Paquet : python-dask-doc (1.0.0 dfsg-2)

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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

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dep: libjs-mathjax

JavaScript display engine for LaTeX and MathML
dep: libjs-sphinxdoc (>= 1.0)

prise en charge de JavaScript pour la documentation de Sphinx
dep: sphinx-rtd-theme-common (>= 0.4.2 dfsg)

sphinx theme from readthedocs.org (common files)

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