Maybe Functions(blog.benwinding.com)
blog.benwinding.com
Maybe Functions
https://blog.benwinding.com/maybe-functions/
102 comments
What constitues the "best" code depends on the incidental complexity of the problems you're trying to solve. Great code is when you have just enough of all those things, but have too much or too little and the code is worse.
You're right, of course — there are parts of my codebase that flagrantly disregard these rules, and did so for good reasons that I don't regret.
But I've found that while "everything is relative and should be situated in the context of the problem you're trying to solve" is a useful truism, it makes for poor praxis. It's hard to improve existing code or develop newer engineers without _some_ set of compasses and heuristics for what "good code" is, and once you develop that set the patterns and strategies for implementing "good code" naturally follows.
But I've found that while "everything is relative and should be situated in the context of the problem you're trying to solve" is a useful truism, it makes for poor praxis. It's hard to improve existing code or develop newer engineers without _some_ set of compasses and heuristics for what "good code" is, and once you develop that set the patterns and strategies for implementing "good code" naturally follows.
I agree, I'd imagine as a senior you have a good sense of what counts as good enough. Unfortunately, there are too many would-be seniors justifying horrendous amounts of accidental complexity as "good practice".
IIRC Rich Hickey says something similar to the "pipeline-oriented programming" piece in his talk about systems: https://www.youtube.com/watch?v=ROor6_NGIWU&pp=ygUccmljaCBoa...
I hold these two essays similarly high in influence for myself. The pipeline/railway oriented programming really made it click about how to use first-class types to deal with error cases elegantly.
Unfortunately, a lot of languages make it difficult to have the compiler enforce exhaustiveness.
Unfortunately, a lot of languages make it difficult to have the compiler enforce exhaustiveness.
Isn't parsing itself a maybe function?
The author has conflated two concepts into "maybe function". Parsing is "maybe" in the sense that the parser will either return your object or fail. But it doesn't have to do any hidden, surprising behaviour like the "if (!loggedIn) {" line in the article.
A better name might be “sometimes function”
No. Maybe functions aren't the result of simply returning different results. It's doing or not doing something, abstracted into a function.
Parsing is determining whether you should do it or not- it's about setting up a boundary from which you never attempt something that would be a maybe.
Parsing is determining whether you should do it or not- it's about setting up a boundary from which you never attempt something that would be a maybe.
Parse, don't validate is fantastic. I read it a few years ago and I still think about it quite often.
Good concepts (although too few text on the slides on the second link)
I feel like there's a whole genre of essays (red vs green functions is the worst example) that could be summarised as:
* Monads naturally arise out of many problems in programming.
* But I don't want my language to support monads.
* So here's something you can do to stay in denial about how much you need monads.
At least this example only involves writing hard-to-analyse code and doesn't lead to you trying to invent green threads.
* Monads naturally arise out of many problems in programming.
* But I don't want my language to support monads.
* So here's something you can do to stay in denial about how much you need monads.
At least this example only involves writing hard-to-analyse code and doesn't lead to you trying to invent green threads.
The kicker here is that the author implemented a functor and called it a monad. So of course readers are going to think "the monad approach" is confusing and stay away.
I mean even if you implement a more standard Monad interface plenty of functional programmers still find working with Monads to be ugly. It's really not a solved area.
I’ll accept that. But do notation is the closest thing to sensible we have, whereas most of these articles are just constantly trying to chip away at part of the problem in the hope that they’ll be able to make the whole mountain disappear one stone at a time. And to date, I don’t find the evidence promising that they can.
I’m not wedded to stuff like monadic state, I think that might be a bridge too far for regular programming (and besides which, it doesn’t really generalise anyway) but that still leaves a large family of issues that we’re all aware of but trying to dodge.
I’m not wedded to stuff like monadic state, I think that might be a bridge too far for regular programming (and besides which, it doesn’t really generalise anyway) but that still leaves a large family of issues that we’re all aware of but trying to dodge.
Can’t disagree more. Solution 1 just presents risk that some calls getUser() without doing the log in check. Then what happens?
It is false that getUser being a “maybe function” forces the other functions like getFriends to be maybe functions. Don’t let them take null in their arguments. Force the caller to deal with the null when it is returned by getUser.
It is false that getUser being a “maybe function” forces the other functions like getFriends to be maybe functions. Don’t let them take null in their arguments. Force the caller to deal with the null when it is returned by getUser.
This looks too easy, the first solution. If there is no logged on user, which User object is fetchUser going to return? Which friends? At the top level, if I were to forget to check if someone is logged in, who knows what would happen here.
I've worked on codebases where people were so allergic to the "billion dollar mistake" of nulls, that they created empty objects to return instead of returning null. This bit us in the ass a couple of times, e.g., when caller code was mistakenly passing the wrong ID variable into a fetch method, and just happily continued working and writing garbage into the DB, because it did not realize that its fetch had actually failed. It took data from the empty result object and happily continued its computation with it.
I've worked on codebases where people were so allergic to the "billion dollar mistake" of nulls, that they created empty objects to return instead of returning null. This bit us in the ass a couple of times, e.g., when caller code was mistakenly passing the wrong ID variable into a fetch method, and just happily continued working and writing garbage into the DB, because it did not realize that its fetch had actually failed. It took data from the empty result object and happily continued its computation with it.
> This looks too easy, the first solution. If there is no logged on user, which User object is fetchUser going to return? Which friends? At the top level, if I were to forget to check if someone is logged in, who knows what would happen here.
It feels like the most likely thing to happen is that the `getUser()` call would throw a Null Pointer Exception?
I think the author is avoiding the pitfall of the NullObject pattern applied incorrectly with solution #1 because they're not masking the 'null-ness' in the code further down, they're just assuming that `null` will never get passed as a value. If it is, code blows up & then gets patched.
It feels like the most likely thing to happen is that the `getUser()` call would throw a Null Pointer Exception?
I think the author is avoiding the pitfall of the NullObject pattern applied incorrectly with solution #1 because they're not masking the 'null-ness' in the code further down, they're just assuming that `null` will never get passed as a value. If it is, code blows up & then gets patched.
I’ve had limited success with the null object pattern but there is one case that it worked really well for me. I worked on a feature that was highly dynamic and users could compose reports selecting data points from tangentially related models. Null objects were a really helpful pattern because it was hard to anticipate how models would be composed and if a developer made a mistake it was hard to notice there was no effect. Our null objects would raise exceptions in development and explain what you need to change but wouldn’t prevent execution in production.
You could easily argue we should have just presented this exception to the user in all cases but this is where we landed. It’s probably the only case this pattern was beneficial for me.
You could easily argue we should have just presented this exception to the user in all cases but this is where we landed. It’s probably the only case this pattern was beneficial for me.
Another option is Exceptions. The function either does what it's supposed to, or freaks out.
You can remove the null checks and the software will raise a null pointer exception. In the first example, could raise a NotLoggedInException.
It's still a maybe function, but you have a mechanism for expressing the why-notness of the function run, as opposed to returning a generic null.
As an aside, I prefer the "Unless" model of thinking vs the "Maybe" model of thinking. It's biased towards success. It presumes that the function is most likely to do something unless a precheck fails. filterBestFriendsUnless vs maybeFilterBestFriends. getUserUnless vs maybeGetUser. If we go this far down the rabbit hole, we can assume there's always an "unless". Programs run out of memory, stacks have limited depth. There are maybe conditions for which we can not account.
You can remove the null checks and the software will raise a null pointer exception. In the first example, could raise a NotLoggedInException.
It's still a maybe function, but you have a mechanism for expressing the why-notness of the function run, as opposed to returning a generic null.
As an aside, I prefer the "Unless" model of thinking vs the "Maybe" model of thinking. It's biased towards success. It presumes that the function is most likely to do something unless a precheck fails. filterBestFriendsUnless vs maybeFilterBestFriends. getUserUnless vs maybeGetUser. If we go this far down the rabbit hole, we can assume there's always an "unless". Programs run out of memory, stacks have limited depth. There are maybe conditions for which we can not account.
I think that's true for checked exceptions; in Typescript, I'd rather see that a function may return a null, rather than get surprised by a possible exception that's not telegraphed.
I think that's my biggest problem with exceptions. I have to rely on the doc comments to figure out whether a method can throw exceptions and which and when. And who knows if that covers all the possible exceptions from all the code that method relies on. It entirely sidesteps the type system and means I can't rely on the input/output types when using a method.
> I have to rely on the doc comments to figure out whether a method can throw exceptions
But you still have to rely on the docs to tell if a function can abort execution (say, by calling std::optional<T>::value() when there's no value). And an unhandled exception would abort just the same. Where do you see there being a difference?
> and which and when.
Maybe types don't tell you that either, you still need documentation for that.
Even worse, Maybe types cannot tell you that unless they're leaf-ish functions. Because they may call opaque functions (such as your own callbacks) for which they have no such knowledge to begin with. Thus they have to support propagating some type-erased error type... which is exactly what exceptions do.
So, again: how is the situation different?
But you still have to rely on the docs to tell if a function can abort execution (say, by calling std::optional<T>::value() when there's no value). And an unhandled exception would abort just the same. Where do you see there being a difference?
> and which and when.
Maybe types don't tell you that either, you still need documentation for that.
Even worse, Maybe types cannot tell you that unless they're leaf-ish functions. Because they may call opaque functions (such as your own callbacks) for which they have no such knowledge to begin with. Thus they have to support propagating some type-erased error type... which is exactly what exceptions do.
So, again: how is the situation different?
I like the philosophy that “exceptions are for exceptional circumstances.” Not being logged in is not exceptional.
for a function called "getUser" it is.
Not exactly. "getUser" not having a user to get is not exceptional unless you only have logged in users. If you have logged-out users, then "getUser" should gracefully handle the case of an unknown, logged-out user (either returning null or some other sentinel value).
Returning null makes "getUser" a "maybeGetUser" function.
Like said in TFA that means that any caller might need to check for nullness
Yes, no matter what, they have to check if there is an actual user if the application can have anonymous users. There’s no way around that.
What the exceptional case is depends on the what the pre- and post-conditions of the function are. If a function assumes that the user is logged in then the user not being logged in is indeed exception. Not to say that it is good design though. That function is quite fragile like this. If it must assume that a user is logged in, then it could easily require a user to be given as an argument which will remove the whole possibility.
Sure but only in langs wich require exception handling! Otherwise it's just hidden behaviour and explicit optional returns are better imo
I am for exceptions but it should not be used for basic control flow. Many techs will treat all exceptions as errors.
In this case, it's not being used for basic control flow. It's a prerequisite of the function that the user is logged in - and you violated that so it's an error. Returning null masks the reason why that happened.
As others already said: you shouldn't even be able to call this function when your pre-requisites for calling it are violated, ideally. You can achieve that by putting this function inside some sort of object which can't be created without a logged in user. If you don't have that, you can't ask for user information.
So what I meant is that you see the exact same maybe pattern in many projects but instead of returning null there is a guard that throws an exception. I agree with the solution.
Interestingly, Python uses exceptions for basic control flow, like end of for-loop.
Semantically, Python separates Exceptions and Errors. The mechanism for throwing and catching them is the same.
Here's a quick description from somewhere on the interwebs: An error is an issue in a program that prevents the program from completing its task. In comparison, an exception is a condition that interrupts the normal flow of the program.
Then there is StopIteration, which does not fit well into either of the two above. It's a wart I've learned to treat as a beauty mark.
Here's a quick description from somewhere on the interwebs: An error is an issue in a program that prevents the program from completing its task. In comparison, an exception is a condition that interrupts the normal flow of the program.
Then there is StopIteration, which does not fit well into either of the two above. It's a wart I've learned to treat as a beauty mark.
Well, by your definition of Exceptions and Errors, errors are something that Python, the formal language as understood by the computer, doesn't know anything about. It's a concept for humans that they can use when analysing programs. And different analyses might come to different conclusions. [0]
You could signal errors via eg returning None or False or throwing an exception. But not throwing an exception could also be an error. (Eg if your for-loop never ends, that might be an error. And that would be synonymous with StopIteration never being thrown.)
[0] Eg for a program like 'cat' it would normally be considered an error, when the file being read doesn't exist. But perhaps in my particular usage, that's expected to occur quite often, and is a normal part of my operation. You can translate this example to Python: FileNotFound might be an error, or a normal condition.
You could signal errors via eg returning None or False or throwing an exception. But not throwing an exception could also be an error. (Eg if your for-loop never ends, that might be an error. And that would be synonymous with StopIteration never being thrown.)
[0] Eg for a program like 'cat' it would normally be considered an error, when the file being read doesn't exist. But perhaps in my particular usage, that's expected to occur quite often, and is a normal part of my operation. You can translate this example to Python: FileNotFound might be an error, or a normal condition.
Well it uses exceptions in the case your generator is at the end, not usually at the end of a for loop because a for loop by definition iterates over a list until the list is finished.
The exception actually occurs when you call next() on a generator which cannot return any more values, or is finished, in which case `StopIteration` is usually raised.
The exception actually occurs when you call next() on a generator which cannot return any more values, or is finished, in which case `StopIteration` is usually raised.
All Python iterators raise StopIteration at the end of iteration. For-loops always use the iterator protocol. Neither generators nor lists are special in this regard.
>>> next(iter([]))
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
StopIteration
>>> next(iter((lambda: (yield 5) if False else None)()))
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
StopIterationThe proliferation of conditional "maybe" functions is a sign that your call graph is contrived and unnatural. You shouldn't be checking "userLoggedIn == true" in each and every accessor function. Ideally, such checks should bubble up towards the top of the call stack, and be performed once in an event loop iteration. The calling code should make sure that some basic prerequisites are met.
I use maybe functions a lot for things like "maybeShowReminderDialog". The conditions for displaying the reminder are wrapped in this maybe function.
Surely that's simpler than specifying those conditions before every call to show this dialog, resulting in plenty of duplicated code. And if those conditions change, there is only one place I need to update it.
Of course I can make a single operation to check those conditions like "shouldShowReminder", but that too is doubling the surface area of this code.
I see the merit of the argument here but disagree with the absolutist stance against "maybe" functions.
Surely that's simpler than specifying those conditions before every call to show this dialog, resulting in plenty of duplicated code. And if those conditions change, there is only one place I need to update it.
Of course I can make a single operation to check those conditions like "shouldShowReminder", but that too is doubling the surface area of this code.
I see the merit of the argument here but disagree with the absolutist stance against "maybe" functions.
There's that. And it also reduces the chance for race conditions:
if ( shouldShow() ) /* state changes here where it should not show */ doShow();I would argue that the vast majority of functions in real world software are maybe functions in that they can fail. You need to be able to deal with failure. Not only can the user not be logged in, there can be a network issue, etc that makes even downstream functions fail.
Also, you have to deal with developer mistakes and what happens when they call incorrectly. This can be something as simple as getting the first element of a collection. What happens when the collection is empty? You can adopt the C++ approach of “undefined behavior” but it turns out to be dangerous.
Monads provide a nice disciplined way to dealing with this and composing together functions that can potentially fail.
Thankfully, newer languages such as providing support for monads and older languages are evolving features/libraries for monadic error handling.
Also, you have to deal with developer mistakes and what happens when they call incorrectly. This can be something as simple as getting the first element of a collection. What happens when the collection is empty? You can adopt the C++ approach of “undefined behavior” but it turns out to be dangerous.
Monads provide a nice disciplined way to dealing with this and composing together functions that can potentially fail.
Thankfully, newer languages such as providing support for monads and older languages are evolving features/libraries for monadic error handling.
> Also, you have to deal with developer mistakes and what happens when they call incorrectly.
There is only one safe(ish) way to deal with programmer errors: crash. Hopefully loudly and early enough so it gets discovered in testing.
There is only one safe(ish) way to deal with programmer errors: crash. Hopefully loudly and early enough so it gets discovered in testing.
Why wait until then? The loudest and earliest crash you can get is a failure to compile with a rich type system (obviously, when possible).
I assume you don't write device drivers or operating systems?
Predicting every possible failure reason for a function is impossible. Every function is a maybe function.
Predicting every possible failure reason for a function is impossible. Every function is a maybe function.
If enumerating every possible failure mode of a function is impossible, then that would underscore the importance of failing fast and dynamically restarting components in order to provide robustness in the face of unforeseeable errors.
Respectfully, I don't think this articles uses monads correctly, because it's not using any. This could be very elegant:
To call, we can do
And if you don't _call_ it mondads (but rather something more approachable), it's not that wild and scary sounding a concept all of a sudden.
That way, your compiler error checks null-type scenarios for you, your type signatures are clean, don't lie, and your compiler forces you to explicitly do something like `runSafely` (or `runUnsafe` etc.), usually a single point of failure.
Bonus, `MonadError`-type constructs are awesome too, since I get
getUser: Option[User]
getFriends(u: User): Seq[Friend]
bestFriends(f: Seq[Friend]): Seq[Friend]
renderFriends(f: Seq[Friend]): Option[UI] // Unit or type UI or HTML or ...
To call, we can do
bestFriends: Option[Seq[Friends]] = getUser.flatMap(u: User => renderFriends(bestFriends(getFriends(u))))
flatMap[B](f: A => Option[B]): Option[B]
And if you don't _call_ it mondads (but rather something more approachable), it's not that wild and scary sounding a concept all of a sudden.
That way, your compiler error checks null-type scenarios for you, your type signatures are clean, don't lie, and your compiler forces you to explicitly do something like `runSafely` (or `runUnsafe` etc.), usually a single point of failure.
Bonus, `MonadError`-type constructs are awesome too, since I get
handleErrorWith[A](fa: F[A])(f: E => F[A]): F[A]
If anything the real lesson here is that you shouldn't try to lift your functions manually in the presence of a Monad. Monads tend to be somewhat 'infectious' in that anything that touches the Monad will need to be monadic. It's the reason why 'nullable' and 'async' can end up transforming most of the code-base to support their use.
And if you are going to write a sum type do it properly. If the language doesn't provide sum types but does have function types just use the category theory definition:
And if you are going to write a sum type do it properly. If the language doesn't provide sum types but does have function types just use the category theory definition:
function maybeWithUser<T>(withUser: User => T, default: () => T): T {
if (!loggedIn) return default()
return withUser(fetchUser());
}
function Page() {
const bestFriends = maybeWithUser(user => {
const friends = getFriends(user);
const bestFriends = filterBestFriends(friends);
return render(bestFriends);
}, null);
return <>
{bestFriends}
</>;
}
Program logic fundamentally has to contend with different conditions.
Sometimes the user will be logged in and have friends, sometimes they won't.
The "maybe" style has the inconsistency embedded in the type system; it's impossible to have an invocation to getFriends and then not handle the resulting possibility of not being logged in.
Shifting it up to the caller just means that you're going to have to remember to ensure the user is logged in before calling getFriends otherwise you'll get some kind of error, which might give you more control, but now there's no guarantee in the type system that you've handled the case where the user isn't logged in.
Writing ifs everywhere to handle failure conditions might be a bit of a pain, but that's more of a failing of the language than the style.
The "maybe" style has the inconsistency embedded in the type system; it's impossible to have an invocation to getFriends and then not handle the resulting possibility of not being logged in.
Shifting it up to the caller just means that you're going to have to remember to ensure the user is logged in before calling getFriends otherwise you'll get some kind of error, which might give you more control, but now there's no guarantee in the type system that you've handled the case where the user isn't logged in.
Writing ifs everywhere to handle failure conditions might be a bit of a pain, but that's more of a failing of the language than the style.
I agree with this. I prefer explicit optional/null return types, otherwise the possibility of an error still exists but is now hidden to the caller. Langs with syntax for concise optional chaining and such fix this problem imo
Note that Typescript - the language of the examples - does have proper null through it's type system. A function that returns `T | null` will require callers check for null before using T.
I know it's a simple example, but the Maybe class should probably use a null check internally rather than a truthy check, so that types like number and string which have falsy values that are nonetheless valid for a use case can be used with Maybe.
The author is conflating two separate concepts, and calling them both "the maybe function":
This applies to both points 1 and 2.
> It’s alternating functionality of “does/doesn’t do something” makes code hard to understand, maintain and debug.
This only applies to point 1.
> They seem to be trivial to add, but difficult to remove. But hopefully this illustrates the concern and ways to fix it.
This cannot apply to point 2, because you cannot take a function which might return a user and `fix` it to make it always return a user.
> Solution 2 - Monads
This is not a monad.
He has implemented the Maybe Functor. runSafely most likely corresponds to map in whatever library you're using, not flatMap.
This is visible from its type signature:
1) functions which do hidden things outside of their contract and/or whose implementation doesn't properly line up with their types.
2) functions which (by necessity) cannot always return the desired value and must return something else instead.
This applies to both points 1 and 2.
> It’s alternating functionality of “does/doesn’t do something” makes code hard to understand, maintain and debug.
This only applies to point 1.
> They seem to be trivial to add, but difficult to remove. But hopefully this illustrates the concern and ways to fix it.
This cannot apply to point 2, because you cannot take a function which might return a user and `fix` it to make it always return a user.
> Solution 2 - Monads
This is not a monad.
He has implemented the Maybe Functor. runSafely most likely corresponds to map in whatever library you're using, not flatMap.
This is visible from its type signature:
> runSafely(fn: (val: T) => V): Maybe<V> // map
> runSafely(fn: (val: T) => Maybe<V>): Maybe<V> // flatMap
function getUser(): User {
if (!loggedIn) {
return null
}
return fetchUser();
}
I think the post is related tothe "Null vs Maybe" problem. See https://web.archive.org/web/20230329075114/https://www.nickk... already discussed here https://news.ycombinator.com/item?id=5577364
Except it isn’t. Returning ‘User | null’ in typescript is the same type-wise as returning Maybe<User>
> Here’s a specific example, it’s a “maybe” function as it only returns the friends of a user, if the user is logged in. Basically it introduces a possible return null.
Since that function will return a list, an empty List might work.
function maybeGetUser(): User | null {
if (!loggedIn) {
return null;
}
return fetchUser();
}
Since that function will return a list, an empty List might work.
I can't wait for more languages to adopt the "?" operator [1] like the Rust one. It's just syntactic sugar for "if expr null return null" but makes it far easier to write code in a more monadic style.
(mostly waiting for this in JS and Go)
[1]: https://doc.rust-lang.org/reference/expressions/operator-exp...
(mostly waiting for this in JS and Go)
[1]: https://doc.rust-lang.org/reference/expressions/operator-exp...
Go actually needs proper nil/null/optionality first before it can get syntax features to deal with them.
I can't wait for more languages to simply not include null at all. It makes trying to spot them in static analysis and runtime checks much easier, because you no longer need either.
In the context of the parent's example, Rust doesn't include null at all, it just has a standard Option type with a None variant. While the other mentioned languages (JS and Go) do have null, they don't necessarily need to remove it to start getting the benefits, they just need to provide standardized alternatives and get the community to follow along (and if, say, a fancy new ? operator only worked on these new types and didn't work on null in general, that would be a strong carrot).
The example of Rust is one where no types are nullable by default, but only if you wrap them in an `Option<T>`.
Given these two function signatures:
Given these two function signatures:
pub fn getUser() -> User
pub fn getMaybeUser() -> Option<User>
pub fn foo() -> Option<String> {
let user = getUser()?;
return user.name
}
pub fn foo2() -> Option<String> {
let user = getMaybeUser()?;
return Some(user.name)
}
i remember using this back in my groovy days https://groovy-lang.org/operators.html#_safe_navigation_oper...
Not everthing that can return null is a maybe function, sometimes you need a difference between zero and nothing.
Solution3 for their example:
Solution3 for their example:
function maybeRenderBestFriends() {
const user = maybeGetUser();
if(user!=null){
const friends = maybeGetFriends(user);
const bestFriends = maybeFilterBestFriends(friends);
return render(bestFriends);
}
return null;
}An alternative I've used or seen used in Java is to put @Nullable on the function. The caller knows the result could be null, and must check for it. Linters/Static analysis can verify when you haven't checked it as well.
There's an urge to return Optional<Object> but now you must check Optional.isPresent AND object != null.
There's an urge to return Optional<Object> but now you must check Optional.isPresent AND object != null.
In C# the closest analogy I can think of is the "Try" pattern. For example, you have int.Parse(string) which returns int, and int.TryParse(string, out int) which returns bool. The fact that the returned value is the validation is a strong incentive to do something with it.
that's a good example!
This is a pattern you cannot always avoid, due to react, but i don't think it should be normalized.
Two remarks:
• the render function is omitted, this pattern as a huge impact on application behaviors, if not for display-as-you-load issues, on DOM hidden state (things like focus, animations, etc…) for web apps.
• App's do have a global state, with self-consistency, scattering it in a mixed match of loading cache and self contained components just make it hard to work with. I think it's better to have a centralized upper level parent component that manage the transitional initialization states and consistency, not necessarily for the whole app, but at least for the whole displayed UI content.
Two remarks:
• the render function is omitted, this pattern as a huge impact on application behaviors, if not for display-as-you-load issues, on DOM hidden state (things like focus, animations, etc…) for web apps.
• App's do have a global state, with self-consistency, scattering it in a mixed match of loading cache and self contained components just make it hard to work with. I think it's better to have a centralized upper level parent component that manage the transitional initialization states and consistency, not necessarily for the whole app, but at least for the whole displayed UI content.
One thing I like about typescript is that unless you’re a masochist, it basically pushes you towards option 1.
If you have to constantly check for null/undefined it gets annoying and you naturally think about narrowing the state space so entire sections of your program don’t have to think about those possible states.
It should also become obvious when you have a possible null/undefined state and it’s super unclear what that piece of your program ought to do about it other than alert the parent (such as throwing an error). If a component doesn’t have a role to play when null, maybe it shouldn’t ever be seeing null as a possible state.
If you have to constantly check for null/undefined it gets annoying and you naturally think about narrowing the state space so entire sections of your program don’t have to think about those possible states.
It should also become obvious when you have a possible null/undefined state and it’s super unclear what that piece of your program ought to do about it other than alert the parent (such as throwing an error). If a component doesn’t have a role to play when null, maybe it shouldn’t ever be seeing null as a possible state.
You do have another solution that can lower the amount of conditions: Null Objects. These don’t fit every use cases, but they can allow you to express what’s missing, or not defined, or empty, and avoid nil pointers dereference or conditions to check the state.
As Sandy Metz is used to say « Nothing is Something »[0]
0: https://youtu.be/OMPfEXIlTVE?si=qmizH1OvqV7eLKNK
As Sandy Metz is used to say « Nothing is Something »[0]
0: https://youtu.be/OMPfEXIlTVE?si=qmizH1OvqV7eLKNK
From the article:
> This is highly related to the "Null Object Pattern", but I thought I would explain it from the perspective of functions.
> This is highly related to the "Null Object Pattern", but I thought I would explain it from the perspective of functions.
After reading this I realise that I am guilty of building many "maybe" functions in my own code. Definitely something I need to be aware of
I feel like this isn't really a general statement on maybe functions but unnecessary maybe functions. If you can make it not "maybe" but "always" then of course that's obviously better.
The real use case is when it really is maybe. (Network call, error handling). Then it's about forcing people to deal with that in a typesafe way and not hiding that it really is maybe.
The real use case is when it really is maybe. (Network call, error handling). Then it's about forcing people to deal with that in a typesafe way and not hiding that it really is maybe.
This is a great example of the issue with using monads and monad-like patterns in languages that don't have proper support via language constructs for these.
In rust for example, this is trivially handled with the questionmark postfix operator — which is just sugar for match — whereas in languages like JS and Java, stacking Optionals and so on can be rather painful as all this sugar is done manually.
In rust for example, this is trivially handled with the questionmark postfix operator — which is just sugar for match — whereas in languages like JS and Java, stacking Optionals and so on can be rather painful as all this sugar is done manually.
What seems that the fundamental problem is that the functions depend on global state that is not explicitly passed in (is the user logged in?). Maybe an explicit session parameter could work better here. You only have a session when the user is logged in, so you can't even pass anything to the functions otherwise. It can of course be passed further recursively.
I got stuck at option 1. Rendering code becomes lot more complex. Also few errors that make it difficult to follow the essay, like "it’s a “maybe” function as it only returns the friends of a user" but the function is getUser, not getFriends.
Or function getFriends(user: User): Friend[] { return fetchUser(); } The body of the function is wrong.
Or function getFriends(user: User): Friend[] { return fetchUser(); } The body of the function is wrong.
You can also handle optionality when using the value.
function maybeRenderBestFriends() {
const user = maybeGetUser();
if (!user) {
return null
}
const friends = maybeGetFriends(user);
const bestFriends = friends ? filterBestFriends(friends) : null;
return bestFriends ? render(bestFriends) : null;
}I'm surprised the option (pun intended) that immediately came to my mind was not discussed: change the getUser function so it has a "LoggedInUser" parameter, instead of pulling the User from some global state. Then (so long as you have a type system) you can't call the function without the user being logged in.
Great point, but I want to bring up another one I'm seeing all the time:
Maybe functions that don't have maybe in their name and just silently don't do something without informing the caller.
This is extremely common and the source of many bugs. If your function is a maybe function, name it accordingly.
Maybe functions that don't have maybe in their name and just silently don't do something without informing the caller.
This is extremely common and the source of many bugs. If your function is a maybe function, name it accordingly.
And what if `fetchUser` hits an error? At the very least pop your de-maybeifier after the async call. Or use something language standardised (like a promise in JS where you can just throw).
I'm all for a perfy shortcut / early return but this maybe just seems like an abstraction on a non-issue.
I'm all for a perfy shortcut / early return but this maybe just seems like an abstraction on a non-issue.
... And TBH the bigger smell is eminating from the explicit `null` returns. Next essay please.
this is basically like bubbles under wallpaper - the "maybeness" is not due to your code, but due to the underlying problem you are solving (a user can either be logged in or not, and if they are not then all user properties are null). the article identifies the problem with various solutions as extra layers of abstraction, but i feel like the real issue is ceremony - whether propagating maybe-coloured functions through your code and checking the return value everywhere, or wrapping everything in a monad, you have to do something to handle the null case when all you really care about is the non-null case, and that something inevitably feels like clutter and overhead.
I find it very interesting that the higher they are in the stack, the more people tend to talk about algebra (monads, functors, etc). I wonder why is that the case? Doesn't kernel or firmware require this level of abstraction?
That's not a monad, that's just a functor. And that's great, because functors are easier to grok than monads! A functor F consists of two things:
- a kind of function on types which transforms any type T to some new type F(T)
- a rule which associates to any function f: T -> S a function fmap(f): F(T) -> F(S)
That's exactly what the author defines here, to a type T we associate Maybe<T>, and to a function f: T -> S we associate `fmap(f)(x) = None if x is None else f(x)`.
A monad needs some structure in addition to fmap, namely bind and return. These allow you to take a function T -> F(S) and a function S -> F(U) and compose them together to a function T -> F(U).
A monad needs some structure in addition to fmap, namely bind and return. These allow you to take a function T -> F(S) and a function S -> F(U) and compose them together to a function T -> F(U).
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You can address this with explicit parameterization instead of global state. That way the missing data is an obvious type error rather than a surprise in the middle of a running function.
Go has a related idiom: the "Must" functions
https://pkg.go.dev/text/template#Must
https://pkg.go.dev/text/template#Must
To be pedantic: Their Maybe class is just a Functor, not a Monad.
What's it missing? flatMap/bind/whatever that's called?
Yes, exactly. It's missing the monadic bind (which for the list monad would be flatMap).
maybe the author does not know wtf he is talking about...
What's the advantage of the Monad approach? Doesn't the render function still have to check whether those Maybes contain values or not?
If you just have 1 step then there is no advantage.
If you have multiple steps then the advantage is that you never have to unpack "in the middle" and you don't have to care - and the compiler has your back.
Classical example: show the street number of the user or show <None> if there is no street number. There can be multiple things missing on the way and multiple transformations might happen on the way. E.g. the user might not even have an adress saved alltogether.
In that case, you only have to "check whether those Maybes contain values or not" once at the very end.
If you have multiple steps then the advantage is that you never have to unpack "in the middle" and you don't have to care - and the compiler has your back.
Classical example: show the street number of the user or show <None> if there is no street number. There can be multiple things missing on the way and multiple transformations might happen on the way. E.g. the user might not even have an adress saved alltogether.
In that case, you only have to "check whether those Maybes contain values or not" once at the very end.
I dont think there is any advantage when the language lacks syntax level support for Monads. E.g. in Haskell (which does) it would look roughly like:
getUser :: Maybe User
getUser = ...
getFriends :: Maybe [User]
getFriends = do
user <- getUser
let friends = getFriendsForUser user
return friends
bestFriends :: Maybe [User]
bestFriends = do
friends <- getFriends
let besties = filter isBestFriend friends
return besties
render :: IO ()
render = do
let bffs = getBestFriends
case bffs of
Just besties -> renderBestFriends besties
Nothing -> renderNoFriends
It saves you from having to write the null check code for other cases.
> “Functions should do something, not maybe do something…”
But it did do something, it checked if the user logged was logged in first.
But it did do something, it checked if the user logged was logged in first.
Wirth entered the chat:
Procedures should do something. Functions should return something.
https://en.wikipedia.org/wiki/Command%E2%80%93query_separati...
By the way, I have never understood the practice of using a verb in the name of a (pure) function; naming the function after its result using a noun or adjective phrase makes much more sense.
Procedures should do something. Functions should return something.
https://en.wikipedia.org/wiki/Command%E2%80%93query_separati...
By the way, I have never understood the practice of using a verb in the name of a (pure) function; naming the function after its result using a noun or adjective phrase makes much more sense.
I think that naming functions with a prefix of maybe is awful. I treat all functions as "maybes".
For collections, returning [] (empty collection) instead of null is almost always what I want.
1. Parse, don't validate (https://lexi-lambda.github.io/blog/2019/11/05/parse-don-t-va...)
2. Pipeline-oriented programming (https://fsharpforfunandprofit.com/pipeline/)
In my experience, the "best" code (defining "best" as some abstract melange of "easy to reason about", "easy to modify", "easy to compose", and "easy to test") ends up following the characteristics outlined by the sum of these three essays — strictly and rigorously elevating exceptions/failures/nulls to first-class types and then pushing them as high in the stack as possible so callers _must_ deal with them.