Enable r-universe build. (dmlc#11365)

Author: trivialfis

R-package/LICENSE

@@ -0,0 +1,36 @@
+## Script used to bootstrap R-universe build.
+
+## Execute git commands to initialize git submodules
+system("git submodule init")
+system("git submodule update")
+
+## core
+file.copy("../src", "./src/", recursive = TRUE)
+file.copy("../include", "./src/", recursive = TRUE)
+file.copy("../amalgamation", "./src/", recursive = TRUE)
+
+## dmlc-core
+dir.create("./src/dmlc-core")
+file.copy("../dmlc-core/include", "./src/dmlc-core/", recursive = TRUE)
+file.copy("../dmlc-core/src", "./src/dmlc-core/", recursive = TRUE)
+
+pkgroot <- function(path) {
+  ## read the file from path, replace the PKGROOT=../../ with PKGROOT=.
+  lines <- readLines(path)
+  lines <- gsub("PKGROOT=../../", "PKGROOT=.", lines, fixed = TRUE)
+  writeLines(lines, path)
+}
+
+## makefile and license
+file.copy("../LICENSE", "./LICENSE")
+pkgroot("./src/Makevars.in")
+pkgroot("./src/Makevars.win.in")
+
+## misc
+path <- file.path("remove_warning_suppression_pragma.sh")
+file.remove(path)
+path <- file.path("CMakeLists.txt")
+file.remove(path)
+
+## remove the directory recursively ./tests/helper_scripts
+unlink("tests/helper_scripts", recursive = TRUE)

R-package/bootstrap.R

@@ -17,9 +17,16 @@ You have found the XGBoost R Package!
 Get Started
 ***********
 
-* Checkout the :doc:`Installation Guide </install>` contains instructions to install xgboost, and :doc:`Tutorials </tutorials/index>` for examples on how to use XGBoost for various tasks.
-* Read the latest `API documentation <../r_docs/R-package/docs/reference/index.html>`__ . This might refer to a newer version than the one on CRAN.
-* Read the `CRAN documentation <https://cran.r-project.org/web/packages/xgboost/xgboost.pdf>`_.
+Since XGBoost 3.0.0, the latest R package is available on
+`https://dmlc.r-universe.dev/builds <R-universe>`__ while the one on CRAN is kept at an
+older version. We will work on helping the CRAN version to catch up in the future. In the
+meantime, please use R-universe packages.
+
+* Check out the :doc:`Installation Guide </install>` for instructions on how to install
+  xgboost, and :doc:`Tutorials </tutorials/index>` for examples on how to use XGBoost for
+  various tasks.
+* Read the latest `API documentation <../r_docs/R-package/docs/reference/index.html>`__.
+* Read the `CRAN documentation <https://cran.r-project.org/web/packages/xgboost/xgboost.pdf>`_. (outdated)
 
 *********
 Vignettes

doc/R-package/index.rst

@@ -127,22 +127,22 @@ Visit the `Miniconda website <https://docs.conda.io/en/latest/miniconda.html>`_
 R
 -
 
-* From CRAN:
+* From R Universe
 
-  .. code-block:: R
+.. code-block:: R
 
-    install.packages("xgboost")
+    install.packages('xgboost', repos = c('https://dmlc.r-universe.dev', 'https://cloud.r-project.org'))
 
-  .. note:: Using all CPU cores (threads) on Mac OSX
+.. note:: Using all CPU cores (threads) on Mac OSX
 
-     If you are using Mac OSX, you should first install OpenMP library (``libomp``) by running
+   If you are using Mac OSX, you should first install OpenMP library (``libomp``) by running
 
-     .. code-block:: bash
+   .. code-block:: bash
 
         brew install libomp
 
-     and then run ``install.packages("xgboost")``. Without OpenMP, XGBoost will only use a
-     single CPU core, leading to suboptimal training speed.
+   and then run ``install.packages("xgboost")``. Without OpenMP, XGBoost will only use a
+   single CPU core, leading to suboptimal training speed.
 
 * We also provide **experimental** pre-built binary with GPU support. With this binary,
   you will be able to use the GPU algorithm without building XGBoost from the source.
@@ -158,6 +158,30 @@ R
     # Install XGBoost
     R CMD INSTALL ./xgboost_r_gpu_linux.tar.gz
 
+
+* From CRAN (outdated):
+
+.. warning::
+
+    We are working on bringing the CRAN version of XGBoost up-to-date, in the meantime,
+    please use packages from the R-universe.
+
+
+.. code-block:: R
+
+    install.packages("xgboost")
+
+.. note:: Using all CPU cores (threads) on Mac OSX
+
+   If you are using Mac OSX, you should first install OpenMP library (``libomp``) by running
+
+   .. code-block:: bash
+
+        brew install libomp
+
+   and then run ``install.packages("xgboost")``. Without OpenMP, XGBoost will only use a
+   single CPU core, leading to suboptimal training speed.
+
 JVM
 ---