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llogiq
bytecount
Rust2017–2018
llogiq / bytecount

bytecount

Counting occurrences of a given byte or UTF-8 characters in a slice of memory – fast

3Distinct people
3Mentions
0Explicit recommenders
239GitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Counting occurrences of a given byte or UTF-8 characters in a slice of memory – fast

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 1:49:46 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 month3 dated mentions

Observed mentions: 2017-08-19 01:37:55 UTC to 2018-06-05 11:04:36 UTC.

012017-08-01 00:00:00 UTC to 2017-09-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsAug 20172017-09-01 00:00:00 UTC to 2017-10-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2017-10-01 00:00:00 UTC to 2017-11-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2017-11-01 00:00:00 UTC to 2017-12-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2017-12-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2018-01-01 00:00:00 UTC to 2018-02-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsJan 20182018-02-01 00:00:00 UTC to 2018-03-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2018-03-01 00:00:00 UTC to 2018-04-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2018-04-01 00:00:00 UTC to 2018-05-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2018-05-01 00:00:00 UTC to 2018-06-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2018-06-01 00:00:00 UTC to 2018-07-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsJun 2018

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
Aug 20172017-08-01 00:00:00 UTC2017-09-01 00:00:00 UTC101
Sep 20172017-09-01 00:00:00 UTC2017-10-01 00:00:00 UTC000
Oct 20172017-10-01 00:00:00 UTC2017-11-01 00:00:00 UTC000
Nov 20172017-11-01 00:00:00 UTC2017-12-01 00:00:00 UTC000
Dec 20172017-12-01 00:00:00 UTC2018-01-01 00:00:00 UTC000
Jan 20182018-01-01 00:00:00 UTC2018-02-01 00:00:00 UTC101
Feb 20182018-02-01 00:00:00 UTC2018-03-01 00:00:00 UTC000
Mar 20182018-03-01 00:00:00 UTC2018-04-01 00:00:00 UTC000
Apr 20182018-04-01 00:00:00 UTC2018-05-01 00:00:00 UTC000
May 20182018-05-01 00:00:00 UTC2018-06-01 00:00:00 UTC000
Jun 20182018-06-01 00:00:00 UTC2018-07-01 00:00:00 UTC101

What Hacker News says

3 sources
The benchmark suite can be run by anyone: https://github.com/BurntSushi/ripgrep/blob/master/benchsuite... I re-ran them :-) https://github.com/BurntSushi/ripgrep/tree/master/benchsuite... TL;DR ripgrep has gotten faster in important areas since the initial set of benchmarks (the proper comparison there would be https://github.com/BurntSushi/ripgrep/tree/master/benchsuite...). The key reasons why are because it grew a parallel directory traverser, and its line counting got vectorized courtesy of the bytecount[1] crate. ucg has gotten a little faster in some cases, but the general conclusion of "ripgrep is the fastest" is still correct. [1] - https://github.com/llogiq/bytecount
In Feature comparison of ack, ag, git-grep, GNU grep and ripgrep
Technically that would be something like Haskell's, but I only have surface-level fluency. More to the point would be the most complex stuff I've had reason to do with a type system, which caps at around this generic state machine: https://play.rust-lang.org/?gist=3fdb20c34d589a2576c6bb137b9... (TL;DR: A type that encodes a state machine (and is generic over the implementation) that allows you to guarantee reaching a terminating state.) In practice I rather my types looking much plainer, though: https://github.com/llogiq/bytecount/blob/master/src/lib.rs
In Why Type Systems Matter

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