Keep in mind while learning FP, that (according to me at least) the most important guideline is to use pure functions as much as possible. That's how you get the maintainability benefits out of FP. Most of the rest of the functional programming patterns are just to support using pure functions. I have a more detailed post about that here. If you just use the patterns without pure functions its not going to get you much over other paradigms. Language suggestions:
Elm will force you to write pure functions. But it is a language/platform focused solely on (web) UI. If you have a project in mind targeting the web, this would be the route to go IMO. Download a high rated starter project so you don't have to get lost in the weeds setting up the build/dev environment. I also highly recommend Semantic UI (just the CSS) for GUI elements.
F# is my favorite. But since it has no distinction between pure and impure functions, it doesn't condition you as heavily into using pure functions. You can always fall back to imperative if a pure solution is elusive. I started with F#, and I feel like this led me to miss the point of FP for a while. (I was focusing on using functional patterns instead of writing pure functions.) But I think it is a great general-purpose FP language, because you can choose to go imperative in performance-critical parts. F# can call C# code and vice versa with no FFI.
OCaml is another option, and F# is based on it.
Haskell will also force you to use pure functions, but is much harder to break into (IMO) due to its complex type system and lots of operator symbols to learn. I'll mention Eta here too, as it is basically Haskell for the JVM.
Clojure is an interesting one. It's a Lisp dialect and dynamically typed so its FP flavoring is a bit different in general. I've heard it said that in Clojure (like Lisp) you write the code that writes the code to solve the problem.
Aside: I hate couching things in terms of purity and impurity... both types of functions are needed for any useful program. But historically those are the terms used in this context. A pure function is really just another name for a deterministic function.
Nice list, Kasey. As Ben already said, ReasonML is really nice to do functional programming in a C-like syntax.
I would also add to this, since Rob mentioned Java, Kotlin and Scala can also be a good choice on doing FP on the JVM. Kotlin particularly is nicer with less syntactic cruft than Scala, and it's gaining traction from Android community.
Great rundown, if you're interested in something new and interesting, check out Reason, and slightly more mature, Elixir language. Elixir is built on the Erlang VM, but has a lot of inspiration ideological inspiration from Ruby.
It's a function that computes the same value, every time you call it with the same arguments, and depends only on those. The value can not depend on time or any mutable state outside of it.
It also can not have any side effects, like throwing exceptions or printing to the console.
This has a lot of benefits for reasonability, testability and compiler/runtime optimization, but can sometimes lead to code that's painfully explicit.
Not really - having each function do a precise task is a general good practice, not a quality of pure functions. A setter, for example, is an impure function that does a precise task.
I converted the array to an object, but the function is still pure(or, more precisely, can be pure - I didn't write Obj.__init__'s body and Python does not guarantee function purity). We still have the original array - we did not change existing values, only returned new ones.
A better example will adding an element to an array:
FP is not about eliminating side effect at all, because a software that does not has any side effect has no use at all. Instead, FP is about making as much area of your code to be pure function so that they are predictable and consistent, while allow only specific module to be impure, i.e. having side effect.
I would think so, yes. You find that most Smalltalk-inspired OOP advocates tend to view sharing of data as a bad thing. Instead, data is private to an object, and you just tell the object what you want it to do (by sending it a message or invoking a method). The object then induces local mutations to itself. It's still not technically a pure function, but this flavor of OOP follows the spirit of not mutating a shared external state. Because that's what makes programs hard to change over time.
A pure function has additional benefits like thread safety.
The two conditions you need for a function to be pure.
The return value of a function depends only on the input parameters.
External values cannot be mutated (input values, globals, etc.).
Example violations.
letmutablex=1letaddXvalue=value+x// violates #1// x is not an input parameter.// probably would still be ok if x was immutable.
typeMyType={mutableAnInt:int}letaddxmyType=// violates #2, mutates the inputmyType.AnInt<-myType.AnInt+x
Mutations to shared data are what makes code hard to follow and hard to fit in your head. This is sometimes called hard to "reason about".
The challenge of FP is figuring out how to get all significant decisions into pure functions. That way they are easy to test and reason about. Then push all side effects out to the impure edges of the application.
Yep. Technically, a mutation of a local, private variable (i.e. not passed by reference in or out), or using a out-of-scope (e.g. global) variable which doesn't change during program execution... both still allow a function to be pure. Such side effects do not affect the caller or any callees.
However, these are not great habits for FP learners to start with. I tend to only do local mutation for performance optimizations. Most of the time they aren't needed.
Modeling with pure functions is difficult at first, particularly if you know imperative programming well. In fact it took me a while to get used to it. But it eventually becomes familiar, and not any harder to do than procedural or OOP. Then you start to wish you had discovered it a lot sooner.
The payoff is well worth it. Primarily because pure functions have linear risk/cost to refactor. I don't know about you, but my experience previously has been that refactors to core code can have an unknown risk of breaking other things... but not so with pure functions. When you look at a function, what you see is what you get... no mysterious external, runtime state changes to account for. Refactorability is a benefit that pays dividends for many years to come. And as I said, once it becomes familiar its not even any more work (and perhaps less) than other methods. The main trade-off is the upfront cost of learning it.
Pure functions are also quite easy to test. If all your significant decisions are in pure functions, you don't really need mocks, fakes, and extensive test frameworks. You just need to vary the inputs and check the outputs. Testing logic is low-cost and easy. Testing side effects becomes integration testing (part of CI workflow, not in unit tests).
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Keep in mind while learning FP, that (according to me at least) the most important guideline is to use pure functions as much as possible. That's how you get the maintainability benefits out of FP. Most of the rest of the functional programming patterns are just to support using pure functions. I have a more detailed post about that here. If you just use the patterns without pure functions its not going to get you much over other paradigms. Language suggestions:
Elm will force you to write pure functions. But it is a language/platform focused solely on (web) UI. If you have a project in mind targeting the web, this would be the route to go IMO. Download a high rated starter project so you don't have to get lost in the weeds setting up the build/dev environment. I also highly recommend Semantic UI (just the CSS) for GUI elements.
F# is my favorite. But since it has no distinction between pure and impure functions, it doesn't condition you as heavily into using pure functions. You can always fall back to imperative if a pure solution is elusive. I started with F#, and I feel like this led me to miss the point of FP for a while. (I was focusing on using functional patterns instead of writing pure functions.) But I think it is a great general-purpose FP language, because you can choose to go imperative in performance-critical parts. F# can call C# code and vice versa with no FFI.
OCaml is another option, and F# is based on it.
Haskell will also force you to use pure functions, but is much harder to break into (IMO) due to its complex type system and lots of operator symbols to learn. I'll mention Eta here too, as it is basically Haskell for the JVM.
Clojure is an interesting one. It's a Lisp dialect and dynamically typed so its FP flavoring is a bit different in general. I've heard it said that in Clojure (like Lisp) you write the code that writes the code to solve the problem.
Aside: I hate couching things in terms of purity and impurity... both types of functions are needed for any useful program. But historically those are the terms used in this context. A pure function is really just another name for a deterministic function.
Nice list, Kasey. As Ben already said, ReasonML is really nice to do functional programming in a C-like syntax.
I would also add to this, since Rob mentioned Java, Kotlin and Scala can also be a good choice on doing FP on the JVM. Kotlin particularly is nicer with less syntactic cruft than Scala, and it's gaining traction from Android community.
Great rundown, if you're interested in something new and interesting, check out Reason, and slightly more mature, Elixir language. Elixir is built on the Erlang VM, but has a lot of inspiration ideological inspiration from Ruby.
Thanks. I knew I would forget some. :)
Note that Reason is just a Javascript-like syntax on top of OCaml. My pref would be to use the OCaml syntax, but dealer's choice.
Another +1 for Elixir here. It's fantastic!
What's a "pure function"?
It's a function that computes the same value, every time you call it with the same arguments, and depends only on those. The value can not depend on time or any mutable state outside of it.
It also can not have any side effects, like throwing exceptions or printing to the console.
This has a lot of benefits for reasonability, testability and compiler/runtime optimization, but can sometimes lead to code that's painfully explicit.
I get it, each function have to do a precise task.
Thanks man :)
Not really - having each function do a precise task is a general good practice, not a quality of pure functions. A setter, for example, is an impure function that does a precise task.
Ok, but you sometimes NEED to do impure function no ?
How could you not change the type of some variables ?
Ex :
You want to get array data to convert into object, you need to do an impure function no ?
Not really:
I converted the array to an object, but the function is still pure(or, more precisely, can be pure - I didn't write
Obj.__init__'s body and Python does not guarantee function purity). We still have the original array - we did not change existing values, only returned new ones.A better example will adding an element to an array:
foois impure, because it changes an existing value.baris pure, because it does not change an existing value - it creates a new one.Now I got it !
Last question, why do we have to do this ?
FP is not about eliminating side effect at all, because a software that does not has any side effect has no use at all. Instead, FP is about making as much area of your code to be pure function so that they are predictable and consistent, while allow only specific module to be impure, i.e. having side effect.
.. So, pure function could also be a priority for OOP no ?
I would think so, yes. You find that most Smalltalk-inspired OOP advocates tend to view sharing of data as a bad thing. Instead, data is private to an object, and you just tell the object what you want it to do (by sending it a message or invoking a method). The object then induces local mutations to itself. It's still not technically a pure function, but this flavor of OOP follows the spirit of not mutating a shared external state. Because that's what makes programs hard to change over time.
A pure function has additional benefits like thread safety.
Ahah thread.. I'm doing PHP :(
The two conditions you need for a function to be pure.
Example violations.
Mutations to shared data are what makes code hard to follow and hard to fit in your head. This is sometimes called hard to "reason about".
The challenge of FP is figuring out how to get all significant decisions into pure functions. That way they are easy to test and reason about. Then push all side effects out to the impure edges of the application.
Just "the input values"?
Yep. Technically, a mutation of a local, private variable (i.e. not passed by reference in or out), or using a out-of-scope (e.g. global) variable which doesn't change during program execution... both still allow a function to be pure. Such side effects do not affect the caller or any callees.
However, these are not great habits for FP learners to start with. I tend to only do local mutation for performance optimizations. Most of the time they aren't needed.
"The input values cannot be mutated" implies that global or closure variables can be mutated.
Nice catch. I revised the wording.
It seem to me ok but.. really hard and annoying.
Why do FP need pure function ?
Modeling with pure functions is difficult at first, particularly if you know imperative programming well. In fact it took me a while to get used to it. But it eventually becomes familiar, and not any harder to do than procedural or OOP. Then you start to wish you had discovered it a lot sooner.
The payoff is well worth it. Primarily because pure functions have linear risk/cost to refactor. I don't know about you, but my experience previously has been that refactors to core code can have an unknown risk of breaking other things... but not so with pure functions. When you look at a function, what you see is what you get... no mysterious external, runtime state changes to account for. Refactorability is a benefit that pays dividends for many years to come. And as I said, once it becomes familiar its not even any more work (and perhaps less) than other methods. The main trade-off is the upfront cost of learning it.
Pure functions are also quite easy to test. If all your significant decisions are in pure functions, you don't really need mocks, fakes, and extensive test frameworks. You just need to vary the inputs and check the outputs. Testing logic is low-cost and easy. Testing side effects becomes integration testing (part of CI workflow, not in unit tests).