{"categories":[{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/4"},{"label":"Database","url":"https://skillfed.io/packages/category/database/3"}],"enrichment":{"capability":"pylibcudf-cu12 provides Python bindings for libcudf, a CUDA C++ library that accelerates tabular data operations on NVIDIA GPUs using Apache Arrow data structures.","skillfed_tags":["gpu-acceleration","cuda","rapids"],"use_cases":["Building custom GPU-accelerated data processing pipelines that need direct access to libcudf algorithms.","Integrating GPU tabular operations into Spark via Spark RAPIDS or other distributed computing frameworks.","Developing specialized data transformations where cudf's high-level API is insufficient.","Creating GPU-native SQL engines or query processors that execute on tabular data.","Accelerating ETL workflows for large datasets on systems with NVIDIA GPUs and CUDA 12."],"what_it_does":"pylibcudf-cu12 is a low-level Python binding layer for libcudf, the core CUDA C++ library in RAPIDS that implements GPU-accelerated tabular data operations. It exposes libcudf's Arrow-compliant data structures and algorithms to Python via Cython, serving as the foundation for higher-level RAPIDS libraries like cudf and dask-cudf.\n\nThis package is designed for developers building GPU-accelerated data processing applications. It requires a CUDA 12 environment and compatible NVIDIA GPU hardware. The package has four runtime dependencies: libcudf-cu12 (the C++ library itself), cuda-bindings, rmm-cu12 (RAPIDS memory manager), and nvtx (NVIDIA tracing tools). Most users interact with pylibcudf indirectly through cudf's pandas-like API or cudf.pandas, which provides a zero-code-change accelerator for existing pandas code.","worth_installing":"Yes, if you have an NVIDIA GPU with CUDA 12 and need GPU-accelerated tabular data processing. Install it as a dependency of cudf or higher-level RAPIDS libraries rather than directly unless you need low-level libcudf access. Active maintenance, no known vulnerabilities, and permissive Apache 2.0 license make it production-ready. Medium install friction is expected given the specialized CUDA runtime requirements."},"id":"pylibcudf-cu12","links":{"html":"https://skillfed.io/packages/pylibcudf-cu12","md":"https://skillfed.io/packages/pylibcudf-cu12.md","pypi":"https://pypi.org/project/pylibcudf-cu12/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-06","license_spdx":"Apache-2.0","license_treatment":"permissive","name":"pylibcudf-cu12","python_support":"supports_current","summary":"pylibcudf - Python bindings for libcudf"},"popularity":{"monthly_downloads":410959,"position":6861,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"26.8.0"}