synthetic | R package for dataset generation and benchmarking | Performance Testing library

You could make use of where with a purrr-like function:

i face the same problem, i think Spark 3.2 is the problem itself

switched to Spark 3.1.2, it works fine

I am not certain that this is all of the problem (not having used fern) but since the input parameter to chain() is generic, it won't automatically coerce your Box to a Box, so you have to do that explicitly:

This is the stack trace when calling new Bar("foo") == new Foo("foo"):

As usual for a process that wants to start another process, it does a fork/exec, like a shell does. But in the new process, GDB doesn't just make an execve system call right away.

Instead, it calls ptrace(PTRACE_TRACEME) to wait for the parent process to attach to it, so GDB (the parent) is already attached before the child process makes an execve() system call to make this process start executing the specified executable file.

Also note in the execve(2) man page:

If the current program is being ptraced, a SIGTRAP signal is sent to it after a successful execve().

So that's how the kernel debugging API supports stopping before the first user-space instruction is executed in a newly-execed process. i.e. exactly what starti wants. This doesn't depend on setting a breakpoint; that can't happen until after execve anyway, and with ASLR the correct address isn't even known until after execve picks a base address. (GDB by default disables ASLR, but it still works if you tell it not to disable ASLR.)

This is also what GDB use if you set breakpoints before run, manually, or by using start to set a one-time breakpoint on main. Before the starti command existed, a hack to emulate that functionality was to set an invalid breakpoint before run, so GDB would stop on that error, giving you control at that point.

If you strace -f -o gdb.trace gdb ./foo or something, you'll see some of what GDB does. (Nested tracing apparently doesn't work, so running GDB under strace means GDB's ptrace system call fails, but we can see what it does leading up to that.)

So I have a final study program that does the required things I wanted, so I am posting this as an answer. Comments after.

I don't believe Dask implements this as of October 2021. This is likely because there's no support for multi-index, which unstack requires. There has been some work on this recently though.

However, I think this still should be possible using the apply-concat-apply paradigm (and apply_concat_apply function).

The solution below works for the example you've provided and in principle, I think, it should work generally, but I am not sure. Please proceed with caution and, if possible, check that results agree with what Pandas gives you. I have also posted this as a feature request on Dask's github itself.

You can create a vector with sequences of dates for each patient and pivot it (unnest):

You can use seaborn.catplot directly. You just need to melt the y-columns first: