add R CMD check

Author: mwien

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

@@ -0,0 +1,51 @@
+# Workflow derived from https://github.com/r-lib/actions/tree/v2/examples
+# Need help debugging build failures? Start at https://github.com/r-lib/actions#where-to-find-help
+on:
+  workflow_dispatch:
+
+name: R-CMD-check.yaml
+
+permissions: read-all
+
+jobs:
+  R-CMD-check:
+    runs-on: ${{ matrix.config.os }}
+
+    name: ${{ matrix.config.os }} (${{ matrix.config.r }})
+
+    strategy:
+      fail-fast: false
+      matrix:
+        config:
+          - {os: macos-latest,   r: 'release'}
+          - {os: windows-latest, r: 'release'}
+          - {os: ubuntu-latest,   r: 'devel', http-user-agent: 'release'}
+          - {os: ubuntu-latest,   r: 'release'}
+          - {os: ubuntu-latest,   r: 'oldrel-1'}
+
+    env:
+      GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
+      R_KEEP_PKG_SOURCE: yes
+
+    steps:
+      - uses: actions/checkout@v4
+
+      - uses: r-lib/actions/setup-pandoc@v2
+
+      - uses: r-lib/actions/setup-r@v2
+        with:
+          r-version: ${{ matrix.config.r }}
+          http-user-agent: ${{ matrix.config.http-user-agent }}
+          use-public-rspm: true
+
+      - uses: r-lib/actions/setup-r-dependencies@v2
+        with:
+          extra-packages: any::rcmdcheck
+          needs: check
+          working-directory: 'flop_r'
+
+      - uses: r-lib/actions/check-r-package@v2
+        with:
+          upload-snapshots: true
+          build_args: 'c("--no-manual","--compact-vignettes=gs+qpdf")'
+          working-directory: 'flop_r'

flop_r/.Rbuildignore

@@ -4,3 +4,4 @@
 ^src/Makevars$
 ^src/Makevars\.win$
 ^README\.Rmd$
+^\.github$

flop_r/README.Rmd

@@ -16,6 +16,7 @@ knitr::opts_chunk$set(
 # flopsearch
 
 <!-- badges: start -->
+[![R-CMD-check](https://github.com/CausalDisco/flop/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/CausalDisco/flop/actions/workflows/R-CMD-check.yaml)
 <!-- badges: end -->
 
 flopsearch provides an effective and easy-to-use causal discovery algorithm for linear additive noise models.