I noticed the same thing, having also written an interpreter for the Wolfram language that focused on the core rule/rewriting/pattern language. At its heart it’s more or less a Lisp-like language where the core can be quite small and a lot of the functionality built via pattern matching and rewriting atop that. Aside from the sheer scale of WL, I ended up setting aside my experiments replicating it when I did performance comparisons and realized how challenging it would be to not just match WL in functionality but performance.

Woxi reminds me of some experiments I did to see how far vibe coding could get me on similar math and symbolic reasoning tools. It seems like unless you explicitly and very actively force a design with a small core, the models tend towards building out a lot of complex, hard-coded logic that ultimately is hard to tune, maintain, or reason about in terms of correctness.

Interesting exercise with woxi in terms of what vibe coding can produce. Not sure about the WL implementation though.

(For context, I write compiler/interpreter tools for a living - have been for a couple decades)

implementing addition in woxilang itself?? this gotta be terribly slow. am i missing something?

Switching out to an interpreted language has got to be anathema to a rewrite-it-in-Rust project

You are missing the term "JIT", which would enable a host of runtime optimizations which include generating calls to some static piece of native code which performs addition.

Oh cool, haven't heard of this before. Could be a good fit - I'll have to try it out some day!

Mh, I thought about this a little and came actually to exactly the opposite conclusion: Implement as much as possible in Rust to get the fastest code possible. Do you have any more insights why this should not be possible / unsustainable?

Sure, but you've got to start somewhere! And with the amount of progress I was able to make in just a few weeks, I'm very optimistic that the polish will come sooner rather than later.

Maybe http://texmacs.org would fit here!

Thank you for sharing this on HN.

It's a worthwhile effort. If successful, Woxi can enable a large mass of scientists and engineers who don't have access to Mathematica to run legacy code written for it. Also, Woxi would give those scientists and engineers who regularly use Mathematica a non-proprietary, less restrictive alternative, which many of them would welcome.

How does Woxi compare to other "clean-room implementations"[a] of the same language?

--

[a] Please check with a lawyer to make sure you won't run into legal or copyright issues.

Half-assed reimplementations of existing software (often in the name of "memory safety") is what the Rust community is best known for.

Similarly I'm not sure Octave ever really got that polish to compete with MATLAB.

SPSS is hilariously painful to use. Still it's only losing ground ever so slowly. PSPP remains almost unheard of among SPSS core users.

Yeah, the Mathematica language is the least interesting aspect of the Mathematica system. Closely followed by the interactive notebooks.

Why should I want them to use it?

There's a mystique around Mathematica's math engine. Is this groundless, or will you eventually run into problems getting correct, identical answers -- especially for answers that Mathematic derives symbolically? The capabilities and results of the computer algebra systems that I've used varied widely.

How does it compare to mathics?

How close is it to being able to run rubi: https://rulebasedintegration.org/?

Interesting, thanks for sharing. Naive question as I'm not familiar with Mathematica much (but aware of it and Wolfram Alpha and related tools), how does it compare to e.g. Jupyter or Julia or maybe another language (with its framework) that might be even closer?

What percentage of the overall code was written primarily by agents?

LSP?

How is the popularity/rank in functions.csv determined?

You have two distinct products 1) An interpreter 2) a math language. Don't write your math in some funny imperative computer language.

Keep the interpreters surface area as small as possible. Do some work to make sure you can accelerate numeric, and JIT/compile functions down to something as close to native as you can.

Wolfram, and Taliesin Beynon have both said Wolfram were working internally to get a JIT working in the interpreter loop. Keep the core small, and do that now while it's easy.

Also, it's just easier to write in Mathematica. It's probably 10x smaller than the rust code:

    f[x_Integer]:=13*x;
    f::help:="Multiplies x by 13, in case you needed an easy function for that."

EDIT: Another important thing to note is the people who really deeply know specific subjects in math won't be the best, or even good rust programmers. So letting them program in woxilang will give the an opportunity to contribute which they wouldn't have had otherwise.

Symbolic manipulation?

Such a massive undertaking would be almost impossible without AI agents, so yeah, they help me. But with around 5000 tests, they are actually helping to improve the software quality!

i'm curious if you intend to reimplement highly optimized numerical algorithms, symbolic algorithms, and so on, accumulated and tuned in mathematica since its 1988 release?

it's a huuuuuuuuge amount of technology in the standard library of mathematica, beyond the surface syntax and rewrite system, i mean.

I find rust to be the best language and tool set in most categories. I still agree with this characterization.

The notebooks were THE thing of Mathematica, at least to me. 12 years ago, as I was finishing my PhD in quantum optics, I wanted to migrate to the stack used in industry - and picked Python. Also, that way I was an early adopter of Jupyter Notebook, as it captured what was need + was open.

Now Mathematica notebooks (still remember, it is .nb) do not have the novelty factor. But they were the first to set a trend, which we now take for granted.

That said, I rarely use notebooks anymore. In the coding time, it is much easier to create scripts and ask to create a visualization in HTML.

Based on the list of contributors to your project, I am not sure this starting location is optimally suited to the task of building a foundation for polished, reliable, expandable software.

I am not sure Octave ever had to put on that much polish. It just had to be decent enough to save $$$$ vs a Matlab license. If it can drop-in run the code that has been keeping the lab going for decades, good enough.

Mathematica is proprietary software. Any reimplementation is better than nothing at all, at least for people that don't run proprietary software

> Closely followed by the interactive notebooks.

Mathematica's notebooks are the only environment where I can do some computation to arrive at a symbolic expression. Copy the expression from the output cell into a new input cell. Then manipulate it by hand into the form I want. Then continue processing it further.

Also, symbolic expressions can be written nicely with actual superscripts and subscripts, and with non-latin characters.

One of the best features of Mathematica system.

According to https://en.wikipedia.org/wiki/Lotus_Development_Corp._v._Bor...., a software clone does not infringe software copyright. So yeah, I'd guess sooner or later everything is going be cloned …

You can find the whole integration routine here https://github.com/ad-si/Woxi/blob/36343ab2cbc97e5081f7c811e.... It's essentially a test mock-up (not even trying partial fraction decomposition for rational functions).

Not yet, but on the roadmap!

That's actually a value that Wolfram determines themselves. Here is the documentation for it: https://reference.wolfram.com/language/ref/WolframLanguageDa...

Here is e.g. all the values for the Plus[] function:

$ wolframscript -code 'WolframLanguageData["Plus", "Ranks"]' {All -> 6, StackExchange -> 8, TypicalNotebookInputs -> 5, TypicalProductionCode -> 6, WolframAlphaCodebase -> 6, WolframDemonstrations -> 4, WolframDocumentation -> 4}

Did you actually review 313,397 LOC written by claude? And you wrote the tests? That's honestly very impressive if yes.

I disagree, the language itself is one of the more elegant parts of the system, and enables a lot of the rest of the elegance.

From a purely programming language theory, it's pretty unique.

I once tried to find a language that had all the same properties, and I failed. The Factor language is probably the closest. But they are still pretty different.

First I believe there is no such thing as the Mathematica language, it's Wolframscript which is useful in a bunch of different applications. And second, if you don't have access to a $1000 / yr wolfram subscription, this would be the next best thing.

Well it would get vastly more popular if it was officially endorsed. Do you want lots of people using it?

Have you considered using quickcheck/random/property-based testing with LLM code generation to automate function implementation?

Why would I use this and not Wolfram Script?

Better license? Allowed for commercial operations?

> what's stopping some employee from something like Mathematica from taking the source code and having an agent port it to open source

Laws against theft. Also the same reason employees don't release the code on pastebin or something.

> Who owns an algorithm?

The org or person who was granted the software patent. https://en.wikipedia.org/wiki/Software_patent

> Will everything get copied eventually?

If we're lucky. More likely everything bitrots as technical capabilities are lost. Slowly at first, then quickly.

I think Wolfram Language is just so much more ergonomic. No need to import dependencies - everything's included and consistent, very readable - yet compact - syntax, less gotchas than Python, R, etc., sensible default, …

Hard to tell honestly. So far there was always some surprisingly straight forward solution If had any problems with the math engine. There is actually a lot of public research how equations can be solved/simplified with computer algorithms. So I'm optimistic. I also stumbled upon a few cases where Mathematica itself didn't quite do things correctly itself (rounding errors, missing simplifications, etc.). So maybe it's actually a little overhyped …

In that case I kindly refer you to the matter of Arkell v. Pressdam.

Useless thing is not less useless by the virtue of being FOSS. That's something FOSS folks have yet to understand.

All the best to the author, they definitely have fun doing this, but I've seen enough of such attempts. Having agents doesn't make much difference.

It's having ~ 5000 tests already. Used correctly, AI agents can help you improve the quality of the code!

The sneering on HN really has no end. This is a good project! I for one am very excited to see an interpreter born out of rust.

MathWorks offers a huge list of "toolboxes", domain specific extensions that cover a lot of features in each domain. Replacing Matlab isn't about the core language alone.

> It just had to be decent enough to save $$$$ vs a Matlab license

And it failed at this.

Have a look at TeXmacs! (https://texmacs.org)

(AFAIK, you can run Mathematica sessions in TeXmacs, get proper typesetting, and can copy/paste expressions for simplification by hand or using other CAS sessions in the same TeXmacs document).

The relevant programming paradigm is string/term rewriting, which is featured in other programming languages such as Pure. It seems to have few direct applications outside of symbolic computing itself, compilers and related fields such as PL theory. (Formal calculi and languages are often specified in PL theory as rewrite rules, even though the practical implementation may ultimately differ.)

They rebranded it to Wolfram Language a few years ago (which I actually appreciate, as it is so much more than just "math" by now!)

https://writings.stephenwolfram.com/2013/02/what-should-we-c...

Exactly! And:

- Faster startup time because of no license check

- Can run multiple instances of Woxi at the same time

- Embeddable via WASM

- Configurable via compile time flags (which features should be included)

- …

Ymmv, but I've found that you sure do need to import things eventually, and it's not so ergonomic because most projects just end up as mega-notebooks.

Just like Python or any other language that looks easy for the learning examples, there are still hairy bits, they're just better hidden. The difference is that the debuggers for Python are far better.

Mathematica is great for quick stuff, but once you hit a particular level complexity it goes crazy. In this regard I find it similar to Bash.

I also found problems with integrating some obscure functions a few years black, though IIRC the issue was remedies by using the amazing Rubi package:

https://rulebasedintegration.org/

Why is that important?

Yeah, I've already looked into it, but decided to keep developing it "example driven" for now. Aka I'm playing around with it, and whenever I find something that's broken I keep a note of it and then I pick those notes one by one and implement them. Once the most common things are implemented I will start writing property tests to catch all the edge cases of each feature.

Which patent are you referring to?

are all the tests hand written or are some agent-contributed? curious

It's a defense mechanism. I was guilty as charge as well initially. Suddenly most of your l33t skillz are trivialized and surpassed by an inhumane actor. It's a tough pill to swallow.

It’s so obnoxious

God help us.

Do you see why this perspective is a red flag on its own?

Which often means that e.g. loading an image for displaying it increases cost by a few thousands

I did my PhD with Octave. Sure, I did not have this nice convex optimization toolbox. But I had everything else I needed and did not need to wait because people arrived earlier in the lab and grabbed all floating licenses of, for instance, the communications toolbox.

However, I switched to Python during the last years.

Because you get changes upstreamed.

I'm saying you can go even further and automate the entire thing using LLMs/agents, it is pretty much the ideal use case: you have a black-box reference implementation to test against; descriptive documentation for what the functions should do; some explicitly supplied examples in the documentation; and the ability to automatically create an arbitrary number of tests.

So not only do you have a closed loop system that has objective/automatic pass-fail criteria you also don't even have to supply the instructions about what the function is supposed to do or the test cases!

Obviously this isn't going to be 100% reliable (especially for edge cases) but you should be able to get an enormous speed up. And in many cases you should be able to supply the edge case tests and have the LLM fix it.

(Codex is still free for the next few days if you want to try their "High"/"Extra high" thinking models)

Any patent. The question was who owns a (arbitrary) algorithm. The elaborated answer is that nobody “owns” an algorithm (i.e. has intellectual property rights to it) without a patent: in USA and many other jurisdictions, patents are the IP tool relating to algorithms.

I certainly don't. If a software developer has found a way to use these tools that works well for them and produces good results, that's a good thing.

What’s the difference if you review the code getting merged?

The price tags are wild for sure. But the sheer number of supported features is what makes them attractive. Cloning that completely is practically infeasable.

No I don’t, review your code

You accidentally raise an interesting point: good, thorough public documentation, once considered a great selling point for your system, now invites automated reimplementation by competition. It would be a shame to see public docs vanish because it turns out they are literally machine readable specs.

i mean idk that's sorta like asking what's the difference of having tests if you review the code getting merged

Reviewing the correctness of code is a lot harder than writing correct code, in my experience. Especially when the code given looks correct on an initial glance, and leads you into faulty assumptions you would not have made otherwise.

I'm not claiming AI-written and human-reviewed code is necessarily bad, just that the claim that reviewing code is equivalent to writing it yourself does not match my experience at all.

The difference is we can't tell if you reviewed the code.

If I go by the contributor numbers on Github, I see Claude has committed something on the order of 300,000 lines of code. I don't think it's reasonable to review that much code, even in weeks worth of time.

Plus if you look at the commit cadence there is a lot of commits like 5-10 minutes a part in places that add new functionality (which I realize doesn't mean they were "written" in that time)

I find people do argue a lot about "if it is reviewed it is the same" which might be easy when you start but I think the allure of just glancing going "it makes sense" and hammering on is super high and hard to resist.

We are still early into the use of these tools so perhaps best practices will need to be adjusted with these tools in mind. At the moment it seems to be a bit of a crap shoot to me.

To be fair, we also couldn’t tell for sure if they hand-wrote the code.

If they hand wrote the code we know they at least looked at it once.