diff --git a/DESCRIPTION b/DESCRIPTION
index 2bd011e60..8b5b8b982 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,6 +1,6 @@
 Package: mlr3pipelines
 Title: Preprocessing Operators and Pipelines for 'mlr3'
-Version: 0.5.1-9000
+Version: 0.5.2-9000
 Authors@R:
     c(person(given = "Martin",
              family = "Binder",
@@ -86,7 +86,8 @@ Suggests:
     GenSA,
     methods,
     vtreat,
-    future
+    future,
+    htmlwidgets
 ByteCompile: true
 Encoding: UTF-8
 Config/testthat/edition: 3
@@ -175,6 +176,7 @@ Collate:
     'operators.R'
     'pipeline_bagging.R'
     'pipeline_branch.R'
+    'pipeline_convert_types.R'
     'pipeline_greplicate.R'
     'pipeline_ovr.R'
     'pipeline_robustify.R'
diff --git a/NAMESPACE b/NAMESPACE
index ab287b3d8..0c06c28ab 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -127,6 +127,7 @@ export(mlr_graphs)
 export(mlr_pipeops)
 export(pipeline_bagging)
 export(pipeline_branch)
+export(pipeline_convert_types)
 export(pipeline_greplicate)
 export(pipeline_ovr)
 export(pipeline_robustify)
diff --git a/NEWS.md b/NEWS.md
index 1923c3e3a..0e40259de 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,4 +1,10 @@
-# mlr3pipelines 0.5.1-9000
+# mlr3pipelines 0.5.2-9000
+
+# mlr3pipelines 0.5.2
+
+* Added new `ppl("convert_types")`.
+* Minor documentation fixes.
+* Test helpers are now available in `inst/`. These are considered experimental and unstable.
 
 * Added marshaling support to `GraphLearner`
 
diff --git a/R/GraphLearner.R b/R/GraphLearner.R
index db254036a..4bf5c573a 100644
--- a/R/GraphLearner.R
+++ b/R/GraphLearner.R
@@ -68,6 +68,7 @@
 #' @family Learners
 #' @export
 #' @examples
+#' \dontshow{ if (requireNamespace("rpart")) \{ }
 #' library("mlr3")
 #'
 #' graph = po("pca") %>>% lrn("classif.rpart")
@@ -86,6 +87,7 @@
 #'
 #' # Feature importance (of principal components):
 #' lr$graph_model$pipeops$classif.rpart$learner_model$importance()
+#' \dontshow{ \} }
 GraphLearner = R6Class("GraphLearner", inherit = Learner,
   public = list(
     initialize = function(graph, id = NULL, param_vals = list(), task_type = NULL, predict_type = NULL, clone_graph = TRUE) {
diff --git a/R/PipeOpBoxCox.R b/R/PipeOpBoxCox.R
index 43924c7f2..45cafc5fc 100644
--- a/R/PipeOpBoxCox.R
+++ b/R/PipeOpBoxCox.R
@@ -48,6 +48,7 @@
 #' Only methods inherited from [`PipeOpTaskPreproc`]/[`PipeOp`].
 #'
 #' @examples
+#' \dontshow{ if (requireNamespace("bestNormalize")) \{ }
 #' library("mlr3")
 #'
 #' task = tsk("iris")
@@ -57,6 +58,7 @@
 #' pop$train(list(task))[[1]]$data()
 #'
 #' pop$state
+#' \dontshow{ \} }
 #' @family PipeOps
 #' @include PipeOpTaskPreproc.R
 #' @template seealso_pipeopslist
diff --git a/R/PipeOpClassifAvg.R b/R/PipeOpClassifAvg.R
index f9efd0e82..694cdda66 100644
--- a/R/PipeOpClassifAvg.R
+++ b/R/PipeOpClassifAvg.R
@@ -64,6 +64,7 @@
 #' @export
 #'
 #' @examples
+#' \dontshow{ if (requireNamespace("rpart")) \{ }
 #' \donttest{
 #' library("mlr3")
 #'
@@ -77,6 +78,7 @@
 #'
 #' resample(tsk("iris"), GraphLearner$new(gr), rsmp("holdout"))
 #' }
+#' \dontshow{ \} }
 PipeOpClassifAvg = R6Class("PipeOpClassifAvg",
   inherit = PipeOpEnsemble,
   public = list(
diff --git a/R/PipeOpEncode.R b/R/PipeOpEncode.R
index 35e630525..e9fb0b51a 100644
--- a/R/PipeOpEncode.R
+++ b/R/PipeOpEncode.R
@@ -5,7 +5,7 @@
 #' @format [`R6Class`] object inheriting from [`PipeOpTaskPreprocSimple`]/[`PipeOpTaskPreproc`]/[`PipeOp`].
 #'
 #' @description
-#' Encodes columns of type `factor`, `character` and `ordered`.
+#' Encodes columns of type `factor` and `ordered`.
 #'
 #' Possible encodings are `"one-hot"` encoding, as well as encoding according to `stats::contr.helmert()`, `stats::contr.poly()`,
 #' `stats::contr.sum()` and `stats::contr.treatment()`.
@@ -14,6 +14,8 @@
 #'
 #' Use the [`PipeOpTaskPreproc`] `$affect_columns` functionality to only encode a subset of columns, or only encode columns of a certain type.
 #'
+#' `character`-type features can be encoded by converting them `factor` features first, using [`ppl("convert_types", "character", "factor")`][mlr_graphs_convert_types].
+#'
 #' @section Construction:
 #' ```
 #' PipeOpEncode$new(id = "encode", param_vals = list())
@@ -26,7 +28,7 @@
 #' @section Input and Output Channels:
 #' Input and output channels are inherited from [`PipeOpTaskPreproc`].
 #'
-#' The output is the input [`Task`][mlr3::Task] with all affected `factor`, `character` or `ordered` parameters encoded according to the `method`
+#' The output is the input [`Task`][mlr3::Task] with all affected `factor` and `ordered` parameters encoded according to the `method`
 #' parameter.
 #'
 #' @section State:
@@ -78,6 +80,14 @@
 #'
 #' poe$param_set$values$method = "sum"
 #' poe$train(list(task))[[1]]$data()
+#'
+#' # converting character-columns
+#' data_chr = data.table::data.table(x = factor(letters[1:3]), y = letters[1:3])
+#' task_chr = TaskClassif$new("task_chr", data_chr, "x")
+#'
+#' goe = ppl("convert_types", "character", "factor") %>>% po("encode")
+#'
+#' goe$train(task_chr)[[1]]$data()
 PipeOpEncode = R6Class("PipeOpEncode",
   inherit = PipeOpTaskPreprocSimple,
   public = list(
diff --git a/R/PipeOpEncodeLmer.R b/R/PipeOpEncodeLmer.R
index abdb031b0..cacb15ea3 100644
--- a/R/PipeOpEncodeLmer.R
+++ b/R/PipeOpEncodeLmer.R
@@ -72,6 +72,8 @@
 #' @include PipeOpTaskPreproc.R
 #' @export
 #' @examples
+#' \dontshow{ if (requireNamespace("nloptr")) \{ }
+#' \dontshow{ if (requireNamespace("lme4")) \{ }
 #' library("mlr3")
 #' poe = po("encodelmer")
 #'
@@ -84,6 +86,8 @@
 #' poe$train(list(task))[[1]]$data()
 #'
 #' poe$state
+#' \dontshow{ \} }
+#' \dontshow{ \} }
 PipeOpEncodeLmer = R6Class("PipeOpEncodeLmer",
   inherit = PipeOpTaskPreprocSimple,
   public = list(
diff --git a/R/PipeOpFilter.R b/R/PipeOpFilter.R
index d8657dce4..321849709 100644
--- a/R/PipeOpFilter.R
+++ b/R/PipeOpFilter.R
@@ -80,6 +80,8 @@
 #' @include PipeOpTaskPreproc.R
 #' @export
 #' @examples
+#' \dontshow{ if (requireNamespace("mlr3filters")) \{ }
+#' \dontshow{ if (requireNamespace("rpart")) \{ }
 #' library("mlr3")
 #' library("mlr3filters")
 #' \dontshow{data.table::setDTthreads(1)}
@@ -107,6 +109,8 @@
 #' learner = GraphLearner$new(gr)
 #' rr = resample(task, learner, rsmp("holdout"), store_models = TRUE)
 #' rr$learners[[1]]$model$auc$scores
+#' \dontshow{ \} }
+#' \dontshow{ \} }
 PipeOpFilter = R6Class("PipeOpFilter",
   inherit = PipeOpTaskPreprocSimple,
   public = list(
diff --git a/R/PipeOpICA.R b/R/PipeOpICA.R
index 9f363ed3e..32b500bc2 100644
--- a/R/PipeOpICA.R
+++ b/R/PipeOpICA.R
@@ -73,6 +73,7 @@
 #' Only methods inherited from [`PipeOpTaskPreproc`]/[`PipeOp`].
 #'
 #' @examples
+#' \dontshow{ if (requireNamespace("fastICA")) \{ }
 #' library("mlr3")
 #'
 #' task = tsk("iris")
@@ -82,6 +83,7 @@
 #' pop$train(list(task))[[1]]$data()
 #'
 #' pop$state
+#' \dontshow{ \} }
 #' @family PipeOps
 #' @template seealso_pipeopslist
 #' @include PipeOpTaskPreproc.R
diff --git a/R/PipeOpImputeLearner.R b/R/PipeOpImputeLearner.R
index 2dd9ef473..e2e4e048c 100644
--- a/R/PipeOpImputeLearner.R
+++ b/R/PipeOpImputeLearner.R
@@ -70,6 +70,7 @@
 #' Only methods inherited from [`PipeOpImpute`]/[`PipeOp`].
 #'
 #' @examples
+#' \dontshow{ if (requireNamespace("rpart")) \{ }
 #' library("mlr3")
 #'
 #' task = tsk("pima")
@@ -93,6 +94,7 @@
 #' new_task = po$train(list(task = task))[[1]]
 #' new_task$missings()
 #'
+#' \dontshow{ \} }
 #' @family PipeOps
 #' @family Imputation PipeOps
 #' @template seealso_pipeopslist
diff --git a/R/PipeOpKernelPCA.R b/R/PipeOpKernelPCA.R
index 5c24b21d4..0adb4017c 100644
--- a/R/PipeOpKernelPCA.R
+++ b/R/PipeOpKernelPCA.R
@@ -52,6 +52,7 @@
 #' Only methods inherited from [`PipeOpTaskPreproc`]/[`PipeOp`].
 #'
 #' @examples
+#' \dontshow{ if (requireNamespace("kernlab")) \{ }
 #' library("mlr3")
 #'
 #' task = tsk("iris")
@@ -59,6 +60,7 @@
 #'
 #' task$data()
 #' pop$train(list(task))[[1]]$data()
+#' \dontshow{ \} }
 #' @family PipeOps
 #' @template seealso_pipeopslist
 #' @include PipeOpTaskPreproc.R
diff --git a/R/PipeOpLearner.R b/R/PipeOpLearner.R
index b35949e78..5894dff94 100644
--- a/R/PipeOpLearner.R
+++ b/R/PipeOpLearner.R
@@ -72,6 +72,7 @@
 #' @include PipeOp.R
 #' @export
 #' @examples
+#' \dontshow{ if (requireNamespace("rpart")) \{ }
 #' library("mlr3")
 #'
 #' task = tsk("iris")
@@ -80,6 +81,7 @@
 #'
 #' lrn_po$train(list(task))
 #' lrn_po$predict(list(task))
+#' \dontshow{ \} }
 PipeOpLearner = R6Class("PipeOpLearner", inherit = PipeOp,
   public = list(
     initialize = function(learner, id = NULL, param_vals = list()) {
diff --git a/R/PipeOpLearnerCV.R b/R/PipeOpLearnerCV.R
index db464aeda..ed7166c70 100644
--- a/R/PipeOpLearnerCV.R
+++ b/R/PipeOpLearnerCV.R
@@ -93,6 +93,7 @@
 #' @include PipeOpTaskPreproc.R
 #' @export
 #' @examples
+#' \dontshow{ if (requireNamespace("rpart")) \{ }
 #' library("mlr3")
 #'
 #' task = tsk("iris")
@@ -113,6 +114,7 @@
 #' graph$pipeops$classif.rpart$learner$predict_type = "prob"
 #'
 #' graph$train(task)
+#' \dontshow{ \} }
 PipeOpLearnerCV = R6Class("PipeOpLearnerCV",
   inherit = PipeOpTaskPreproc,
   public = list(
diff --git a/R/PipeOpNMF.R b/R/PipeOpNMF.R
index bb99d02b1..b6ff08842 100644
--- a/R/PipeOpNMF.R
+++ b/R/PipeOpNMF.R
@@ -88,6 +88,8 @@
 #' Only methods inherited from [`PipeOpTaskPreproc`]/[`PipeOp`].
 #'
 #' @examples
+#' \dontshow{ if (requireNamespace("NMF")) \{ }
+#' \dontshow{ if (requireNamespace("MASS")) \{ }
 #' if (requireNamespace("NMF")) {
 #' library("mlr3")
 #'
@@ -99,6 +101,8 @@
 #'
 #' pop$state
 #' }
+#' \dontshow{ \} }
+#' \dontshow{ \} }
 #' @family PipeOps
 #' @template seealso_pipeopslist
 #' @include PipeOpTaskPreproc.R
diff --git a/R/PipeOpOVR.R b/R/PipeOpOVR.R
index e8d7c6e78..814041b75 100644
--- a/R/PipeOpOVR.R
+++ b/R/PipeOpOVR.R
@@ -68,11 +68,13 @@
 #' @include PipeOp.R
 #' @export
 #' @examples
+#' \dontshow{ if (requireNamespace("rpart")) \{ }
 #' library(mlr3)
 #' task = tsk("iris")
 #' po = po("ovrsplit")
 #' po$train(list(task))
 #' po$predict(list(task))
+#' \dontshow{ \} }
 PipeOpOVRSplit = R6Class("PipeOpOVRSplit",
   inherit = PipeOp,
   public = list(
@@ -174,6 +176,7 @@ mlr_pipeops$add("ovrsplit", PipeOpOVRSplit)
 #' @include PipeOpEnsemble.R
 #' @export
 #' @examples
+#' \dontshow{ if (requireNamespace("rpart")) \{ }
 #' library(mlr3)
 #' task = tsk("iris")
 #' gr = po("ovrsplit") %>>% lrn("classif.rpart") %>>% po("ovrunite")
@@ -181,6 +184,7 @@ mlr_pipeops$add("ovrsplit", PipeOpOVRSplit)
 #' gr$predict(task)
 #' gr$pipeops$classif.rpart$learner$predict_type = "prob"
 #' gr$predict(task)
+#' \dontshow{ \} }
 PipeOpOVRUnite = R6Class("PipeOpOVRUnite",
   inherit = PipeOpEnsemble,
   public = list(
diff --git a/R/PipeOpProxy.R b/R/PipeOpProxy.R
index 5d7b91236..0a61c1177 100644
--- a/R/PipeOpProxy.R
+++ b/R/PipeOpProxy.R
@@ -55,6 +55,7 @@
 #' Only methods inherited from [`PipeOp`].
 #'
 #' @examples
+#' \dontshow{ if (requireNamespace("rpart")) \{ }
 #' library("mlr3")
 #' library("mlr3learners")
 #'
@@ -73,6 +74,7 @@
 #' g$param_set$values$learner.content = lrn("classif.rpart")
 #' rr_pca_rpart = resample(task, learner = GraphLearner$new(g), resampling = rsmp("cv", folds = 3))
 #' rr_pca_rpart$aggregate(msr("classif.ce"))
+#' \dontshow{ \} }
 #' @family PipeOps
 #' @template seealso_pipeopslist
 #' @include PipeOp.R
diff --git a/R/PipeOpRandomResponse.R b/R/PipeOpRandomResponse.R
index b883c8858..336f83f6c 100644
--- a/R/PipeOpRandomResponse.R
+++ b/R/PipeOpRandomResponse.R
@@ -63,6 +63,7 @@
 #' @include PipeOp.R
 #' @export
 #' @examples
+#' \dontshow{ if (requireNamespace("rpart")) \{ }
 #' library(mlr3)
 #' library(mlr3learners)
 #'
@@ -79,6 +80,7 @@
 #' g2$pipeops$regr.lm$learner$predict_type = "se"
 #' set.seed(2906)
 #' g2$predict(task2)
+#' \dontshow{ \} }
 PipeOpRandomResponse = R6Class("PipeOpRandomResponse",
   inherit = PipeOp,
   public = list(
diff --git a/R/PipeOpRegrAvg.R b/R/PipeOpRegrAvg.R
index 2d3ca5d16..0aaf1dcea 100644
--- a/R/PipeOpRegrAvg.R
+++ b/R/PipeOpRegrAvg.R
@@ -57,6 +57,7 @@
 #' @include PipeOpEnsemble.R
 #' @export
 #' @examples
+#' \dontshow{ if (requireNamespace("rpart")) \{ }
 #' library("mlr3")
 #'
 #' # Simple Bagging
@@ -68,6 +69,7 @@
 #'   po("classifavg")
 #'
 #' resample(tsk("iris"), GraphLearner$new(gr), rsmp("holdout"))
+#' \dontshow{ \} }
 PipeOpRegrAvg = R6Class("PipeOpRegrAvg",
   inherit = PipeOpEnsemble,
 
diff --git a/R/PipeOpSmote.R b/R/PipeOpSmote.R
index 9e512bbd0..cdf18a363 100644
--- a/R/PipeOpSmote.R
+++ b/R/PipeOpSmote.R
@@ -54,6 +54,7 @@
 #' @include PipeOpTaskPreproc.R
 #' @export
 #' @examples
+#' \dontshow{ if (requireNamespace("smotefamily")) \{ }
 #' library("mlr3")
 #'
 #' # Create example task
@@ -67,6 +68,7 @@
 #' pop = po("smote")
 #' smotedata = pop$train(list(task))[[1]]$data()
 #' table(smotedata$result)
+#' \dontshow{ \} }
 PipeOpSmote = R6Class("PipeOpSmote",
   inherit = PipeOpTaskPreproc,
   public = list(
diff --git a/R/PipeOpTextVectorizer.R b/R/PipeOpTextVectorizer.R
index 8550fdb22..3a78fd967 100644
--- a/R/PipeOpTextVectorizer.R
+++ b/R/PipeOpTextVectorizer.R
@@ -140,6 +140,8 @@
 #' Only methods inherited from [`PipeOpTaskPreproc`]/[`PipeOp`].
 #'
 #' @examples
+#' \dontshow{ if (requireNamespace("stopwords")) \{ }
+#' \dontshow{ if (requireNamespace("quanteda")) \{ }
 #' library("mlr3")
 #' library("data.table")
 #' # create some text data
@@ -157,6 +159,8 @@
 #' one_line_of_iris$data()
 #'
 #' pos$predict(list(one_line_of_iris))[[1]]$data()
+#' \dontshow{ \} }
+#' \dontshow{ \} }
 #' @family PipeOps
 #' @template seealso_pipeopslist
 #' @include PipeOpTaskPreproc.R
diff --git a/R/PipeOpThreshold.R b/R/PipeOpThreshold.R
index 3f9dae220..18b8f7e74 100644
--- a/R/PipeOpThreshold.R
+++ b/R/PipeOpThreshold.R
@@ -42,12 +42,14 @@
 #' Only methods inherited from [`PipeOp`].
 #'
 #' @examples
+#' \dontshow{ if (requireNamespace("rpart")) \{ }
 #' library("mlr3")
 #' t = tsk("german_credit")
 #' gr = po(lrn("classif.rpart", predict_type = "prob")) %>>%
 #'   po("threshold", param_vals = list(thresholds = 0.9))
 #' gr$train(t)
 #' gr$predict(t)
+#' \dontshow{ \} }
 #' @family PipeOps
 #' @template seealso_pipeopslist
 #' @include PipeOp.R
diff --git a/R/PipeOpTrafo.R b/R/PipeOpTrafo.R
index 101256cd0..0d360c1ae 100644
--- a/R/PipeOpTrafo.R
+++ b/R/PipeOpTrafo.R
@@ -309,6 +309,7 @@ mlr_pipeops$add("targetinvert", PipeOpTargetInvert)
 #' Only methods inherited from [`PipeOpTargetTrafo`]/[`PipeOp`].
 #'
 #' @examples
+#' \dontshow{ if (requireNamespace("rpart")) \{ }
 #' library(mlr3)
 #' task = tsk("boston_housing")
 #' po = PipeOpTargetMutate$new("logtrafo", param_vals = list(
@@ -339,6 +340,7 @@ mlr_pipeops$add("targetinvert", PipeOpTargetInvert)
 #' tt = ppl("targettrafo", graph = PipeOpLearner$new(LearnerRegrRpart$new()))
 #' tt$param_set$values$targetmutate.trafo = function(x) log(x, base = 2)
 #' tt$param_set$values$targetmutate.inverter = function(x) list(response = 2 ^ x$response)
+#' \dontshow{ \} }
 #' @family PipeOps
 #' @template seealso_pipeopslist
 #' @include PipeOp.R
@@ -436,6 +438,7 @@ mlr_pipeops$add("targetmutate", PipeOpTargetMutate)
 #' Only methods inherited from [`PipeOpTargetTrafo`]/[`PipeOp`].
 #'
 #' @examples
+#' \dontshow{ if (requireNamespace("rpart")) \{ }
 #' library(mlr3)
 #' task = tsk("boston_housing")
 #' po = PipeOpTargetTrafoScaleRange$new()
@@ -449,6 +452,7 @@ mlr_pipeops$add("targetmutate", PipeOpTargetMutate)
 #' ttscalerange$train(task)
 #' ttscalerange$predict(task)
 #' ttscalerange$state$regr.rpart
+#' \dontshow{ \} }
 #' @family PipeOps
 #' @template seealso_pipeopslist
 #' @include PipeOp.R
@@ -548,6 +552,7 @@ mlr_pipeops$add("targettrafoscalerange", PipeOpTargetTrafoScaleRange)
 #' Only methods inherited from [`PipeOp`].
 #'
 #' @examples
+#' \dontshow{ if (requireNamespace("rpart")) \{ }
 #' \dontrun{
 #' # Create a binary class task from iris
 #' library(mlr3)
@@ -556,6 +561,7 @@ mlr_pipeops$add("targettrafoscalerange", PipeOpTargetTrafoScaleRange)
 #' po$train(list(tsk("iris")))
 #' po$predict(list(tsk("iris")))
 #' }
+#' \dontshow{ \} }
 #' @family mlr3pipelines backend related
 #' @family PipeOps
 #' @template seealso_pipeopslist
diff --git a/R/PipeOpTuneThreshold.R b/R/PipeOpTuneThreshold.R
index e4891eb6f..f15e4ade8 100644
--- a/R/PipeOpTuneThreshold.R
+++ b/R/PipeOpTuneThreshold.R
@@ -57,6 +57,8 @@
 #' Only methods inherited from [`PipeOp`].
 #'
 #' @examples
+#' \dontshow{ if (requireNamespace("bbotk")) \{ }
+#' \dontshow{ if (requireNamespace("rpart")) \{ }
 #' library("mlr3")
 #'
 #' task = tsk("iris")
@@ -67,6 +69,8 @@
 #' pop$train(task)
 #'
 #' pop$state
+#' \dontshow{ \} }
+#' \dontshow{ \} }
 #' @family PipeOps
 #' @template seealso_pipeopslist
 #' @export
diff --git a/R/PipeOpVtreat.R b/R/PipeOpVtreat.R
index 677fbc7dd..4520d913e 100644
--- a/R/PipeOpVtreat.R
+++ b/R/PipeOpVtreat.R
@@ -102,6 +102,7 @@
 #' Only methods inherited from [`PipeOpTaskPreproc`]/[`PipeOp`].
 #'
 #' @examples
+#' \dontshow{ if (requireNamespace("vtreat")) \{ }
 #' library("mlr3")
 #'
 #' set.seed(2020)
@@ -120,6 +121,7 @@
 #'
 #' pop = PipeOpVtreat$new()
 #' pop$train(list(task))
+#' \dontshow{ \} }
 #' @family PipeOps
 #' @template seealso_pipeopslist
 #' @include PipeOpTaskPreproc.R
diff --git a/R/PipeOpYeoJohnson.R b/R/PipeOpYeoJohnson.R
index 99d309f7c..510107141 100644
--- a/R/PipeOpYeoJohnson.R
+++ b/R/PipeOpYeoJohnson.R
@@ -50,6 +50,7 @@
 #' Only methods inherited from [`PipeOpTaskPreproc`]/[`PipeOp`].
 #'
 #' @examples
+#' \dontshow{ if (requireNamespace("bestNormalize")) \{ }
 #' library("mlr3")
 #'
 #' task = tsk("iris")
@@ -59,6 +60,7 @@
 #' pop$train(list(task))[[1]]$data()
 #'
 #' pop$state
+#' \dontshow{ \} }
 #' @family PipeOps
 #' @template seealso_pipeopslist
 #' @include PipeOpTaskPreproc.R
diff --git a/R/mlr_graphs.R b/R/mlr_graphs.R
index f1103da05..c711ea351 100644
--- a/R/mlr_graphs.R
+++ b/R/mlr_graphs.R
@@ -25,6 +25,7 @@
 #' @family Dictionaries
 #' @export
 #' @examples
+#' \dontshow{ if (requireNamespace("rpart")) \{ }
 #' library(mlr3)
 #' lrn = lrn("regr.rpart")
 #' task = mlr_tasks$get("boston_housing")
@@ -38,6 +39,7 @@
 #'
 #' # all Graphs currently in the dictionary:
 #' as.data.table(mlr_graphs)
+#' \dontshow{ \} }
 mlr_graphs = R6Class("DictionaryGraph", inherit = mlr3misc::Dictionary,
   cloneable = FALSE,
   public = list(
diff --git a/R/mlr_pipeops.R b/R/mlr_pipeops.R
index e498ffd19..80dcea406 100644
--- a/R/mlr_pipeops.R
+++ b/R/mlr_pipeops.R
@@ -34,6 +34,7 @@
 #' @family Dictionaries
 #' @export
 #' @examples
+#' \dontshow{ if (requireNamespace("rpart")) \{ }
 #' library("mlr3")
 #'
 #' mlr_pipeops$get("learner", lrn("classif.rpart"))
@@ -43,6 +44,7 @@
 #'
 #' # all PipeOps currently in the dictionary:
 #' as.data.table(mlr_pipeops)[, c("key", "input.num", "output.num", "packages")]
+#' \dontshow{ \} }
 mlr_pipeops = R6Class("DictionaryPipeOp", inherit = mlr3misc::Dictionary,
   cloneable = FALSE,
   public = list(
diff --git a/R/pipeline_bagging.R b/R/pipeline_bagging.R
index 31b743d32..d1ec2cec3 100644
--- a/R/pipeline_bagging.R
+++ b/R/pipeline_bagging.R
@@ -34,6 +34,7 @@
 #' @return [`Graph`]
 #' @export
 #' @examples
+#' \dontshow{ if (requireNamespace("rpart")) \{ }
 #' \donttest{
 #' library(mlr3)
 #' lrn_po = po("learner", lrn("regr.rpart"))
@@ -46,6 +47,7 @@
 #'   averager = po("regravg", collect_multiplicity = TRUE))
 #' resample(task, GraphLearner$new(gr), rsmp("holdout"))$aggregate()
 #' }
+#' \dontshow{ \} }
 pipeline_bagging = function(graph, iterations = 10, frac = 0.7, averager = NULL, replace = FALSE) {
   g = as_graph(graph)
   assert_count(iterations)
diff --git a/R/pipeline_convert_types.R b/R/pipeline_convert_types.R
new file mode 100644
index 000000000..7b1ec2f75
--- /dev/null
+++ b/R/pipeline_convert_types.R
@@ -0,0 +1,101 @@
+#' @include mlr_graphs.R
+
+#' @title Convert Column Types
+#' @name mlr_graphs_convert_types
+#' @description
+#' Converts all columns of type `type_from` to `type_to`, using the corresponding R function (e.g. `as.numeric()`, `as.factor()`).
+#' It is possible to further subset the columns that should be affected using the `affect_columns` argument.
+#' The resulting [`Graph`] contains a [`PipeOpColApply`], followed, if appropriate, by a [`PipeOpFixFactors`].
+#'
+#' Unlike R's `as.factor()` function, `ppl("convert_types")` will convert `ordered` types into (unordered) `factor` vectors.
+#'
+#' @param type_from `character` \cr
+#'   Which column types to convert. May be any combination of `"logical"`, `"integer"`, `"numeric"`, `"factor"`, `"ordered"`, `"character"`, or `"POSIXct"`.
+#' @param type_to `character(1)` \cr
+#'   Which type to convert to. Must be a scalar value, exactly one of the types allowed in `type_from`.
+#' @param affect_columns `function` | [`Selector`] | `NULL` \cr
+#'   Which columns to affect. This argument can further restrict the columns being converted, beyond the `type_from` argument.
+#'   Must be a [`Selector`]-like function, which takes a [`Task`][mlr3::Task] as argument and returns a `character` of features to use.
+#' @param id `character(1)` | `NULL` \cr
+#'   ID to give to the constructed [`PipeOp`]s.
+#'   Defaults to an ID built automatically from `type_from` and `type_to`.
+#'   If a [`PipeOpFixFactors`] is appended, its ID will be `paste0(id, "_ff")`.
+#' @param fixfactors `logical(1)` | `NULL` \cr
+#'   Whether to append a [`PipeOpFixFactors`]. Defaults to `TRUE` if and only if `type_to` is `"factor"` or `"ordered"`.
+#' @param more_args `list` \cr
+#'   Additional arguments to give to the conversion function. This could e.g. be used to pass the timezone to `as.POSIXct`.
+#'
+#' @return [`Graph`]
+#' @export
+#' @examples
+#' library("mlr3")
+#'
+#' data_chr = data.table::data.table(
+#'   x = factor(letters[1:3]),
+#'   y = letters[1:3],
+#'   z = letters[1:3]
+#' )
+#' task_chr = TaskClassif$new("task_chr", data_chr, "x")
+#' str(task_chr$data())
+#'
+#' graph = ppl("convert_types", "character", "factor")
+#' str(graph$train(task_chr)[[1]]$data())
+#'
+#' graph_z = ppl("convert_types", "character", "factor",
+#'   affect_columns = selector_name("z"))
+#' graph_z$train(task_chr)[[1]]$data()
+#'
+#' # `affect_columns` and `type_from` are both applied. The following
+#' # looks for a 'numeric' column with name 'z', which is not present;
+#' # the task is therefore unchanged.
+#' graph_z = ppl("convert_types", "numeric", "factor",
+#'   affect_columns = selector_name("z"))
+#' graph_z$train(task_chr)[[1]]$data()
+pipeline_convert_types = function(type_from, type_to, affect_columns = NULL, id = NULL, fixfactors = NULL, more_args = list()) {
+  coltypes = mlr_reflections$task_feature_types
+
+
+  assert_character(type_from, any.missing = FALSE, unique = TRUE)
+  assert_subset(type_from, coltypes)
+  assert_choice(type_to, coltypes)
+  assert_function(affect_columns, null.ok = TRUE)
+  assert_string(id, null.ok = TRUE)
+  assert_flag(fixfactors, null.ok = TRUE)
+  assert_list(more_args)
+
+  selector = selector_type(type_from)
+  if (!is.null(affect_columns)) {
+    selector = selector_intersect(selector, affect_columns)
+  }
+  if (is.null(id)) {
+    id = sprintf("convert_%s_to_%s",
+      paste(names(coltypes)[match(type_from, coltypes)], collapse = ""),
+      names(coltypes)[match(type_to, coltypes)]
+    )
+  }
+
+  converter = switch(type_to,
+    factor = crate(function(x) {
+        if (is.ordered(x)) {
+          cls <- class(x)
+          class(x) <- cls[cls != "ordered"]
+        }
+        as.factor(x)
+      }),
+    get(paste0("as.", type_to))
+  )
+  if (length(more_args)) {
+    converter = crate(function(x) {
+      mlr3misc::invoke(converter, x = x, .args = more_args)
+    }, converter, more_args)
+  }
+  if (is.null(fixfactors)) {
+    fixfactors = type_to %in% c("factor", "ordered")
+  }
+  po("colapply",
+    id = id, applicator = converter, affect_columns = selector
+  ) %>>!% if (fixfactors) po("fixfactors", id = paste0(id, "_ff"))
+}
+
+mlr_graphs$add("convert_types", pipeline_convert_types)
+
diff --git a/R/pipeline_ovr.R b/R/pipeline_ovr.R
index c4c7411fc..fc4c1dc5e 100644
--- a/R/pipeline_ovr.R
+++ b/R/pipeline_ovr.R
@@ -15,6 +15,7 @@
 #' @return [`Graph`]
 #' @export
 #' @examples
+#' \dontshow{ if (requireNamespace("rpart")) \{ }
 #' library("mlr3")
 #'
 #' task = tsk("wine")
@@ -42,6 +43,7 @@
 #'   po("classifavg", collect_multiplicity = TRUE)
 #' g3$train(task)
 #' g3$predict(task)
+#' \dontshow{ \} }
 pipeline_ovr = function(graph) {
   PipeOpOVRSplit$new() %>>!% graph %>>!% PipeOpOVRUnite$new()
 }
diff --git a/R/pipeline_robustify.R b/R/pipeline_robustify.R
index abb386c4b..fbce8d84a 100644
--- a/R/pipeline_robustify.R
+++ b/R/pipeline_robustify.R
@@ -60,6 +60,7 @@
 #' @return [`Graph`]
 #' @export
 #' @examples
+#' \dontshow{ if (requireNamespace("rpart")) \{ }
 #' \donttest{
 #' library(mlr3)
 #' lrn = lrn("regr.rpart")
@@ -67,6 +68,7 @@
 #' gr = pipeline_robustify(task, lrn) %>>% po("learner", lrn)
 #' resample(task, GraphLearner$new(gr), rsmp("holdout"))
 #' }
+#' \dontshow{ \} }
 pipeline_robustify = function(task = NULL, learner = NULL,
   impute_missings = NULL, factors_to_numeric = NULL, max_cardinality = 1000,
   ordered_action = "factor", character_action = "factor", POSIXct_action = "numeric") {
diff --git a/R/pipeline_stacking.R b/R/pipeline_stacking.R
index 4ac1f0a0d..26741e4ac 100644
--- a/R/pipeline_stacking.R
+++ b/R/pipeline_stacking.R
@@ -26,6 +26,7 @@
 #'
 #' @export
 #' @examples
+#' \dontshow{ if (requireNamespace("rpart")) \{ }
 #' if (requireNamespace("kknn")) {
 #' library(mlr3)
 #' library(mlr3learners)
@@ -40,6 +41,7 @@
 #' graph_learner = as_learner(graph_stack)
 #' graph_learner$train(tsk("german_credit"))
 #' }
+#' \dontshow{ \} }
 pipeline_stacking = function(base_learners, super_learner, method = "cv", folds = 3, use_features = TRUE) {
   assert_learners(base_learners)
   assert_learner(super_learner)
diff --git a/R/pipeline_targettrafo.R b/R/pipeline_targettrafo.R
index 72fff3483..5a3989e31 100644
--- a/R/pipeline_targettrafo.R
+++ b/R/pipeline_targettrafo.R
@@ -25,6 +25,7 @@
 #' @return [`Graph`]
 #' @export
 #' @examples
+#' \dontshow{ if (requireNamespace("rpart")) \{ }
 #' library("mlr3")
 #'
 #' tt = pipeline_targettrafo(PipeOpLearner$new(LearnerRegrRpart$new()))
@@ -46,6 +47,7 @@
 #'   src_channel = 2, dst_channel = 1)
 #' g$add_edge(src_id = "regr.rpart", dst_id = "targetinvert",
 #'   src_channel = 1, dst_channel = 2)
+#' \dontshow{ \} }
 pipeline_targettrafo = function(graph, trafo_pipeop = PipeOpTargetMutate$new(), id_prefix = "") {
   graph = as_graph(graph, clone = TRUE)
   if (graph$pipeops[[graph$input$op.id]]$innum != 1L) {
diff --git a/R/po.R b/R/po.R
index e071ffe7b..c60cdaea3 100644
--- a/R/po.R
+++ b/R/po.R
@@ -32,6 +32,7 @@
 #' @return A [`PipeOp`] (for `po()`), or a `list` of [`PipeOp`]s (for `pos()`).
 #' @export
 #' @examples
+#' \dontshow{ if (requireNamespace("rpart")) \{ }
 #' library("mlr3")
 #'
 #' po("learner", lrn("classif.rpart"), cp = 0.3)
@@ -43,6 +44,7 @@
 #'   param_vals = list(cp = 0.3))
 #'
 #' pos(c("pca", original = "nop"))
+#' \dontshow{ \} }
 po = function(.obj, ...) {
   UseMethod("po")
 }
diff --git a/R/ppl.R b/R/ppl.R
index 1754fb9de..900dd53a0 100644
--- a/R/ppl.R
+++ b/R/ppl.R
@@ -18,10 +18,12 @@
 #' @return [`Graph`] (for `ppl()`) or `list` of [`Graph`]s (for `ppls()`).
 #' @export
 #' @examples
+#' \dontshow{ if (requireNamespace("rpart")) \{ }
 #' library("mlr3")
 #'
 #' gr = ppl("bagging", graph = po(lrn("regr.rpart")),
 #'   averager = po("regravg", collect_multiplicity = TRUE))
+#' \dontshow{ \} }
 ppl = function(.key, ...) {
   dictionary_sugar_get(dict = mlr_graphs, .key = .key, ...)
 }
diff --git a/attic/dependify.sh b/attic/dependify.sh
new file mode 100755
index 000000000..cd67d86df
--- /dev/null
+++ b/attic/dependify.sh
@@ -0,0 +1,32 @@
+#!/bin/bash
+if [ -z "$2" ] ; then
+  echo "Usage: $0 <library to look for> <things to require>" >&2
+  exit 1
+fi
+PATPART="$1"
+REQUIRE="$2"
+# Loop through each .R file in the current directory
+for file in *.R; do
+  # Check if file contains the pattern "^#'.*rpart"
+  if grep -q "^#'.*${PATPART}" "$file"; then
+    # Use awk to edit the file in-place
+    awk '
+      # Set a flag when the @examples line is found
+      /^#'"'"' @examples$/ { 
+        print;
+        print "#'"'"' \\dontshow{ if (requireNamespace(\"'"${REQUIRE}"'\")) \\{ }";
+        found = 1; 
+        next; 
+      }
+
+      # After the @examples line, insert the closing dontshow before the first non-#" or #" @ line
+      found && (!/^#'"'"'/ || /^#'"'"' @/) {
+        print "#'"'"' \\dontshow{ \\} }";
+        found = 0;
+      }
+
+      # Print every line of the file
+      { print; }
+    ' "$file" > tmp_file && mv tmp_file "$file"
+  fi
+done
diff --git a/attic/dependify_tests.sh b/attic/dependify_tests.sh
new file mode 100755
index 000000000..481de7a81
--- /dev/null
+++ b/attic/dependify_tests.sh
@@ -0,0 +1,49 @@
+#!/bin/bash
+
+if [ -z "$2" ] ; then
+  echo "Usage: $0 <pattern to look for> <package on which to skip>" >&2
+  exit 1
+fi
+PATPART="$1"
+REQUIRE="$2"
+
+# Loop through all .R files in the current directory
+for file in *.R; do
+    # Use awk to edit the file in-place
+    awk '
+        # Enter a test_that block
+        /^test_that\(/ { 
+            buffer = $0 # Start buffering the block
+            capture = 1  # Set flag to capture lines
+            insert_needed = 0  # Reset insertion flag
+            next
+        }
+
+        # Detect the end of a block
+        /^})$/ && capture {
+            if (insert_needed) {
+                # Insert the line at the beginning of the block
+                sub(/\{/, "{\n  skip_if_not_installed(\"'"${REQUIRE}"'\")", buffer)
+            }
+            print buffer  # Print the modified buffer
+            print "})"
+            buffer = ""  # Clear buffer
+            capture = 0  # Stop capturing
+            next
+        }
+
+        # While capturing the block
+        capture {
+            buffer = buffer "\n" $0  # Add line to buffer
+            # If line contains "PipeOpLrnRP", mark for insertion
+            if (/'"${PATPART}"'/)
+                insert_needed = 1
+        }
+
+        # Print all lines outside of blocks normally
+        !capture {
+            print
+        }
+    ' "$file" > tmpfile && mv tmpfile "$file"  # Output redirection and file replacement
+done
+
diff --git a/attic/experiments.R b/attic/experiments.R
index 40122d84b..e94bfad85 100644
--- a/attic/experiments.R
+++ b/attic/experiments.R
@@ -10,11 +10,13 @@ data.table::setDTthreads(0)
 data.table::setDTthreads(1)
 Sys.setenv(NOT_CRAN = "true")
 
-devtools::document("mlr3pipelines")
+devtools::document()
 
 # devtools::load_all("paradox")
 
-devtools::load_all("mlr3pipelines")
+devtools::load_all()
+
+devtools::test(filter = "textvectorizer")
 
 Sys.setenv(TESTTHAT_CPUS = 20)
 testthat::test_package("mlr3pipelines")
diff --git a/tests/testthat/helper_compat.R b/inst/testthat/helper_compat.R
similarity index 100%
rename from tests/testthat/helper_compat.R
rename to inst/testthat/helper_compat.R
diff --git a/tests/testthat/helper_functions.R b/inst/testthat/helper_functions.R
similarity index 98%
rename from tests/testthat/helper_functions.R
rename to inst/testthat/helper_functions.R
index 5eb4006b8..2ee53cace 100644
--- a/tests/testthat/helper_functions.R
+++ b/inst/testthat/helper_functions.R
@@ -233,10 +233,10 @@ expect_datapreproc_pipeop_class = function(poclass, constargs = list(), task,
   expect_equal(po$innum, 1)
   expect_equal(po$outnum, 1)
 
-  expect_true(are_types_compatible(po$input$train, "Task"))
-  expect_true(are_types_compatible(po$input$predict, "Task"))
-  expect_true(are_types_compatible(po$output$train, "Task"))
-  expect_true(are_types_compatible(po$output$predict, "Task"))
+  expect_true(mlr3pipelines:::are_types_compatible(po$input$train, "Task"))
+  expect_true(mlr3pipelines:::are_types_compatible(po$input$predict, "Task"))
+  expect_true(mlr3pipelines:::are_types_compatible(po$output$train, "Task"))
+  expect_true(mlr3pipelines:::are_types_compatible(po$output$predict, "Task"))
 
   expect_error(po$train(list(NULL)), "class.*Task.*but has class")
 
diff --git a/tests/testthat/helper_test_pipeops.R b/inst/testthat/helper_test_pipeops.R
similarity index 96%
rename from tests/testthat/helper_test_pipeops.R
rename to inst/testthat/helper_test_pipeops.R
index 5265177bb..7ca37f5cf 100644
--- a/tests/testthat/helper_test_pipeops.R
+++ b/inst/testthat/helper_test_pipeops.R
@@ -71,7 +71,7 @@ VarargPipeop = R6Class("VarargPipeop",
   public = list(
     initialize = function(id = "vararg", innum = 0, param_vals = list()) {
       super$initialize(id, param_vals = param_vals,
-        input = data.table(name = c("...", rep_suffix("input", innum)), train = "*", predict = "*"),
+        input = data.table(name = c("...", mlr3pipelines:::rep_suffix("input", innum)), train = "*", predict = "*"),
         output = data.table(name = "output", train = "*", predict = "*")
       )
     }),
diff --git a/man/mlr_graphs.Rd b/man/mlr_graphs.Rd
index 116ed9b07..e11fcf981 100644
--- a/man/mlr_graphs.Rd
+++ b/man/mlr_graphs.Rd
@@ -35,6 +35,7 @@ Returns a \code{data.table} with column \code{key} (\code{character}).
 }
 
 \examples{
+\dontshow{ if (requireNamespace("rpart")) \{ }
 library(mlr3)
 lrn = lrn("regr.rpart")
 task = mlr_tasks$get("boston_housing")
@@ -48,6 +49,7 @@ gr = ppl("robustify", task, lrn) \%>>\% po("learner", lrn)
 
 # all Graphs currently in the dictionary:
 as.data.table(mlr_graphs)
+\dontshow{ \} }
 }
 \seealso{
 Other mlr3pipelines backend related: 
diff --git a/man/mlr_graphs_bagging.Rd b/man/mlr_graphs_bagging.Rd
index 58d5e1e83..790562c66 100644
--- a/man/mlr_graphs_bagging.Rd
+++ b/man/mlr_graphs_bagging.Rd
@@ -54,6 +54,7 @@ This is done as follows:
 All input arguments are cloned and have no references in common with the returned \code{\link{Graph}}.
 }
 \examples{
+\dontshow{ if (requireNamespace("rpart")) \{ }
 \donttest{
 library(mlr3)
 lrn_po = po("learner", lrn("regr.rpart"))
@@ -66,4 +67,5 @@ gr = ppl("bagging", lrn_po, frac = 1, replace = TRUE,
   averager = po("regravg", collect_multiplicity = TRUE))
 resample(task, GraphLearner$new(gr), rsmp("holdout"))$aggregate()
 }
+\dontshow{ \} }
 }
diff --git a/man/mlr_graphs_convert_types.Rd b/man/mlr_graphs_convert_types.Rd
new file mode 100644
index 000000000..c557c04b9
--- /dev/null
+++ b/man/mlr_graphs_convert_types.Rd
@@ -0,0 +1,73 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/pipeline_convert_types.R
+\name{mlr_graphs_convert_types}
+\alias{mlr_graphs_convert_types}
+\alias{pipeline_convert_types}
+\title{Convert Column Types}
+\usage{
+pipeline_convert_types(
+  type_from,
+  type_to,
+  affect_columns = NULL,
+  id = NULL,
+  fixfactors = NULL,
+  more_args = list()
+)
+}
+\arguments{
+\item{type_from}{\code{character} \cr
+Which column types to convert. May be any combination of \code{"logical"}, \code{"integer"}, \code{"numeric"}, \code{"factor"}, \code{"ordered"}, \code{"character"}, or \code{"POSIXct"}.}
+
+\item{type_to}{\code{character(1)} \cr
+Which type to convert to. Must be a scalar value, exactly one of the types allowed in \code{type_from}.}
+
+\item{affect_columns}{\code{function} | \code{\link{Selector}} | \code{NULL} \cr
+Which columns to affect. This argument can further restrict the columns being converted, beyond the \code{type_from} argument.
+Must be a \code{\link{Selector}}-like function, which takes a \code{\link[mlr3:Task]{Task}} as argument and returns a \code{character} of features to use.}
+
+\item{id}{\code{character(1)} | \code{NULL} \cr
+ID to give to the constructed \code{\link{PipeOp}}s.
+Defaults to an ID built automatically from \code{type_from} and \code{type_to}.
+If a \code{\link{PipeOpFixFactors}} is appended, its ID will be \code{paste0(id, "_ff")}.}
+
+\item{fixfactors}{\code{logical(1)} | \code{NULL} \cr
+Whether to append a \code{\link{PipeOpFixFactors}}. Defaults to \code{TRUE} if and only if \code{type_to} is \code{"factor"} or \code{"ordered"}.}
+
+\item{more_args}{\code{list} \cr
+Additional arguments to give to the conversion function. This could e.g. be used to pass the timezone to \code{as.POSIXct}.}
+}
+\value{
+\code{\link{Graph}}
+}
+\description{
+Converts all columns of type \code{type_from} to \code{type_to}, using the corresponding R function (e.g. \code{as.numeric()}, \code{as.factor()}).
+It is possible to further subset the columns that should be affected using the \code{affect_columns} argument.
+The resulting \code{\link{Graph}} contains a \code{\link{PipeOpColApply}}, followed, if appropriate, by a \code{\link{PipeOpFixFactors}}.
+
+Unlike R's \code{as.factor()} function, \code{ppl("convert_types")} will convert \code{ordered} types into (unordered) \code{factor} vectors.
+}
+\examples{
+library("mlr3")
+
+data_chr = data.table::data.table(
+  x = factor(letters[1:3]),
+  y = letters[1:3],
+  z = letters[1:3]
+)
+task_chr = TaskClassif$new("task_chr", data_chr, "x")
+str(task_chr$data())
+
+graph = ppl("convert_types", "character", "factor")
+str(graph$train(task_chr)[[1]]$data())
+
+graph_z = ppl("convert_types", "character", "factor",
+  affect_columns = selector_name("z"))
+graph_z$train(task_chr)[[1]]$data()
+
+# `affect_columns` and `type_from` are both applied. The following
+# looks for a 'numeric' column with name 'z', which is not present;
+# the task is therefore unchanged.
+graph_z = ppl("convert_types", "numeric", "factor",
+  affect_columns = selector_name("z"))
+graph_z$train(task_chr)[[1]]$data()
+}
diff --git a/man/mlr_graphs_ovr.Rd b/man/mlr_graphs_ovr.Rd
index eb8064d89..c38449cfa 100644
--- a/man/mlr_graphs_ovr.Rd
+++ b/man/mlr_graphs_ovr.Rd
@@ -23,6 +23,7 @@ perform "One vs. Rest" classification.
 All input arguments are cloned and have no references in common with the returned \code{\link{Graph}}.
 }
 \examples{
+\dontshow{ if (requireNamespace("rpart")) \{ }
 library("mlr3")
 
 task = tsk("wine")
@@ -50,4 +51,5 @@ g3 = po("replicate", reps = 3) \%>>\%
   po("classifavg", collect_multiplicity = TRUE)
 g3$train(task)
 g3$predict(task)
+\dontshow{ \} }
 }
diff --git a/man/mlr_graphs_robustify.Rd b/man/mlr_graphs_robustify.Rd
index 0487f03d0..7845cae3b 100644
--- a/man/mlr_graphs_robustify.Rd
+++ b/man/mlr_graphs_robustify.Rd
@@ -86,6 +86,7 @@ factor variables, no encoding is performed.
 All input arguments are cloned and have no references in common with the returned \code{\link{Graph}}.
 }
 \examples{
+\dontshow{ if (requireNamespace("rpart")) \{ }
 \donttest{
 library(mlr3)
 lrn = lrn("regr.rpart")
@@ -93,4 +94,5 @@ task = mlr_tasks$get("boston_housing")
 gr = pipeline_robustify(task, lrn) \%>>\% po("learner", lrn)
 resample(task, GraphLearner$new(gr), rsmp("holdout"))
 }
+\dontshow{ \} }
 }
diff --git a/man/mlr_graphs_stacking.Rd b/man/mlr_graphs_stacking.Rd
index 1c29e56d3..799ae5ee3 100644
--- a/man/mlr_graphs_stacking.Rd
+++ b/man/mlr_graphs_stacking.Rd
@@ -43,6 +43,7 @@ features in order to predict the outcome.
 All input arguments are cloned and have no references in common with the returned \code{\link{Graph}}.
 }
 \examples{
+\dontshow{ if (requireNamespace("rpart")) \{ }
 if (requireNamespace("kknn")) {
 library(mlr3)
 library(mlr3learners)
@@ -57,4 +58,5 @@ graph_stack = pipeline_stacking(base_learners, super_learner)
 graph_learner = as_learner(graph_stack)
 graph_learner$train(tsk("german_credit"))
 }
+\dontshow{ \} }
 }
diff --git a/man/mlr_graphs_targettrafo.Rd b/man/mlr_graphs_targettrafo.Rd
index 847e35b31..7f4664334 100644
--- a/man/mlr_graphs_targettrafo.Rd
+++ b/man/mlr_graphs_targettrafo.Rd
@@ -40,6 +40,7 @@ parameters \code{trafo} and \code{inverter} of the \code{param_set} of the resul
 All input arguments are cloned and have no references in common with the returned \code{\link{Graph}}.
 }
 \examples{
+\dontshow{ if (requireNamespace("rpart")) \{ }
 library("mlr3")
 
 tt = pipeline_targettrafo(PipeOpLearner$new(LearnerRegrRpart$new()))
@@ -61,4 +62,5 @@ g$add_edge(src_id = "targetmutate", dst_id = "regr.rpart",
   src_channel = 2, dst_channel = 1)
 g$add_edge(src_id = "regr.rpart", dst_id = "targetinvert",
   src_channel = 1, dst_channel = 2)
+\dontshow{ \} }
 }
diff --git a/man/mlr_learners_graph.Rd b/man/mlr_learners_graph.Rd
index e5d52542a..e331c9776 100644
--- a/man/mlr_learners_graph.Rd
+++ b/man/mlr_learners_graph.Rd
@@ -83,6 +83,7 @@ recommended.
 }
 
 \examples{
+\dontshow{ if (requireNamespace("rpart")) \{ }
 library("mlr3")
 
 graph = po("pca") \%>>\% lrn("classif.rpart")
@@ -101,6 +102,7 @@ lr$graph_model$pipeops$classif.rpart$learner_model$model
 
 # Feature importance (of principal components):
 lr$graph_model$pipeops$classif.rpart$learner_model$importance()
+\dontshow{ \} }
 }
 \seealso{
 Other Learners: 
diff --git a/man/mlr_pipeops.Rd b/man/mlr_pipeops.Rd
index aa16b447e..bb4c99164 100644
--- a/man/mlr_pipeops.Rd
+++ b/man/mlr_pipeops.Rd
@@ -46,6 +46,7 @@ Returns a \code{data.table} with columns \code{key} (\code{character}), \code{pa
 }
 
 \examples{
+\dontshow{ if (requireNamespace("rpart")) \{ }
 library("mlr3")
 
 mlr_pipeops$get("learner", lrn("classif.rpart"))
@@ -55,6 +56,7 @@ po("learner", learner = lrn("classif.rpart"))
 
 # all PipeOps currently in the dictionary:
 as.data.table(mlr_pipeops)[, c("key", "input.num", "output.num", "packages")]
+\dontshow{ \} }
 }
 \seealso{
 Other mlr3pipelines backend related: 
diff --git a/man/mlr_pipeops_boxcox.Rd b/man/mlr_pipeops_boxcox.Rd
index 5ab6764c6..6fdb67c46 100644
--- a/man/mlr_pipeops_boxcox.Rd
+++ b/man/mlr_pipeops_boxcox.Rd
@@ -67,6 +67,7 @@ Only methods inherited from \code{\link{PipeOpTaskPreproc}}/\code{\link{PipeOp}}
 }
 
 \examples{
+\dontshow{ if (requireNamespace("bestNormalize")) \{ }
 library("mlr3")
 
 task = tsk("iris")
@@ -76,6 +77,7 @@ task$data()
 pop$train(list(task))[[1]]$data()
 
 pop$state
+\dontshow{ \} }
 }
 \seealso{
 https://mlr-org.com/pipeops.html
diff --git a/man/mlr_pipeops_classifavg.Rd b/man/mlr_pipeops_classifavg.Rd
index e01d42e9d..3bc15b736 100644
--- a/man/mlr_pipeops_classifavg.Rd
+++ b/man/mlr_pipeops_classifavg.Rd
@@ -77,6 +77,7 @@ Only methods inherited from \code{\link{PipeOpEnsemble}}/\code{\link{PipeOp}}.
 }
 
 \examples{
+\dontshow{ if (requireNamespace("rpart")) \{ }
 \donttest{
 library("mlr3")
 
@@ -90,6 +91,7 @@ gr = ppl("greplicate",
 
 resample(tsk("iris"), GraphLearner$new(gr), rsmp("holdout"))
 }
+\dontshow{ \} }
 }
 \seealso{
 https://mlr-org.com/pipeops.html
diff --git a/man/mlr_pipeops_encode.Rd b/man/mlr_pipeops_encode.Rd
index 6a8c513c5..94f09b863 100644
--- a/man/mlr_pipeops_encode.Rd
+++ b/man/mlr_pipeops_encode.Rd
@@ -8,7 +8,7 @@
 \code{\link{R6Class}} object inheriting from \code{\link{PipeOpTaskPreprocSimple}}/\code{\link{PipeOpTaskPreproc}}/\code{\link{PipeOp}}.
 }
 \description{
-Encodes columns of type \code{factor}, \code{character} and \code{ordered}.
+Encodes columns of type \code{factor} and \code{ordered}.
 
 Possible encodings are \code{"one-hot"} encoding, as well as encoding according to \code{stats::contr.helmert()}, \code{stats::contr.poly()},
 \code{stats::contr.sum()} and \code{stats::contr.treatment()}.
@@ -16,6 +16,8 @@ Newly created columns are named via pattern \verb{[column-name].[x]} where \code
 \code{"treatment"} encoding, and an integer sequence otherwise.
 
 Use the \code{\link{PipeOpTaskPreproc}} \verb{$affect_columns} functionality to only encode a subset of columns, or only encode columns of a certain type.
+
+\code{character}-type features can be encoded by converting them \code{factor} features first, using \code{\link[=mlr_graphs_convert_types]{ppl("convert_types", "character", "factor")}}.
 }
 \section{Construction}{
 
@@ -34,7 +36,7 @@ List of hyperparameter settings, overwriting the hyperparameter settings that wo
 
 Input and output channels are inherited from \code{\link{PipeOpTaskPreproc}}.
 
-The output is the input \code{\link[mlr3:Task]{Task}} with all affected \code{factor}, \code{character} or \code{ordered} parameters encoded according to the \code{method}
+The output is the input \code{\link[mlr3:Task]{Task}} with all affected \code{factor} and \code{ordered} parameters encoded according to the \code{method}
 parameter.
 }
 
@@ -97,6 +99,14 @@ poe$train(list(task))[[1]]$data()
 
 poe$param_set$values$method = "sum"
 poe$train(list(task))[[1]]$data()
+
+# converting character-columns
+data_chr = data.table::data.table(x = factor(letters[1:3]), y = letters[1:3])
+task_chr = TaskClassif$new("task_chr", data_chr, "x")
+
+goe = ppl("convert_types", "character", "factor") \%>>\% po("encode")
+
+goe$train(task_chr)[[1]]$data()
 }
 \seealso{
 https://mlr-org.com/pipeops.html
diff --git a/man/mlr_pipeops_encodelmer.Rd b/man/mlr_pipeops_encodelmer.Rd
index ca483a8b0..ce9b96575 100644
--- a/man/mlr_pipeops_encodelmer.Rd
+++ b/man/mlr_pipeops_encodelmer.Rd
@@ -88,6 +88,8 @@ Only methods inherited \code{\link{PipeOpTaskPreproc}}/\code{\link{PipeOp}}.
 }
 
 \examples{
+\dontshow{ if (requireNamespace("nloptr")) \{ }
+\dontshow{ if (requireNamespace("lme4")) \{ }
 library("mlr3")
 poe = po("encodelmer")
 
@@ -100,6 +102,8 @@ task = TaskClassif$new("task",
 poe$train(list(task))[[1]]$data()
 
 poe$state
+\dontshow{ \} }
+\dontshow{ \} }
 }
 \seealso{
 https://mlr-org.com/pipeops.html
diff --git a/man/mlr_pipeops_filter.Rd b/man/mlr_pipeops_filter.Rd
index 552e8fee0..650f46504 100644
--- a/man/mlr_pipeops_filter.Rd
+++ b/man/mlr_pipeops_filter.Rd
@@ -98,6 +98,8 @@ Methods inherited from \code{\link{PipeOpTaskPreprocSimple}}/\code{\link{PipeOpT
 }
 
 \examples{
+\dontshow{ if (requireNamespace("mlr3filters")) \{ }
+\dontshow{ if (requireNamespace("rpart")) \{ }
 library("mlr3")
 library("mlr3filters")
 \dontshow{data.table::setDTthreads(1)}
@@ -125,6 +127,8 @@ gr = po("filter", filter = flt("auc"), filter.frac = 0.5) \%>>\%
 learner = GraphLearner$new(gr)
 rr = resample(task, learner, rsmp("holdout"), store_models = TRUE)
 rr$learners[[1]]$model$auc$scores
+\dontshow{ \} }
+\dontshow{ \} }
 }
 \references{
 Wu Y, Boos DD, Stefanski LA (2007).
diff --git a/man/mlr_pipeops_ica.Rd b/man/mlr_pipeops_ica.Rd
index e17f982fc..f7394979a 100644
--- a/man/mlr_pipeops_ica.Rd
+++ b/man/mlr_pipeops_ica.Rd
@@ -93,6 +93,7 @@ Only methods inherited from \code{\link{PipeOpTaskPreproc}}/\code{\link{PipeOp}}
 }
 
 \examples{
+\dontshow{ if (requireNamespace("fastICA")) \{ }
 library("mlr3")
 
 task = tsk("iris")
@@ -102,6 +103,7 @@ task$data()
 pop$train(list(task))[[1]]$data()
 
 pop$state
+\dontshow{ \} }
 }
 \seealso{
 https://mlr-org.com/pipeops.html
diff --git a/man/mlr_pipeops_imputelearner.Rd b/man/mlr_pipeops_imputelearner.Rd
index 1a829285f..bfd74292d 100644
--- a/man/mlr_pipeops_imputelearner.Rd
+++ b/man/mlr_pipeops_imputelearner.Rd
@@ -90,6 +90,7 @@ Only methods inherited from \code{\link{PipeOpImpute}}/\code{\link{PipeOp}}.
 }
 
 \examples{
+\dontshow{ if (requireNamespace("rpart")) \{ }
 library("mlr3")
 
 task = tsk("pima")
@@ -113,6 +114,7 @@ po = po("imputelearner",
 new_task = po$train(list(task = task))[[1]]
 new_task$missings()
 
+\dontshow{ \} }
 }
 \seealso{
 https://mlr-org.com/pipeops.html
diff --git a/man/mlr_pipeops_kernelpca.Rd b/man/mlr_pipeops_kernelpca.Rd
index 99ccd8150..0d969f45b 100644
--- a/man/mlr_pipeops_kernelpca.Rd
+++ b/man/mlr_pipeops_kernelpca.Rd
@@ -70,6 +70,7 @@ Only methods inherited from \code{\link{PipeOpTaskPreproc}}/\code{\link{PipeOp}}
 }
 
 \examples{
+\dontshow{ if (requireNamespace("kernlab")) \{ }
 library("mlr3")
 
 task = tsk("iris")
@@ -77,6 +78,7 @@ pop = po("kernelpca", features = 3)  # only keep top 3 components
 
 task$data()
 pop$train(list(task))[[1]]$data()
+\dontshow{ \} }
 }
 \seealso{
 https://mlr-org.com/pipeops.html
diff --git a/man/mlr_pipeops_learner.Rd b/man/mlr_pipeops_learner.Rd
index a23afe960..41cfc22f2 100644
--- a/man/mlr_pipeops_learner.Rd
+++ b/man/mlr_pipeops_learner.Rd
@@ -89,6 +89,7 @@ Methods inherited from \code{\link{PipeOp}}.
 }
 
 \examples{
+\dontshow{ if (requireNamespace("rpart")) \{ }
 library("mlr3")
 
 task = tsk("iris")
@@ -97,6 +98,7 @@ lrn_po = mlr_pipeops$get("learner", learner)
 
 lrn_po$train(list(task))
 lrn_po$predict(list(task))
+\dontshow{ \} }
 }
 \seealso{
 https://mlr-org.com/pipeops.html
diff --git a/man/mlr_pipeops_learner_cv.Rd b/man/mlr_pipeops_learner_cv.Rd
index 49c852291..b66dbd246 100644
--- a/man/mlr_pipeops_learner_cv.Rd
+++ b/man/mlr_pipeops_learner_cv.Rd
@@ -112,6 +112,7 @@ Methods inherited from \code{\link{PipeOpTaskPreproc}}/\code{\link{PipeOp}}.
 }
 
 \examples{
+\dontshow{ if (requireNamespace("rpart")) \{ }
 library("mlr3")
 
 task = tsk("iris")
@@ -132,6 +133,7 @@ graph$train(task)
 graph$pipeops$classif.rpart$learner$predict_type = "prob"
 
 graph$train(task)
+\dontshow{ \} }
 }
 \seealso{
 https://mlr-org.com/pipeops.html
diff --git a/man/mlr_pipeops_nmf.Rd b/man/mlr_pipeops_nmf.Rd
index f1c88aeef..7ecab68d5 100644
--- a/man/mlr_pipeops_nmf.Rd
+++ b/man/mlr_pipeops_nmf.Rd
@@ -106,6 +106,8 @@ Only methods inherited from \code{\link{PipeOpTaskPreproc}}/\code{\link{PipeOp}}
 }
 
 \examples{
+\dontshow{ if (requireNamespace("NMF")) \{ }
+\dontshow{ if (requireNamespace("MASS")) \{ }
 if (requireNamespace("NMF")) {
 library("mlr3")
 
@@ -117,6 +119,8 @@ pop$train(list(task))[[1]]$data()
 
 pop$state
 }
+\dontshow{ \} }
+\dontshow{ \} }
 }
 \seealso{
 https://mlr-org.com/pipeops.html
diff --git a/man/mlr_pipeops_ovrsplit.Rd b/man/mlr_pipeops_ovrsplit.Rd
index 4e100c041..9ab399f84 100644
--- a/man/mlr_pipeops_ovrsplit.Rd
+++ b/man/mlr_pipeops_ovrsplit.Rd
@@ -81,11 +81,13 @@ Only methods inherited from \code{\link{PipeOp}}.
 }
 
 \examples{
+\dontshow{ if (requireNamespace("rpart")) \{ }
 library(mlr3)
 task = tsk("iris")
 po = po("ovrsplit")
 po$train(list(task))
 po$predict(list(task))
+\dontshow{ \} }
 }
 \seealso{
 https://mlr-org.com/pipeops.html
diff --git a/man/mlr_pipeops_ovrunite.Rd b/man/mlr_pipeops_ovrunite.Rd
index ddfabdba8..504030b05 100644
--- a/man/mlr_pipeops_ovrunite.Rd
+++ b/man/mlr_pipeops_ovrunite.Rd
@@ -74,6 +74,7 @@ Only methods inherited from \code{\link{PipeOpEnsemble}}/\code{\link{PipeOp}}.
 }
 
 \examples{
+\dontshow{ if (requireNamespace("rpart")) \{ }
 library(mlr3)
 task = tsk("iris")
 gr = po("ovrsplit") \%>>\% lrn("classif.rpart") \%>>\% po("ovrunite")
@@ -81,6 +82,7 @@ gr$train(task)
 gr$predict(task)
 gr$pipeops$classif.rpart$learner$predict_type = "prob"
 gr$predict(task)
+\dontshow{ \} }
 }
 \seealso{
 https://mlr-org.com/pipeops.html
diff --git a/man/mlr_pipeops_proxy.Rd b/man/mlr_pipeops_proxy.Rd
index 109a82307..2cd62784b 100644
--- a/man/mlr_pipeops_proxy.Rd
+++ b/man/mlr_pipeops_proxy.Rd
@@ -74,6 +74,7 @@ Only methods inherited from \code{\link{PipeOp}}.
 }
 
 \examples{
+\dontshow{ if (requireNamespace("rpart")) \{ }
 library("mlr3")
 library("mlr3learners")
 
@@ -92,6 +93,7 @@ g$param_set$values$preproc.content = po("pca")
 g$param_set$values$learner.content = lrn("classif.rpart")
 rr_pca_rpart = resample(task, learner = GraphLearner$new(g), resampling = rsmp("cv", folds = 3))
 rr_pca_rpart$aggregate(msr("classif.ce"))
+\dontshow{ \} }
 }
 \seealso{
 https://mlr-org.com/pipeops.html
diff --git a/man/mlr_pipeops_randomresponse.Rd b/man/mlr_pipeops_randomresponse.Rd
index 78b211feb..f6ad01ecb 100644
--- a/man/mlr_pipeops_randomresponse.Rd
+++ b/man/mlr_pipeops_randomresponse.Rd
@@ -79,6 +79,7 @@ Only methods inherited from \code{\link{PipeOp}}.
 }
 
 \examples{
+\dontshow{ if (requireNamespace("rpart")) \{ }
 library(mlr3)
 library(mlr3learners)
 
@@ -95,6 +96,7 @@ g2$train(task2)
 g2$pipeops$regr.lm$learner$predict_type = "se"
 set.seed(2906)
 g2$predict(task2)
+\dontshow{ \} }
 }
 \seealso{
 https://mlr-org.com/pipeops.html
diff --git a/man/mlr_pipeops_regravg.Rd b/man/mlr_pipeops_regravg.Rd
index 95d8b4c7b..fee7ae964 100644
--- a/man/mlr_pipeops_regravg.Rd
+++ b/man/mlr_pipeops_regravg.Rd
@@ -70,6 +70,7 @@ Only methods inherited from \code{\link{PipeOpEnsemble}}/\code{\link{PipeOp}}.
 }
 
 \examples{
+\dontshow{ if (requireNamespace("rpart")) \{ }
 library("mlr3")
 
 # Simple Bagging
@@ -81,6 +82,7 @@ gr = ppl("greplicate",
   po("classifavg")
 
 resample(tsk("iris"), GraphLearner$new(gr), rsmp("holdout"))
+\dontshow{ \} }
 }
 \seealso{
 https://mlr-org.com/pipeops.html
diff --git a/man/mlr_pipeops_smote.Rd b/man/mlr_pipeops_smote.Rd
index ae4035a88..18986b57d 100644
--- a/man/mlr_pipeops_smote.Rd
+++ b/man/mlr_pipeops_smote.Rd
@@ -65,6 +65,7 @@ Only methods inherited from \code{\link{PipeOpTaskPreproc}}/\code{\link{PipeOp}}
 }
 
 \examples{
+\dontshow{ if (requireNamespace("smotefamily")) \{ }
 library("mlr3")
 
 # Create example task
@@ -78,6 +79,7 @@ table(task$data()$result)
 pop = po("smote")
 smotedata = pop$train(list(task))[[1]]$data()
 table(smotedata$result)
+\dontshow{ \} }
 }
 \references{
 Chawla NV, Bowyer KW, Hall LO, Kegelmeyer WP (2002).
diff --git a/man/mlr_pipeops_targetmutate.Rd b/man/mlr_pipeops_targetmutate.Rd
index d3cab4420..2d65b74f5 100644
--- a/man/mlr_pipeops_targetmutate.Rd
+++ b/man/mlr_pipeops_targetmutate.Rd
@@ -78,6 +78,7 @@ Only methods inherited from \code{\link{PipeOpTargetTrafo}}/\code{\link{PipeOp}}
 }
 
 \examples{
+\dontshow{ if (requireNamespace("rpart")) \{ }
 library(mlr3)
 task = tsk("boston_housing")
 po = PipeOpTargetMutate$new("logtrafo", param_vals = list(
@@ -108,6 +109,7 @@ g$predict(task)
 tt = ppl("targettrafo", graph = PipeOpLearner$new(LearnerRegrRpart$new()))
 tt$param_set$values$targetmutate.trafo = function(x) log(x, base = 2)
 tt$param_set$values$targetmutate.inverter = function(x) list(response = 2 ^ x$response)
+\dontshow{ \} }
 }
 \seealso{
 https://mlr-org.com/pipeops.html
diff --git a/man/mlr_pipeops_targettrafoscalerange.Rd b/man/mlr_pipeops_targettrafoscalerange.Rd
index 0cd636479..4979df763 100644
--- a/man/mlr_pipeops_targettrafoscalerange.Rd
+++ b/man/mlr_pipeops_targettrafoscalerange.Rd
@@ -61,6 +61,7 @@ Only methods inherited from \code{\link{PipeOpTargetTrafo}}/\code{\link{PipeOp}}
 }
 
 \examples{
+\dontshow{ if (requireNamespace("rpart")) \{ }
 library(mlr3)
 task = tsk("boston_housing")
 po = PipeOpTargetTrafoScaleRange$new()
@@ -74,6 +75,7 @@ ttscalerange = ppl("targettrafo", trafo_pipeop = PipeOpTargetTrafoScaleRange$new
 ttscalerange$train(task)
 ttscalerange$predict(task)
 ttscalerange$state$regr.rpart
+\dontshow{ \} }
 }
 \seealso{
 https://mlr-org.com/pipeops.html
diff --git a/man/mlr_pipeops_textvectorizer.Rd b/man/mlr_pipeops_textvectorizer.Rd
index a352669ae..2b4a186c3 100644
--- a/man/mlr_pipeops_textvectorizer.Rd
+++ b/man/mlr_pipeops_textvectorizer.Rd
@@ -155,6 +155,8 @@ Only methods inherited from \code{\link{PipeOpTaskPreproc}}/\code{\link{PipeOp}}
 }
 
 \examples{
+\dontshow{ if (requireNamespace("stopwords")) \{ }
+\dontshow{ if (requireNamespace("quanteda")) \{ }
 library("mlr3")
 library("data.table")
 # create some text data
@@ -172,6 +174,8 @@ one_line_of_iris = task$filter(13)
 one_line_of_iris$data()
 
 pos$predict(list(one_line_of_iris))[[1]]$data()
+\dontshow{ \} }
+\dontshow{ \} }
 }
 \seealso{
 https://mlr-org.com/pipeops.html
diff --git a/man/mlr_pipeops_threshold.Rd b/man/mlr_pipeops_threshold.Rd
index 9df94aa3b..a5a7fef22 100644
--- a/man/mlr_pipeops_threshold.Rd
+++ b/man/mlr_pipeops_threshold.Rd
@@ -61,12 +61,14 @@ Only methods inherited from \code{\link{PipeOp}}.
 }
 
 \examples{
+\dontshow{ if (requireNamespace("rpart")) \{ }
 library("mlr3")
 t = tsk("german_credit")
 gr = po(lrn("classif.rpart", predict_type = "prob")) \%>>\%
   po("threshold", param_vals = list(thresholds = 0.9))
 gr$train(t)
 gr$predict(t)
+\dontshow{ \} }
 }
 \seealso{
 https://mlr-org.com/pipeops.html
diff --git a/man/mlr_pipeops_tunethreshold.Rd b/man/mlr_pipeops_tunethreshold.Rd
index e56953239..683c87f61 100644
--- a/man/mlr_pipeops_tunethreshold.Rd
+++ b/man/mlr_pipeops_tunethreshold.Rd
@@ -78,6 +78,8 @@ Only methods inherited from \code{\link{PipeOp}}.
 }
 
 \examples{
+\dontshow{ if (requireNamespace("bbotk")) \{ }
+\dontshow{ if (requireNamespace("rpart")) \{ }
 library("mlr3")
 
 task = tsk("iris")
@@ -88,6 +90,8 @@ task$data()
 pop$train(task)
 
 pop$state
+\dontshow{ \} }
+\dontshow{ \} }
 }
 \seealso{
 https://mlr-org.com/pipeops.html
diff --git a/man/mlr_pipeops_updatetarget.Rd b/man/mlr_pipeops_updatetarget.Rd
index e7499b9b8..188199986 100644
--- a/man/mlr_pipeops_updatetarget.Rd
+++ b/man/mlr_pipeops_updatetarget.Rd
@@ -70,6 +70,7 @@ Only methods inherited from \code{\link{PipeOp}}.
 }
 
 \examples{
+\dontshow{ if (requireNamespace("rpart")) \{ }
 \dontrun{
 # Create a binary class task from iris
 library(mlr3)
@@ -78,6 +79,7 @@ po = PipeOpUpdateTarget$new(param_vals = list(trafo = trafo_fun, new_target_name
 po$train(list(tsk("iris")))
 po$predict(list(tsk("iris")))
 }
+\dontshow{ \} }
 }
 \seealso{
 https://mlr-org.com/pipeops.html
diff --git a/man/mlr_pipeops_vtreat.Rd b/man/mlr_pipeops_vtreat.Rd
index 4589fdb3b..e9c26a3b2 100644
--- a/man/mlr_pipeops_vtreat.Rd
+++ b/man/mlr_pipeops_vtreat.Rd
@@ -122,6 +122,7 @@ Only methods inherited from \code{\link{PipeOpTaskPreproc}}/\code{\link{PipeOp}}
 }
 
 \examples{
+\dontshow{ if (requireNamespace("vtreat")) \{ }
 library("mlr3")
 
 set.seed(2020)
@@ -140,6 +141,7 @@ task = TaskRegr$new("vtreat_regr", backend = make_data(100), target = "y")
 
 pop = PipeOpVtreat$new()
 pop$train(list(task))
+\dontshow{ \} }
 }
 \seealso{
 https://mlr-org.com/pipeops.html
diff --git a/man/mlr_pipeops_yeojohnson.Rd b/man/mlr_pipeops_yeojohnson.Rd
index 0c4c220f3..1fe4e40fe 100644
--- a/man/mlr_pipeops_yeojohnson.Rd
+++ b/man/mlr_pipeops_yeojohnson.Rd
@@ -68,6 +68,7 @@ Only methods inherited from \code{\link{PipeOpTaskPreproc}}/\code{\link{PipeOp}}
 }
 
 \examples{
+\dontshow{ if (requireNamespace("bestNormalize")) \{ }
 library("mlr3")
 
 task = tsk("iris")
@@ -77,6 +78,7 @@ task$data()
 pop$train(list(task))[[1]]$data()
 
 pop$state
+\dontshow{ \} }
 }
 \seealso{
 https://mlr-org.com/pipeops.html
diff --git a/man/po.Rd b/man/po.Rd
index 963049501..4f44dd219 100644
--- a/man/po.Rd
+++ b/man/po.Rd
@@ -48,6 +48,7 @@ it to a \code{\link{PipeOp}}. \code{pos()} (with plural-s) takes either a \code{
 list of objects, and creates a \code{list} of \code{\link{PipeOp}}s.
 }
 \examples{
+\dontshow{ if (requireNamespace("rpart")) \{ }
 library("mlr3")
 
 po("learner", lrn("classif.rpart"), cp = 0.3)
@@ -59,4 +60,5 @@ mlr_pipeops$get("learner", lrn("classif.rpart"),
   param_vals = list(cp = 0.3))
 
 pos(c("pca", original = "nop"))
+\dontshow{ \} }
 }
diff --git a/man/ppl.Rd b/man/ppl.Rd
index 713312f33..7a00567ee 100644
--- a/man/ppl.Rd
+++ b/man/ppl.Rd
@@ -32,8 +32,10 @@ Creates a \code{\link{Graph}} from \code{\link{mlr_graphs}} from given ID
 vector of any list and returns a \code{list} of possibly muliple \code{\link{Graph}}s.
 }
 \examples{
+\dontshow{ if (requireNamespace("rpart")) \{ }
 library("mlr3")
 
 gr = ppl("bagging", graph = po(lrn("regr.rpart")),
   averager = po("regravg", collect_multiplicity = TRUE))
+\dontshow{ \} }
 }
diff --git a/tests/testthat/helper_mlr3pipelines.R b/tests/testthat/helper_mlr3pipelines.R
new file mode 100644
index 000000000..851c20f87
--- /dev/null
+++ b/tests/testthat/helper_mlr3pipelines.R
@@ -0,0 +1,8 @@
+library("mlr3pipelines")
+library("checkmate")
+library("testthat")
+library("R6")
+library("mlr3misc")
+library("paradox")
+
+lapply(list.files(system.file("testthat", package = "mlr3pipelines"), pattern = "^helper.*\\.[rR]", full.names = TRUE), source)
diff --git a/tests/testthat/test_Graph.R b/tests/testthat/test_Graph.R
index ed6f900d8..6a6004df4 100644
--- a/tests/testthat/test_Graph.R
+++ b/tests/testthat/test_Graph.R
@@ -1,6 +1,7 @@
 context("Graph")
 
 test_that("linear graph", {
+  skip_if_not_installed("rpart")
   g = Graph$new()
   expect_equal(g$ids(sorted = TRUE), character(0))
 
@@ -78,6 +79,7 @@ test_that("complex graph", {
       "Training debug3 with input list(input_1 = 3, input_2 = 5, input_3 = 5)"),
     info = paste0("'", lines, "'", collapse = "', '"))
 
+  skip_if_not_installed("igraph")
   pdf(file = NULL)  # don't show plot. It is annoying.
   biggraph$plot()
   dev.off()
@@ -149,6 +151,7 @@ test_that("input / output lists and naming", {
   # output should be debug2.3, debug3.1, debug3.2
   # (inputs and outputs in PipeOp order first, in channel order second)
 
+  skip_if_not_installed("igraph")
   pdf(file = NULL)  # don't show plot. It is annoying.
   gr$plot()
   dev.off()
@@ -246,6 +249,7 @@ test_that("Empty Graph", {
 
   expect_output(print(Graph$new()), "^Empty Graph\\.$")
 
+  skip_if_not_installed("igraph")
   expect_output(Graph$new()$plot(), "^Empty Graph, not plotting\\.$")
 
   expect_equal(gunion(list()), Graph$new())
@@ -377,6 +381,7 @@ test_that("Graph with vararg input", {
 })
 
 test_that("single pipeop plot", {
+  skip_if_not_installed("igraph")
   imp_num = po("imputehist")
   graph = as_graph(imp_num)
 
diff --git a/tests/testthat/test_GraphLearner.R b/tests/testthat/test_GraphLearner.R
index 631aec822..b8d7068b0 100644
--- a/tests/testthat/test_GraphLearner.R
+++ b/tests/testthat/test_GraphLearner.R
@@ -1,6 +1,7 @@
 context("GraphLearner")
 
 test_that("basic graphlearner tests", {
+  skip_if_not_installed("rpart")
   skip_on_cran()  # takes too long
   task = mlr_tasks$get("iris")
 
@@ -73,6 +74,7 @@ test_that("basic graphlearner tests", {
 })
 
 test_that("GraphLearner clone_graph FALSE", {
+  skip_if_not_installed("rpart")
 
   # prepare graph
   gr1 = po("pca") %>>% lrn("classif.rpart")
@@ -174,6 +176,7 @@ test_that("graphlearner parameters behave as they should", {
 })
 
 test_that("graphlearner type inference", {
+  skip_if_not_installed("rpart")
   skip_on_cran()  # takes too long
   # default: classif
   lrn = GraphLearner$new(mlr_pipeops$get("nop"))
@@ -242,6 +245,7 @@ test_that("graphlearner type inference", {
 })
 
 test_that("graphlearner type inference - branched", {
+  skip_if_not_installed("rpart")
   skip_on_cran()  # takes too long
 
   # default: classif
@@ -306,6 +310,7 @@ test_that("graphlearner type inference - branched", {
 })
 
 test_that("graphlearner predict type inference", {
+  skip_if_not_installed("rpart")
   skip_on_cran()  # takes too long
   # Getter:
 
@@ -403,6 +408,7 @@ test_that("graphlearner predict type inference", {
 
 
 test_that("GraphLearner model", {
+  skip_if_not_installed("rpart")
   graph = po("pca") %>>% lrn("classif.rpart")
   graph2 = graph$clone(deep = TRUE)
   graph_orig = graph$clone(deep = TRUE)
@@ -437,6 +443,7 @@ test_that("GraphLearner model", {
 })
 
 test_that("predict() function for Graph", {
+  skip_if_not_installed("rpart")
 
   lx = as_graph(lrn("classif.rpart"))
 
@@ -465,6 +472,7 @@ test_that("predict() function for Graph", {
 })
 
 test_that("base_learner() works", {
+  skip_if_not_installed("rpart")
   # graph containing single PipeOpLearner
   x = as_learner(as_graph(lrn("classif.rpart")))
   # untrained
@@ -517,6 +525,7 @@ test_that("base_learner() works", {
 
 
 test_that("GraphLearner hashes", {
+  skip_if_not_installed("rpart")
 
 
   learner1 = as_learner(ppl("robustify") %>>% lrn("regr.rpart"))
diff --git a/tests/testthat/test_conversion.R b/tests/testthat/test_conversion.R
index 5960a4abe..ad77300e4 100644
--- a/tests/testthat/test_conversion.R
+++ b/tests/testthat/test_conversion.R
@@ -22,6 +22,8 @@ test_that("type conversions in graph creation", {
 })
 
 test_that("learner conversion in graph creation", {
+  skip_if_not_installed("rpart")
+  skip_if_not_installed("rpart")
   gr1 = Graph$new()$add_pipeop(lrn("classif.rpart"))
   gr2 = Graph$new()$add_pipeop(LearnerClassifRpart$new())
   gr3 = Graph$new()$add_pipeop(mlr_pipeops$get("learner", lrn("classif.rpart")))
@@ -50,6 +52,7 @@ test_that("learner conversion in graph creation", {
 })
 
 test_that("assertions work", {
+  skip_if_not_installed("rpart")
 
   expect_error(as_pipeop("test"))
   expect_error(assert_pipeop(lrn("classif.rpart")))
@@ -90,6 +93,7 @@ test_that("auto-gunion", {
 })
 
 test_that("po for Filter", {
+  skip_if_not_installed("mlr3filters")
   flt = mlr3filters::FilterVariance$new()
   flt$param_set$values$na.rm = TRUE
 
@@ -105,6 +109,7 @@ test_that("po for Filter", {
 })
 
 test_that("po for Learner", {
+  skip_if_not_installed("rpart")
   lrn = LearnerClassifRpart$new()
   lrn$param_set$values$xval = 9
 
@@ -120,6 +125,7 @@ test_that("po for Learner", {
 })
 
 test_that("Graph to GraphLearner", {
+  skip_if_not_installed("rpart")
 
   grph = po("pca") %>>% po(lrn("classif.rpart"))
 
@@ -142,6 +148,7 @@ test_that("Graph to GraphLearner", {
 })
 
 test_that("PipeOp to GraphLearner", {
+  skip_if_not_installed("rpart")
 
   po = po("proxy", param_vals = list(content = lrn("classif.rpart")))
 
diff --git a/tests/testthat/test_dictionary.R b/tests/testthat/test_dictionary.R
index 1a598668c..a35a902fa 100644
--- a/tests/testthat/test_dictionary.R
+++ b/tests/testthat/test_dictionary.R
@@ -2,6 +2,8 @@ context("Dictionary")
 
 # we check that all pipeops that are exported are also in the dictionary, and can be constructed from there.
 test_that("Dictionary contains all PipeOps", {
+  skip_if_not_installed("mlr3filters")
+  skip_if_not_installed("rpart")
   skip_on_cran()
 
   oldwarn = options(warn = 2)
@@ -80,6 +82,7 @@ test_that("Dictionary contains all PipeOps", {
 
   # the loop now checks whether we can construct each pipeop from the dictionary *and* by itself
   for (idx in seq_along(dictnames)) {
+    if (dictnames[[idx]] == "filter") next  # TODO: remove this when https://github.com/mlr-org/mlr3filters/issues/162 is solved
 
     pogen = get(pipeops[idx], pkgenv)  # the constructor, as found in the package namespace
     dictname = dictnames[idx]  # the "key" in the mlr_pipeops dictionary
@@ -217,6 +220,7 @@ test_that("data.table of pipeops looks as it should", {
 })
 
 test_that("GraphLearner is in mlr_learners", {
+  skip_if_not_installed("rpart")
 
   expect_data_table(as.data.table(mlr_learners))  # can construct mlr_learners table
 
diff --git a/tests/testthat/test_learner_weightedaverage.R b/tests/testthat/test_learner_weightedaverage.R
index 560e9fa8e..dc77bd815 100644
--- a/tests/testthat/test_learner_weightedaverage.R
+++ b/tests/testthat/test_learner_weightedaverage.R
@@ -1,6 +1,7 @@
 context("WeightedAverage Learner")
 
 test_that("LearnerClassifAvg", {
+  skip_if_not_installed("rpart")
   skip_on_cran()  # takes too long
   lrn = LearnerClassifAvg$new()
   expect_learner(lrn)
@@ -100,6 +101,7 @@ test_that("LearnerRegrAvg", {
 })
 
 test_that("LearnerClassifAvg Pipeline", {
+  skip_if_not_installed("rpart")
   skip_on_cran()  # takes too long
   tsk = mlr_tasks$get("iris")
   # Works for response
@@ -146,6 +148,7 @@ test_that("LearnerClassifAvg Pipeline", {
 })
 
 test_that("LearnerRegrAvg Pipeline", {
+  skip_if_not_installed("rpart")
   skip_on_cran()  # takes too long
   tsk = mlr_tasks$get("boston_housing_classic")
   # Works for response
diff --git a/tests/testthat/test_mlr_graphs_bagging.R b/tests/testthat/test_mlr_graphs_bagging.R
index 3cd5bee95..14836b705 100644
--- a/tests/testthat/test_mlr_graphs_bagging.R
+++ b/tests/testthat/test_mlr_graphs_bagging.R
@@ -1,6 +1,7 @@
 context("ppl - pipeline_bagging")
 
 test_that("Bagging Pipeline", {
+  skip_if_not_installed("rpart")
   skip_on_cran()  # takes too long
 
   expect_error(ppl("bagging", graph = lrn("classif.rpart"), averager = po("classifavg", collect_multiplicity = FALSE)),
@@ -39,6 +40,7 @@ test_that("Bagging Pipeline", {
 })
 
 test_that("Bagging with replacement", {
+  skip_if_not_installed("rpart")
   tsk = tsk("iris")
   lrn = lrn("classif.rpart")
   p = ppl("bagging", graph = po(lrn), replace = TRUE, averager = po("classifavg", collect_multiplicity = TRUE))
diff --git a/tests/testthat/test_mlr_graphs_branching.R b/tests/testthat/test_mlr_graphs_branching.R
index 92f635d59..e76a55473 100644
--- a/tests/testthat/test_mlr_graphs_branching.R
+++ b/tests/testthat/test_mlr_graphs_branching.R
@@ -1,6 +1,7 @@
 context("ppl - pipeline_branch")
 
 test_that("Branching Pipeline", {
+  skip_if_not_installed("rpart")
   lrns = map(list(lrn("classif.rpart"), lrn("classif.featureless")), po)
   task = mlr_tasks$get("boston_housing_classic")
   gr = pipeline_branch(lrns)
diff --git a/tests/testthat/test_mlr_graphs_convert_types.R b/tests/testthat/test_mlr_graphs_convert_types.R
new file mode 100644
index 000000000..e75f0fc0c
--- /dev/null
+++ b/tests/testthat/test_mlr_graphs_convert_types.R
@@ -0,0 +1,159 @@
+context("ppl - pipeline_convert_types")
+
+test_that("general tests", {
+
+  data_chr = data.table::data.table(
+    x = factor(letters[1:3]),
+    y = letters[1:3],
+    z = letters[1:3]
+  )
+
+  data_fct = data.table::data.table(
+    x = factor(letters[1:3]),
+    y = factor(letters[1:3]),
+    z = factor(letters[1:3])
+  )
+
+  data_ord = data.table::data.table(
+    x = factor(letters[1:3]),
+    y = ordered(letters[1:3]),
+    z = ordered(letters[1:3])
+  )
+
+  task_chr = TaskClassif$new("task_chr", data_chr, "x")
+  task_fct = TaskClassif$new("task_fct", data_fct, "x")
+  task_ord = TaskClassif$new("task_ord", data_ord, "x")
+
+  graph = ppl("convert_types", "character", "factor")
+  expect_equal(graph$train(task_chr)[[1]]$data(), data_fct)
+
+  graph = ppl("convert_types", c("ordered", "character"), "factor")
+  expect_equal(graph$train(task_chr)[[1]]$data(), data_fct)
+  expect_equal(graph$train(task_ord)[[1]]$data(), data_fct)
+
+  graph_z = ppl("convert_types", "character", "factor",
+    affect_columns = selector_name("z"))
+  expect_equal(graph_z$train(task_chr)[[1]]$data()[, c("x", "z", "y")], cbind(data_fct[, c("x", "z")], data_chr[, "y"]))
+
+  graph_z = ppl("convert_types", "numeric", "factor",
+    affect_columns = selector_name("z"))
+  expect_equal(graph_z$train(task_chr)[[1]]$data(), data_chr)
+
+  graph_z = ppl("convert_types", "ordered", "factor",
+    affect_columns = selector_name("z"))
+  expect_equal(graph_z$train(task_ord)[[1]]$data()[, c("x", "z", "y")], cbind(data_fct[, c("x", "z")], data_ord[, "y"]))
+
+  expect_equal(graph_z$train(task_fct)[[1]]$data()[, c("x", "z", "y")], data_fct[, c("x", "z", "y")])
+  expect_equal(graph_z$train(task_chr)[[1]]$data()[, c("x", "z", "y")], data_chr[, c("x", "z", "y")])
+
+})
+
+test_that("more_args", {
+  data_time = data.table::data.table(
+    x = factor(letters[1:3]),
+    y = paste0("2024-02-01 00:00:0", 1:3)
+  )
+
+  data_time_weird = data.table::data.table(
+    x = factor(letters[1:3]),
+    y = paste0("02/2024/01 00:00:0", 1:3)
+  )
+
+  task_time = TaskClassif$new("task_time", data_time, "x")
+  task_time_weird = TaskClassif$new("task_time_weird", data_time_weird, "x")
+
+  expect_equal(
+    ppl("convert_types", "character", "POSIXct")$train(task_time)[[1]]$data()[, y],
+    as.POSIXct(data_time$y)
+  )
+
+  expect_equal(
+    ppl("convert_types", "character", "POSIXct",
+      more_args = list(format = "%m/%Y/%d %H:%M:%OS")
+    )$train(task_time_weird)[[1]]$data()[, y],
+    as.POSIXct(data_time$y)
+  )
+})
+
+test_that("fixfactors", {
+
+  data_chr = data.table::data.table(
+    x = factor(letters[1:3]),
+    y = letters[1:3],
+    z = letters[1:3]
+  )
+
+  data_fct = data.table::data.table(
+    x = factor(letters[1:3]),
+    y = factor(letters[1:3]),
+    z = factor(letters[1:3])
+  )
+  task_chr = TaskClassif$new("task_chr", data_chr, "x")
+  task_fct = TaskClassif$new("task_fct", data_fct, "x")
+
+  nadata <- data.table(y = factor(c("a", "b", NA)), z = factor(c("a", "b", NA)))
+
+
+  graph = ppl("convert_types", "character", "factor")
+
+  graph$train(task_chr$clone(deep = TRUE)$filter(1:2))
+  expect_equal(graph$predict(task_chr)[[1]]$data()[, c("y", "z")], nadata)
+
+  graph$train(task_fct$clone(deep = TRUE)$filter(1:2))
+  expect_equal(graph$predict(task_fct)[[1]]$data()[, c("y", "z")], nadata)
+
+  graph = ppl("convert_types", "character", "numeric")
+
+  graph$train(task_fct$clone(deep = TRUE)$filter(1:2))
+  expect_equal(graph$predict(task_fct)[[1]]$data()[, c("y", "z")], data_fct[, c("y", "z")])
+
+  graph = ppl("convert_types", "character", "numeric", fixfactors = TRUE)
+  graph$train(task_fct$clone(deep = TRUE)$filter(1:2))
+  expect_equal(graph$predict(task_fct)[[1]]$data()[, c("y", "z")], nadata)
+
+  graph = ppl("convert_types", "character", "factor", fixfactors = FALSE)
+
+  graph$train(task_chr$clone(deep = TRUE)$filter(1:2))
+  expect_equal(graph$predict(task_chr)[[1]]$data()[, c("y", "z")], data_fct[, c("y", "z")])
+
+
+  graph = ppl("convert_types", "character", "factor")
+  graph$train(task_chr$clone(deep = TRUE)$filter(1:2))
+
+  graph_z = ppl("convert_types", "character", "factor",
+    affect_columns = selector_name("z"))
+  graph_z$train(task_chr$clone(deep = TRUE)$filter(1:2))
+
+  expect_equal(graph_z$predict(task_chr)[[1]]$data()[, c("y", "z")], cbind(data_chr[, "y"], nadata[, "z"]))
+
+})
+
+
+test_that("id", {
+
+  expect_equal(
+    ppl("convert_types", "character", "factor")$ids(),
+    c("convert_chr_to_fct", "convert_chr_to_fct_ff")
+  )
+
+  expect_equal(
+    ppl("convert_types", c("character", "POSIXct"), "factor")$ids(),
+    c("convert_chrpxc_to_fct", "convert_chrpxc_to_fct_ff")
+  )
+
+  expect_equal(
+    ppl("convert_types", c("character", "POSIXct"), "factor", fixfactors = FALSE)$ids(),
+    "convert_chrpxc_to_fct"
+  )
+
+  expect_equal(
+    ppl("convert_types", c("character", "POSIXct"), "factor", id = "abc")$ids(),
+    c("abc", "abc_ff")
+  )
+
+  expect_equal(
+    ppl("convert_types", c("character", "POSIXct"), "factor", id = "abc", fixfactors = FALSE)$ids(),
+    "abc"
+  )
+
+})
diff --git a/tests/testthat/test_mlr_graphs_ovr.R b/tests/testthat/test_mlr_graphs_ovr.R
index 71663a3e7..8ba4df4d6 100644
--- a/tests/testthat/test_mlr_graphs_ovr.R
+++ b/tests/testthat/test_mlr_graphs_ovr.R
@@ -1,6 +1,7 @@
 context("ppl - pipeline_ovr")
 
 test_that("OVR Pipeline", {
+  skip_if_not_installed("rpart")
   task = tsk("wine")
 
   # assertions on graph
diff --git a/tests/testthat/test_mlr_graphs_robustify.R b/tests/testthat/test_mlr_graphs_robustify.R
index b412990bd..8720ca0af 100644
--- a/tests/testthat/test_mlr_graphs_robustify.R
+++ b/tests/testthat/test_mlr_graphs_robustify.R
@@ -1,6 +1,7 @@
 context("ppl - pipeline_robustify")
 
 test_that("Robustify Pipeline", {
+  skip_if_not_installed("rpart")
   skip_on_cran()
   lrn = lrn("classif.rpart")
 
@@ -103,6 +104,7 @@ test_that("Robustify Pipeline", {
 
 
 test_that("Robustify Pipeline Impute Missings", {
+  skip_if_not_installed("rpart")
   tmissings = tsk("pima")
   tnomissings = tsk("iris")
 
@@ -151,6 +153,7 @@ makeTypeTask = function(types) {
 
 
 test_that("Robustify Pipeline factor to numeric", {
+  skip_if_not_installed("rpart")
 
   alltask = makeTypeTask(c("integer", "numeric", "logical", "character", "POSIXct"))
 
diff --git a/tests/testthat/test_mlr_graphs_stacking.R b/tests/testthat/test_mlr_graphs_stacking.R
index 8cd0d6735..c11eee099 100644
--- a/tests/testthat/test_mlr_graphs_stacking.R
+++ b/tests/testthat/test_mlr_graphs_stacking.R
@@ -1,6 +1,7 @@
 context("ppl - pipeline_stacking")
 
 test_that("Stacking Pipeline", {
+  skip_if_not_installed("rpart")
 
   base_learners = list(
     lrn("classif.rpart", predict_type = "prob", id = "base.rpart")
diff --git a/tests/testthat/test_mlr_graphs_targettrafo.R b/tests/testthat/test_mlr_graphs_targettrafo.R
index fcc40fec4..9ddd32f95 100644
--- a/tests/testthat/test_mlr_graphs_targettrafo.R
+++ b/tests/testthat/test_mlr_graphs_targettrafo.R
@@ -1,6 +1,7 @@
 context("ppl - pipeline_targettrafo")
 
 test_that("Target Trafo Pipeline", {
+  skip_if_not_installed("rpart")
   task = tsk("boston_housing_classic")
 
   tt = ppl("targettrafo", graph = PipeOpLearner$new(LearnerRegrRpart$new()))
@@ -45,6 +46,7 @@ test_that("Target Trafo Pipeline", {
 })
 
 test_that("More Complex Target Trafo Pipelines", {
+  skip_if_not_installed("rpart")
  task = tsk("mtcars")
  tt = pipeline_targettrafo((po("select") %>>% ppl("branch", list(lrn("regr.featureless"), lrn("regr.rpart")))))
  expect_equal(tt$input$op.id, "targetmutate")
diff --git a/tests/testthat/test_multichannels.R b/tests/testthat/test_multichannels.R
index 7d2c2c00e..f0a1a0730 100644
--- a/tests/testthat/test_multichannels.R
+++ b/tests/testthat/test_multichannels.R
@@ -8,6 +8,7 @@ test_that("adding multiple edges to output channels works", {
 
   expect_output(print(graph), c("scale.*subsample,pca.*\n.*subsample.*scale.*\n.*pca.*scale"))
 
+  skip_if_not_installed("igraph")
   pdf(file = NULL)  # don't show plot. It is annoying.
   graph$plot()
   dev.off()
@@ -96,6 +97,7 @@ test_that("adding multiple edges to vararg input channel works", {
 
   expect_output(print(graph), c("scale.*vararg.*\n.*pca.*vararg.*\n.*vararg.*scale,pca"))
 
+  skip_if_not_installed("igraph")
   pdf(file = NULL)  # don't show plot. It is annoying.
   graph$plot()
   dev.off()
diff --git a/tests/testthat/test_multiplicities.R b/tests/testthat/test_multiplicities.R
index a938ce1ca..cbb362fd7 100644
--- a/tests/testthat/test_multiplicities.R
+++ b/tests/testthat/test_multiplicities.R
@@ -116,6 +116,7 @@ test_that("PipeOp - evaluate_multiplicities", {
 })
 
 test_that("Graph - add_edge", {
+  skip_if_not_installed("rpart")
   learner = lrn("classif.rpart")
   g1 = PipeOpOVRSplit$new() %>>% learner %>>% PipeOpOVRUnite$new()
   g2 = Graph$new()
diff --git a/tests/testthat/test_pipeop_boxcox.R b/tests/testthat/test_pipeop_boxcox.R
index 4216bdd5c..63a2547d8 100644
--- a/tests/testthat/test_pipeop_boxcox.R
+++ b/tests/testthat/test_pipeop_boxcox.R
@@ -1,6 +1,7 @@
 context("PipeOpBoxCox")
 
 test_that("PipeOpBoxCox - general functionality", {
+  skip_if_not_installed("bestNormalize")
   task = mlr_tasks$get("iris")
   op = PipeOpBoxCox$new()
   expect_pipeop(op)
@@ -15,6 +16,7 @@ test_that("PipeOpBoxCox - general functionality", {
 })
 
 test_that("PipeOpBoxCox - receive expected result", {
+  skip_if_not_installed("bestNormalize")
   task = mlr_tasks$get("iris")
   op = PipeOpBoxCox$new(param_vals = list(standardize = FALSE))
   result = train_pipeop(op, inputs = list(task))
diff --git a/tests/testthat/test_pipeop_encodelmer.R b/tests/testthat/test_pipeop_encodelmer.R
index 1fabbc454..8ec4b297a 100644
--- a/tests/testthat/test_pipeop_encodelmer.R
+++ b/tests/testthat/test_pipeop_encodelmer.R
@@ -5,6 +5,8 @@ sample_n_letters = function(n, l = 3) {
 }
 
 test_that("PipeOpEncodeLmer regr", {
+  skip_if_not_installed("nloptr")
+  skip_if_not_installed("lme4")
   set.seed(8008135)
   task = mlr_tasks$get("boston_housing_classic")
   chaslevels = task$levels()$chas
@@ -25,6 +27,8 @@ test_that("PipeOpEncodeLmer regr", {
 
 
 test_that("PipeOpEncodeLmer multi and binaryclass", {
+  skip_if_not_installed("nloptr")
+  skip_if_not_installed("lme4")
   set.seed(8008135)
 
   # Multiclass
@@ -68,6 +72,8 @@ test_that("PipeOpEncodeLmer multi and binaryclass", {
 })
 
 test_that("PipeOpEncodeLmer Edge Cases", {
+  skip_if_not_installed("nloptr")
+  skip_if_not_installed("lme4")
   set.seed(8008135)
   task = mlr3::TaskClassif$new("task",
     data.table::data.table(x = sample_n_letters(10, 2), y = 1:10, z = 1:10), "x")
@@ -89,6 +95,8 @@ test_that("PipeOpEncodeLmer Edge Cases", {
 
 
 test_that("Confirms to sensible values", {
+  skip_if_not_installed("nloptr")
+  skip_if_not_installed("lme4")
   logit = function(x) {exp(-x) / (1+exp(-x))}
 
   data = data.table::data.table(y = factor(sample_n_letters(200, 2)))
diff --git a/tests/testthat/test_pipeop_featureunion.R b/tests/testthat/test_pipeop_featureunion.R
index f408fb196..50348a091 100644
--- a/tests/testthat/test_pipeop_featureunion.R
+++ b/tests/testthat/test_pipeop_featureunion.R
@@ -49,6 +49,7 @@ test_that("PipeOpFeatureUnion - train and predict", {
 })
 
 test_that("PipeOpFeatureUnion - train and predict II", {
+  skip_if_not_installed("rpart")
   # Define PipeOp's
   scatter = PipeOpCopy$new(2)
   op2a = PipeOpPCA$new()
@@ -129,6 +130,7 @@ test_that("PipeOpFeatureUnion - levels are preserved", {
 })
 
 test_that("feature renaming", {
+  skip_if_not_installed("rpart")
   expect_pipeop_class(PipeOpFeatureUnion, list(letters[1:3]))
 
   expect_equal(nrow(PipeOpFeatureUnion$new(c("a", "b", "c"))$input), 3)
diff --git a/tests/testthat/test_pipeop_filter.R b/tests/testthat/test_pipeop_filter.R
index a02239fc5..b4ecee96a 100644
--- a/tests/testthat/test_pipeop_filter.R
+++ b/tests/testthat/test_pipeop_filter.R
@@ -1,6 +1,7 @@
 context("PipeOpFilter")
 
 test_that("PipeOpFilter", {
+  skip_if_not_installed("mlr3filters")
   task = mlr_tasks$get("boston_housing_classic")
 
   expect_datapreproc_pipeop_class(PipeOpFilter,
@@ -46,6 +47,7 @@ test_that("PipeOpFilter", {
 
 
 test_that("PipeOpFilter parameters", {
+  skip_if_not_installed("mlr3filters")
 
   po = PipeOpFilter$new(mlr3filters::FilterVariance$new())
 
@@ -64,6 +66,7 @@ test_that("PipeOpFilter parameters", {
 
 
 test_that("PipeFilter permuted", {
+  skip_if_not_installed("mlr3filters")
   set.seed(1)
   N = 50
   task = tgen("2dnormals")$generate(N)
diff --git a/tests/testthat/test_pipeop_ica.R b/tests/testthat/test_pipeop_ica.R
index c93237873..73eaebb54 100644
--- a/tests/testthat/test_pipeop_ica.R
+++ b/tests/testthat/test_pipeop_ica.R
@@ -1,6 +1,7 @@
 context("PipeOpICA")
 
 test_that("PipeOpICA - basic properties", {
+  skip_if_not_installed("fastICA")
   task = mlr_tasks$get("iris")
 
   expect_datapreproc_pipeop_class(PipeOpICA, task = task,
@@ -16,6 +17,7 @@ test_that("PipeOpICA - basic properties", {
 })
 
 test_that("PipeOpICA - compare to fastICA", {
+  skip_if_not_installed("fastICA")
   # Default parameters
   task = mlr_tasks$get("iris")
   op = PipeOpICA$new()
diff --git a/tests/testthat/test_pipeop_imputelearner.R b/tests/testthat/test_pipeop_imputelearner.R
index a443605c2..cf8a37705 100644
--- a/tests/testthat/test_pipeop_imputelearner.R
+++ b/tests/testthat/test_pipeop_imputelearner.R
@@ -1,6 +1,7 @@
 context("PipeOpImputeLearner")
 
 test_that("PipeOpImputeLearner - simple tests", {
+  skip_if_not_installed("rpart")
   # Pima has several missings
   task = mlr_tasks$get("pima")
   po = PipeOpImputeLearner$new(learner = lrn("regr.rpart"))
@@ -37,6 +38,7 @@ test_that("PipeOpImputeLearner - simple tests", {
 })
 
 test_that("PipeOpImputeLearner", {
+  skip_if_not_installed("rpart")
   skip_on_cran()  # slow test, so we don't do it on cran
 
   task = mlr_tasks$get("pima")
diff --git a/tests/testthat/test_pipeop_learner.R b/tests/testthat/test_pipeop_learner.R
index 048d46b58..9b45b707d 100644
--- a/tests/testthat/test_pipeop_learner.R
+++ b/tests/testthat/test_pipeop_learner.R
@@ -19,6 +19,7 @@ test_that("PipeOpLearner - basic properties", {
 })
 
 test_that("PipeOpLearner - param_set and values", {
+  skip_if_not_installed("rpart")
   lrn = mlr_learners$get("classif.rpart")
   po = PipeOpLearner$new(lrn)
 
@@ -55,6 +56,7 @@ test_that("PipeOpLearner - param_set and values", {
 })
 
 test_that("PipeOpLearner - graph but no id", {
+  skip_if_not_installed("rpart")
   g = PipeOpNOP$new() %>>% PipeOpLearner$new(LearnerClassifRpart$new())
   po = PipeOpLearner$new(g)
   expect_string(po$id)
@@ -84,6 +86,8 @@ test_that("PipeOpLearner - model active binding to state", {
 })
 
 test_that("packages", {
+  skip_if_not_installed("rpart")
+
   expect_set_equal(
     c("mlr3pipelines", lrn("classif.rpart")$packages),
     po("learner", learner = lrn("classif.rpart"))$packages
diff --git a/tests/testthat/test_pipeop_learnercv.R b/tests/testthat/test_pipeop_learnercv.R
index 3248925b0..83577295f 100644
--- a/tests/testthat/test_pipeop_learnercv.R
+++ b/tests/testthat/test_pipeop_learnercv.R
@@ -39,6 +39,7 @@ test_that("PipeOpLearnerCV - basic properties", {
 })
 
 test_that("PipeOpLearnerCV - param values", {
+  skip_if_not_installed("rpart")
   lrn = mlr_learners$get("classif.rpart")
   polrn = PipeOpLearnerCV$new(lrn)
   expect_subset(c("minsplit", "resampling.method", "resampling.folds"), polrn$param_set$ids())
@@ -50,6 +51,7 @@ test_that("PipeOpLearnerCV - param values", {
 })
 
 test_that("PipeOpLearnerCV - within resampling", {
+  skip_if_not_installed("rpart")
   lrn = mlr_learners$get("classif.rpart")
   gr = GraphLearner$new(PipeOpLearnerCV$new(lrn) %>>% po(id = "l2", lrn))
   rr = resample(tsk("iris"), gr, rsmp("holdout"))
@@ -57,6 +59,7 @@ test_that("PipeOpLearnerCV - within resampling", {
 })
 
 test_that("PipeOpLearnerCV - insample resampling", {
+  skip_if_not_installed("rpart")
   lrn = mlr_learners$get("classif.featureless")
   iris_with_unambiguous_mode = mlr_tasks$get("iris")$filter(c(1:49, 52:150))  # want featureless learner without randomness
 
@@ -72,6 +75,7 @@ test_that("PipeOpLearnerCV - insample resampling", {
 })
 
 test_that("PipeOpLearnerCV - graph but no id", {
+  skip_if_not_installed("rpart")
   g = PipeOpNOP$new() %>>% PipeOpLearner$new(LearnerClassifRpart$new())
   po = PipeOpLearnerCV$new(g)
   expect_string(po$id)
@@ -101,6 +105,7 @@ test_that("PipeOpLearnerCV - model active binding to state", {
 })
 
 test_that("predict_type", {
+  skip_if_not_installed("rpart")
   expect_equal(po("learner_cv", lrn("classif.rpart", predict_type = "response"))$predict_type, "response")
   expect_equal(po("learner_cv", lrn("classif.rpart", predict_type = "prob"))$predict_type, "prob")
 
diff --git a/tests/testthat/test_pipeop_missind.R b/tests/testthat/test_pipeop_missind.R
index 320484cb6..5754e8c24 100644
--- a/tests/testthat/test_pipeop_missind.R
+++ b/tests/testthat/test_pipeop_missind.R
@@ -99,6 +99,7 @@ test_that("PipeOpMissInd", {
 
 # https://stackoverflow.com/questions/60512348/how-to-impute-data-with-mlr3-and-predict-with-na-values
 test_that("union with missing rows", {
+  skip_if_not_installed("rpart")
   data("mtcars", package = "datasets")
   data = mtcars[, 1:3]
   # Train task
diff --git a/tests/testthat/test_pipeop_ovr.R b/tests/testthat/test_pipeop_ovr.R
index 3dd9169d9..6a76eae65 100644
--- a/tests/testthat/test_pipeop_ovr.R
+++ b/tests/testthat/test_pipeop_ovr.R
@@ -49,6 +49,7 @@ test_that("PipeOpOVRUnite - basic properties", {
 })
 
 test_that("PipeOpOVRUnite- train and predict", {
+  skip_if_not_installed("rpart")
   # toy tasks that are splitted, trained and predicted manually
   feature = rep(c(1, 0), c(10, 20))
   dat1 = data.table(target = as.factor(rep(c("a", "rest"), c(10, 20))), feature = feature)
@@ -94,6 +95,7 @@ test_that("PipeOpOVRUnite- train and predict", {
 context("PipeOpOVRSplit and PipeOpOVRUnite")
 
 test_that("PipeOpOVRSplit and PipeOpOVRUnite - train and predict", {
+  skip_if_not_installed("rpart")
   # same toy task but now we compare the results to the automated Graph's results
   feature = rep(c(1, 0), c(10, 20))
   dat0 = data.table(target = as.factor(rep(c("a", "b", "c"), each = 10)), feature = feature)
@@ -127,6 +129,7 @@ test_that("PipeOpOVRSplit and PipeOpOVRUnite - train and predict", {
 })
 
 test_that("PipeOpOVRSplit and PipeOpOVRUnite - task size", {
+  skip_if_not_installed("rpart")
   gr = PipeOpOVRSplit$new() %>>% LearnerClassifRpart$new() %>>% PipeOpOVRUnite$new()
   gr$train(tsk("iris")$filter(c(1:30, 51:80, 101:130)))
   prd = gr$predict(tsk("iris")$filter(c(1:30, 51:80, 101:130)))[[1]]
diff --git a/tests/testthat/test_pipeop_proxy.R b/tests/testthat/test_pipeop_proxy.R
index 960fab124..bc50ae73b 100644
--- a/tests/testthat/test_pipeop_proxy.R
+++ b/tests/testthat/test_pipeop_proxy.R
@@ -94,6 +94,7 @@ Training debug2 with input list\\(input_1 = 2\\)$")
 Predicting debug2 with input list\\(input_1 = 4\\) and state list\\(input_1 = 2\\)$")
 
 
+  skip_if_not_installed("fastICA")
   # ---------
   # NOP | feature union | NOP; feature union has vararg
 
@@ -119,6 +120,7 @@ Training debug2 with input list\\(input_1 = 2\\)$")
 
 
 test_that("Cloning as expected", {
+  skip_if_not_installed("rpart")
 
   gr = PipeOpProxy$new() %>>% LearnerClassifRpart$new()
 
diff --git a/tests/testthat/test_pipeop_randomresponse.R b/tests/testthat/test_pipeop_randomresponse.R
index 6284be65d..486340879 100644
--- a/tests/testthat/test_pipeop_randomresponse.R
+++ b/tests/testthat/test_pipeop_randomresponse.R
@@ -13,6 +13,8 @@ test_that("basic properties", {
 
 
 test_that("train and predict", {
+  skip_if_not_installed("rpart")
+  skip_if_not_installed("rpart")
   task1 = mlr_tasks$get("iris")
   task1$row_roles$use = c(1:10, 140:150)
   g1 = LearnerClassifRpart$new() %>>% PipeOpRandomResponse$new()
diff --git a/tests/testthat/test_pipeop_smote.R b/tests/testthat/test_pipeop_smote.R
index 0f6181f8e..9e2e1b7ee 100644
--- a/tests/testthat/test_pipeop_smote.R
+++ b/tests/testthat/test_pipeop_smote.R
@@ -1,6 +1,7 @@
 context("PipeOpSmote")
 
 test_that("PipeOpSmote - basic properties", {
+  skip_if_not_installed("smotefamily")
   set.seed(1234)
   data = smotefamily::sample_generator(1000, ratio = 0.80)
   data$result = as.factor(data$result)
@@ -18,6 +19,7 @@ test_that("PipeOpSmote - basic properties", {
 })
 
 test_that("compare to smotefamily::SMOT", {
+  skip_if_not_installed("smotefamily")
   set.seed(1234)
   data = smotefamily::sample_generator(1000, ratio = 0.80)
   data$result = as.factor(data$result)
diff --git a/tests/testthat/test_pipeop_targetmutate.R b/tests/testthat/test_pipeop_targetmutate.R
index 940fa2212..1d06fd01d 100644
--- a/tests/testthat/test_pipeop_targetmutate.R
+++ b/tests/testthat/test_pipeop_targetmutate.R
@@ -1,6 +1,7 @@
 context("PipeOpTargetMutate")
 
 test_that("PipeOpTargetMutate - basic properties", {
+  skip_if_not_installed("rpart")
   expect_pipeop_class(PipeOpTargetMutate, list(id = "po"))
 
   po = PipeOpTargetMutate$new("po")
@@ -38,6 +39,7 @@ test_that("PipeOpTargetMutate - basic properties", {
 })
 
 test_that("PipeOpTargetMutate - log base 2 trafo", {
+  skip_if_not_installed("rpart")
  g = Graph$new()
  g$add_pipeop(PipeOpTargetMutate$new("logtrafo",
    param_vals = list(
diff --git a/tests/testthat/test_pipeop_targettrafoscalerange.R b/tests/testthat/test_pipeop_targettrafoscalerange.R
index 9ae209993..d66f34d31 100644
--- a/tests/testthat/test_pipeop_targettrafoscalerange.R
+++ b/tests/testthat/test_pipeop_targettrafoscalerange.R
@@ -1,6 +1,7 @@
 context("PipeOpTargetTrafoScaleRange")
 
 test_that("PipeOpTargetTrafoScaleRange - basic properties", {
+  skip_if_not_installed("rpart")
   expect_pipeop_class(PipeOpTargetTrafoScaleRange, list(id = "po"))
 
   po = PipeOpTargetTrafoScaleRange$new()
@@ -48,6 +49,7 @@ test_that("PipeOpTargetTrafoScaleRange - basic properties", {
 })
 
 test_that("PipeOpTargetTrafoScaleRange - row use subsets", {
+  skip_if_not_installed("rpart")
   po = PipeOpTargetTrafoScaleRange$new()
 
   task = mlr_tasks$get("boston_housing_classic")
diff --git a/tests/testthat/test_pipeop_textvectorizer.R b/tests/testthat/test_pipeop_textvectorizer.R
index d916ad29c..4f13fa4b3 100644
--- a/tests/testthat/test_pipeop_textvectorizer.R
+++ b/tests/testthat/test_pipeop_textvectorizer.R
@@ -155,6 +155,7 @@ test_that("PipeOpTextVectorizer - integer sequence", {
   skip_if_not_installed("quanteda")
   suppressWarnings(loadNamespace("quanteda"))  # TODO: see https://github.com/quanteda/quanteda/issues/2116 , may not be an issue in the future
 
+  set.seed(1)
   task = mlr_tasks$get("iris")
   # create hacky text data:
   dt = data.table("txt" = apply(iris, 1, function(x) {
diff --git a/tests/testthat/test_pipeop_threshold.R b/tests/testthat/test_pipeop_threshold.R
index 6b2e2e5f8..18a334518 100644
--- a/tests/testthat/test_pipeop_threshold.R
+++ b/tests/testthat/test_pipeop_threshold.R
@@ -14,6 +14,7 @@ test_that("threshold general", {
 
 
 test_that("thresholding works for binary", {
+  skip_if_not_installed("rpart")
   po_lrn = po(lrn("classif.rpart", predict_type = "prob"))
 
   # binary
@@ -63,6 +64,7 @@ test_that("thresholding works for binary", {
 
 
 test_that("thresholding works for multiclass", {
+  skip_if_not_installed("rpart")
   po_lrn = po(lrn("classif.rpart", predict_type = "prob"))
 
   # multiclass
diff --git a/tests/testthat/test_pipeop_tunethreshold.R b/tests/testthat/test_pipeop_tunethreshold.R
index 4e22728af..09f9159ae 100644
--- a/tests/testthat/test_pipeop_tunethreshold.R
+++ b/tests/testthat/test_pipeop_tunethreshold.R
@@ -1,6 +1,7 @@
 context("tunethreshold")
 
 test_that("threshold works for multiclass", {
+  skip_if_not_installed("rpart")
   t = tsk("iris")
   po_cv =  po("learner_cv", learner = lrn("classif.rpart", predict_type = "prob"))
   res = po_cv$train(list(t))
@@ -17,6 +18,7 @@ test_that("threshold works for multiclass", {
 })
 
 test_that("threshold works for binary", {
+  skip_if_not_installed("rpart")
   t = tsk("pima")
   po_cv =  po("learner_cv", learner = lrn("classif.rpart", predict_type = "prob"))
   res = po_cv$train(list(t))
@@ -36,6 +38,7 @@ test_that("threshold works for binary", {
 })
 
 test_that("tunethreshold graph works", {
+  skip_if_not_installed("rpart")
 
   graph = po("learner_cv", lrn("classif.rpart", predict_type = "prob")) %>>% po("tunethreshold")
 
diff --git a/tests/testthat/test_pipeop_updatetarget.R b/tests/testthat/test_pipeop_updatetarget.R
index 484c78dc5..67f1425e4 100644
--- a/tests/testthat/test_pipeop_updatetarget.R
+++ b/tests/testthat/test_pipeop_updatetarget.R
@@ -85,6 +85,7 @@ test_that("rename target", {
 })
 
 test_that("update resample and predict_newdata", {
+  skip_if_not_installed("rpart")
   skip_on_cran()
   t = tsk("wine")
   pom = PipeOpUpdateTarget$new(param_vals = list(new_target_name = "type", new_task_type = "classif"))
diff --git a/tests/testthat/test_pipeop_yeojohnson.R b/tests/testthat/test_pipeop_yeojohnson.R
index 7fb2c29ac..78f79d23d 100644
--- a/tests/testthat/test_pipeop_yeojohnson.R
+++ b/tests/testthat/test_pipeop_yeojohnson.R
@@ -1,6 +1,7 @@
 context("PipeOpYeoJohnson")
 
 test_that("PipeOpYeoJohnson - general functionality", {
+  skip_if_not_installed("bestNormalize")
   task = mlr_tasks$get("iris")
   op = PipeOpYeoJohnson$new()
   expect_pipeop(op)
@@ -12,6 +13,7 @@ test_that("PipeOpYeoJohnson - general functionality", {
 })
 
 test_that("PipeOpYeoJohnson - receive expected result", {
+  skip_if_not_installed("bestNormalize")
   task = mlr_tasks$get("iris")
   op = PipeOpYeoJohnson$new(param_vals = list(standardize = FALSE))
   result = train_pipeop(op, inputs = list(task))
diff --git a/tests/testthat/test_po.R b/tests/testthat/test_po.R
index 3438330d3..f52ea538a 100644
--- a/tests/testthat/test_po.R
+++ b/tests/testthat/test_po.R
@@ -1,6 +1,7 @@
 context("mlr_pipeops")
 
 test_that("mlr_pipeops access works", {
+  skip_if_not_installed("rpart")
 
   expect_equal(po(), mlr_pipeops)
 
@@ -204,6 +205,7 @@ test_that("mlr_pipeops multi-access works", {
 })
 
 test_that("Incrementing ids works", {
+  skip_if_not_installed("rpart")
   x = po("pca_123")
   expect_true(x$id == "pca_123")
   expect_r6(x, "PipeOpPCA")
diff --git a/tests/testthat/test_ppl.R b/tests/testthat/test_ppl.R
index 9c88f868b..700eff726 100644
--- a/tests/testthat/test_ppl.R
+++ b/tests/testthat/test_ppl.R
@@ -59,6 +59,7 @@ test_that("mlr_pipeops multi-access works", {
 })
 
 test_that("mlr3book authors don't sleepwalk through life", {
+  skip_if_not_installed("rpart")
 
   tasks = tsks(c("breast_cancer", "sonar"))
 
diff --git a/tests/testthat/test_resample.R b/tests/testthat/test_resample.R
index ea8763385..bf165d298 100644
--- a/tests/testthat/test_resample.R
+++ b/tests/testthat/test_resample.R
@@ -1,6 +1,7 @@
 context("resample")
 
 test_that("PipeOp - Resample", {
+  skip_if_not_installed("rpart")
   task = mlr_tasks$get("iris")
   op1 = PipeOpScale$new()
   lrn = mlr_learners$get("classif.rpart")
diff --git a/tests/testthat/test_typecheck.R b/tests/testthat/test_typecheck.R
index fdd99966e..bb496c57a 100644
--- a/tests/testthat/test_typecheck.R
+++ b/tests/testthat/test_typecheck.R
@@ -2,6 +2,7 @@ context("Typecheck")
 
 
 test_that("utility function works", {
+  skip_if_not_installed("rpart")
   expect_equal(get_r6_inheritance("data.table"), NULL)
 
   expect_equal(get_r6_inheritance("PipeOp"), "PipeOp")
@@ -182,6 +183,7 @@ test_that("Autoconversion for pipeops works", {
 
 
 test_that("R6 inheritance inference works with packages that are not loaded", {
+  skip_if_not_installed("ranger")
   skip_if_not_installed("mlr3learners")
   skip_on_cran()
   library("mlr3learners")
diff --git a/tests/testthat/test_usecases.R b/tests/testthat/test_usecases.R
index 40117175b..aafb0ea65 100644
--- a/tests/testthat/test_usecases.R
+++ b/tests/testthat/test_usecases.R
@@ -19,6 +19,8 @@ test_graph = function(g, n_nodes, n_edges) {
 }
 
 test_that("linear: scale + pca + learn", {
+  skip_if_not_installed("rpart")
+  skip_if_not_installed("rpart")
   g = PipeOpScale$new() %>>% PipeOpPCA$new() %>>% PipeOpLrnRP
   z = test_graph(g, n_nodes = 3L, n_edges = 2L)
 
@@ -44,6 +46,7 @@ test_that("linear: scale + pca + learn", {
 })
 
 test_that("featureunion", {
+  skip_if_not_installed("rpart")
   g = gunion(list(PipeOpPCA$new(), PipeOpNOP$new())) %>>%
     PipeOpFeatureUnion$new(2L) %>>% PipeOpLrnRP
   z = test_graph(g, n_nodes = 4L, n_edges = 3L)
@@ -60,6 +63,8 @@ test_that("featureunion", {
 # FIXME: have a look at intermediate results in all usecase, we should expect some stuff there
 
 test_that("bagging", {
+  skip_if_not_installed("rpart")
+  skip_if_not_installed("rpart")
   g = pipeline_greplicate(PipeOpSubsample$new() %>>% PipeOpLrnRP, 2L) %>>% PipeOpClassifAvg$new(innum = 2L)
   g$pipeops$subsample_1$param_set$values$frac = .5
   g$pipeops$subsample_2$param_set$values$frac = .5
@@ -72,6 +77,8 @@ test_that("bagging", {
 
 
 test_that("branching", {
+  skip_if_not_installed("rpart")
+  skip_if_not_installed("rpart")
   # FIXME: are we REALLY sure that stuff here gets connected in the correct order?
   # i doubt that and this looks really bad and errorprone
   # b) we really want to have an associated order in the graph which is determined by
@@ -100,6 +107,8 @@ test_that("branching", {
 })
 
 test_that("branching with varargs", {
+  skip_if_not_installed("rpart")
+  skip_if_not_installed("rpart")
   g = PipeOpBranch$new(2L) %>>% gunion(list(PipeOpLrnRP, PipeOpLrnFL)) %>>% PipeOpUnbranch$new()
   z = test_graph(g, n_nodes = 4L, n_edges = 4L)
 
@@ -123,12 +132,14 @@ test_that("branching with varargs", {
 
 
 test_that("task chunking", {
+  skip_if_not_installed("rpart")
   g = PipeOpChunk$new(2L) %>>% pipeline_greplicate(PipeOpLrnRP, 2L) %>>% PipeOpClassifAvg$new(2L)
   z = test_graph(g, n_nodes = 4L, n_edges = 4L)
 })
 
 
 test_that("stacking", {
+  skip_if_not_installed("rpart")
   task = mlr_tasks$get("iris")
 
   lrn1 = mlr_learners$get("classif.rpart")