`libcudf-cu12` is the underlying C++ library for cuDF, a GPU-accelerated DataFrame library for Python, part of the NVIDIA RAPIDS ecosystem. It enables pandas-like data manipulation directly on the GPU, leveraging CUDA for high performance. This PyPI meta-package primarily serves as a runtime dependency that transitively pulls in the Python `cudf-cu12` package. cuDF follows a rapid monthly release cadence (YYYY.MM.patch), consistently introducing new features and breaking changes. The current stable version is `26.4.0`.
pip install libcudf-cu12Verified import paths — ran on the pinned version, not inferred.
This quickstart demonstrates how to create a basic cuDF DataFrame and perform a simple aggregation, showcasing its pandas-like API for GPU data manipulation.
Thoroughly review release notes on the GitHub repository (`github.com/rapidsai/cudf/releases`) for specific version updates and migration guides. Pin exact versions of `cudf-cuXX` and its core dependencies (`cupy-cudaXX`, `pyarrow`) to ensure stability.
Always ensure `pyarrow` and `cupy-cudaXX` versions precisely match the `cudf-cuXX` requirements specified in the `cudf` documentation, PyPI dependencies, or `conda` environment. Use `pip show cudf-cu12` to inspect required distributions.
Migrate your code to use the recommended alternative APIs as documented in the official cuDF documentation or detailed in the respective release notes. Avoid using experimental or preview features in production without careful testing.