hope | Hope programming language interpreter | Functional Programming library

The following method avoids overflow and should result in fairly efficient assembly (example) without depending on non-standard features:

Currently (2022-02-05), CRAN builds R binaries for Apple silicon using Apple clang (from Command Line Tools for Xcode 12.4) and an experimental build of gfortran.

If you obtain R from CRAN (i.e., here), then you need to replicate CRAN's compiler setup on your system before building R packages that contain C/C++/Fortran code from their sources (and before using Rcpp, etc.). This requirement ensures that your package builds are compatible with R itself.

A further complication is the fact that Apple clang doesn't support OpenMP, so you need to do even more work to compile programs that make use of multithreading. You could circumvent the issue by building R itself and all R packages from sources with LLVM clang, which does support OpenMP, but this approach is onerous and "for experts only". There is another approach that has been tested by a few people, including Simon Urbanek, the maintainer of R for macOS. It is experimental and also "for experts only", but seems to work on my machine and is simpler than trying to build R yourself.

Warning: These instructions come with no warranty and could break at any time. They assume some level of familiarity with C/C++/Fortran program compilation, Makefile syntax, and Unix shells. As usual, sudo at your own risk.

I will try to address compilers and OpenMP support at the same time. I am going to assume that you are starting from nothing. Feel free to skip steps you've already taken, though you might find a fresh start helpful.

I've tested these instructions on a machine running Big Sur, and at least one person has tested them on a machine running Monterey. I would be glad to hear from others.

1. Download an R binary from CRAN here and install. Be sure to select the binary built for Apple silicon.

2. Run

This is currently a known bug in Rakudo. The intended behavior is for has to support list assignment, which would make syntax very much like that shown in the question work.

I am not sure if the supported syntax will be:

You could use django's receiver annotation.

For example, if you want to detect any call of the save method, you could do:

I think it is a bug in Funding Choices.

Deep down in some ad-blocking detection code loaded by Funding Choices I found the following being part of a reportClientEvent(...) call:

According to Quinn “The Eskimo!” at Apple Developer Technical Support, this message is Xcode log noise and can be ignored.

An Apple bug report should be filed to help flag and silence the log.

• https://developers.apple.com/forums/thread/689066
• https://developer.apple.com/forums/thread/115461

It’s important to keep an eye on log messages and fix any obvious problems they call out. However, if you see a log message that’s not obviously your fault, it could just be log noise.

There are two criteria you should apply here:

• Is the log message associated with a specific failure? That is, when you see the log message, do you also see other problems?
• Is the log message written in terms you understand? That is, does it reference APIs or data that you’re using?

If the answer to both of these questions is “No”, it’s reasonable to conclude that the log message is just noise and you can ignore it. If you find it to be particularly irksome, file a bug report requesting that it be silenced.

It turns out that there's already an issue and discussion regarding this:

• https://github.com/docker/compose/issues/3874

The thread points out that this is the expected behavior and is documented here: https://docs.docker.com/compose/extends/#understanding-multiple-compose-files

When you use multiple configuration files, you must make sure all paths in the files are relative to the base Compose file (the first Compose file specified with -f). This is required because override files need not be valid Compose files. Override files can contain small fragments of configuration. Tracking which fragment of a service is relative to which path is difficult and confusing, so to keep paths easier to understand, all paths must be defined relative to the base file.

There's a workaround within that discussion that works fairly well: https://github.com/docker/compose/issues/3874#issuecomment-470311052

The workaround is to use a ENV var that has a default:

• ${PROXY:-.}/haproxy/conf:/usr/local/etc/haproxy

Or in my case:

Contrary to common belief Haskell is quite friendly with respect to problems like that. The real issue is that the array library that comes with GHC is total garbage. Another big problem is that everyone is taught in Haskell to use lists where arrays should be used instead, which is usually one of the major sources of slow code and memory bloated programs. So, it is not surprising that GC takes a long time, it is because there is way too much stuff being allocation. Here is a run on the supplied input for the solution provided below:

Error seems to be related to a bug in Git for Windows 2.32. Upgrading to Git for Windows 2.33+ has fixed it for several people.