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- NVIDIA/cudf
- 최근 소스 활동
- 2026년 3월 24일 23:14
- 감지된 SKILL.md 언어
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설치 방법
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소스 파일 검토
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
메뉴
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/NVIDIA/cudf --skill build-test-cudf명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.
SOC 직업 분류 기준
SKILL.md 표시 중
| name | build-test-cudf |
| description | Use this skill to build and test code changes inside a cudf devcontainer. |
Detect cudf devcontainer usage by checking if the username is coder. If not, ignore everything else in this file and skip.
cudf packages must be built in this order as needed (each depends on the previous):
.pyx files)When rebuilding a package, ensure its dependencies are already built. Since we are in cudf devcontainer, DO NOT run the build.sh script or install any packages yourself. Instead, always use the build-*, test-*, rapids-*, clean-* scripts located at /usr/bin.
Whenever building libcudf from scratch (CMake has not been run before), run:
build-cudf-cpp -j0
For incremental builds, you can also just navigate to cpp/build/latest and run:
ninja
Both build-cudf-cpp and configure-cudf-cpp accept CMake -D options directly as arguments. See cpp/CMakeLists.txt for a full list of available CMake options
# Default option
build-cudf-cpp -j0 -DBUILD_BENCHMARKS=ON
# Multiple options can be combined
build-cudf-cpp -j0 -DBUILD_BENCHMARKS=ON -DBUILD_TESTS=OFF
Similarly, configure without building:
configure-cudf-cpp -DBUILD_BENCHMARKS=ON
build-libcudf-python
build-pylibcudf-python
build-cudf-python # cudf-python
build-cudf-polars-python # cudf-polars
Similar to build instructions, we can use clean-cudf-xxx scripts also located at /usr/bin. Use clean-cudf to clean everything.
If there are build errors, cleaning before building will usually resolve problems. If we run into a fatal CMake error while building libcudf indicating packages/version mismatch, update the environment using the following script. If the error persists, use --force flag with the script
rapids-make-${PYTHON_PACKAGE_MANAGER}-env
Make sure to run clean-cudf after running this for a fresh subsequent build.
Make sure that libcudf has been built before running any of these. Discover all Google test name binaries at cpp/build/latest/gtests and run relevant Google tests using test-cudf-xxx script located at /usr/bin.
test-cudf-cpp -j10 # all tests 10 parallel jobs
test-cudf-cpp -R <NAME>_TEST # specific test suite
cd cpp/build/latest/gtests && <NAME>_TEST --gtest_filter="<pattern>" # Run tests matching the <pattern> from the <NAME>_TEST
These instructions are applicable for running tests for pylibcudf and high-level python packages. Make sure that the package has been built before running its pytests. Pylibcudf tests can be discovered at: python/pylibcudf/tests and subfolders. Run them using:
pytest python/pylibcudf/tests/<subfolder>/test_<name>.py # specific pylibcudf test suite
cudf-python pytests can be discovered at: python/cudf/cudf/tests and subfolders. Run them using:
test-cudf-python # run all cudf-python Pytests
pytest python/cudf/cudf/tests/<subfolder>/test_<name>.py # specific cudf-python test suite
Similarly, cudf-polars pytests can be discovered at: python/cudf_polars/tests and subfolders. Run them using:
test-cudf-polars-python