Thanks Maciej, Matti! That was really helpful! Could you please point me to the place where I could find overview of numpypy architecture? (if it exists) I got some vision after looking at the code. I would be grateful if someone says if it’s correct. -Implementation of numpy for pypy is splitted into two parts: micronumpy and numpypy -micronumpy is implementation of basic concepts of numpy inside pypy. Source code is in https://bitbucket.org/pypy/pypy/ ->pypy/module/micronumpy. --micronumpy is compiled together with pypy itself and cannot be compiled separately. --micronumpy uses timsort instead of quicksort in original numpy -numpypy implements the rest of the library (not everything is implemented yet). Source code is in https://bitbucket.org/pypy/numpypy. This module must be installed manually. --numpypy uses basic entities from micronumpy --Source code of numpypy contains source codes of numpy with a bunch of fixes. Code is partially unused because versions from micronumpy is used instead. Looking at the code is the only way to find out which part of the code is used. Also I have a couple of naive questions about pypy in general. I investigated very little here. Feel free to skip. -Compiling pypy for linux on takes about 1 hour, right? -Does faster build mode exist? Probably with less optimizations (without -O3 etc.) -Is there way to rebuild only micronumpy? -How do developers usually debug modules such as micronumpy? I am curious about tools and techniques. On Sat, Jan 2, 2016 at 6:17 PM, Matti Picus <matti.picus@gmail.com> wrote:
On 02/01/16 01:44, Sergey Matyunin wrote:
Dear Maciej,
Thanks for the answer! Does it make sense to fix failing tests? Or may be they were left as is because they are irrelevant?
Do numpypy developers use these tests or some other tests? Does any guidelines exist for numpypy developers? Do I need to create an issue for each PR?
Is this maillist the right place for asking that questions?
The test suite in the pypy/numpy repo is forked directly from the upstream numpy repo. We so far consider our inability to run them failures in the pypy/pypy micronumpy module. You should not fix these tests or the pypy/numpy repo itself for most of these issues, rather the essence of the failing test should be rewritten in pypy/pypy/module/micronumpy/tests/test*.py and fixed there. Some of the failures may actually require modification of the pypy/numpy repo, but that would be only after we exhaust options to make our micronumpy implementation 100% compatible.
And just to point out one such exception to the rule of modifying only micronumpy: One of the most prevalent test failures (as can be seen here https://gist.github.com/mattip/2e6f05f1900eb6a9fd99 ) is the lack of numpy.ndarray.partition. I have a plan to reimplement this in the pypy/numpy repo in cffi (see here for an outline https://gist.github.com/mattip/ab34268b049b859554ad ) rather than rewriting it in rpython, but have not been able to get around to actually doing it.
Feel free to ask here or on IRC for more help
Matti
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