The main property of SGML-derived languages is that they make "list" a first class object, and nesting second class (by requiring "end" tags), and have two axes for adding metadata: one being the tag name, another being attributes.
So while it is a suitable DSL for many things (it is also seeing new life in web components definition), we are mostly only talking about XML-lookalike language, and not XML proper. If you go XML proper, you need to throw "cheap" out the window.
Another comment to make here is that you can have an imperative looking DSL that is interpreted as a declarative one: nothing really stops you from saying that
totalOwed = totalTax - totalPayments
totalTax = tentativeTaxNetNonRefundableCredits + totalOtherTaxes
totalPayments = totalEstimatedTaxesPaid +
totalTaxesPaidOnSocialSecurityIncome +
totalRefundableCredits
means exactly the same as the XML-alike DSL you've got.One declarative language looking like an imperative language but really using "equations" which I know about is METAFONT. See eg. https://en.wikipedia.org/wiki/Metafont#Example (the example might not demonstrate it well, but you can reorder all equations and it should produce exactly the same result).
Or, y'know, use the language you have (JavaScript) properly, eg. add a `sum` abstraction instead of `.reduce((acc, val) => { return acc+val }, 0)`.
In particular, the problem of "all the calculations are blocked for a single user input" is solved by eg. applicatives or arrows (these are fairly trivial abstract algebraic concepts, but foreign to most programmers), which have syntactic support in the abovementioned languages.
(Of course, avoid the temptation to overcomplicate it with too abstract functional programming concepts.)
If you write an XML DSL:
1. You have to solve the problem of "what parts can I parallelize and evaluate independently" anyway. Except in this case, that problem has been solved a long time ago by functional programming / abstract algebra / category-theoretic concepts.
2. It looks ugly (IMHO).
3. You are inventing an entirely new vocabulary unreadable to fellow programmers.
4. You will very likely run into Greenspun's tenth rule if the domain is non-trivial.
{"GreaterOf": [
{"Value": [0, "Dollar"]},
{"Subtract": [
{"Dependency": ["/totalTentativeTax"]},
{"Dependency": ["/totalNonRefundableCredits"]}
]}
]}
Basically, a node is an object with one entry, whose key is the type and whose value is an array. It's a rather S-expressiony approach. if you really don't like using arrays for all the contents, you could always use more normal values at the leaves: {"GreaterOf": [
{"Value": {"value": 0, "kind": "Dollar"}},
{"Subtract": {
"minuend": {"Dependency": "/totalTentativeTax"},
"subtrahend": {"Dependency": "/totalNonRefundableCredits"}
}}
]}
It has the nice property that you're always guaranteed to see the type before any of the contents, even if object keys get reordered, so you can do streaming decoding without having to buffer arbitrary amounts of JSON. Probably not important when parsing a tax code, but can be useful for big datasets.EDIT: obviously, JSON tooling sprang up because JSON became the lingua franca. I meant that it became necessary to address the shortcomings of JSON, which XML had solved.
1. https://gitlab.com/canvasui/canvasui-engine/-/blame/main/exa...
2. https://gitlab.com/canvasui/canvasui-engine/-/blob/main/exam...
In unrelated news, the main author of the VAT Act is offering tax consulting services, as Registered Tax Advisor #00001.
It's one of many equivalent such parser tools, a particularly verbose one. As such it's best for stuff not written by hand, but it's ok for generated text.
It has some advantages mostly stemming from its ubiquity, so it has a big tool kit. It has a lot of (somewhat redundant) features, making it complex compared to other options, but sometimes one of those features really fits your use case.
It was also about how easy it was to generate great XML.
Because it is complicated and everyone doesn't really agree on how to properly representative an idea or concept, you have to deal with varying output between producers.
I personally love well formed XML, but the std dev is huge.
Things like JSON have a much more tighter std dev.
The best XML I've seen is generated by hashdeep/md5deep. That's how XML should be.
Financial institutions are basically run on XML, but we do a tonne of work with them and my god their "XML" makes you pray and weep for a swift end.
My experience has been the people complaining about it were simply not using automated tools to handle it. It’s be like people complaining that “binaries/assembly are too hard to handle” and never using a disassembler.
For comparison JSON is a terrible markup language, a pretty good data interchange format, and again, a deeply regrettable programing language. I don't know if anyone has put programing language in straight JSON (I suspect they have shudders) but ansible has quite a few programing structures and is in YAML which is JSON dressed in a config language's clothes.
However as a counter point to my json indictment, it may be possible to make a decent language out of it, look to lisp, it's S-expressions are a sort of a data interchange format(roughly equivalent to json) and it is a pretty good language.
Heh, a couple of years ago I walked past a cart of free-to-take discards at the uni, full of thousand-page tomes about exciting subjects like SOAP, J2EE and CORBA. I wonder how many of the current students even recognized any of those terms.
In Norway, we've had a more or less automated tax system for many years; every year you get a notification that the tax settlement is complete, you log in and check if everything is correct (and edit if desired) and click OK.
It shouldn't be more difficult than this.
If I do, the IRS will be the first to know about it! I'll staple an announcement to my 1040. ;-)
Welcome to SWI-Prolog (threaded, 64 bits, version 9.2.9)
?- use_module(library(clpBNR)).
% *** clpBNR v0.12.2 ***.
true.
?- {TotalOwed == TotalTax - TotalPayments}.
TotalOwed::real(-1.0Inf, 1.0Inf),
TotalTax::real(-1.0Inf, 1.0Inf),
TotalPayments::real(-1.0Inf, 1.0Inf).
?- {TotalOwed == TotalTax - TotalPayments}, TotalTax = 10, TotalPayments = 5.
TotalOwed = TotalPayments, TotalPayments = 5,
TotalTax = 10.
If you restrict yourself to the pure subset of prolog, you can even express complicated computation involving conditions or recusions.
However, this means that your graph is now encoded into the prolog code itself, which is harder to manipulate, but still fully manipulable in prolog itself.But the author talks about xml as an interchange format which is indeed better than prolog code...
JSON: No comments, no datatypes, no good system for validation.
YAML: Arcane nonsense like sexagesimal number literals, footguns with anchors, Norway problem, non-string keys, accidental conversion to a number, CODE INJECTION!
I don't know why, but XML's verbosity seems to cause such a visceral aversion in a lot of people that they'd rather write a bunch of boring code to make sure a JSON parses to something sensible, or spend a day scratching their head about why a minor change in YAML caused everything to explode.
Actually my own problem with XML was annoyance that back when I had the thought of doing a complex config format in XML, the idea of modifying it programmatically while retaining comments turned out to be absolutely non-trivial. In comparison with the mess one can make with YAML that's just a trivial thing.
1. standardize on JSON as the internal representation, and
2. write a simple (<1kloc) Python-based compiler that takes human-friendly, Pythonic syntax and transforms it into that JSON, based on operator overloading.
So you would write something like:
from factgraph import Max, Dollar # or just import *
tentative_tax_net_nonrefundable_credits = Max(Dollar(0), total_tentative_tax - total_nonrefundable_credits)
and then in class Node (in the compiler): def __sub__(self, other):
return SubtractNode(minuent=self, subtrachents=[other])
Values like total_nonrefundable_credits would be objects of class Node that "know where they come from", not imperatively-calculated numbers. The __sub__ method (which is Python's way of operator overloading) would return a new node when two nodes are subtracted.[0]: https://github.com/rsesek/ustaxlib
[1]: https://github.com/rsesek/ustaxviewer
[2]: https://github.com/rsesek/ustaxlib/blob/master/src/fed2019/F...
[3]: https://github.com/AustinWise/TaxStuff/blob/master/TaxStuff/...
const totalEstimatedTaxesPaid = writable("totalEstimatedTaxesPaid", {
type: "dollar",
});
const totalPayments = fact(
"totalPayments",
sum([
totalEstimatedTaxesPaid,
totalTaxesPaidOnSocialSecurityIncome,
totalRefundableCredits,
]),
);
const totalOwed = fact("totalOwed", diff(totalTax, totalPayments));
This way it's a lot terser, you have auto-completion and real-time type-checking.The code that processes the graph will also be simpler as you don't have to parse the XML graph and turn it into something that can be executed.
And if you still need XML, you can generate it easily.
Because of the tooling, you weren't actually writing the XML either, you used a custom built editor (a tree view with a property panel). It all sucked. I was looking at the thing trying to figure out if I could create an intermediate language with my own "compiler" to get around the xml editors they build.
Anyway, every developer hated it. All of them. Well, everyone but the guy that created the monstrosity anyway.
invoice "INV-001" for "ACME Corp"
item "Hosting" 100 x 3
item "Support" 50 x 2
tax 20%
invoice "INV-002" for "Globex"
item "Consulting" 200 x 5
discount 10%
tax 21%
In contrast to XML (even with authoring tools), my feeling is that XML (or any angle-bracket language tbh) is just too hard to write correctly (ie XML syntax and XMl schema parsing is very unforgiving) and has a lot of noise when you read it that obscures the main intent of the DSL code.Just kind of spitballing here, but in a world where can point AI at some good, or badly formed -- XML, json, toml whatever and just kind of say "hey, what's going on here, fix it?"
But please don't write DSLs anymore. If you have to, probably even just using Opus to write something for you is better. And AI doesn't like DSLs that can't be in its training base.
At work, we have an XML DSL that bridges two services. It's actually a series of API calls with JSONPath mappings. It has if-else and goto, but no real math (you can only add 1 to a variable though) and no arrays. Debugging is such a pain, makes me wonder why we don't just write Java.
That is so powerful and the reason domain driven design is still a powerful concept.
On the other hand it is horrible to read and write for humans. Nowadays I would rather use JSON with JSON Schema.
No, you don’t. Those are dependent on the actual implementation.
The XML layer is a neat looking storefront hiding the crimes being committed in the back room.
{
"path": "/tentativeTaxNetNonRefundableCredits",
"description": "Total tentative tax after applying non-refundable credits, but before applying refundable credits.",
"maxOf": [
{
"const": {
"value": 0,
"currency": "Dollar"
}
},
{
"subtract": {
"from": "/totalTentativeTax",
"amount": "/totalNonRefundableCredits"
}
}
]
}Oh and the universe is written in lisp (but mostly perl).
The markup includes self-describing metadata and constantly reminds the GPT model of explicit context.
…note this doesn’t really say much. Both are terrible.
preach. I'm convinced there are cycles in the tax code that can be exploited for either infinite taxes or zero taxes. Can Claude find them?