HPy Sprint Status Update and Feedback Session
As we announced in this blog post, we are currently having our joint PyPy/HPy/GraalPy sprint in Düsseldorf.
On Thursday (September 22nd, 2022), we did the HPy sprint report. Most notably, we also had several CPython core developers in the call.
The sprint report was streamed on Twitch and the recording is available here:
HPy Sprint Call with CPython Core Developers¶
One of the main goals in the sprint was to write a PEP to officially propose HPy as an Python C extension API. We started to do so but before we actually submit this PEP, we wanted to have some feedback. So, we invited the Python core developers to our call and some of them joined.
We gave a short overview of HPy since not everyone might know it yet. We talked about the goals and non-goals of HPy and basically asked if Python core developers would be willing to participate in HPy design discussions. We discussed PSF endorsement and the conclusion was that we need to talk to the PSF.
We had some very good discussions and we also got some valuable feedback. Our next steps are now to incorporate this feedback and prepare the PEP to continue discussions there and gather more feedback.
We thank the Python core developers for participating in the call and for the offered support.
Call with NumPy Core Developer Sebastian Berg¶
Since we are working on the migration of NumPy to HPy, we had a call with Sebastian Berg on Tuesday (September 20th, 2022).
We discussed some problems we discovered during our migration work and were discussing how to solve it.
These were the main discussion points:
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NumPy's structured data type allows to have objects in NumPy arrays which problematic for HPy. This is mainly because doesn't allow to use the API during deallocation of an object. Hence, there is no way to determine the location of those objects by fetching the data type (which requires an API call). We discussed to mirror the structure in pure C-level data structures instead.
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HPy requires to migration all static types to heap types and we discovered that static type behave a bit differently compared to heap types in the case of multiple inheritance. We discussed if that is a bug that CPython needs to solve or if that is something that NumPy should change. So far, it looks rather to be a CPython problem since heap types are pretty new.
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We further discussed how to handle NumPy's C API when migrating to HPy. We agreed that we will probably need to provide a separate NumPy HPy C API as well which will maybe removed at some point in future.
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