papers-we-love VS learnxinyminutes-docs

Papers We Love (PWL) is a community built around reading, discussing and learning more about academic computer science papers. This repository serves as a directory of some of the best papers the community can find, bringing together documents scattered across the web. You can also visit the Papers We Love site for more info.

You might find the paper Out of the Tar Pit interesting if you haven't already read it: https://github.com/papers-we-love/papers-we-love/blob/main/d...

The ideas and approaches you talk about evoked some of the concepts from that paper for me. It talks a lot about separating accidental complexity and infrastructure so you can focus only on what is essential to define your solutions.

Sure he was expecting a practical language and was designing one. Lisp was from day zero a project to implement a real programming language for a computer.

Earlier he experimented with IPL and also list processing programming on Fortran. The plan was to implement a Lisp compiler. At first the Lisp code McCarthy was experimenting with, was manually translated to machine code.

Then came up the idea to use EVAL as a base for an interpreter, which was implemented by manually translating the Lisp code to machine language. Around 1962 then a compiler followed.

https://github.com/papers-we-love/papers-we-love/blob/main/c...

I'm in a 4th camp: we should be writing our applications against a relational data model and _not_ marshaling query results into and out of Objects at all.

Elaborations on this approach:

- https://github.com/papers-we-love/papers-we-love/blob/main/d...

- https://riffle.systems/essays/prelude/

The short ask: Anyone know of any projects that bring incremental view maintenance to SQLite?

The why:

Applications are usually read heavy. It is a sad state of affairs that, for these kinds of apps, we don't put more work on the write path to allow reads to benefit.

Would the whole No-SQL movement ever even have been a thing if relational databases had great support for materialized views that updated incrementally? I'd like to think not.

And more context:

I'm working to push the state of "functional relational programming" [1], [2] further forward. Materialized views with incremental updates are key to this. Bringing them to SQLite so they can be leveraged one the frontend would solve this whole quagmire of "state management libraries." I've been solving the data-sync problem in SQLite (https://vlcn.io/) and this piece is one of the next logical steps.

If nobody knows of an existing solution, would love to collaborate with someone on creating it.

[1] - https://github.com/papers-we-love/papers-we-love/blob/main/design/out-of-the-tar-pit.pdf

Here is a great Repo on GitHub named paers-we-love. You will surely find some great papers there and also some good other resources. Hope this helps.

However, f and g are interchangeable anywhere else (this is not actually true because their addresses can be obtained and compared; showing that a C-like language retains its referential transparency despite the existence of so-called l-values was the point of what I think is the first paper to introduce the notion referential transparency to the study of programming languages: https://github.com/papers-we-love/papers-we-love/blob/main/l...)

> Sure, maybe for some esoteric edge cases, but 5 mins on https://learnxinyminutes.com/ should get you 80% of the way there, and an afternoon looking at big projects or guidelines/examples should you another 18% of the way.

Not for C++, and even for other languages, it's not the language that's hard, it's the idioms.

Python written by experts can be well-nigh incomprehensible (you can save typing out exactly one line if you use list-comprehensions everywhere!).

Someone who knows Javascript well still needs to know all the nooks and crannies of the popular frameworks.

Java with the most popular frameworks (Spring/Boot/etc) can be impossible for a non-Java programmer to reason about (where's all this fucking magic coming from? Where is it documented? What are the other magic words I can put into comments?)

C# is turning into a C++ wannabe as far as comprehension complexity goes.

Right now, the quickest onboarding I've seen by far are Go codebases.

The knowledge tree required to contribute to a codebase can exists on a Deep axis and a Wide axis. C++ goes Deep and Wide. Go and C are the only projects I've seen that goes neither deep nor wide.

Learn x in y minutes: Concise tutorials to learn various programming languages and tools quickly.

StackOverflow's making their own competing LLM for all this stuff.

IMO, one of the biggest problems with the way people use LLMs right now, is that they're being treated as a single oracle: to know Java, it must be trained on examples of Java.

It would be much better if their language comprehension abilities were kept separated from their knowledge (and there are development efforts in this direction), so in this example it would be trained to be able to be able to read a Java tutorial rather than by actually reading a Java tutorial, so when the overall system is asked to write something in Java, the language model within the system decides to do this by opening https://learnxinyminutes.com and combining the user query with the webpage.

I think this will help make the models more compact, which is a benefit all by itself, but it would also mean that knowledge can be updated much more easily.

Someone would have to actually do this in order to see if those benefits are worth the extra cost of having to load a potentially huge a tutorial into the context window, and likewise the extent to which a more compact training set makes the language comprehension worse.

The project was created and is maintained by Adam Bard, but is open sourced with over 1.7k contributors since 2013

https://github.com/adambard/learnxinyminutes-docs

So you have studied programming for at least 5 years, what kinds of programs have you written? Apparently you have already applied your skills, since you have "created a good reputation among developers"? Why a time-frame of 20 years, why not 20 months or 20 weeks? Heck, you can learn a lot in even 20 days!

Once you have learned a few languages, libraries and frameworks then learning new stuff becomes much easier. At that point I'd recommend to check the website https://learnxinyminutes.com. Meanwhile, continue asking questions here and elsewhere :)

An other tip, if you are into computer science and algorithms stuff I recommend you try to solve problems which are posted at https://codegolf.stackexchange.com. You don't need to try solving them in less than X characters, but just to get them solved by any means necessary. And don't take too much bad influence from the posted solutions.

If you want a brief overview, go to https://learnxinyminutes.com/ and look for Javascript. I guess it should be roughly the time it took to learn C++ or possibly less, but JS has its own quirks. Often learning a second language is difficult as the first.

Very light compared to the other resources people have linked for you, but I love https://learnxinyminutes.com/