flexsearch
FrameworkBenchmarks
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flexsearch | FrameworkBenchmarks | |
---|---|---|
12 | 366 | |
11,839 | 7,378 | |
4.2% | 1.1% | |
7.1 | 9.8 | |
4 months ago | 6 days ago | |
JavaScript | Java | |
Apache License 2.0 | GNU General Public License v3.0 or later |
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.
flexsearch
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Nextra 2 – Next.js Static Site Generator
Full-text search is powered by FlexSearch and Nextra will index all of your pages at build time ⚡.
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How to link search results back to original HTML when clicked?
I have a web page that reads in various .md files and displays them as HTML. The app uses the marked library to convert the markdown into HTML for display. I create a flexsearch search index out of the raw text values from the documents (raw text is gathered using DOMParser over all HTML elements) so that user can search for keywords in the docs and get back a table of results. The order of operations and search index code looks like:
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How can I set up this Typescript project to use a Javascript library?
I am trying to get flexsearch (a lib written in js) up and running in a TS project and found a working example here. I downloaded the project and ran 'yarn add flexsearch' and also 'yarn add @/types/flexsearch' since I know that you need a special index.d.ts file to convert the JS to TS properly.... however the code errors out during the Index object creation with the message.
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Best way to implement a search feature over raw HTML using Typescript/React?
Try using a proper browser search like Lunr or Flexsearch
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Lyra: Fast, in-memory, typo-tolerant, full-text search engine in TypeScript
Current version of FlexSearch (0.7.2) is not typo tolerant, see https://github.com/nextapps-de/flexsearch/issues/118
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Writing a Fuzzy Search Component With Preact and Fuse for Astro
Very nice! Seems to perform very well. I'm curious, have you compared Fuse with other search engines? Like flex search or elasticlunr? Why did you choose fuse ?
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Comparing English and Spanish Words in JavaScript
I actually looked into this term before localeCompare(): Full Text Search. It's pretty heavy duty. In JavaScript, this can come in the form of a library dependency like FlexSearch. Far too bulky for the humble sorting task I have at hand.
- Quick live-search on 1M strings in React native
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In memory full text search in Rust?
Javascript seems to have a comprehensive in memory solution https://github.com/nextapps-de/flexsearch
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DynamoDB full text search
Another option that was often suggested to me was building the search index with a library such as https://github.com/nextapps-de/flexsearch and distribute the index than to the client and handle it one the client. But yeah sounds like a lot of overhead and I haven't tried it.
FrameworkBenchmarks
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Why choose async/await over threads?
Neat. Thanks for sharing!
Interestingly, may-minihttp is faring very well in the TechEmpower benchmark [1], for whatever those benchmarks are worth. The code is also surprisingly straightforward [2].
[1] https://www.techempower.com/benchmarks/
[2] https://github.com/TechEmpower/FrameworkBenchmarks/blob/mast...
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Ntex: Powerful, pragmatic, fast framework for composable networking services
ntex was formed after a schism in actix-web and Rust safety/unsafety, with ntex allowing more unsafe code for better performance.
ntex is at the top of the TechEmpower benchmarks, although those benchmarks are not apples-to-apples since each uses its own tricks: https://www.techempower.com/benchmarks/#hw=ph&test=fortune&s...
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A decent VS Code and Ruby on Rails setup
Ruby is slow. Very slow. How much you may ask? https://www.techempower.com/benchmarks/#hw=ph&test=fortune&s... fastest Ruby entry is at 272th place. Sure, top entries tend to have questionable benchmark-golfing implementations, but it gives you a good primer on the overhead imposed by Ruby.
It is also not early 00s anymore, when you pick an interpreted language, you are not getting "better productivity and tooling". In fact, most interpreted languages lag behind other major languages significantly in the form of JS/TS, Python and Ruby suffering from different woes when it comes to package management and publishing. I would say only TS/JS manages to stand apart with being tolerable, and Python sometimes too by a virtue of its popularity and the amount of information out there whenever you need to troubleshoot.
If you liked Go but felt it being a too verbose to your liking, give .NET a try. I am advocating for it here on HN mostly for fun but it is, in fact, highly underappreciated, considered unsexy and boring while it's anything but after a complete change of trajectory in the last 3-5 years. It is actually the* stack people secretly want but simply don't know about because it is bundled together with Java in the public perception.
*productive CLI tooling, high performance, works well in a really wide range of workloads from low to high level, by far the best ORM across all languages and back-end framework that is easier to work with than Node.JS while consuming 0.1x resources
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The Erlang Ecosystem [video]
Although that seems to have improved in recent years.
https://www.techempower.com/benchmarks/#hw=ph&test=json§...
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Ruby 3.3
RoR and whatever C++ based web backend there is count as a valid comparison in my book. But comparing the languages itself is maybe a bit off.
On a side note, you can actually compare their performance here if you’re really curious. But take it with a grain of salt since these are synthetic benchmarks.
https://www.techempower.com/benchmarks
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API: Go, .NET, Rust
Most benchmarks you'll find essentially have someone's thumb on the scale (intentionally or unintentionally). Most people won't know the different languages well enough to create comparable implementations and if you let different people create the implementations, cheating happens. The TechEmpower benchmarks aren't bad, but many implementations put their thumb on the scale (https://www.techempower.com/benchmarks). For example, a lot of the Go implementations avoid the GC by pre-allocating/reusing structs or allocate arrays knowing how big they need to be in advance (despite that being against the rules). At some point, it becomes "how many features have you turned off." Some Go http routers (like fasthttp and those built off it like Atreugo and Fiber) aren't actually correct and a lot of people in the Go community discourage their use, but they certainly top the benchmarks. Gin and Echo are usually the ones that are well-respected in the Go community.
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Rage: Fast web framework compatible with Rails
There is certainly a lot of speculation in Techempower benchmarks and top entries can utilize questionable techniques like simply writing a byte array literal to output stream instead of constructing a response, or (in the past) DB query coalescing to work around inherent limitations of the DB in case of Fortunes or DB quries.
And yet, the fastest Ruby entry is at 274th place while Rails is at 427th.
https://www.techempower.com/benchmarks/#hw=ph&test=fortune&s...
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Node.js – v20.8.1
oh what machine? with how many workers? doing what?
search for "node" on this page: https://www.techempower.com/benchmarks/#section=data-r21
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Strong typing, a hill I'm willing to die on
JustJS would like a word https://www.techempower.com/benchmarks/#section=data-r20&tes...
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Rust vs Go: A Hands-On Comparison
In terms of RPS, this web service is more-or-less the fortunes benchmark in the techempower benchmarks, once the data hits the cache: https://www.techempower.com/benchmarks/#section=data-r21
Or, at least, they would be after applying optimizations to them.
In short, both of these would serve more rps than you will likely ever need on even the lowest end virtual machines. The underlying API provider will probably cut you off from querying them before you run out of RPS.
What are some alternatives?
minisearch - Tiny and powerful JavaScript full-text search engine for browser and Node
zio-http - A next-generation Scala framework for building scalable, correct, and efficient HTTP clients and servers
Fuse - Lightweight fuzzy-search, in JavaScript
drogon - Drogon: A C++14/17 based HTTP web application framework running on Linux/macOS/Unix/Windows [Moved to: https://github.com/drogonframework/drogon]
elasticsearch-js - Official Elasticsearch client library for Node.js
django-ninja - 💨 Fast, Async-ready, Openapi, type hints based framework for building APIs
itemsjs - Extremely fast faceted search engine in JavaScript - lightweight, flexible, and simple to use
LiteNetLib - Lite reliable UDP library for Mono and .NET
TNTSearch - A fully featured full text search engine written in PHP
C++ REST SDK - The C++ REST SDK is a Microsoft project for cloud-based client-server communication in native code using a modern asynchronous C++ API design. This project aims to help C++ developers connect to and interact with services.
lunr.js - A bit like Solr, but much smaller and not as bright
SQLBoiler - Generate a Go ORM tailored to your database schema.