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Vector array #16224

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@mattip mattip commented May 4, 2017

alt to #16193, appends to #16222
closes #15854

@chris-b1 comment from #16222 : This has the downside of introducing more manual memory management, but on the plus side removes the interim gil acquisition from some algos.

I couldn't figure out how to append to #16222, so I started another pull request, sorry, but added fixes (the missing data.m = data.n caused a segfault), more checks, and an improved test

FWIW, this allows PyPy to pass the hashtable tests

@mattip mattip force-pushed the vector-array branch 2 times, most recently from 8f3dd75 to e0e5321 Compare May 4, 2017 10:27
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mattip commented May 4, 2017

These changes require the factorize() function to use a local uniques vector, and not a class instance

EDIT: that approach did not work, try allowing multiple calls to to_array()

@jreback jreback mentioned this pull request May 4, 2017
@mattip mattip force-pushed the vector-array branch 2 times, most recently from e197f7c to f755c50 Compare May 4, 2017 21:38
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mattip commented May 5, 2017

There are too many edge cases. I will try another approach; adding the external_view_exists flag to the class without changing the underlying data storage strategy

@mattip mattip closed this May 5, 2017
@mattip mattip deleted the vector-array branch May 5, 2017 14:08
@jreback jreback added the Compat pandas objects compatability with Numpy or Python functions label May 6, 2017
@TomAugspurger TomAugspurger added this to the No action milestone May 27, 2017
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COMPAT: hashtable vectors depend on refcount semantics which do not work on PyPy
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