{"library":"rapids-dask-dependency","title":"RAPIDS Dask Dependency Pinning","description":"rapids-dask-dependency is a meta-package within the RAPIDS ecosystem that pins compatible versions of Dask and Distributed for a specific RAPIDS release. Its primary function is to ensure that users working with RAPIDS libraries like cuDF and Dask-cuDF have a consistent and stable Dask environment, preventing common version mismatch issues. It aligns with the RAPIDS release cadence, currently at version 26.4.0.","language":"python","status":"active","last_verified":"Thu Apr 16","install":{"commands":["pip install rapids-dask-dependency==26.4.0"],"cli":null},"imports":[],"auth":{"required":false,"env_vars":[]},"quickstart":{"code":"# This package doesn't provide direct Python imports for functionality.\n# Its purpose is to ensure compatible Dask/Distributed versions are installed.\n# You install it to set up your environment *before* using Dask with RAPIDS.\n#\n# After installing, you can then import Dask components, which will be\n# the versions specified by rapids-dask-dependency:\n\n# Example of using Dask after installation:\nimport dask.array as da\nimport dask.dataframe as dd\nfrom dask.distributed import Client\n\n# This code will now run with Dask/Distributed versions compatible\n# with the 26.04 RAPIDS release.\n\n# client = Client()\n# print(client)\n# client.close()\n\nprint(f\"Dask Array imported successfully: {da.__version__}\")\nprint(f\"Dask DataFrame imported successfully: {dd.__version__}\")\n# print(f\"Dask Distributed imported successfully: {Client.__module__}\")","lang":"python","description":"rapids-dask-dependency is installed to manage your environment, not imported for direct use. The quickstart shows how to install it to ensure compatible Dask/Distributed versions are present, which then allows you to seamlessly use Dask with other RAPIDS libraries.","tag":null,"tag_description":null,"last_tested":null,"results":[]},"compatibility":null}