Apple now ships Macs which are running on an arm64 variant machine with the latest version of MacOS, Big Sur M1. We are getting requests for PyPy to support this new architecture. Here is our position on this topic (or at least mine, Armin Rigo's), and how you can help.

Porting PyPy is harder than just re-running the compiler, because PyPy contains a few big architecture-dependent "details", like the JIT compiler and the foreign function interfaces (CFFI and ctypes).

Fixing the JIT compiler should not be too much work: we already support arm64, just the Linux one. But Apple made various details different (like the calling conventions). A few other parts need to be fixed too, notably CFFI and ctypes, again because of the calling conventions.

Fixing that would be a reasonable amount of work. I would do it myself for a small amount of money. However, the story doesn't finish here. Obviously, the start of the story would be to get ssh access to a Big Sur M1 machine. (If at this point you're thinking "sure, I can give you ssh access for three months", then please read on.) The next part of the story is that we need a machine available long term. It can be either a machine provided and maintained by a third party, or alternatively a pot of money big enough to support the acquision of a machine and ongoing work of one of us.

If we go with the provided-machine solution: What we need isn't a lot of resources. Our CI requires maybe 10 GB of disk space, and a few hours of CPU per run. It should fit into 8 GB of RAM. We normally do a run every night but we can certainly lower the frequency a bit if that would help. However, we'd ideally like some kind of assurance that you are invested into maintaining the machine for the next 3-5 years (I guess, see below). We had far too many machines that disappeared after a few months.

If we go with the money-supported solution: it's likely that after 3-5 years the whole Mac base will have switched to arm64, we'll drop x86-64 support for Mac, and we'll be back to the situation of the past where there was only one kind of Mac machine to care about. In the meantime, we are looking at 3-5 years of lightweight extra maintenance. We have someone that has said he would do it, but not for free.

If either of these two solutions occurs, we'll still have, I quote, "probably some changes in distutils-type stuff to make python happy", and then some packaging/deployment changes to support the "universal2" architecture, i.e. including both versions inside a single executable (which will not be just an extra switch to clang, because the two versions need a different JIT backend and so must be translated separately).

So, now all the factors are on the table. We won't do the minimal "just the JIT compiler fixes" if we don't have a plan that goes farther. Either we get sufficient money, and maybe support, and then we can do it quickly; or PyPy will just remain not natively available on M1 hardware for the next 3-5 years. We are looking forward to supporting M1, and view resources contributed by the community as a vote of confidence in assuring the future of PyPy on this hardware. Contact us: pypy-dev@python.org, or our private mailing list pypy-z@python.org.

Thanks for reading!

Armin Rigo

 The PyPy team is proud to release the version 7.3.3 of PyPy, which includes three different interpreters:

• PyPy2.7, which is an interpreter supporting the syntax and the features of Python 2.7 including the stdlib for CPython 2.7.18 (updated from the previous version)
• PyPy3.6: which is an interpreter supporting the syntax and the features of Python 3.6, including the stdlib for CPython 3.6.12 (updated from the previous version).
• PyPy3.7 beta: which is our second release of an interpreter supporting the syntax and the features of Python 3.7, including the stdlib for CPython 3.7.9. We call this beta quality software, there may be issues about compatibility with new and changed features in CPython 3.7. Please let us know what is broken or missing. We have not implemented the documented changes in the re module, and a few other pieces are also missing. For more information, see the PyPy 3.7 wiki page

The interpreters are based on much the same codebase, thus the multiple release. This is a micro release, all APIs are compatible with the 7.3 releases, but read on to find out what is new.

Several issues found in the 7.3.2 release were fixed. Many of them came from the great work by conda-forge to ship PyPy binary packages. A big shout out to them for taking this on.

Development of PyPy has moved to https://foss.heptapod.net/pypy/pypy. This was covered more extensively in this blog post. We have seen an increase in the number of drive-by contributors who are able to use gitlab + mercurial to create merge requests.

The CFFI backend has been updated to version 1.14.3. We recommend using CFFI rather than c-extensions to interact with C, and using cppyy for performant wrapping of C++ code for Python.

A new contributor took us up on the challenge to get windows 64-bit support. The work is proceeding on the win64 branch, more help in coding or sponsorship is welcome. In anticipation of merging this large change, we fixed many test failures on windows.

As always, this release fixed several issues and bugs. We strongly recommend updating. Many of the fixes are the direct result of end-user bug reports, so please continue reporting issues as they crop up.

You can find links to download the v7.3.3 releases here:

https://pypy.org/download.html

We would like to thank our donors for the continued support of the PyPy project. If PyPy is not quite good enough for your needs, we are available for direct consulting work.

We would also like to thank our contributors and encourage new people to join the project. PyPy has many layers and we need help with all of them: PyPy and RPython documentation improvements, tweaking popular modules to run on pypy, or general help with making RPython’s JIT even better. Since the previous release, we have accepted contributions from 2 new contributors, thanks for pitching in.

If you are a python library maintainer and use c-extensions, please consider making a cffi / cppyy version of your library that would be performant on PyPy. In any case both cibuildwheel and the multibuild system support building wheels for PyPy.

• PyPy2.7, which is an interpreter supporting the syntax and the features of Python 2.7 including the stdlib for CPython 2.7.13
• PyPy3.6: which is an interpreter supporting the syntax and the features of Python 3.6, including the stdlib for CPython 3.6.9.
• PyPy3.7 alpha: which is our first release of an interpreter supporting the syntax and the features of Python 3.7, including the stdlib for CPython 3.7.9. We call this an alpha release since it is our first. It is based off PyPy 3.6 so issues should be around compatibility and not stability. Please try it out and let us know what is broken or missing. We have not implemented some of the documented changes in the re module, and other pieces are also missing. For more information, see the PyPy 3.7 wiki page

The interpreters are based on much the same codebase, thus the multiple release. This is a micro release, all APIs are compatible with the 7.3.0 (Dec 2019) and 7.3.1 (April 2020) releases, but read on to find out what is new.

Conda Forge now supports PyPy as a python interpreter. The support is quite complete for linux and macOS. This is the result of a lot of hard work and good will on the part of the Conda Forge team. A big shout out to them for taking this on.

Development of PyPy has transitioning to https://foss.heptapod.net/pypy/pypy. This move was covered more extensively in this blog post. We have seen an increase in the number of drive-by contributors who are able to use gitlab + mercurial to create merge requests.

The CFFI backend has been updated to version 1.14.2. We recommend using CFFI rather than c-extensions to interact with C, and using cppyy for performant wrapping of C++ code for Python.

NumPy has begun shipping wheels on PyPI for PyPy, currently for linux 64-bit only. Wheels for PyPy windows will be available from the next NumPy release. Thanks to NumPy for their support.

A new contributor took us up on the challenge to get windows 64-bit support. The work is proceeding on the win64 branch, more help in coding or sponsorship is welcome.

As always, this release fixed several issues and bugs. We strongly recommend updating. Many of the fixes are the direct result of end-user bug reports, so please continue reporting issues as they crop up.

You can find links to download the v7.3.2 releases here:

https://pypy.org/download.html

We would like to thank our donors for the continued support of the PyPy project. Please help support us at Open Collective. If PyPy is not yet good enough for your needs, we are available for direct consulting work.

We would also like to thank our contributors and encourage new people to join the project. PyPy has many layers and we need help with all of them: PyPy and RPython documentation improvements, tweaking popular modules to run on pypy, or general help with making RPython’s JIT even better. Since the previous release, we have accepted contributions from 8 new contributors, thanks for pitching in.

If you are a python library maintainer and use c-extensions, please consider making a cffi / cppyy version of your library that would be performant on PyPy. In any case both cibuildwheel and the multibuild system support building wheels for PyPy.

Hi all,

PyPy is now a member of Open Collective, a fiscal host. We have been thinking about switching to this organization for a couple of years; we like it for various reasons, like the budget transparency and the lightweight touch. We can now officially announce our membership!

With this, we are now again free to use PyPy for all financial issues, like receiving funds professionally, paying parts of sprint budgets as we like, and so on. We will shortly be reintroducing buttons that link to Open Collective from the PyPy web site.

Although the old donation buttons were removed last year, we believe that there are still a few people that send regularly money to the SFC, the not-for-profit charity we were affiliated with. If you do, please stop doing it now (and, if you like to do so, please set up an equivalent donation to PyPy on Open Collective).

And by the way, sorry for all of you who were getting mixed feelings from the previous blog post (co-written with the SFC). PyPy is committed to continue being Open Source just like before. This was never in question. What these two blog posts mean is only that we switched to a different organization for our internal finances.

We're looking forward to how this new relationship will go!

Armin Rigo, for the PyPy team