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dask - Scale Python data and compute workflows with Dask

Scales pandas, NumPy, and custom Python workflows across memory limits, cores, or clusters using Dask collections and schedulers.

Tags

Updated: 2026-10-03
Daskparallel computingdistributed computingpandasNumPyDataFramearray processingtask scheduling

Capabilities

Scale tabular data processingProcess blocked array computationsProcess unstructured recordsSubmit dependent tasks

Typical Inputs

Tabular data filesScientific array datasetsText, JSON, or log files

Typical Outputs

Computed DataFramesComputed arrays and valuesDistributed task results

What this skill does

  • Scale tabular data processing
  • Process blocked array computations
  • Process unstructured records
  • Submit dependent tasks
  • Select execution schedulers
  • Monitor distributed execution

Inputs

  • Tabular data files
  • Scientific array datasets
  • Text, JSON, or log files
  • Python task functions
  • Scheduler configuration
  • Cluster resources
  • Cloud storage credentials

Outputs

  • Computed DataFrames
  • Computed arrays and values
  • Distributed task results
  • Execution dashboard and diagnostics

Requirements

  • Python 3.10 or later
  • dask 2026.8.0
  • pandas 2 or later for DataFrames
  • PyArrow 16 or later for DataFrames
  • s3fs or gcsfs for cloud paths
  • dask.distributed for cluster deployment

Source

  • Spec: SKILL.md

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