11–20 of 33 posts
Interesting testimonials section. Two out of five are "this looks interesting" and "this might be useful." Another two seem unclear on if they've actually used it. The last one does seem to be from an actual user (and is very positive, for what it's worth).
For those Python programmers out there, if you don't mind sharing your experiences, do you spend any time at all on the REPL? If so, what fraction of the time, approximately? Using IPython, JupyterLab, or something else? Or do you just run it directly from an VS Code or PyCharm? Anything you may want to add about your routine would be appreciated. Oh, if you (experienced programmer or not) happen to know about a good…
Notebooks are just plain awesome. Whenever I use a new api or service, I'll make a notebook with cells showing how to call/run each operation and commit as a sort of executable documentation.
For those Python programmers out there, if you don't mind sharing your experiences, do you spend any time at all on the REPL? If so, what fraction of the time, approximately? Using IPython, JupyterLab, or something else? Or do you just run it directly from an VS Code or PyCharm? Anything you may want to add about your routine would be appreciated. Oh, if you (experienced programmer or not) happen to know about a good…
The reason is that Jupyter environment is lightyears more powerful than REPL. Feels like REPL is for those who don't code / only those who don't code would use REPL. I don't even use that after the first day.
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
Another side node: Bloomberg has a couple of nice open source projects. E.g. I just realized, PyStack (https://bloomberg.github.io/pystack/) is also by Bloomberg.
For those Python programmers out there, if you don't mind sharing your experiences, do you spend any time at all on the REPL? If so, what fraction of the time, approximately? Using IPython, JupyterLab, or something else? Or do you just run it directly from an VS Code or PyCharm? Anything you may want to add about your routine would be appreciated. Oh, if you (experienced programmer or not) happen to know about a good…
Particularly in cases where I'm trying to figure out how I want to modify some object.
I dabble largely due to Ansible and system administration purposes. IDEs and the like aren't a thing for me; neovim/LSP instead.
Found the issue almost immediately with the high watermark analysis which provides visibility into the part of the codebase/call stack that allocated every bit of allocated memory that was still live at the high watermark time. Made diagnosing the issue (an unexpectedly large amount of memory required when using a method from a third party library -- xarray.merge) and remedying the issue incredibly easy.
I was very impressed by the quality and utility of this tool and am now a huge fan!
For those Python programmers out there, if you don't mind sharing your experiences, do you spend any time at all on the REPL? If so, what fraction of the time, approximately? Using IPython, JupyterLab, or something else? Or do you just run it directly from an VS Code or PyCharm? Anything you may want to add about your routine would be appreciated. Oh, if you (experienced programmer or not) happen to know about a good…
For those Python programmers out there, if you don't mind sharing your experiences, do you spend any time at all on the REPL? If so, what fraction of the time, approximately? Using IPython, JupyterLab, or something else? Or do you just run it directly from an VS Code or PyCharm? Anything you may want to add about your routine would be appreciated. Oh, if you (experienced programmer or not) happen to know about a good…
I'm probably not the average python programmer. But I normally just create two terminals (I have a tiling window manager) and in one I open a python file under /tmp/ write my code and execute it in the other terminal. I would probably use a REPL if it was integrated in my favorite editor ( https://helix-editor.com ). But everything else I tried was to "clunky" for me. Though I work with data scientists, and they love…
I use helix in the terminal, regularly opening up a split pane in tmux to either breakpoint in, or test out bits of code interactively. I'm not quite as organized as having two regular panes- I'll close and open them pretty quickly. Often just to try some toy example of reorganising a duct or something before writing it out into code.