issue_comments: 278788467
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| html_url | issue_url | id | node_id | user | created_at | updated_at | author_association | body | reactions | performed_via_github_app | issue |
|---|---|---|---|---|---|---|---|---|---|---|---|
| https://github.com/pydata/xarray/issues/1257#issuecomment-278788467 | https://api.github.com/repos/pydata/xarray/issues/1257 | 278788467 | MDEyOklzc3VlQ29tbWVudDI3ODc4ODQ2Nw== | 1217238 | 2017-02-09T22:02:00Z | 2017-02-09T22:02:00Z | MEMBER | Yes, some sort of automated benchmarking could be valuable, especially for noticing and fixing regressions. I've done occasional benchmarks before to optimize bottlenecks (e.g., class constructors) but it's all been ad-hoc stuff with ASV seems like a pretty sane way to do this. pytest-benchmark can trigger test failures if performance goes below some set level but I suspect performance is too subjective and stochastic to be reliable. |
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