Comment by addicted44 | Hacker News Reader

Comment by addicted44 | Hacker News Reader

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Hash maps also don't (usually) have external effects.

There arent many hash map methods that will actually modify the data.

Standard OOP, on the other hand, seems to encourage such behavior. So, for example, a Company object could contain a bunch of Department objects, each of which contained a bunch of Employee objects.

These people objects could also be referenced in areas outside of the company object.

If I called a company.giveFinanceDepartmentARaiseInDollars(10000) function on the Company object, it would have an unpredictable impact on the Department/Employee objects. It may also have cascading effects in other parts of the application that may not be clear.

On the other hand, if you represented this as a company hashmap, with the keys the department structs, you would have to do something like the following instead:

company["finance"].employees.forEach(x => x.salary = x.salary + 10000); company["finance"].base_salary = company["finance"].base_salary 10000

This contrived example shows some of the pros/cons. OOP allows us to hide a lot of behavior/changes, which may mean less repetitive code. OTOH, it hides a lot of behavior/changes.

I think the problem is that your example is too contrived and you can hide implementation details by just having a function giveFinanceDepartmentARaiseInDollars(company, dollarAmount) that exhibits the same issues as the “object oriented version”.

More generally the issue of global mutable state and keeping your own sanity as a developer is a problem across paradigms.

The real problem with my example was that I modified the strict instead of returning a new one.

My “functional” code wasn’t actually functional.

If I had written that correctly, by returning a modified copy using a map instead of modifying the strict in a loop, your example would also be covered, because the function you’re describing would not modify any of its inputs, but instead would return a new copy. And the function wouldn’t have any side effects either, so it would once again be completely clear what’s happening.

But now you have a stale data problem.

Creating a new value only gives you a stale data problem if you had pointers to the old value. You don't have to have pointers like that, it's a choice.

To take an obvious example, you might load a value from a database (company or employees, say), create a new value (with the higher salary, say), then write the new value to the database.

I think the point being made here was that alternative approach don't eliminate the difficulties of global state. Simply using immutable object doesn't make all your problems go away, it makes them different. I think it makes them better, but let's not pretend that all the challenges of dealing with state can be eliminated.

Quite so. I was just trying to make some small suggestions on how to handle the consequences of making that object immutable.

Here are some links along the same lines:

* _Aggregate Roots_ in DDD limit pointers, https://martinfowler.com/bliki/DDD_Aggregate.html * Guidance on where to mutate, _Functional core, imperative shell_, https://www.destroyallsoftware.com/screencasts/catalog/funct...

> using immutable object doesn't make all your problems go away, it makes them different

Yes, and here is a concrete example of the kind of 'different' problems you get: nested immutable structures, say `a.b.c.d`, become harder to update than simply `a.b.c.d = newValue`. The functional solution for this is 'lenses' (and other 'optics'). My favourite Kotlin framework that I use in my day job provides lenses for HTTP - URL query parameters, request and response bodies and so on - which work very well.

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