Quickly visualize which folders are taking the most disk space
I’m currently migrating to a new computer, and in the process I have to move (or, if it appears to be a better choice, drop) all my browser profiles. And as it turns out, after some years, they get big. Huge, I’d even say. Notably Vivaldi (which turned out impossible to move properly because the idiots will drop both cookies and extensions while pretending it’s a useful feature), even though I didn’t use it much: 1.5 GiB profile size, mind you. That’s a bit more than my main Firefox profile, which I’ve used a lot a lot a lot more and which, very notably, includes around 800 MiB just for Telegram local storage (or should I say included, now I removed it once and for all).
Anyway, I thought that even though I didn’t want to start from scratch, it would be nice to tidy up a little bit. But that profile contains so many folders… That’s where JDiskReport becomes useful. Even though the UI of the new version 2 isn’t quite finished (the top PITA IMO is that you can’t copy/paste a folder path but you have to browse to it), it’s a pretty convenient and light tool to visualize the respective size of subfolders. Great to target the few big ones so that you don’t waste time on the tiny ones.
I’m aware that there are some more integrated tools, but since it’s not something I use more than once on twice a year, I like the fast that it’s purely portable. Nothing to install (except see below), just download and run the 3 MiB JAR file.
There really isn’t much to say, except maybe that it’s written in Java so yup, you’ll need that annoying JRE (but you probably already have it anyway, and in this day and age it’s not that big nor slow anyway). My current favorite is Adoptium / Eclipse Temurin, just don’t forget to pick the JRE because the JDK, which the download page defaults to, is much fatter (yes, I said fatter, not faster).
Update (2023-03-01): I just ran this on my new computer, and it’s actually super fast. Analyzed a folder with 3k+ sub-folders and 20k+ files within a split second. I guess it was slow-ish on my previous computer because I had a really slow SSD on it.
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