py35-dask (python/py-dask) Add to my watchlist

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: 2.6.0 License: BSD
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117 build(s) found

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Builder Build Number Start Time Elapsed Time Watcher Build Status
10.5_ppc 94323 2019-03-01 22:10:52 0:03:58 21851 build successful
10.12 85788 2019-03-01 22:00:10 0:02:50 21561 build successful
10.10 80995 2019-03-01 21:53:34 0:02:28 22616 build successful
10.13 51028 2019-03-01 21:48:41 0:02:30 13537 build successful
10.14 25000 2019-03-01 21:41:05 0:02:26 4247 build successful
10.11 80496 2019-03-01 21:36:55 0:02:23 22568 build successful
10.9 82926 2019-03-01 21:19:41 0:01:47 22561 build successful
10.5_ppc 92108 2019-02-01 14:46:26 0:03:40 21073 build successful
10.12 83758 2019-02-01 14:29:12 0:02:52 20783 build successful
10.10 78889 2019-02-01 14:02:35 0:02:09 21838 build successful
10.13 48905 2019-02-01 14:00:59 0:02:19 12759 build successful
10.11 78389 2019-02-01 13:46:23 0:01:58 21790 build successful
10.14 22815 2019-02-01 13:39:58 0:02:30 3468 build successful
10.9 80734 2019-02-01 13:13:36 0:01:29 21783 build successful
10.5_ppc 91170 2019-01-21 15:09:27 0:03:56 20776 build successful
10.5_ppc 86520 2018-12-04 22:31:22 0:03:09 19724 build successful
10.5_ppc 85814 2018-11-19 18:59:48 0:03:16 19451 build successful


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