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Documentation related to python-dask-doc
Description: Minimal task scheduling abstraction documentation
Dask is a flexible parallel computing library for analytics,
containing two components.
1. Dynamic task scheduling optimized for computation. This is similar
to Airflow, Luigi, Celery, or Make, but optimized for interactive
computational workloads.
2. "Big Data" collections like parallel arrays, dataframes, and lists
that extend common interfaces like NumPy, Pandas, or Python iterators
to larger-than-memory or distributed environments. These parallel
collections run on top of the dynamic task schedulers.
This contains the documentation
Homepage: https://github.com/dask/dask
copyright | Debian changelog
Other documents:
Other packages built from the same source: