On syntax, in Haskell and Lisp

Yes, but not so much simplicity of syntax. I’m misled here by a superficial resemblance between the cultures of Haskell and Lisp. Both cultures are obsessed with mechanically processing code, and therefore want the language core to be as simple as possible. Since a minimal core is impractical to program in, both expect a larger, more useful language to be defined by translation to the core, so its complexity can be mechanically eliminated. And both consider the representation of code as text to be separate, at least in principle, from the core. So at first glance, it seems as if they should have the same attitude to syntactic complexity.

But they treat it quite differently. Lisp’s culture considers syntax unimportant, and therefore tries to make it as simple and transparent as possible, so it won’t prevent humans from seeing through it — because code is much more interesting than its textual representation. But Haskell’s culture considers syntax safely separate from the language core, and is therefore willing to tolerate complexity in it. Since it goes away without inflicting any complexity on the core, why shouldn’t it include whatever features are convenient?

Nit-picking languages

It’s that (too frequent) time again … when I anxiously (and full of fickleness) wonder what language to increase familiarity with.

The last year, I learnt quite a bit of common lisp, or atleast enough to write a lot of exploratory code in, working with libraries, timing, profiling, improving, and so on.

I had a rude shock when I learnt from one of my Scheme heroes that he really just prefers…

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Nit-picking languages

It’s that (too frequent) time again … when I anxiously (and full of fickleness) wonder what language to increase familiarity with.

The last year, I learnt quite a bit of common lisp, or atleast enough to write a lot of exploratory code in, working with libraries, timing, profiling, improving, and so on.

I had a rude shock when I learnt from one of my Scheme heroes that he really just prefers Haskell now. WTF? But seriously, he makes good points, chief among which is the lack of confidence in refactoring existing lisp code.

But both have the same “lack of libraries” barrier (sure, you’d say, why don’t you build your own — but that’s not the point).

So I’ve been moving around among these, toying with some web-development style languages (and always recoiling from JS), when I suddenly realized that I have absolutely zero experience with any of the .Net languages.

So, (just thinking out loud here) why not learn me some F#, and kill two birds with one stone?

Lisp, CLOS and Math

Lisp, CLOS and Math

What, you say, mathematicians just have to use Haskell ??

Stop right there, and read this.

Technically, there’s nothing new to see here at all. Lisp is high-level and low-level. Lisp is multi-paradigm. Lisp has uniform syntax. Blah blah blah. You’ve heard it all.

Still, some people seem to require an “argument from authority” (and usually still keep looking) … in which case you might be persuaded…

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Lisp, CLOS and Math

What, you say, mathematicians just have to use Haskell ??

Stop right there, and read this.

Technically, there’s nothing new to see here at all. Lisp is high-level and low-level. Lisp is multi-paradigm. Lisp has uniform syntax. Blah blah blah. You’ve heard it all.

Still, some people seem to require an “argument from authority” (and usually still keep looking) … in which case you might be persuaded by this.

An extract (describing how defclass and defgeneric can be handily abused to yield whatever you like):

For example, a mathematician who installs under CLOS the traditional mathematical categories must organize his work as follows:

  • The defclass statements will be used to define what a “set” object is, what a “group” object is, what a “chain complex” object is, and so on.

  • The defgeneric statements will be used to define functions working on these objects, but these “functions” are traditionally called in this case functors in mathematics; therefore one defgeneric statement for the sum functor, another defgeneric for the classifying space functor, and so on.

  • Finally each generic function will have various methods to adapt the generic function to specific cases; for example the product of two objects of some category is also an object of this category with the corresponding structure to be defined. Therefore one product method for the sets, another product method for the magmas, another method for the monoids, and so on. The call-next-method and change-class functions will allow these methods to possibly refer to the less specific ones.

Silicon Valley, and everything it stands for metonymically in our culture, has indeed affected billions of people around the planet. The innovations have come fast and furious, turning the past four decades into a series of “before and after” divides: before and after personal computers, before and after Google, before and after Facebook, iPhones, Twitter, and so forth. In the silicon age, “changing the world” means at bottom finding new and more ingenious ways to turn my computer or smart phone into my primary—and eventually my only—access to “reality.”