Some Notes About How I Write Haskell
blog.infinitenegativeutility.com
blog.infinitenegativeutility.com
Probably the most countercultural paragraph is the paragraph on recommending you make a fresh type rather than reuse an existing type. I think that you lose so many useful operations eschewing maybe for your uniquely named Maybe [1] that a type alias is probably a much better call there, and also captures what you meant more generically. Further, stuff like Maybe over a more specific instance works much better with valuable tools like Compose.
Similarly, the redundant constraint on Empty is the sort of thing that will only trip you up in the real world.
All in all, great article tho.
[1]: People underestimate the compiler cost of deriving instances. It adds up very fast if you derive lots of functors and foldables in your quest for unique names everywhere.
Seeing knowledgeable people comment on things written by other knowledgeable people seems to be the best way to learn how Haskell is done in the wild (i.e. anything outside the text I’m learning Haskell from at the moment)!
You can certainly do things the way Hedgehog does and it's great. I think many of the nice parts of Hedgehog are not incompatible with quickcheck.
This means these instances must be defined in standalone packages where they're necessarily orphans. The cultural prohibition against orphans means there aren't as many of these orphan instances packages as you'd like so you can end up redefining instances in every consumer project.
With the Hedgehog approach, there's no problem whatsoever with creating separate packages for these instances.
Do you pay this price when you derive via a `newtype`? Or does GHC figure out that the instance it would write out would be identical (modulo coercions)?
I found it understandable but for me the issue was: all the problems that author pointed out are true but you're not forced to make an instance of Arbitrary. I rarely do in my tests. But some times it really does make sense and in those cases it's nice to have.
That's irrelevant, as early computers weren't programmed in LC, not build on such an architecture. And of course algorithms and even programs (e.g for Babbage's computer) existed before LC.
However, most programming languages(including C, Java, etc.) look much more similar to lambda calculus than a description of a Turing Machine - and for very good reason. Have you ever tried describing a TM that encodes even the simplest logic? It is a pain in the ass.
Indeed, most courses on the theory of computation that discuss Turing Machines etc. don't ever expect students to fully describe a Turing Machine. Many times they use a language reminiscent of the lambda calculus to describe Turing Machines.
Just take a look at the definition of Turing Machines on wikipedia and examples of TMs: https://en.wikipedia.org/wiki/Turing_machine#Formal_definiti...
https://en.wikipedia.org/wiki/Turing_machine_examples
That resembles no description of programs that are written by humans to run on computer systems, unlike the lambda calculus.
That's because we don't actually have tape, but random access memory. But a turing machine is just a limited form of imperative programming, and much closer to Assembly, or C, Fortran, BASIC, or even Java, than Lambda Calculus.
>That resembles no description of programs that are written by humans to run on computer systems, unlike the lambda calculus.
Actually looks like a pretty run of the mill description of working with memory locations, gotos, conditional jumps and so on. Substitute the need to run through the tape for random access memory, and you're there.
The examples don't remind you of programs written by humans mostly because they're visual examples showing the whole state configuration. If we similarly mapped the memory states during various steps of the execution of a common imperative program, it would look very much like those tables.
The beauty of a declarative notation is not that you get to ditch representation of state, is that you can represent such state in a much more compact and tractable way than what is required by theoretical representations of imperative machines. Trying to do mathematical reasoning with Hoare logic is a pain in the ass.
- Donald Knuth
Incidentally, the earliest expression of this idea that I’ve seen is from a talk by Fischer Black [0] in 1963, published a year later in a volume on LISP [1]:
Programming style is not a matter of efficiency in a program. It is a matter of how easy it is to write or read a program, how easy it is to explain the program to someone else, how easy it is to figure out what the program does a year after you've written it; and above all, style is a matter of taste, of aesthetics, of what you think looks nice, of what you think is elegant.
Although style is mainly a matter of taste, a programmer with a "good" style will find his programs easy to write, easy to read, and easy to explain to others. ...
In particular, you may have acquired special programming tricks that you are very fond of, and that aren't used by other programmers, but that don't make your programs much more efficient. I urge you to stop using those tricks. As Samuel Johnson once said, "Read over your compositions, and when you meet with a passage which you think is particularly fine, strike it out."
In other words, make your style simple, not complicated, even though the complicated style may seem to have some abstract virtues. ...
0. Yes, this is the same Fischer Black of the Black-Scholes duo of financial fame. His PhD, informally supervised by Marvin Minsky, was on artificial intelligence. Myron Scholes, for that matter, was also a good programmer and made money programming for economics professors at Chicago while he did his PhD there.
1. F. Black, “Styles of Programming in LISP,” in The Programming Language LISP: Its Operations and Applications, ed. E. Berkeley and D. Bobrow (1964), p96 (p106 of the PDF): http://www.softwarepreservation.com/projects/LISP/book/III_L... [PDF]
Even for programs that are meant to be written and compiled once and never maintained, the programmer needs to build in their mind the whole story of the required computation, and put it in words for the compiler to transform it to low-level instructions. The clearer the programming language, the easier will be to reason about that story.
When a value is bound in do-notation, the pattern on the
left hand side of <- might not match. In this case, this
class provides a function to recover.
I'm not really sure of the future of the language. Most of the super committed community members are fans of the Haskell inspired style, which is great (its how I write Scala, personally) but I'm not sure why you'd then choose Scala over Haskell, or if you need the JVM, Eta or even Frege. The majority of 'casual' Scala people seem to use it as Kotlin with implicits more or less, and as more and more libraries and features come up for Kotlin I'm not even sure that it makes sense to use Scala for those people, given the larger backing, better tooling, easier on boarding, etc for Kotlin.
If you're looking for an ML kind of experience, Kotlin is a joke, it doesn't even have pattern matching.
Can't agree with this more. I just cannot figure the raison d'être of Kotlin.
If I had to build a company today Kotlin would definitely be at the top of my list; I may love other languages much more, but Kotlin and C# are easily at the top of the developer experience imo, since they've got great tooling/ecosystem/support and both are very approachable/average languages that won't really scare anyone away like how Haskell might (despite it being one of the most underrated/most scare monegered/most misunderstood languages out there imo)
ML on the JVM seems like a nice niche for it, but I'm not sure I really have seen libraries or Scala devs sorta advertise their style/library as ML inspired. I've seen OCaml mentioned as an inspiration to Scala before, but there are some notable differences between the two (e.g. inheritance vs structural typing)
http://www.lihaoyi.com/post/StrategicScalaStylePrincipleofLe...
especially the reasoning that you should try to avoid mutability, but when something is mutable, just make it mutable. This is much more in line with ML approach than with typical Haskell concerns around effects systems.
Just one example: Everybody pretends that e. g. the map function in collections is totally unrelated to the one in Futures, or the one in Slick, or the one in Quill, or the one in Spark. We all know that this is not just a random coincidence in naming.