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Carl Zeiss, Explained by Asianometry (2021)
Source. This is where "fun" stuff is likely to be.
This doesn't do a hole lot. Ciro Santilli wouldn't really call it a web framework. It's more like a middleware. Real web frameworks are built on top of it.
Examples under: nodejs/express:
- nodejs/express/min.js: minimal example. Visit localhost:3000 and it shows
hello world. It is a bit wrong because the headers say HTML but we return plaintext. - nodejs/express/index.js: example dump with automated tests where possible. The automated tests are run at startup after the server launches. Then the server keeps running so you can interact with it.
Looks interesting.
It seems to abstract the part about the client messaging the backend, which focuses on being able to easily plug in a number of Front-end web framework to manage client state.
Uses Socket.IO, which allows the client Javascript to register callbacks when data is updated to achieve Socket.IO, e.g. their default chat app does:so that message appear immediately as they are sent.
client.service('messages').on('created', addMessage);Their standard template from But it is in itself a completely boring app with a single splash page, and no database interaction, so not a good showcase. The actual showcase app is feathersjs/feathers-chat.
feathers generate app on @feathersjs/cli@4.5.0 includes:which looks promising! They don't have a default template for a Front-end web framework however unfortunately: docs.feathersjs.com/guides/frameworks.html#the-feathers-chat lists a few chat app versions, which is their hello world:
- Front-end web framework: not built-in on generator, but there are some sample repos pointed from the documentation, and they did work out-of-box:
And there is no official example of the chat app that is immediately deployable to Heroku: FeathersJS Heroku deployment, all setups require thinking.
The idea is cool. It really unifies front-and back end.
But Ciro Santilli feels the approach proposed by FeathersJS of being a glue between bigger third-party Front-end web frameworks like React and backend (object-relational mapping) is more promising and flexible.
Front-end web framework integration: no native one:
- React:
- Vue.js:
- github.com/mikermcneil/ration Issue tracker disabled...
- live at: ration.io/
- selling a course at: courses.platzi.com/courses/sails-js/
- platzi.com/cursos/javascript-pro/ non-free and in Spanish pointed to from official README...
- Nuxt.js:
- github.com/mikermcneil/ration Issue tracker disabled...
TODO server-side rendering anyone??
- stackoverflow.com/questions/32412590/how-to-use-react-js-to-render-server-side-template-on-sails-js
- stackoverflow.com/questions/54217147/ssr-for-react-redux-application-with-sails
- gist.github.com/duffpod/746a660bcddfd986878c92dde1a04f06
- www.reddit.com/r/reactjs/comments/7saoqm/sailsjs_or_adonisjs_designed_for_server_side/
In this section we will use the file nodejs/bench_mem.js, tests are run on Node.js v16.14.2 from NVM, Ubuntu 21.10, on Lenovo ThinkPad P51 (2017) which has 32 GB RAM.
Related answer: stackoverflow.com/questions/12023359/what-do-the-return-values-of-node-js-process-memoryusage-stand-for/72043884#72043884
First using
topp from stackoverflow.com/questions/1221555/retrieve-cpu-usage-and-memory-usage-of-a-single-process-on-linux/40576129#40576129 let's observe the memory usage of some baseline cases.For a Node.js infinite loop nodejs/infinite_loop.jsThis gives approximately:
topp infinite_loop.js- RSS: 20 MB
- VSZ: 230 MB
Adding a single hello world to it as in nodejs/infinite_hello.js and running:leads to:We understand that Node.js preallocates VSZ wildly. No big deal, but it does mean that VSZ is a useless measure for Node.js.
topp infinite_hello.js- RSS: 26 MB
- VSZ: 580 MB
Forcing garbage collection as in nodejs/infinite_hello.js brings it down to 20 MB however:
topp node --expose-gc infinite_hello_gc.jsFinally let's see a baseline for which gives initially:but after a few seconds randomly jumps to:so we understand that
process.memoryUsage nodejs/infinite_memoryusage.js:node --expose-gc infinite_memoryusage.js{
rss: 23851008,
heapTotal: 6987776,
heapUsed: 3674696,
external: 285296,
arrayBuffers: 10422
}{
rss: 26005504,
heapTotal: 9084928,
heapUsed: 3761240,
external: 285296,
arrayBuffers: 10422
}First a baseline case with an array of length 1:This gives the same results as with:
node --expose-gc bench_mem.js n 1node --expose-gc infinite_memoryusage.js. The same result is obtained by doing:a = undefinednode --expose-gc bench_mem.js deallocIf we use we see that the memory is now, unsurprisingly, accounted for under Results for different N:We see therefore that typed arrays are much closer to what they advertise (4 bytes per element), even for smaller element counts, as expected.
Int32Array typed array buffers instead of a simple Array:node --expose-gc bench_mem.js array-buffer n NarrayBuffers, e.g. for N 1 million:{
rss: 31776768,
heapTotal: 6463488,
heapUsed: 3674520,
external: 4285296,
arrayBuffers: 4010422
}|| N
|| `arrayBuffers`
|| `rss`
|| `rss` per elem
| 1 M
| 4 MB
| 31 MB
| 5
| 10 M
| 40 MB
| 67 MB
| 4.6
| 100 M
| 40 MB
| 427 MB
| 4Now let's try one million objects of type gives:Disaster! Memory usage is up to 70 MB! Why?? We were expecting only about 24, 4 baseline + 2 * 10 for each million int?!
{ a: 1, b: -1 }:node --expose-gc bench_mem.js obj{
rss: 138969088,
heapTotal: 105246720,
heapUsed: 70103896,
external: 285296,
arrayBuffers: 10422
}And now an equivalent version using gives the same result.
class:node --expose-gc bench_mem.js classLet's try Array:is even worse at 78 MB!! OMG why.
node --expose-gc bench_mem.js arr{
rss: 164597760,
heapTotal: 129363968,
heapUsed: 78117008,
external: 285296,
arrayBuffers: 10422
}- www.cell.com/cell-systems/fulltext/S2405-4712(16)30120-X
- www.cell.com/cell-systems/fulltext/S2405-4712(16)30151-X A Genome-Scale Database and Reconstruction of Caenorhabditis elegans Metabolism Gebauer, Juliane et al. Cell Systems , Volume 2 , Issue 5 , 312 - 322
A Three-Dimensional Model of the Myoglobin Molecule Obtained by X-Ray Analysis (1958) by 
Ciro Santilli 40 Updated 2025-07-16
Ciro Santilli 40 Updated 2025-07-16To Ciro Santilli, a key observation is:Clearly the rich will be much, much more shielded by keeping large parts of their wealth in shares... from this point of view, it is insane to print money!!! Tax the rich instead...
The rich are more easily able to avoid the harm than poor and middle-class people [...] they are more likely to have large amounts of non-cash assets to shield themselves from inflation.
It is a shame, but this game just doesn't feel good. The controls are just not as snappy as Mario Kart 64, the levels are too wide which limits player interaction, and the weapons feel clumsy weak and unexciting. These are all aspects that the closed source smashkarts.io gets pretty well.
Pinned article: Introduction to the OurBigBook Project
Welcome to the OurBigBook Project! Our goal is to create the perfect publishing platform for STEM subjects, and get university-level students to write the best free STEM tutorials ever.
Everyone is welcome to create an account and play with the site: ourbigbook.com/go/register. We belive that students themselves can write amazing tutorials, but teachers are welcome too. You can write about anything you want, it doesn't have to be STEM or even educational. Silly test content is very welcome and you won't be penalized in any way. Just keep it legal!
Intro to OurBigBook
. Source. We have two killer features:
- topics: topics group articles by different users with the same title, e.g. here is the topic for the "Fundamental Theorem of Calculus" ourbigbook.com/go/topic/fundamental-theorem-of-calculusArticles of different users are sorted by upvote within each article page. This feature is a bit like:
- a Wikipedia where each user can have their own version of each article
- a Q&A website like Stack Overflow, where multiple people can give their views on a given topic, and the best ones are sorted by upvote. Except you don't need to wait for someone to ask first, and any topic goes, no matter how narrow or broad
This feature makes it possible for readers to find better explanations of any topic created by other writers. And it allows writers to create an explanation in a place that readers might actually find it.
Figure 1. Screenshot of the "Derivative" topic page. View it live at: ourbigbook.com/go/topic/derivativeVideo 2. OurBigBook Web topics demo. Source. - local editing: you can store all your personal knowledge base content locally in a plaintext markup format that can be edited locally and published either:This way you can be sure that even if OurBigBook.com were to go down one day (which we have no plans to do as it is quite cheap to host!), your content will still be perfectly readable as a static site.
- to OurBigBook.com to get awesome multi-user features like topics and likes
- as HTML files to a static website, which you can host yourself for free on many external providers like GitHub Pages, and remain in full control
Figure 2. You can publish local OurBigBook lightweight markup files to either OurBigBook.com or as a static website.
Figure 3. Visual Studio Code extension installation.
Figure 5. . You can also edit articles on the Web editor without installing anything locally. Video 3. Edit locally and publish demo. Source. This shows editing OurBigBook Markup and publishing it using the Visual Studio Code extension. 
- Infinitely deep tables of contents:
All our software is open source and hosted at: github.com/ourbigbook/ourbigbook
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