wiki VS knowledge

I collected a list of profilers (also memory profilers, also specifically for Python) here: https://github.com/albertz/wiki/blob/master/profiling.md

Currently I actually need a Python memory profiler, because I want to figure out whether there is some memory leak in my application (PyTorch based training script), and where exactly (in this case, it's not a problem of GPU memory, but CPU memory).

I tried Scalene (https://github.com/plasma-umass/scalene), which seems to be powerful, but somehow the output it gives me is not useful at all? It doesn't really give me a flamegraph, or a list of the top lines with memory allocations, but instead it gives me a listing of all source code lines, and prints some (very sparse) information on each line. So I need to search through that listing now by hand to find the spots? Maybe I just don't know how to use it properly.

I tried Memray, but first ran into an issue (https://github.com/bloomberg/memray/issues/212), but after using some workaround, it worked now. I get a flamegraph out, but it doesn't really seem accurate? After a while, there don't seem to be any new memory allocations at all anymore, and I don't quite trust that this is correct.

There is also Austin (https://github.com/P403n1x87/austin), which I also wanted to try (have not yet).

Somehow this experience so far was very disappointing.

(Side node, I debugged some very strange memory allocation behavior of Python before, where all local variables were kept around after an exception, even though I made sure there is no reference anymore to the exception object, to the traceback, etc, and I even called frame.clear() for all frames to really clear it. It turns out, frame.f_locals will create another copy of all the local variables, and the exception object and all the locals in the other frame still stay alive until you access frame.f_locals again. At that point, it will sync the f_locals again with the real (fast) locals, and then it can finally free everything. It was quite annoying to find the source of this problem and to find workarounds for it. https://github.com/python/cpython/issues/113939)

We use a shell history per directory per user. This is very helpful, esp in distributed shared environments.

https://github.com/albertz/wiki/blob/master/shell.md#history

There is much more, though.

See here for an overview:

https://github.com/albertz/wiki/blob/master/terminal-escape-...

There are a couple of non-standard extensions, e.g. by iTerm:

https://iterm2.com/documentation-escape-codes.html https://iterm2.com/documentation-images.html

Some of them are pretty complicated to standardize. E.g. see this discussion on simple image support:

https://gitlab.freedesktop.org/terminal-wg/specifications/-/...

Skimming through this, it looks more like organized public bookmarks. Many of the pages just contain (mostly) a list of links. There are barely any notes.

I actually do this as well. Just some text files, where I put links I stumble upon, which I find interesting. Not always all links but only really interesting ones. Also maybe only for topics where I think it's not so easy to find such links later on via Google.

Sometimes I also do research on some new topic, and for that I keep notes. If I think the research / overview / my notes of this topic are of any value to others, I would maybe just make it public somewhere.

Some of these links and notes I keep private. If it is public, I would probably just put it here:

https://github.com/albertz/wiki

Currently put it all into markdown files here: https://github.com/nikitavoloboev/knowledge

Building a tool to make this easier: https://github.com/learn-anything/learn-anything

And although these are not obsidian vaults, they are also great digital gardens: - My knowledge wiki by Nikita Voloboev - Andy's working notes by Andy Matuschak - maggieappleton.com by Maggie Appleton