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'''Dask''' is an open source library for [[parallel computing]] written in [[Python (programming language)|Python]].<ref>{{cite book |last=Daniel |first=Jesse C. |year=2019 |title=Data Science at Scale with Python and Dask |publisher=Manning Publications |isbn=9781617295607}}</ref><ref>{{cite journal |last1=Rocklin |first1=Matthew |title=Dask: Parallel Computation with Blocked algorithms and Task Scheduling |journal=Proceedings of the 14th Python in Science Conference |date=2015 |pages=126–132 |doi=10.25080/Majora-7b98e3ed-013 |url=https://conference.scipy.org/proceedings/scipy2015/matthew_rocklin.html}}</ref> Originally developed by Matthew Rocklin, Dask is a community project maintained and sponsored by developers and organizations. |
'''Dask''' is an open source library for [[parallel computing]] written in [[Python (programming language)|Python]].<ref>{{cite book |last=Daniel |first=Jesse C. |year=2019 |title=Data Science at Scale with Python and Dask |publisher=Manning Publications |isbn=9781617295607}}</ref><ref>{{cite journal |last1=Rocklin |first1=Matthew |title=Dask: Parallel Computation with Blocked algorithms and Task Scheduling |journal=Proceedings of the 14th Python in Science Conference |date=2015 |pages=126–132 |doi=10.25080/Majora-7b98e3ed-013 |url=https://conference.scipy.org/proceedings/scipy2015/matthew_rocklin.html}}</ref> Originally developed by Matthew Rocklin, Dask is a community project maintained and sponsored by developers and organizations. |
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Revision as of 18:53, 31 March 2020
| Original author(s) | Matthew Rocklin |
|---|---|
| Developer(s) | Dask |
| Initial release | October 28, 2018 |
| Stable release | 2.13.0
/ March 25, 2020 |
| Repository | Dask Repository |
| Written in | Python[1] |
| Operating system | Linux, Microsoft Windows, macOS |
| Available in | Python |
| Type | Data analytics |
| License | New BSD |
| Website | dask |
Dask is an open source library for parallel computing written in Python.[2][3] Originally developed by Matthew Rocklin, Dask is a community project maintained and sponsored by developers and organizations.
Overview
Dask is a library composed of two parts. It includes a task scheduling component for building dependency graphs and scheduling tasks. Second, it includes the distributed data structures with APIs similar to Pandas Dataframes or NumPy arrays. Dask has a variety of use cases and can be run with a single node and scale to thousand node clusters.[4]
References
- ^ "Dask: Parallel Computation with Blocked algorithms and Task Scheduling" (PDF).
This paper introduces dask, a specification to encode parallel algorithms, using primitive Python dictionaries, tuples, and callables.
- ^ Daniel, Jesse C. (2019). Data Science at Scale with Python and Dask. Manning Publications. ISBN 9781617295607.
- ^ Rocklin, Matthew (2015). "Dask: Parallel Computation with Blocked algorithms and Task Scheduling". Proceedings of the 14th Python in Science Conference: 126–132. doi:10.25080/Majora-7b98e3ed-013.
- ^ https://docs.dask.org/en/latest/
External links
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