Application overview
Dask provides APIs for parallel task execution and collections. Distributed deployment needs suitable cluster resources and a deployment integration; a local package install alone does not configure a cluster.
Typical use cases
Parallel Python data and task workflows.
HPC compatibility
Compatibility details shown here reflect administrator-maintained project information. Review the upstream release documentation against your exact operating system, drivers, accelerator, MPI stack, and cluster policy before deployment.
GPU compatibility is not specified in this directory record.
Installation instructions
Commands are project-specific notes. Confirm prerequisites and linked upstream instructions for your own release and system. Do not run administrative commands without review.
Install Dask with complete extras
Prerequisites: Python 3 and venv; complete extras install multiple dependencies
python -m venv .venv
# Linux / macOS: source .venv/bin/activate
# Windows PowerShell: .venv\Scripts\Activate.ps1
python -m pip install --upgrade pip
python -m pip install "dask[complete]"Creates an isolated environment and installs Dask plus its documented optional collection dependencies.
Verify: python -c "import dask; print(dask.__version__)"
Review: The complete extra can download many dependencies. For clusters, configure a scheduler/deployment integration separately.
Documentation for these steps ↗Upstream references
- Project homepage ↗
- Source repository ↗ Link status: Verified
- Documentation ↗
- Download / package page ↗
Link details last reviewed 2026-10-12 by MCR Tech. Project versions, licenses, hardware behavior, and hosted model access can change; follow current upstream terms.
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