # appel
-  res <- do.call(run_arb, param_run)
+  invisible( do.call(run_arb, param_run) )
 
   # RESULTAT .............................
   if(output_type == 4){
@@ -316,16 +323,16 @@ and the process may take longer.")
       row.names = FALSE
     )
 
-    return(mask)
-
-  }else{
-    if(unif_labels){
-      res <- cbind.data.frame(
-        apply(res[,explanatory_vars,drop=FALSE], 2, rev_var_pour_tau_argus),
-        res[, !names(res) %in% explanatory_vars]
+    if(summary_secret){
+      return(
+        list(
+          mask = mask,
+          stats = summarize_secret(mask, var = value, secret_var = secret_var)
+        )
       )
+    }else{
+      return(mask)
     }
-    return(res)
   }
 
 }
@@ -442,6 +449,7 @@ tab_rtauargus2 <- function(
   params$dir_name = if(params$split_tab) file.path(dir_name, files_name) else dir_name
   params$nb_tab_option = nb_tab_option
   params$limit = limit
+  params$summary_secret = FALSE
   params$show_batch_console = FALSE
   params$output_type = 4
   params$output_options = ""
diff --git a/R/writehrc.R b/R/writehrc.R
index 4c4b9da..3ade366 100644
--- a/R/writehrc.R
+++ b/R/writehrc.R
@@ -273,8 +273,11 @@ vect_aro <- Vectorize(arobase, vectorize.args = c("string", "number"))
 #'     "telluric", "gasgiant", "bluestar", "whitedwarf",
 #'     "reddwarf", "blackhole", "pulsar")
 #' )
+#' \dontrun{
 #' path <- write_hrc2(astral)
-#' \dontrun{read.table(path)}
+#' read.table(path)
+#' }
+#'
 #' # Note that line order was changed ('other' comes before 'planet'), to no
 #' # consequence whatsoever for Tau-Argus.
 #' # Remarque : l'ordre des lignes a été modifié ('other' arrive avant 'planet'),
@@ -288,16 +291,21 @@ vect_aro <- Vectorize(arobase, vectorize.args = c("string", "number"))
 #'     "reddwarf", "blackhole", "pulsar"),
 #'     type = c("planet", "planet", "star", "star", "star", "other", "other")
 #' )
+#' \dontrun{
 #' path <- write_hrc2(astral_inv)
-#' \dontrun{read.table(path)}
+#' read.table(path)
+#' }
+#'
 #' # Because of the inverted order, everything is written backwards : planet is a
 #' # subtype of gasgiant, etc.
 #' # À cause de l'inversion des colonnes, tout est écrit à l'envers : planet est
 #' # devenu une sous-catégorie de gasgiant, par exemple.
 #'
 #' # Correction :
+#' \dontrun{
 #' path <- write_hrc2(astral_inv, rev = TRUE)
-#' \dontrun{read.table(path)}
+#' read.table(path)
+#' }
 #'
 #' # 2.1 Sparse case
 #' # Cas creux
@@ -310,8 +318,10 @@ vect_aro <- Vectorize(arobase, vectorize.args = c("string", "number"))
 #' # NAs in general are risky, but, in this case, the function works well.
 #' # Les valeurs manquantes causent un risque, mais, dans ce genre de cas,
 #' # la fonction a le comportement attendu.
+#' \dontrun{
 #' path <- write_hrc2(astral_sparse)
-#' \dontrun{read.table(path)}
+#' read.table(path)
+#' }
 #'
 #' # 2.2 Non-uniform depth
 #' # Hiérarchie non-uniforme
@@ -331,8 +341,10 @@ vect_aro <- Vectorize(arobase, vectorize.args = c("string", "number"))
 #'   details  = c("telluric", "gasgiant", "star", "blackhole", "pulsar")
 #' )
 #' # The following code will work
+#' \dontrun{
 #' path <- write_hrc2(astral_nu_fill)
-#' \dontrun{read.table(path)}
+#' read.table(path)
+#' }
 #'
 #' @importFrom zoo na.locf
 #' @export
diff --git a/_pkgdown.yml b/_pkgdown.yml
index 5253665..95cd36f 100644
--- a/_pkgdown.yml
+++ b/_pkgdown.yml
@@ -24,6 +24,7 @@ reference:
     - tab_rtauargus2
     - tab_rtauargus4
     - tabulate_micro_data
+    - summarize_secret
   - title: Proceed to an automatic analysis
     desc: >
       Functions to help the links analysis between tables from a metadata file.
diff --git a/man/summarize_secret.Rd b/man/summarize_secret.Rd
new file mode 100644
index 0000000..876f857
--- /dev/null
+++ b/man/summarize_secret.Rd
@@ -0,0 +1,64 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/summarize_secret.R
+\name{summarize_secret}
+\alias{summarize_secret}
+\title{Provide the summary of the suppression pattern from a rtauargus result}
+\usage{
+summarize_secret(res_tau, var = NULL, secret_var = "is_secret_prim")
+}
+\arguments{
+\item{res_tau}{either the data.frame resulting from tab_rtauargus run or
+the list of data.frame resulting from tab_multimanager run}
+
+\item{var}{the quantitative variable name to use for values stats of suppression
+(default to \code{NULL} that is the stats are only computed depending on the number of cells )}
+
+\item{secret_var}{the name of the variable indicating the primary suppressed cells}
+}
+\value{
+data.frame or list of data.frames
+}
+\description{
+Provide the summary of the suppression pattern from a rtauargus result
+}
+\examples{
+\dontrun{
+library(dplyr)
+data(turnover_act_size)
+
+# Prepare data with primary secret ----
+turnover_act_size <- turnover_act_size \%>\%
+  mutate(
+    is_secret_freq = N_OBS > 0 & N_OBS < 3,
+    is_secret_dom = ifelse(MAX == 0, FALSE, MAX/TOT>0.85),
+    is_secret_prim = is_secret_freq | is_secret_dom
+  )
+
+# Make hrc file of business sectors ----
+data(activity_corr_table)
+hrc_file_activity <- activity_corr_table \%>\%
+  write_hrc2(file_name = "hrc/activity")
+
+# Compute the secondary secret ----
+options(
+  rtauargus.tauargus_exe =
+    "Y:/Logiciels/TauArgus/TauArgus4.2.3/TauArgus.exe"
+)
+
+res <- tab_rtauargus(
+  tabular = turnover_act_size,
+  files_name = "turn_act_size",
+  dir_name = "tauargus_files",
+  explanatory_vars = c("ACTIVITY", "SIZE"),
+  hrc = c(ACTIVITY = hrc_file_activity),
+  totcode = c(ACTIVITY = "Total", SIZE = "Total"),
+  secret_var = "is_secret_prim",
+  value = "TOT",
+  freq = "N_OBS",
+  verbose = FALSE
+)
+
+summarize_secret(res, "TOT")
+summarize_secret(res)
+}
+}
diff --git a/man/tab_multi_manager.Rd b/man/tab_multi_manager.Rd
index 872e54c..6859740 100644
--- a/man/tab_multi_manager.Rd
+++ b/man/tab_multi_manager.Rd
@@ -20,6 +20,7 @@ tab_multi_manager(
   ip_start = 10,
   ip_end = 0,
   num_iter_max = 10,
+  summary_secret = FALSE,
   split_tab = FALSE,
   nb_tab_option = "smart",
   limit = 14700,
@@ -89,6 +90,8 @@ parameters for it.\cr
 
 \item{num_iter_max}{integer: Maximum of treatments to do on each table (default to 10)}
 
+\item{summary_secret}{If \code{TRUE}, a statistical summary of the suppression is provided along with the masked data.}
+
 \item{split_tab}{\ifelse{html}{\href{https://lifecycle.r-lib.org/articles/stages.html#experimental}{\figure{lifecycle-experimental.svg}{options: alt='[Experimental]'}}}{\strong{[Experimental]}} boolean,
 whether to reduce dimension to 3 while treating a table of dimension 4 or 5
 (default to \code{FALSE})}
diff --git a/man/tab_rtauargus.Rd b/man/tab_rtauargus.Rd
index 7803b44..c365d5a 100644
--- a/man/tab_rtauargus.Rd
+++ b/man/tab_rtauargus.Rd
@@ -20,6 +20,7 @@ tab_rtauargus(
   maxscore = NULL,
   suppress = "MOD(1,5,1,0,0)",
   safety_rules = paste0("MAN(", ip, ")"),
+  summary_secret = FALSE,
   show_batch_console = FALSE,
   output_type = 4,
   output_options = "",
@@ -114,6 +115,8 @@ for example.\cr
 Chaîne de caractères en syntaxe batch Tau-Argus. Si le secret primaire
 a été traité dans un fichier d'apriori : utiliser "MAN(10)")}
 
+\item{summary_secret}{If \code{TRUE}, a statistical summary of the suppression is provided along with the masked data.}
+
 \item{show_batch_console}{to display the batch progress in the
 console. \cr
 (pour afficher le déroulement du batch dans la
@@ -156,12 +159,16 @@ tauargus failures}
 for the treatment of tabular.}
 }
 \value{
-If output_type equals to 4 and split_tab = FALSE,
+If output_type equals to 4 and summary_secret = FALSE and split_tab = FALSE,
 then the original tabular is returned with a new
 column called Status, indicating the status of the cell coming from Tau-Argus :
 "A" for a primary secret due to frequency rule, "B" for a primary secret due
 to dominance rule, "D" for secondary secret and "V" for no secret cell.
 
+If summary_secret = TRUE,
+then the function returns a list of two data.frames,
+including the masked data (\code{mask}) and the stats data (\code{stats}).
+
 If split_tab = TRUE,
 then the original tabular is returned with some new columns which are boolean
 variables indicating the status of a cell at each iteration of the protection
@@ -170,7 +177,8 @@ denotes a cell that have to be suppressed. The last column is then the
 final status of the suppression process of the original table.
 
 If \code{split_tab = FALSE} and  \code{output_type} doesn't equal to \code{4},
-then the raw result from tau-argus is returned.
+then the raw result from tau-argus is written as a csv file in \code{dir_name}
+directory and \code{NULL} is returned to R.
 }
 \description{
 The function prepares all the files needed by Tau-Argus and launches the
diff --git a/man/write_hrc2.Rd b/man/write_hrc2.Rd
index b44ea90..644ebeb 100644
--- a/man/write_hrc2.Rd
+++ b/man/write_hrc2.Rd
@@ -253,8 +253,11 @@ astral <- data.frame(
     "telluric", "gasgiant", "bluestar", "whitedwarf",
     "reddwarf", "blackhole", "pulsar")
 )
+\dontrun{
 path <- write_hrc2(astral)
-\dontrun{read.table(path)}
+read.table(path)
+}
+
 # Note that line order was changed ('other' comes before 'planet'), to no
 # consequence whatsoever for Tau-Argus.
 # Remarque : l'ordre des lignes a été modifié ('other' arrive avant 'planet'),
@@ -268,16 +271,21 @@ astral_inv <- data.frame(
     "reddwarf", "blackhole", "pulsar"),
     type = c("planet", "planet", "star", "star", "star", "other", "other")
 )
+\dontrun{
 path <- write_hrc2(astral_inv)
-\dontrun{read.table(path)}
+read.table(path)
+}
+
 # Because of the inverted order, everything is written backwards : planet is a
 # subtype of gasgiant, etc.
 # À cause de l'inversion des colonnes, tout est écrit à l'envers : planet est
 # devenu une sous-catégorie de gasgiant, par exemple.
 
 # Correction :
+\dontrun{
 path <- write_hrc2(astral_inv, rev = TRUE)
-\dontrun{read.table(path)}
+read.table(path)
+}
 
 # 2.1 Sparse case
 # Cas creux
@@ -290,8 +298,10 @@ astral_sparse <- data.frame(
 # NAs in general are risky, but, in this case, the function works well.
 # Les valeurs manquantes causent un risque, mais, dans ce genre de cas,
 # la fonction a le comportement attendu.
+\dontrun{
 path <- write_hrc2(astral_sparse)
-\dontrun{read.table(path)}
+read.table(path)
+}
 
 # 2.2 Non-uniform depth
 # Hiérarchie non-uniforme
@@ -311,7 +321,9 @@ astral_nu_fill <- data.frame(
   details  = c("telluric", "gasgiant", "star", "blackhole", "pulsar")
 )
 # The following code will work
+\dontrun{
 path <- write_hrc2(astral_nu_fill)
-\dontrun{read.table(path)}
+read.table(path)
+}
 
 }