minisearch
regex-benchmark
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minisearch | regex-benchmark | |
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10 | 9 | |
4,081 | 309 | |
- | - | |
7.6 | 0.0 | |
19 days ago | 16 days ago | |
JavaScript | Dockerfile | |
MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
minisearch
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Character and Subsector generators for Classic Traveller, with TAS Forms!
I wrote an online catalog a while back (and I need to get back on adding graphics and products at some point). Itβs written using Eleventy and the minisearch library. The source and data are available on Github if you want to see how I did things. Iβm not a professional web designer either, but it was a fun project.
- What is your go to client-side fuzzy searching library?
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Meilisearch v1.0 β the open-source Rust alternative to Algolia and Elasticsearch
You could have a look at https://github.com/lucaong/minisearch/
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What do you use for site search? Custom built solution? Meilisearch? Algolia?
If you're dealing with thousands of records or less, searching titles and summaries rather than long bodies of text, I recommend looking into client-side solutions. Nothing beats the responsiveness of search-as-you-type entirely on the client side. It can be fairly sophisticated fulltext search. For example, I've built had great success with MiniSearch.
- MiniSearch β fuzzy match search in TypeScript
- Minisearch: Tiny, powerful JavaScript full-text search engine for browser, Node
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Lyra: Fast, in-memory, typo-tolerant, full-text search engine in TypeScript
I quite enjoy minisearch[1] which is also 0 dependencies, actively maintained, and I expect would work well in a worker environment. I dropped it into a service worker and plugged it with a simple point in polygon script to enable geosearch for a recent project[2] and it played v. nicely.
[1] https://github.com/lucaong/minisearch
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I highly recommend the Omnisearch plugin.
No magic here, the underlying engine is Minisearch, which uses the BM25 algorithm (the de facto standard among search libraries). Omnisearch adds a magic sauce during indexing by converting notes into custom objects, with the following fields: - body (the plain markdown text) - filename & yaml aliases - level 1 headers - level 2 headers - level 3 headers
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For lovers of instant search and Ctrl+K menus, we made an open-source tool to add that to your website in 2 steps: 1. Enter your URL 2. Add code snippet to <head>. Links and code in comments!
It's actually really simple! Minisearch did most of the heavy lifting so all we needed to do was the crawling, storing and UI etc. I'd check that out if you're interested in the search part!
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I made a tool to add instant search to your site in 2 steps: 1. Enter your URL 2. Add code snippet to <head>. Links in comments!
We use MiniSearch for searching, while fast-fuzzy is used for highlighting of detected search terms.
regex-benchmark
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Best regexp alternative for Go. Benchmarks. Plots.
Before we start comparing the aforementioned solutions, it is worth to show how bad things are with the standard regex library in Go. I found the project where the author compares the performance of standard regex engines of various languages. The point of this benchmark is to repeatedly run 3 regular expressions over a predefined text. Go came in 3rd place in this benchmark! From the end....
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Rust vs. Go in 2023
* Let you clone a map without rehashing every key to a new seed. I generally measure at least 15x speedup from this alone, unlocking very useful design patterns like "clone a map and apply a few temporary updates for a one-off operation like validation or simulation" with no extra code complexity. Go gives you no better option than slowly rehashing the entire map.
And that's just hash maps. How about Go's regex engine being one of the slowest in the world while Rust's regex crate being one of the fastest:
https://github.com/mariomka/regex-benchmark#optimized
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Regex for lazy developers
Languages Regex Benchmark
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Elon is your new boss, time to refactor!
Java is still pretty bad compared to C# (not to mention Rust or Nim)
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Lyra: Fast, in-memory, typo-tolerant, full-text search engine in TypeScript
https://github.com/mariomka/regex-benchmark
And the always interesting techempower Project, which leaves the implementation to participants of each round. https://www.techempower.com/benchmarks/#section=data-r21&tes...
Choose whatever category you wish there, js is faster in then go in almost all categories there.
Even though I said it before, I'm going to repeat myself as I expect you to ignore my previous message: the language doesn't make any implementation fast or slow. You can have a well performing search engine in go, and JS. The performance difference will most likely not be caused by the language with these two choices. And the same will apply with C/Rust. The language won't make the engine performant creating a maximally performant search engine is hard
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i'd like you to meet regex-
Also, regex engines are not created equally, at all. One of the best writeups I've ever read is from the ripgrep blog. Burntsushi knows regex. There's also this benchmark site which illustrates how general language performance is an entirely different metric than regex performance. Don't assume those benchmarks will cover your particular use case, though--different regex engines might handle your particular situation differently.
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Go performance from version 1.2 to 1.18
Interesting. Looking at this repo, they have
Rust -> Ruby -> Java -> Golang
https://github.com/mariomka/regex-benchmark
Though it appears the numbers are two years old or so, and only for 3 specific regexes.
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Hajime can now get hardware information about your MC server, all from Minecraft itself!
id also be careful in claiming C++ std regex is faster than python, unless you actually have proof. there's a ton of information that in many cases its actually slower. https://github.com/mariomka/regex-benchmark. have you actually benchmarked your code? or was it just a naive assumption that because its C++ its just fast?
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A Complete Course of the Raku programming language
It is a matter of personal preference.
I find that regular expressions and text-wrangling tasks are faster and easier in Perl than in other programming languages due to its accessible syntax and regular expression engine speed.
This article shows the regular expression syntax in several popular programming languages: https://cs.lmu.edu/~ray/notes/regex/
This GitHub repo gives some regex performance test benchmarks: https://github.com/mariomka/regex-benchmark Perl is pretty fast among the scripting languages that were benchmarked.
If you are familiar with C / C++, then learning Perl is relatively fast and easy: https://perldoc.perl.org/perlintro
What are some alternatives?
flexsearch - Next-Generation full text search library for Browser and Node.js
hyperscan - High-performance regular expression matching library
lunr.js - A bit like Solr, but much smaller and not as bright
regex - An implementation of regular expressions for Rust. This implementation uses finite automata and guarantees linear time matching on all inputs.
orama - π Fast, dependency-free, full-text and vector search engine with typo tolerance, filters, facets, stemming, and more. Works with any JavaScript runtime, browser, server, service!
sqlx - π§° The Rust SQL Toolkit. An async, pure Rust SQL crate featuring compile-time checked queries without a DSL. Supports PostgreSQL, MySQL, and SQLite.
itemsjs - Extremely fast faceted search engine in JavaScript - lightweight, flexible, and simple to use
obsidian-omnisearch - A search engine that "just works" for Obsidian. Supports OCR and PDF indexing.
raku-course
Lyra - A simple to use, composable, command line parser for C++ 11 and beyond
rakudo-appimage