lovasoa

This resonates with me. I used to love tinkering with "underdog" tech. I did frontends in svelte before it was cool. But for new projects, I now always default to react+tailwind, because that's what Claude knows best. And for the backend, I'm working on a SQL-only framework, because LLMs are now at almost 100% accuracy on text-to-sql.

And since the gold supply is limited, fewer shovels would indeed be required.

Law enforcement could probably just ask cloudflare for the exact IP address that retrieved the attachment.

The principle of the software seems to be that the original data is never altered. It is a postgres extension that "masks" the data for certain postgres users. You can always connect as the root user and see everything when you need to.

Does anyone here know more about the unreliability of Google's sub claim? I am using it, and have never had issues with it, but this post seems to just dismiss it without more details.

When does Google change the subject of a token for a given user account?

Dashes in API keys are really annoying. Double-clicking doesn’t select the full key, which just adds extra hassle. It would be much better if they used a continuous string without any separators. Makes copying and pasting way easier, and doesn't affect security at all.

I have never heard of anyone in the developed world who would be afraid to criticize Al-Qaeda or the Taliban or Isis. Actually I have never heard anyone NOT criticize them when talking about them.

Making a good user interface is definitely not easy. Yet it's orders of magnitude easier than writing ffmpeg.

That said, there is nothing wrong with a paid wrapper around a large and complex open source library. Distributing their work more widely is not a disservice.

The best solution, that the LLM did not find, is

     def find_difference(nums):
         try: nums.index(3999), nums.index(99930)
         except ValueError: raise Exception("the numbers are not random")
         return 99930 - 3999

It's asymptotically correct and is better than O(n) :p

Starting with a Google Sheet is perfectly fine, but for building a non tabular user interface, or having a few thousand records, I would directly switch to something like SQLPage with a SQLite database.

The researchers leverage existing language Chain-of-Thought data, where each sample consists of a question, reasoning steps, and the final answer. At stage 0, the model does not generate any thought tokens, and is just trained to yield the reasoning traces and correct answers for the Chain-of-Thought samples. In the subsequent stages, at each stage, we remove one reasoning step from the sample, and instead add thought tokens. In the illustration above, a single thought token is added in each stage, instead of a single reasoning step, but this is controlled by a hyperparameter ‘c’.

All I want for Christmas is a good LSP for SQL ! Ideally one that would be customizable enough to allow SQLPage functions and parameters.

ccp is the Chinese version of c++. Or maybe they meant ссср, the Soviet version.

I would love to see it succeed!

They mention testing that bytecode generation generates the exact same results as SQLite... Does this exclude writing new optimization passes that are not in sqlite?

doesn't this apply to most websites on the web?

But aren't these folks already served well by PocketBase ?

And by the time they get a million user, they will probably not be hosting on a single "tiny box" anyway. At what point do you think : okay, I need PocketBase, but ten times faster ?

The project looks great !

But I wonder who the audience is... The website says "serve millions of customers from a tiny box". Who does this appeal to ?

Solo developers who have million of users, need very low latency, yet are happy with a just a SQLite database for their backend ?

This is a cool approach to integrating SQL with static site generation!

If you're into SQL-powered tooling, you might find something like https://sql-page.com interesting as a comparison point. It flips the model by letting you create dynamic web apps entirely in SQL, skipping the static file generatio step.

Anyways it's really nice to see new tooling removing a lot of the plumbing work needed to go from database to website.

From a practical standpoint, for anyone who needs to parse SQL today, I can recommend datafusion's sqlparser-rs. This is what we use in http://sql-page.com , and I regularly contribute to it. I don't know anything else that matches its level of support for all the crazy little-known syntax particularities of the various SQL dialects.

In particular, Microsoft SQL Server seems to do everything just a little bit differently, and sqlparser-rs does support its idiosyncrasies most of the time.

An interesting topic is how to fight Hyrum's law. A possibility is to add randomness in things you don't want people to rely on. If I remember well, this is what the QUIC protocol does. Some fields are unused in the current version, but required by the specification to be set to random values, not null bytes, so that routers don't start relying on them to identify the packets.

EDIT.

I think I found the source: https://www.rfc-editor.org/rfc/rfc9000#section-17.2.1

> The value in the Unused field is set to an arbitrary value by the server. Clients MUST ignore the value of this field. [...] Note that other versions of QUIC might not make a similar recommendation.

I think they call it "greasing", to prevent "ossification".

Optimizing out static expressions can be done in linear time at best. So if the number of clauses in WHERE is huge and the size of the underlying table is tiny (such as in the examples shown in the article we are commenting on), it will be better not to run the optimization.

But of course, in normal life, outside of the world of people having fun with Homomorphisms, queries are much smaller than databases.

The topic of huge queries on tiny databases makes me think of this recent discussion on the SQLite forum: https://sqlite.org/forum/forumpost/0d18320369

Someone had an issue because SQLite failed to optimize the following query

    select * from t where x = 'x' or '' = 'x'

Someone said that SQLite could not optimize out the "or '' = 'x'" because it would be too expensive to compute. Which is obviously true only for huge queries on tiny datasets.

This sounds like a cool project! Does anyone here knows how it compares to univerjs ?

I currently use univerjs to power the open source sql spreadsheet component I work on (https://github.com/sqlpage/sqlpage-spreadsheet/). My experience with it has been that it's very powerful, but quite difficult to use due to the boilerplate involved, the lacking documentation, and the fact that it seems to be developed mainly for the Chinese market.

> $ sqlite3 whois-log-copy.db "select source from queries"|sort|uniq|wc -l

Oh cool they saved the logs in a database ! Wait... |sort|uniq|wc -l ?? But why ?

I think getting support requests from users who don't know what they are doing is actually a great problem to have.

I have a project that allows building web applications out of SQL queries [1]. When I started receiving support requests by people who did not know SQL and were basically learning it along, I was thrilled. I was happy that my tool had a greater audience than I initially envisioned.

In any given domain, specialists are the minority. If the thing I am building is unexpectedly appealing to non-specialists, I rejoice, even if it means getting strange support requests. In the end, it helps me making the project more approachable and easy to use for everyone.

[1] https://sql.datapage.app

It's strange to call CTEs a "postgres feature". It's standard SQL, it's in all databases.

Thank you! I'd love to get your feedback if you use it.

I would even go further: this sounds like a database problem.

Is the set of ship positions and watched polygons entirely different from run to run? If not, it should be possible to go much faster than even the new rust based approach that takes 6 hours.

I would have used a postgres database with a PostGIS spatial index.

It's encouraging to see how digital tools are helping address the "legacy data backlog". This aligns well with the collaborative open-science approach.

For those interested, I recently translated an article by french archeologists on the same topic: https://sql.ophir.dev/blog.sql?post=How%20archaeology%20is%2...

How can it be a good idea to have a time limit for the compilation of expressions in a compiler ?

Doesn't that mean that your program can compile fine in the morning, and fail to compile in the afternoon because you have an HD youtube video playing in the background ?

Or the same program could compile fine on your computer, and fail to compile on less powerful CI servers ?