[Numpy-discussion] test code for user defined types in numpy

Charles R Harris charlesr.harris at gmail.com
Wed Dec 21 07:56:36 EST 2011


Hi Geoffrey,

On Tue, Dec 20, 2011 at 7:24 PM, Geoffrey Irving <irving at naml.us> wrote:

> Hello,
>
> As a followup to the prior thread on bugs in user defined types in
> numpy, I converted my rational number class from C++ to C and switched
> to 32 bits to remove the need for unportable 128 bit numbers.  It
> should be usable as a fairly thorough test case for user defined types
> now.  It does rather more than a minimal test case would need to do,
> but that isn't a problem unless you're concerned about code size.  Let
> me know if any further changes are needed before it's suitable for
> inclusion in numpy as a test case.  The repository is here:
>
>    https://github.com/girving/rational
>
> The tests run under either py.test or nose.
>
> For completeness, my branch fixing all but one of the bugs I found in
> numpy user defined types is here:
>
>    https://github.com/girving/numpy/tree/fixuserloops
>
> The remaining bug is that numpy incorrectly releases the GIL during
> casts even though NPY_NEEDS_API is set.  The resulting crash goes away
> if the line defining ACQUIRE_GIL is uncommented.  With the necessary
> locks in place, all my tests pass with my branch of numpy.  I haven't
> tracked this one down and fixed it yet, but it shouldn't be hard to do
> so.
>
>
A few preliminary comments on the C code (since I can't comment directly on
github)

1) The C++ style comments aren't portable.

2) The trailing comments would (IMHO) look better on the line above.

3) The inline keyword isn't portable, use NPY_INLINE instead.

4) We've mostly used the

    int
    foo(void)
    {
    }

style of function definition.

5) And for if statements

    if (is_toohot) {
        change_seats();
    }
    else if (is_toocold) {
        change_seats();
    }
    else {
        eat_cereal();
    }

6) Because Python assert disappears in release code, the tests need to use
assert_(...) imported from numpy.testing

Chuck
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