py312-dask (python/py-dask) Updated: 11 months, 1 week ago 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: 2024.4.1 License: BSD
GitHub
17 build(s) found
| Builder | Build Number | Start Time | Elapsed Time | Watcher | Build Status |
|---|---|---|---|---|---|
| 10.6 | 160264 | 2024-04-08 11:42:55 | 0:01:11 | 57099 | build successful |
| 10.6.x86_64 | 196007 | 2024-04-08 11:42:36 | 0:01:07 | 57146 | build successful |
| 10.11 | 257914 | 2024-04-08 11:42:01 | 0:01:28 | 84572 | build successful |
| 10.7 | 183691 | 2024-04-08 11:41:32 | 0:00:49 | 56874 | build successful |
| 10.15 | 178282 | 2024-04-08 11:41:06 | 0:01:10 | 55153 | build successful |
| 11 | 149161 | 2024-04-08 11:40:11 | 0:01:27 | 45081 | build successful |
| 10.8 | 171029 | 2024-04-08 11:39:51 | 0:00:50 | 54935 | build successful |
| 10.12 | 267317 | 2024-04-08 11:39:25 | 0:01:01 | 83352 | build successful |
| 10.10 | 262943 | 2024-04-08 11:39:02 | 0:00:41 | 84462 | build successful |
| 10.13 | 227128 | 2024-04-08 11:38:42 | 0:00:50 | 75409 | build successful |
| 14.arm64 | 23166 | 2024-04-08 11:38:23 | 0:00:55 | 7626 | build successful |
| 14 | 34655 | 2024-04-08 11:37:46 | 0:02:34 | 7950 | build successful |
| 10.6 | 158164 | 2024-03-22 7:28:25 | 0:01:21 | 56427 | build successful |
| 10.12 | 265337 | 2024-03-22 7:28:04 | 0:01:16 | 82682 | build successful |
| 10.9 | 268111 | 2024-03-22 7:27:42 | 0:01:19 | 83473 | build successful |
| 10.6.x86_64 | 186717 | 2024-01-25 2:01:46 | 0:00:38 | 54243 | build successful |
| 10.6 | 151262 | 2024-01-25 1:59:50 | 0:00:59 | 54198 | build successful |