Transform printout from message to output

Author: lona-k

R/Graph.R

@@ -414,7 +414,7 @@ Graph = R6Class("Graph",
           scc = self$edges[, list(sccssors = paste(unique(dst_id), collapse = ",")), by = list(ID = src_id)]
           lines = scc[prd[lines, on = "ID"], on = "ID"][, c("ID", "State", "sccssors", "prdcssors")]
           lines[is.na(lines)] = ""
-          cli_h1("Graph with {nrow(lines)} PipeOps:")
+          cat_cli(cli_h1("Graph with {nrow(lines)} PipeOps:"))
           ## limit column width ##
 
           outwidth = getOption("width") %??% 80  # output width we want (default 80)
@@ -430,7 +430,7 @@ Graph = R6Class("Graph",
             ppunit = "<SUPPRESSED>"
           }
           pp = paste0(c("<INPUT>", ppunit, "<OUTPUT>"), collapse = " -> ")
-          cli_h3("Pipeline: {.strong {pp}}")
+          cat_cli(cli_h3("Pipeline: {.strong {pp}}"))
         } else {
           cat("Empty Graph.\n")
         }

R/GraphLearner.R

@@ -322,7 +322,7 @@ GraphLearner = R6Class("GraphLearner", inherit = Learner,
         ppunit = "<SUPPRESSED>"
       }
       pp = paste0(c("<INPUT>", ppunit, "<OUTPUT>"), collapse = " -> ")
-      cli_h3("Pipeline: {.strong {pp}}")
+      cat_cli(cli_h3("Pipeline: {.strong {pp}}"))
     }
   ),
   active = list(

R/PipeOp.R

@@ -278,11 +278,15 @@ PipeOp = R6Class("PipeOp",
       }
 
       msg_h = if (self$is_trained) "" else "not "
-      cli_h1("PipeOp {self$id}: {msg_h}trained")
-      cli_text("values: {.arg {as_short_string(self$param_set$values)}}")
-      cli_h3("{.strong Input channels:}")
+      cat_cli({
+        cli_h1("PipeOp {.cls {self$id}}: {msg_h}trained")
+        cli_text("Values: {as_short_string(self$param_set$values)}")
+        cli_h3("{.strong Input channels:}")
+      })
       type_table_printout(self$input)
-      cli_h3("{.strong Output channels:}")
+      cat_cli({
+        cli_h3("{.strong Output channels:}")
+      })
       type_table_printout(self$output)
     },
 

inst/testthat/helper_functions.R

@@ -97,7 +97,7 @@ expect_pipeop = function(po, check_ps_default_values = TRUE) {
   expect_class(po$param_set, "ParamSet", label = label)
   expect_list(po$param_set$values, names = "unique", label = label)
   expect_flag(po$is_trained, label = label)
-  expect_message(print(po), "PipeOp", label = label)
+  expect_output(print(po), "PipeOp", label = label)
   expect_character(po$packages, any.missing = FALSE, unique = TRUE, label = label)
   expect_function(po$train, nargs = 1)
   expect_function(po$predict, nargs = 1)

tests/testthat/_snaps/PipeOp.md

@@ -2,20 +2,17 @@
 
     Code
       print(PipeOpNOP$new())
-    Message
+    Output
       
-      -- PipeOp nop: not trained -----------------------------------------------------
-      values: `list()`
+      -- PipeOp <nop>: not trained ---------------------------------------------------
+      Values: list()
       
       -- Input channels: 
-    Output
          name  train predict
        <char> <char>  <char>
         input      *       *
-    Message
       
       -- Output channels: 
-    Output
          name  train predict
        <char> <char>  <char>
        output      *       *
@@ -24,22 +21,19 @@
 
     Code
       print(PipeOpDebugMulti$new(3, 4))
-    Message
+    Output
       
-      -- PipeOp debug.multi: not trained ---------------------------------------------
-      values: `list()`
+      -- PipeOp <debug.multi>: not trained -------------------------------------------
+      Values: list()
       
       -- Input channels: 
-    Output
           name  train predict
         <char> <char>  <char>
        input_1      *       *
        input_2      *       *
        input_3      *       *
-    Message
       
       -- Output channels: 
-    Output
            name  train predict
          <char> <char>  <char>
        output_1      *       *
@@ -51,13 +45,12 @@
 
     Code
       print(PipeOpDebugMulti$new(100, 0))
-    Message
+    Output
       
-      -- PipeOp debug.multi: not trained ---------------------------------------------
-      values: `list()`
+      -- PipeOp <debug.multi>: not trained -------------------------------------------
+      Values: list()
       
       -- Input channels: 
-    Output
           name  train predict
         <char> <char>  <char>
        input_1      *       *
@@ -66,10 +59,8 @@
        input_4      *       *
        input_5      *       *
       [...] (95 rows omitted)
-    Message
       
       -- Output channels: 
-    Output
           name  train predict
         <char> <char>  <char>
        output_      *       *
@@ -78,20 +69,17 @@
 
     Code
       print(PipeOpBranch$new(c("odin", "dva", "tri")))
-    Message
+    Output
       
-      -- PipeOp branch: not trained --------------------------------------------------
-      values: `selection=odin`
+      -- PipeOp <branch>: not trained ------------------------------------------------
+      Values: selection=odin
       
       -- Input channels: 
-    Output
          name  train predict
        <char> <char>  <char>
         input      *       *
-    Message
       
       -- Output channels: 
-    Output
          name  train predict
        <char> <char>  <char>
          odin      *       *
@@ -102,20 +90,17 @@
 
     Code
       print(PipeOpLearner$new(mlr_learners$get("classif.debug")))
-    Message
+    Output
       
-      -- PipeOp classif.debug: not trained -------------------------------------------
-      values: `list()`
+      -- PipeOp <classif.debug>: not trained -----------------------------------------
+      Values: list()
       
       -- Input channels: 
-    Output
          name       train     predict
        <char>      <char>      <char>
         input TaskClassif TaskClassif
-    Message
       
       -- Output channels: 
-    Output
          name  train           predict
        <char> <char>            <char>
        output   NULL PredictionClassif

tests/testthat/test_Graph.R

@@ -20,14 +20,14 @@ test_that("linear graph", {
 
   expect_graph(g)
 
-  expect_message(print(g), "Graph with 2 PipeOps:")
+  expect_output(print(g), "Graph with 2 PipeOps:")
   expect_output(print(g), ".*subsample.*UNTRAINED.*pca.*UNTRAINED")
 
   inputs = mlr_tasks$get("iris")
   x = g$train(inputs)
   expect_task(x[[1]])
 
-  expect_message(print(g), "Graph with 2 PipeOps")
+  expect_output(print(g), "Graph with 2 PipeOps")
   expect_output(print(g), ".*subsample.*list.*pca.*prcomp")
 
   out = g$predict(inputs)

tests/testthat/test_PipeOp.R

@@ -9,7 +9,7 @@ test_that("PipeOp - General functions", {
   expect_false(po_1$is_trained)
   expect_class(po_1$param_set, "ParamSet")
   expect_list(po_1$param_set$values, names = "unique")
-  expect_message(print(po_1), "PipeOp")
+  expect_output(print(po_1), "PipeOp")
   expect_equal(po_1$packages, "mlr3pipelines")
   expect_null(po_1$state)
   assert_subset(po_1$tags, mlr_reflections$pipeops$valid_tags)