I've often felt that some people dislike types because they expect to be able to write code in a certain way that they know will make some very narrow happy path work now and they get really frustrated when the compiler tells them that there are other paths in the code that don't work. "Why is this stupid compiler slowing me down?!". This frustration betrays the programmer's indifference toward the broader quality of the project and their willingness to trade bugs in other paths for a feature that appears to be working. The cognitive mismatch is that it's intended change the way you think and program so you can move quickly on many paths at once (not only your very narrow happy path)--with a well-crafted type system, we can move fast and have quality. Note also that 'quality' isn't just about bugs, but also about a code base that is maintainable, similar to the GP's and the parent's observations about the unmaintainability of their PHP and Perl code bases.

Yea, I agree and for this reason when I teach type systems to new programming students, I tell them that a type is somewhat analogous to a building material. You have brick, wood, steel and iron. You want to build a house that has solid bedrock and has easy forest fires in the area. What material would you use? Most would say rock.

Then I tell them about strings and ints. You can represent 66 both with strings and ints, but one is usable for computation where the other one is simply usable to write Alice in Wonderland with it, or simpler forms of text. Sometimes I get the question then: why can't a string both be computational and as a means of character display? And then I list the upsides and downsides of such a system, just like the upsides and downsides of mixing brick and wood to build the outer wall of a house.

I'm curious if people can think of other analogies that they use for teaching.

Why do you need an analogy at all? Are your students deeply familiar with the construction characteristics of wood and brick already and ready to draw parallels to software? How do those things relate at all to the subject at hand, strings as “means of display” (data?) versus strings as “computational” (keywords, operators, etc?).

Personally, I avoid analogies because they usually mean I don’t really know how to teach the topic, and I’m “hand-waving” on the fly. I either find a way to build on the student’s existing knowledge or I “park” the topic for discussion when the student has enough knowledge to give a correct answer.

I appreciate analogies when I start learning something. Although it's not a perfect representation of what's being taught, it makes it easier for me to start thinking about the topic I'm learning. I can fill in the details later. I think it's useful for certain types of learners such as myself. Although I'm not deeply familiar with the characteristics of construction materials, I was more familiar with them compared to types when I was learning about them. So it would've been a helpful analogy for someone like me.

I don’t know if this is pedagogically useful, but I think of types as shapes, variables (including struct fields and function parameters) as a shaped hole, and values as a shaped thing that can fit (or not fit) into those holes. Kind of like the children’s toy. You don’t want to pass a circle in to a function that needs a square shaped thing, and the type system helps make sure you don’t do that by accident.

If we think of variables as boxes and types as label on those boxes, does it makes sense to have labels on the boxes if complexity of opening the box just to see what is inside goes up?

I think types also get in the way of writing speculative code, which is something I did a lot more often when I was new.

Run what you have so far. Print the last value you computed. Crash. Verify the data has the "shape" you expect it to. Write a bit more code. Repeat.

Probably a little. I might lack average cognitive facilities, but I find that types pay off for me very early. When I worked in a Python shop, I would prototype in Go because the types helped me move fast, and then I could port it to Python (often for a huge performance loss, not to speak of maintainability) to integrate with the code base.

On the other hand, Python’s repl was nice for a small handful of tasks (although I mostly used it for figuring out what the actual type of some variable was, which is obviously a non-problem in the statically typed world).

In the Clojure world we use clj-kondo, maps, and spec to solve these problems

We get editor time feedback of mistakes with optional type hints + light inferance via clj-kondo and a data modelling system that we can export out as database schema, JSON schema etc

And dynamic enough constraint system to express something like all human names must be "Tony" only on Tuesdays

The same constraint that can be shared server side and client side without writing it twice without learning more syntax

Additionally check what the expected inputs for a function are by checking the function specs I think guardrails pro will make this more ergonomic when released

And finally ask the constraint system to generate valid examples of the constraints great for mocking data

I don't miss type systems but I also understand if you're not using solutions here then you're in trouble

Ya, that's why I think each language kind of benefit to different levels of having static type checkers and of various features as well. You can't just blanket say all type checkers are bad, or all language without one are bad.

Clojure is a good example here, it actually can be used with a very powerful static type checker core.typed, yet its users chose not too for reasons that say in JavaScript maybe a different choice would have been made. The REPL for example catches lots of type errors as you code. Other languages don't have such a coding workflow, so a static type checker feels really great in that it too will catch type errors as you code, etc.

Does anyone still use core.typed? My impression was that Circle CI's article announcing that it was moving away from core.typed was effectively a death blow to its community. One of Circle CI's founders later went on to use OCaml instead of Clojure on his next project (Dark) precisely for its static type system.

None of that is to say OCaml is "superior" to Clojure in some way. I disagree with a lot of the ways that the OCaml type system has evolved and I wouldn't be surprised to see people who have moved to Clojure from OCaml. However, having programmed professionally in Clojure (although it's been quite a few years so I'm not familiar with the latest advancements in e.g. spec) I still think a Clojure-like language could benefit from a static type system.

I don't think it'll work for Clojure itself because of a variety of patterns and choices in the standard library (which is in part why I think core.typed died, we also found core.typed painful to use in some of our experiments at my old job both in how it interacted with Clojure and the tooling around it). And philosophically Rich Hickey would probably kill Clojure before he ever considered designing Clojure around a static type system. However a programming language based off the same data driven ideas could maybe do it.

While a REPL and hot code reloading are absolutely huge productivity boosts, they are more or less orthogonal to the benefits provided by a good static type system (see e.g. hot code reloading with Elm or Purescript which comes quite close).

The thing that static type systems provide over tests and runtime contracts is the ability to constrain users of the API of a library. We use regression tests to make sure regressions in code we write doesn't happen again. Likewise types are effectively regression tests at the API level to make sure certain regressions in code that calls our code doesn't happen again. That is an extremely powerful capability that I consistently miss in dynamically typed languages.

The thing is, core.typed is a really powerful type system, but the ergonomics with the way Clojure works didn't work out, so people prefer not to use it when developing with Clojure.

That's what I find interesting about it. Not all language benefit from a type system in the same ways, some, like Clojure, actually get crippled. Now, it can mean that you need to find the right kind of type checker that provides the correct ergonomics for Clojure and maybe that would work. But it's still quite interesting.

For example, Erlang has a bit of a similar thing, Dyalizer made specific choices to work within Erlang's design. Had it not done so, it probably wouldn't have found adoption. Same with TypeScript.

So what's interesting here is that you have an apples to apples comparison where a language is found to be better without the constraints of static type checking.

When you look at other statically typed languages, they're oftened designed around the static type checker. That's the main focus, and the language itself revolves around that. So obviously in such a language, the type checker would be a necessity, as it's the main draw. So it's interesting to look at Clojure for a counter example.

That said, JavaScript you could argue is also an apples to apples comparison, and people opted for types. It'll be interesting to see also where Ruby and Python go, now that they have type checking features as well.

I still can feel very lost when refactoring a complex clojure system as opposed to something like Rust, because you have very little information about all the places in your codebase where a certain assumption was made.

You can go crazy and spec everything, in fact that can help, but:

- In practise, nobody does it

- Specs come with no guarantees. They could even be wrong.

- The official implementation stubbornly insists on not checking return types, so half of your annotation may just be glorified documentation (although you can use third party libs like orchestra)

Just imagine: Add a new required field to a spec, and get a convenient list of source code locations that you need to review. That's the promise of a statically checked system. It's not a silver bullet, but not having this leads to what I like calling "refactor anxiety" (i.e.: did I handle all cases?)

I still love clojure no matter what. I think in practise you can express so much, so elegantly, and with far less code, that your project size is always sorta manageable.

You don’t miss type systems, because you’re using something very similar.

I did Java dev for a while, after being C before then. I felt like everything needed a pile of typecasting in front of it to work, even though these were often objects for classes you'd think should all play nicely. I realized only after dealing with it for so long that Java wasn't supposed to work that way, but how things can work when well written, vs old apps where half the code is written by a long line of 4-month co-op students, are two very different things.

Ultimately I think people just weren't given any credit for making good, reusable types, because then the next dev who submits a better feature faster using your work gets a raise, but you look like a kook ranting about best practices who doesn't do anything "business".

Type systems limit the set of programs accepted by the compiler. A sound type system will reject every bad program - but also may reject some good programs. Type systems therefore also will have escape hatches to let the programmer overrule the compiler.

Bad type systems need you to use the escape hatches frequently - you can't write much C without using casts.

I haven't yet used a language with no need at all for an escape hatch - but some languages need them far less often than others.

Java's type system is better than it was. The main places it still has weaknesses are around exceptions (you will need to wrap checked exceptions in runtime exceptions in places you'd have preferred to specify an exception type via generics, eg) and the occasional cast after an instance type check.

You can phrase good development practices in business terms: what are the risks to the business due to sloppy code? Are they greater than the risk of being slow to market?

Sloppy code has accumulating costs. A good type system can help greatly with refactoring to address those costs, but it cannot help with the attitude that those costs aren't real and don't need to be paid.