mxe VS manylinux

Cross compiler 64bit minGW along with MXE environment

I used to use MXE [1] to compile fully static Windows binaries on Linux VMs hosted with Travis. It needed to crane in everything though, so it was a source of bottlenecks from time to time. I was also uncertain about the provenance of a lot of the dependencies in that toolchain. So when Travis died I took the opportunity to move Windows builds back to gnu with msys2, all over GH Actions. These are actually comparatively snappy and I’m reasonably satisfied with it.

[1] https://mxe.cc/

MXE readily supports GCC 12 as a plugin (just a configuration line): https://github.com/mxe/mxe/tree/master/plugins/gcc12

Also, if you don't have any other significant dependencies, getting the development tools on Windows is not that hard with the Qt installer. Alternatively, there is MXE.

MXE (https://mxe.cc/) is a great cross compiler environment (on linux) that uses mingw.

You can install Docker to build on any Linux distro, and if one of those is Ubuntu then you can use https://github.com/mxe/mxe to further build for Windows. Or VirtualBox + Ubuntu + MXE.

I use manylinux containers as the OS for compilation. It tries to ensure as much cross-os / libc / etc.. as much as possible for precompiled libraries. https://github.com/pypa/manylinux

Just to clarify for anyone who isn't aware, the "compiling issues", at least historically, have been that that Alpine uses musl, and PyPI's manylinux wheels are built against old glibc versions. So stuff like numpy that would trivially and quickly install from whl on glibc distros (like a bare-bones Ubuntu image) trigger compilations and the installation of build-only dependencies on Alpine.

That said, it looks like as of late-2021, at least some projects are offering musllinux wheels as well, per the discussion here: https://github.com/pypa/manylinux/issues/37 (not numpy, though: https://pypi.org/project/numpy/#files)

It's very hard. Incompatible glibc ABIs make this nigh impossible, there's a reason Steam installs a vcredistributable.dll for pretty much every game on Windows.

Look no further than the hoops you need jump through to distribute a Linux binary on PyPI [1]. Despite tons of engineering effort, and tons of hoop jumping from packagers, getting a non-trivial binary to run across all distros is still considered functionally impossible.

[1]: https://github.com/pypa/manylinux

As a user, if you build every python package from source, it's ok. But if you a maintainer of an OSS project and you need to publish binary packages for it, then you will hit the trouble. Binaries built on Ubuntu 20.04 can only support Ubuntu 20.04 and newer. So you'd better to choose an older Linux release to target broader users. Now most python packages choose CentOS 6 or 7. See https://github.com/pypa/manylinux/issues/1012 for more details. They need help!

I recently learned that Clang supports this kind of cross-compiling out of the box. https://mcilloni.ovh/2021/02/09/cxx-cross-clang/

The main difference is that Clang does not ship with headers/libraries for different platforms, as Zig appears to do. You need to give Clang a "sysroot" -- a path that has the headers/libraries for the platform you want to compile for.

If you create a bunch of sysroots for various architectures, you can do some pretty "easy" cross-compiling with just a single compiler binary. Docker can be a nice way of packaging up these sysroots (especially combined with Docker images like manylinux: https://github.com/pypa/manylinux). Gone are the days when you had to build a separate GCC cross-compiler for each platform you want to target.

Now you come and use manylinux to build. (https://github.com/pypa/manylinux) so you are based on the CentOS 7 toolchain (at best if you use manylinux2014) or Debian 9 toolchain (if you use manylinux_2_24).

I think the generally accepted way to do that would be a container image running a relatively old distribution. This is exactly what python packages do when they need to distribute binary packages on linux [0]. You are supposed to compile the package in a container (or VM) that runs CentOS 7 (or older if you want broader support), although now the baseline is moving gradually to Debian 9.

[0]: https://github.com/pypa/manylinux