{"id":21097,"library":"dask-cudf-cu12","title":"dask-cudf-cu12","description":"Utilities for integrating Dask with cuDF on CUDA 12.x. This package provides the distributed DataFrame functionality backed by cuDF, leveraging cuDF's GPU-accelerated columnar operations. Version 26.4.0 requires Python >=3.11 and is part of the RAPIDS 26.04 release. Releases follow a quarterly cadence aligned with RAPIDS.","status":"active","version":"26.4.0","language":"python","source_language":"en","source_url":"https://github.com/rapidsai/cudf","tags":["rapids","cuda","gpu","dataframe","dask","distributed","cuDF"],"install":[{"cmd":"pip install dask-cudf-cu12","lang":"bash","label":"PyPI install"},{"cmd":"conda install -c rapidsai -c conda-forge dask-cudf-cu12","lang":"bash","label":"Conda install"}],"dependencies":[{"reason":"Core cuDF library required for GPU DataFrames","package":"cudf-cu12","optional":false},{"reason":"Dask distributed scheduling and DataFrame API","package":"dask","optional":false},{"reason":"GPU-backed array operations for cuDF","package":"cupy-cuda12x","optional":false}],"imports":[{"note":"","symbol":"dask_cudf","correct":"import dask_cudf"},{"note":"cudf.DataFrame is local GPU DataFrame, not distributed.","wrong":"from cudf import DataFrame","symbol":"DataFrame","correct":"from dask_cudf import DataFrame"}],"quickstart":{"code":"import dask_cudf\nimport cudf\n\n# Create a cuDF Series and then a dask_cudf DataFrame\ndf_cudf = cudf.DataFrame({'a': [1, 2, 3], 'b': [4, 5, 6]})\nddf = dask_cudf.from_cudf(df_cudf, npartitions=2)\nprint(ddf.compute())","lang":"python","description":"Creates a dask_cudf DataFrame from a cuDF DataFrame and computes the result."},"warnings":[{"fix":"Check your CUDA version with nvidia-smi. Install dask-cudf-cu12 if CUDA >=12.0, otherwise dask-cudf.","message":"dask-cudf-cu12 is CUDA 12.x only. Use dask-cudf for CUDA 11.x or older. Installing the wrong variant for your CUDA version will cause import errors.","severity":"breaking","affected_versions":"all"},{"fix":"Replace df.apply_chunks(func, ...) with df.map_partitions(func). For grouped operations, use groupby_obj.apply(func, meta=...).","message":"DataFrame.apply_chunks and Groupby.apply_grouped have been removed since v25.12.00. Use map_partitions or groupby.apply instead.","severity":"deprecated","affected_versions":">=25.12.00"},{"fix":"Use separate conda environments for CUDA 11.x and 12.x, or pip install only the correct variant.","message":"Conda environment with both dask-cudf-cu12 and dask-cudf leads to import confusion. Pip similarly can mix packages. Only one variant should be installed.","severity":"gotcha","affected_versions":"all"},{"fix":"Use npartitions parameter explicitly: dask_cudf.from_cudf(df, npartitions=len(gpu_devices)).","message":"dask_cudf.from_cudf() does not automatically repartition data. If the source cuDF DataFrame has too few rows, Dask may underutilize GPUs.","severity":"gotcha","affected_versions":"all"}],"env_vars":null,"last_verified":"2026-04-27T00:00:00.000Z","next_check":"2026-07-26T00:00:00.000Z","problems":[{"fix":"pip install dask-cudf-cu12 (for CUDA 12.x) or pip install dask-cudf (for CUDA 11.x).","cause":"Package not installed or wrong variant installed.","error":"ModuleNotFoundError: No module named 'dask_cudf'"},{"fix":"Upgrade packages: pip install --upgrade dask-cudf-cu12 cudf-cu12","cause":"Old or mismatched version of dask-cudf/cudf.","error":"AttributeError: module 'dask_cudf' has no attribute 'from_cudf'"}],"ecosystem":"pypi","meta_description":null,"install_score":null,"install_tag":null,"quickstart_score":null,"quickstart_tag":null}