| > You can create an object with the right members and pass it in to a function expecting an interface without even explicitly identifying it as "implementing" the interface. Row polymorphism is indeed very useful. Purescript (a Haskell descendant compiling to js) has it and I wish Haskell did too. > The point of using OO in a giant complex program is the isolation you get, so that a team of 1000 people can develop the app in a reasonable way. > Not everything is easily isolated: Sometimes you need a control over here to poke into the state of a control over there, and you don't want that information in some "god object" at the top level; you want a direct connection and mutability. The above two statements directly contradict each other. Yes, OOP preaches isolation and programming against abstract interfaces, in theory. In practice, more often than not one is tempted to do something the easy way and "poke into the state" of another object. This has disastrous consequences: you never know what will happen where when you call a method. Everything is fair game. It's like changing the lock of the basement door in a skyscraper somewhere only to have it fall because the steal beams depended on this exact lock to hold some state, since it was "faster that way". It's insane. I've seen so many OOP clusterfucks that I seriously can't believe that you haven't in your much longer career. Sometimes FP is not a good idea - mostly when performance, memory or deterministic runtime behaviour is a must. But even there languages like Rust show that it may be possible to have one's cake and eat it too. Other than that, I'd be genuinely interested in hearing what kind of problems you think FP wouldn't work well for. > Which is why it's so popular for solving complex problems? It is, actually. I've worked on a very complex codebase in Haskell at my last job (a pathfinding and ticket price calculation backend with ridiculous specifications full of special cases and exceptions that changed almost every day) and I was able to be productive almost from day one. We could refactor with almost absolute confidence because the language is pure and type safe, and we had to because the specs changed so quickly. Facebook's spam filter and Jane Street's OCaml stack come to mind as other examples. There aren't as many applications written in FP languages simply because these languages aren't that popular. But popularity isn't a metric of quality. > If you're putting more cognitive load on the developer, then you're just changing the problems, not preventing them. I absolutely find the opposite to be the case. Haskell reduces the cognitive load on the programmer, because it is pure (i.e. no need to keeping track of dozens of interactions at once) and type safe (i.e. a function marked as pure can't call a function with IO). Not to mention things like an actual working software transactional memory implementation that makes concurrent programming as easy as writing a single threaded program. No other language, with the notable exception of maybe Clojure, has a practical STM library. But anyway, STM is just a bonus. In short, I would say that FP actually delivers what OOP set out to but couldn't. Many FP ideas that were almost unheard of just a couple years ago, like immutable data, pure functions, composition over inheritance, non-nullable types, algebraic data types and so on are slowly but surely taking hold in the mainstream. Pure FP languages just take it to the next level :) |
When I said "poke into another object" above, I didn't mean literally mutate the data of another object. Private data is a good thing. I meant grab onto a handle to the object and changes its state through its public interface.
None of the "complex" problems you're talking about hit that level for me; they're mostly the kind of algorithm you can easily approach from multiple directions. Pathfinding, ticket price calculation with a million special cases -- these are broad-but-shallow problems for the most part. A spam filter is one or more algorithms applied to a data stream. I don't know Jane Street's OCaml stack, and a quick Google isn't explaining it to me, but it looks like some kind of parser?
A game might use pathfinding, but an A-star or one of the many newer algorithms is pretty straightforward. Not the kind of complexity I'm talking about. I'm talking about needing to deal with the state of a hundred or a thousand items that have various ways they can interact with each other and that are expected to have emergent behavior. Like you'd find in games, but as you may also find in stock analysis (speaking of a domain where speed can be critical).
I've avoided the worst of OOP I think because I've avoided enterprise work, except for one greenfield project where I got to create an app for the retail space -- and I ran into some pretty awful code that was wrapped in a giant black box that only ran on Windows and required about 160Mb of RAM per user...to run a cash register. No I'm not exaggerating. It was insane.
The problem with using concurrency in FP is that the entire point of concurrency is speed, and on the problems that most need speed you get more out of an imperative language.
There was an attempt to code an image convolution algorithm in Haskell that I read about. A PhD tried his hardest to parallelize the algorithm and beat the speed of C code handling the same problem. I turned out to be impossible; the asymptotic speed of the Haskell code as you added cores never ended up faster than the C code on one core. Amdahl's Law is a hard limit for a lot of problems. [1]
[1] https://en.wikipedia.org/wiki/Amdahl%27s_law