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Minimal task scheduling abstraction.Dask provides multi-core execution on larger-than-memory datasets using blocked algorithms and task scheduling. It maps high-level NumPy, Pandas, and list operations on large datasets on to many operations on small in-memory datasets. It then executes these graphs in parallel on a single machine. Dask lets us use traditional NumPy, Pandas, and list programming while operating on inconveniently large data in a small amount of space.
Version: 1.2.2 License: BSD84 build(s) found
| Builder | Build Number | Start Time | Elapsed Time | Watcher | Build Status |
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| 12.arm64 | 3547 | 2021-11-03 14:47:29 | 0:00:41 | 228 | build successful |
| 10.15 | 8981 | 2019-12-03 0:26:21 | 0:02:27 | 1042 | build successful |
| 10.6.x86_64 | 9556 | 2019-11-20 17:38:57 | 0:01:50 | 2014 | build successful |
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| 10.10 | 90397 | 2019-07-10 21:31:34 | 0:09:49 | 25976 | build successful |
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| 10.5_ppc | 95012 | 2019-03-11 17:03:34 | 0:04:45 | 22086 | build successful |
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| 10.5_ppc | 91161 | 2019-01-21 14:36:46 | 0:05:02 | 20776 | build successful |
| 10.5_ppc | 86507 | 2018-12-04 21:48:58 | 0:03:29 | 19724 | build successful |
| 10.5_ppc | 85784 | 2018-11-19 16:42:23 | 0:03:35 | 19451 | build successful |