flexsearch VS nanoid

Full-text search is powered by FlexSearch and Nextra will index all of your pages at build time ⚡.

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:

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.

Try using a proper browser search like Lunr or Flexsearch

Current version of FlexSearch (0.7.2) is not typo tolerant, see https://github.com/nextapps-de/flexsearch/issues/118

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 ?

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.

Javascript seems to have a comprehensive in memory solution https://github.com/nextapps-de/flexsearch

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.

Our API is in node. And God, how I suffered to import nanoid in an esmodule project. I had to vendor it, since using a previous version was not ideal. With bun, we can no longer worry about that. Just import what you need and done.

No thread about UUID is complete without a plug for NanoID! https://github.com/ai/nanoid/blob/main/README.md

Generate a unique file name using the nanoid library.

The syntax should read similar to SQL itself. We’re using a Python port of nanoid to generate our IDs. There’s only one thing missing… how do we actually create the table?

I usually go for Nano Id for new projects https://github.com/ai/nanoid

Nano ID

In another comment I mentioned I use nanoid in my projects now. It has a default space of 64^21 and has an a page where you can play with key lengths and alphabet sizes and see the probability of collisions :

https://zelark.github.io/nano-id-cc/

At the default 64 character alphabet with a 21 character key length it would take ~41 million years in order to have a 1% probability of at least one collision if you generated 1000 ids per second.

Using randomly generated IDs like Nano ID could be a good alternative, however, as a developer, we must understand what Nano ID really does in our application. Defining the number of characters in the generated IDs is also important, to help with that Nano ID has a Collision Calculator to give us how many years in order to have a 1% probability of collision.

IDs used here for buttons and tasks must be unique to work correctly. This is ensured by using the nanoid package, which automatically generates unique ids.