Merge branch 'main' into ajr-add-predict-types-issue-1281

Author: topepo

.Rbuildignore

@@ -22,3 +22,4 @@ derby.log
 ^vignettes/articles$
 ^[\.]?air\.toml$
 ^\.vscode$
+^[.]?air[.]toml$

.github/workflows/R-CMD-check.yaml

@@ -59,20 +59,19 @@ jobs:
           extra-packages: any::rcmdcheck
           needs: check
 
-      - name: Install reticulate
-        run: pak::pkg_install('reticulate')
+      - name: Install dev reticulate
+        run: pak::pkg_install('rstudio/reticulate')
         shell: Rscript {0}
 
-      - name: Install Miniconda
-        # conda can fail at downgrading python, so we specify python version in advance
-        env:
-          RETICULATE_MINICONDA_PYTHON_VERSION: "3.8"
-        run: reticulate::install_miniconda() # creates r-reticulate conda env by default
-        shell: Rscript {0}
+      - uses: actions/setup-python@v4
+        with:
+          python-version: 3.11
 
       - name: Install TensorFlow
         run: |
-          tensorflow::install_tensorflow(version='2.13', conda_python_version = NULL)
+          reticulate::virtualenv_create('r-reticulate', python='3.11')
+          reticulate::use_virtualenv('r-reticulate')
+          tensorflow::install_tensorflow(version='2.16')
         shell: Rscript {0}
 
       - uses: r-lib/actions/check-r-package@v2

.github/workflows/test-coverage.yaml

@@ -32,15 +32,14 @@ jobs:
         shell: Rscript {0}
 
       - name: Install Miniconda
-        # conda can fail at downgrading python, so we specify python version in advance
-        env:
-          RETICULATE_MINICONDA_PYTHON_VERSION: "3.8"
-        run: reticulate::install_miniconda() # creates r-reticulate conda env by default
+        run: |
+          reticulate::install_miniconda()
         shell: Rscript {0}
-
+ 
       - name: Install TensorFlow
         run: |
-          tensorflow::install_tensorflow(version='2.13', conda_python_version = NULL)
+          reticulate::conda_create('r-reticulate', packages = c('python==3.11'))
+          tensorflow::install_tensorflow(version='2.16')
         shell: Rscript {0}
 
       - name: Test coverage

.vscode/settings.json

@@ -2,5 +2,9 @@
     "[r]": {
         "editor.formatOnSave": true,
         "editor.defaultFormatter": "Posit.air-vscode"
+    },
+    "[quarto]": {
+        "editor.formatOnSave": true,
+        "editor.defaultFormatter": "quarto.quarto"
     }
 }

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: parsnip
 Title: A Common API to Modeling and Analysis Functions
-Version: 1.3.3.9000
+Version: 1.3.3.9001
 Authors@R: c(
     person("Max", "Kuhn", , "[email protected]", role = c("aut", "cre")),
     person("Davis", "Vaughan", , "[email protected]", role = "aut"),
@@ -71,7 +71,7 @@ Suggests:
 VignetteBuilder: 
     knitr
 ByteCompile: true
-Config/Needs/website: brulee, C50, dbarts, earth, glmnet, keras, kernlab,
+Config/Needs/website: brulee, C50, dbarts, earth, glmnet, grf, keras, kernlab,
     kknn, LiblineaR, mgcv, nnet, parsnip, quantreg, randomForest, ranger,
     rpart, rstanarm, tidymodels/tidymodels, tidyverse/tidytemplate,
     rstudio/reticulate, xgboost, rmarkdown
@@ -80,4 +80,4 @@ Config/testthat/edition: 3
 Encoding: UTF-8
 LazyData: true
 Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.3.2
+RoxygenNote: 7.3.3

NEWS.md

@@ -1,5 +1,18 @@
 # parsnip (development version)
 
+* Fixes issue with running predictions for Decision Trees in Spark (#1309)
+
+* Updates to some boosting tuning parameter information: (#1306)
+  - lightgbm and catboost have smaller default ranges for the learning rate: -3 to -1 / 2 in log10 units.
+  - lightgbm, xgboost, catboost, and C5.0 have smaller default ranges for the sampling proportion: 0.5 to 1.0.
+  - catboost engine arguments were added for `max_leaves` and `l2_leaf_reg`. 
+
+* Enable generalized random forest (`grf`) models for classification, regression, and quantile regression modes. (#1288)
+
+* `surv_reg()` is now defunct and will error if called. Please use `survival_reg()` instead (#1206).
+
+* Enable parsnip to work with xgboost version > 2.0.0.0. (#1227)
+
 # parsnip 1.3.3
 
 * Bug fix in how tunable parameters were configured for brulee neural networks. 

R/aaa-import-standalone-obj-type.R

@@ -89,12 +89,11 @@ obj_type_friendly <- function(x, value = TRUE) {
           typeof(x),
           logical = "`NA`",
           integer = "an integer `NA`",
-          double =
-            if (is.nan(x)) {
-              "`NaN`"
-            } else {
-              "a numeric `NA`"
-            },
+          double = if (is.nan(x)) {
+            "`NaN`"
+          } else {
+            "a numeric `NA`"
+          },
           complex = "a complex `NA`",
           character = "a character `NA`",
           .rlang_stop_unexpected_typeof(x)
@@ -296,14 +295,16 @@ obj_type_oo <- function(x) {
 #' @param ... Arguments passed to [abort()].
 #' @inheritParams args_error_context
 #' @noRd
-stop_input_type <- function(x,
-                            what,
-                            ...,
-                            allow_na = FALSE,
-                            allow_null = FALSE,
-                            show_value = TRUE,
-                            arg = caller_arg(x),
-                            call = caller_env()) {
+stop_input_type <- function(
+  x,
+  what,
+  ...,
+  allow_na = FALSE,
+  allow_null = FALSE,
+  show_value = TRUE,
+  arg = caller_arg(x),
+  call = caller_env()
+) {
   # From standalone-cli.R
   cli <- env_get_list(
     nms = c("format_arg", "format_code"),