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bootandy
dust
Rust2018–2026
bootandy / dust

dust

A more intuitive version of du in rust

19Distinct people
22Mentions
0Explicit recommenders
12.6KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

A more intuitive version of du in rust

GitHub

Where it is used

No documented product use was verified in the last source check.

What people are saying

No recommendation phrase was found in the indexed comments.

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Also in these discussions

Mentioned in the same Hacker News threads. That is not proof they are substitutes.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 12:54:37 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year22 dated mentions

Observed mentions: 2018-04-13 13:58:37 UTC to 2026-08-16 04:11:42 UTC.

02462018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 comments20182019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 6 mentions; 1 submissions, 5 comments2021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 4 mentions; 2 submissions, 2 comments2022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments20222023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 5 mentions; 2 submissions, 3 comments2025-01-01 00:00:00 UTC to 2026-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2026-01-01 00:00:00 UTC to 2027-01-01 00:00:00 UTC (exclusive): 3 mentions; 0 submissions, 3 comments. Incomplete calendar period.2026*

* An incomplete calendar period is marked with an outlined bar. Its count is not directly comparable with a full period.

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC110
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC000
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC615
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC422
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC000
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC202
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC523
20252025-01-01 00:00:00 UTC2026-01-01 00:00:00 UTC101
2026 (partial)2026-01-01 00:00:00 UTC2027-01-01 00:00:00 UTC303

What Hacker News says

22 sources
201984·Jul 10, 2024Submission

Show HN: Dut – a fast Linux disk usage calculator

"dut" is a disk usage calculator that I wrote a couple months ago in C. It is multi-threaded, making it one of the fastest such programs. It beats normal "du" in all cases, and beats all other similar programs when Linux's caches are warm (so, not on the first run). I wrote "dut" as a challenge to beat similar programs that I used a lot, namely pdu[1] and dust[2]. "dut" displays a tree of the biggest things under your current directory, and it also shows the size of hard-links under each directory as well. The hard-link tallying was inspired by ncdu[3], but I don't like how unintuitive the readout is. Anyone have ideas for a better format? There's installation instructions in the README. dut is a single source file, so you only need to download it and copy-paste the compiler command, and then copy somewhere on your path like /usr/local/bi
Read the rest
n. I went through a few different approaches writing it, and you can see most of them in the git history. At the core of the program is a datastructure that holds the directories that still need to be traversed, and binary heaps to hold statted files and directories. I had started off using C++ std::queues with mutexes, but the performance was awful, so I took it as a learning opportunity and wrote all the datastructures from scratch. That was the hardest part of the program to get right. These are the other techniques I used to improve performance: * Using fstatat(2) with the parent directory's fd instead of lstat(2) with an absolute path. (10-15% performance increase) * Using statx(2) instead of fstatat. (perf showed fstatat running statx code in the kernel). (10% performance increase) * Using getdents(2) to get directory contents instead of opendir/readdir/closedir. (also around 10%) * Limiting inter-thread communication. I originally had fs-traversal results accumulated in a shared binary heap, but giving each thread a binary-heap and then merging them all at the end was faster. I couldn't find any information online about fstatat and statx being significantly faster than plain old stat, so maybe this info will help someone in the future. [1]: https://github.com/KSXGitHub/parallel-disk-usage [2]: https://github.com/bootandy/dust [3]: https://dev.yorhel.nl/doc/ncdu2, see "Shared Links"
396 points · Open discussion
Related, updating difftastic and friends if you installed via cargo: cargo install cargo-update cargo install-update --list cargo install-update --all Other fun Rust projects available via cargo: https://mise.jdx.dev/ mise-en-place, a drop-in replacement for asdf https://asdf-vm.com/ that is really fast and flexible. https://github.com/ajeetdsouza/zoxide is a fantastic cd replacement, which stores where you cd to, and you can then do a partial match like "z hel" might take you to "~/projects/helloworld". https://github.com/bootandy/dust is a compliment to "du", shows which directories are using the most disk space.
In Difftastic, a structural diff tool that understands syntax
tl;dr: - zsh+ohmyzsh - fdfind github.com/sharkdp/fd - duf github.com/muesli/duf "better df" - dust github.com/bootandy/dust "more intuitive du" - tldr github.com/tldr-pages/tldr-python-client tldr client in python - ripgrep github.com/BurntSushi/ripgrep This constitutes the "great" tools, there are more that are "good"
In The Most Useful Command Line Tools (2023 Edition)

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