issues: 206632333
This data as json
| id | node_id | number | title | user | state | locked | assignee | milestone | comments | created_at | updated_at | closed_at | author_association | active_lock_reason | draft | pull_request | body | reactions | performed_via_github_app | state_reason | repo | type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 206632333 | MDU6SXNzdWUyMDY2MzIzMzM= | 1257 | PERF: Add benchmarking? | 5635139 | closed | 0 | 9 | 2017-02-09T21:17:40Z | 2017-07-26T16:17:34Z | 2017-07-26T16:17:34Z | MEMBER | Because xarray is all python and generally not doing much compute itself (i.e. it marshals other libraries to do that), this hasn't been that important. IIRC most of the performance issues have arisen where xarray builds on (arguably) shaky foundations, like Though as we mature, is it worth adding some benchmarks? If so, what's a good way to do this? Pandas uses asv successfully. I don't have experience with https://github.com/ionelmc/pytest-benchmark but that could be a lower cost way of getting started. Any others? |
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completed | 13221727 | issue |