igel
rupy
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igel
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Show HN: Machine learning automation from creating to using models in production
Thanks for the feedback! When I first started the project, it was not thought for production. Just for fast prototyping and experimenting with no efforts at all. However, users liked the tool and started requesting more features including support for serving models and eventually deploying (e.g this issue https://github.com/nidhaloff/igel/issues/62)
I agree with your point of vue. However, igel is fairly new and evolving fast. Using igel to serve trained model is a new feature that was implemented in the new release so igel has a long way to go in order to be a solid product for production use.It will surely get more mature with time.
Finally, notice that I didn't recommend running it in production. Just mentioned that it is possible and takes no efforts at all. However, if the user generated a trained model then anything can be done with it from there. Technically, the user can implement his/her own server and use the model as wanted. Obviously, users should do that if they want more control ;)
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Sponsoring open source projects, share about your project
- igel: https://github.com/nidhaloff/igel a delightful tool that allows using ML without writing code. I'm also working on an even simpler cross-platform frontend for it written in electronjs (check it here https://github.com/nidhaloff/igel-ui)
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Ask HN: What are some tools / libraries you built yourself?
Last year I built deep-translator https://github.com/nidhaloff/deep-translator
I wanted a tool where multiple translators are integrated and where I can get translations from different sources but only using one tool. I then tried to build a cross platform mobile app using python (which is not the best language for this, I know) https://github.com/nidhaloff/Translator-pp
Probably the best project I built/started last year is the machine learning package igel: https://github.com/nidhaloff/igel
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Weekly Developer Roundup #16 - Sun Oct 04 2020
Show HN: Igel – A CLI tool to run machine learning without writing code: https://github.com/nidhaloff/igel
rupy
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Considerations for a long-running Raspberry Pi
I have been running a Raspberry 2 cluster for 10 years: http://host.rupy.se
A few weeks back the first SD card to fail got so corrupted it failed to reboot!
My key learning is use oversized cards, because then the bitcycle will wear slower!
I'm going from 32GB to 256/512/1024!
- Sandstorm: Open-source platform for self-hosting web app
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You Want Modules, Not Microservices
I think we're all confused over the definition. Also one might understand what all the proponents are talking about better if they think about this more as a process and not some technological solution:
https://github.com/tinspin/rupy/wiki/Process
All input I have is you want your code to run on many machines, in fact you want it to run the same on all machines you need to deliver and preferably more. Vertically and horizontally at the same time, so your services only call localhost but in many separate places.
This in turn mandates a distributed database. And later you discover it has to be capable of async-to-async = no blocking ever anywhere in the whole solution.
The way I do this is I hot-deploy my applications async. to all servers in the cluster, this is what a cluster node looks like in practice (the name next to Host: is the node): http://host.rupy.se if you click "api & metrics" you'll see the services.
With this not only do you get scalability, but also redundancy and development is maintained at live coding levels.
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I wish my web server were in the corner of my room
I have hosted my own web server both physically and codevise since 2014.
It's on a Raspberry 2 cluster:
Since 2016 i have my own database also coded from scratch:
We need to implement HTTP/1.1 with less bloat, a C non-blocking web server that can share memory between threads is probably the most interesting project for humans right now, is anyone working on that?
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Ask HN: Free and open source distributed database written in C++ or C
I have one in Java: https://github.com/tinspin/rupy
Here is the 2000 lines of code of the entire database: http://root.rupy.se/code?path=/Root.java
And here you can try it out: http://root.rupy.se
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Dokku – Free Heroku Alternative
The smallest PaaS you have ever seen is one order of magnitude larger than mine: https://github.com/tinspin/rupy
And I bet you the same goes for performance, if not two!
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Server-Sent Events: the alternative to WebSockets you should be using
Absolutely not, HTTP/1.1 is the way to make SSE fly:
https://github.com/tinspin/rupy/wiki/Comet-Stream
Old page search for "event-stream"... Comet-stream is a collection of techniques of which SSE is one. My findings are that SSE go through anti-viruses better!
I would look at my own app-server: https://github.com/tinspin/rupy
It's not the most well documented but it's the smallest implementation while still being one of the most performant so you can learn more than just SSE.
The data is here: http://fuse.rupy.se/about.html
Under Performance. Per watt the fuse/rupy platform completely crushes all competition because of 2 reasons:
- Event driven protocol design, averages at about 4 messages/player/second (means you cannot do spraying or headshots f.ex. which is another feature in my game design opinion).
- Java's memory model with atomic concurrency which needs a VM and GC (C++ copied that memory model in C++11, but it failed completely because they lack both VM and GC, but that model is still to this day the one C++ uses), you can read more about this here: https://github.com/tinspin/rupy/wiki
You can argue those points are bad arguments, but if you look at performance per watt with some consideration for developer friendlyness, I'm pretty sure in 100 years we will still be coding minimalist JavaSE on the server and vanilla C (compiled with C++ compiler) on the client.
- Jodd – The Unbearable Lightness of Java
What are some alternatives?
huproxy
Home Assistant - :house_with_garden: Open source home automation that puts local control and privacy first.
cmdg - Command line Gmail client
Nullboard - Nullboard is a minimalist kanban board, focused on compactness and readability.
cakephp-swagger-bake - Automatically generate OpenAPI, Swagger, and Redoc documentation from your existing CakePHP code.
GoJS, a JavaScript Library for HTML Diagrams - JavaScript diagramming library for interactive flowcharts, org charts, design tools, planning tools, visual languages.
dbmate - :rocket: A lightweight, framework-agnostic database migration tool.
Aerospike - Aerospike Database Server – flash-optimized, in-memory, nosql database
simonw - https://simonwillison.net/2020/Jul/10/self-updating-profile-readme/
AI-Expert-Roadmap - Roadmap to becoming an Artificial Intelligence Expert in 2022
Pion WebRTC - Pure Go implementation of the WebRTC API
profanity - Ncurses based XMPP client