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  • Zac-HD · 2 ✖

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  • Automatic duck array testing - reductions · 2 ✖

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828924833 https://github.com/pydata/xarray/pull/4972#issuecomment-828924833 https://api.github.com/repos/pydata/xarray/issues/4972 MDEyOklzc3VlQ29tbWVudDgyODkyNDgzMw== Zac-HD 12229877 2021-04-29T04:03:39Z 2021-04-29T04:03:39Z CONTRIBUTOR

is there a way to separate sizes into dims and shape without using draw? I tried dims, shape = sizes.map(lambda s: tuple(zip(*s))), but since the map strategy is not iterable the final unpacking fails.

You've just got to use draw for this.

I'd prefer the verbose repr of st.builds() when debugging strategies, but if I know the strategy is correct and understand what it generates I'd probably prefer the smaller repr of @st.composite.

That's a good way of thinking about it :slightly_smiling_face: 

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   Automatic duck array testing - reductions 818059250
808736180 https://github.com/pydata/xarray/pull/4972#issuecomment-808736180 https://api.github.com/repos/pydata/xarray/issues/4972 MDEyOklzc3VlQ29tbWVudDgwODczNjE4MA== Zac-HD 12229877 2021-03-27T13:51:54Z 2021-03-27T13:51:54Z CONTRIBUTOR

Looking at https://github.com/keewis/xarray/compare/duckarray-tests...duckarray-tests-hypothesis, for high-level feedback:

  • Overall it looks pretty good; though ping me again if/when it's a PR and I'll do line-level feedback on idiom issues
  • A more general test would generate the shapes, and the axes to reduce over - reducing a 1D array over the first dimension is going to miss things
  • You use @st.composite when the .map() method and a lambda would suffice (though the perf gain is small enough that this is mostly a readability issue)
  • I don't see the point of Label, and we advise against mixing "a strategy or a value". We break this rule a few times for backwards-compatibility in our Numpy support, but wouldn't write such an API these days.

And I'm always delighted to see people using Hypothesis to test libraries that I use and love 🥰🤩

 
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   Automatic duck array testing - reductions 818059250

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