[docs] [R-package] mention {bonsai} in the docs (#5652)

R-package/README.md

@@ -484,13 +484,6 @@ These tests can also be triggered on any pull request by leaving a comment in a
 
 > /gha run r-valgrind
 
-External (Unofficial) Repositories
-----------------------------------
-
-Projects listed here are not maintained or endorsed by the `LightGBM` development team, but may offer some features currently missing from the main R package.
-
-* [lightgbm.py](https://github.com/kapsner/lightgbm.py): This R package offers a wrapper built with `reticulate`, a package used to call Python code from R. If you are comfortable with the added installation complexity of installing `lightgbm`'s Python package and the performance cost of passing data between R and Python, you might find that this package offers some features that are not yet available in the native `lightgbm` R package.
-
 Known Issues
 ------------
 

R-package/cran-comments.md

@@ -59,7 +59,7 @@ Accepted to CRAN
 
 Submitted with the following comment:
 
-> This submission contains {lightgbm} 3.3.3.
+> This submission contains {lightgbm} 3.3.4
 
 > Per CRAN's policies, I am submitting it on behalf of the project's maintainer (Yu Shi), with his permission.
 

README.md

@@ -61,6 +61,9 @@ Some old update logs are available at [Key Events](https://github.com/microsoft/
 External (Unofficial) Repositories
 ----------------------------------
 
+Projects listed here offer alternative ways to use LightGBM.
+They are not maintained or officially endorsed by the `LightGBM` development team.
+
 FLAML (AutoML library for hyperparameter optimization): https://github.com/microsoft/FLAML
 
 Optuna (hyperparameter optimization framework): https://github.com/optuna/optuna
@@ -115,7 +118,7 @@ lightgbm-rs (Rust binding): https://github.com/vaaaaanquish/lightgbm-rs
 
 MLflow (experiment tracking, model monitoring framework): https://github.com/mlflow/mlflow
 
-`{treesnip}` (R `{parsnip}`-compliant interface): https://github.com/curso-r/treesnip
+`{bonsai}` (R `{parsnip}`-compliant interface): https://github.com/tidymodels/bonsai
 
 `{mlr3extralearners}` (R `{mlr3}`-compliant interface): https://github.com/mlr-org/mlr3extralearners