Related
The language suggestion states that the advantages are detailed in the linked paper. I had a quick skim through and I can't see it spelled out explicitly.
Is the advantage just that each statement gets executed in parallel so I might get a speed boost?
Or is there some kind of logic it caters for, that is not convenient using the usual monadic let!?
I understand that, this being applicative, means that it comes with the limitation that I can't use previous expressions to determine the logic of subsequent expressions. So does that mean the trade off is flexibility for efficiency?
The way I understood Don Syme's description, when I read it a while ago, was every step in the let! ... and! ... chain will be executed, unlike when you use let! ... let! .... Say, for instance, that you use the option CE. Then if you write
option {
let! a = parseInt("a")
let! b = parseInt("b")
return a + b
}
only the first let! will be executed, as the CE short-circuits as soon as it meets a None. Writing instead let! a ... and! b = ... will try to parse both strings; though not necessarily in parallel, as I understand it.
I see a huge benefit in this, when parsing data from external sources. Consider for instance running
parse {
let! name = tryParse<Name>("John Doe")
and! email = tryParse<EMail>("johndoe#")
and! age = tryParse<uint>("abc")
return (name, email, age)
}
and getting an Error(["'johndoe#' isn't a valid e-mail"; "'abc' isn't a valid uint"]) in return, instead of only the first of the errors. That's pretty neat to me.
I am excited for this for two reasons. Potentially better performance and that some things that can't fit into the Monad pattern can fit into the Applicative Functor pattern.
In order to support the already existing let! one need to implement Bind and Return, ie the Monad pattern.
let! and and! requires Apply and Pure (not exactly sure what F# the equivalent are named), ie the Applicative Functor pattern.
Applicative Functors are less powerful than Monads but still very useful. For example, in parsers.
As mentioned by Philip Carter, Applicative Functor can be made more efficient than Monads as it's possible to cache them.
The reason is the signature of Bind: M<'T> -> ('T -> M<'U>) -> M<'U>.
One typical way you implement bind is that you "execute" the first argument to produce a value of 'T and pass it the second argument to get the next step M<'U> which you execute as well.
As the second argument is a function that can return any M<'U> it means caching is not possible.
With Apply the signature is: M<'T -> 'U> -> M<'T> -> M<'U>. As neither of the two inputs are functions you can potentially cache them or do precomputation.
This is useful for parsers, for example in FParsec for performance reasons it's not recommended to use Bind.
In addition; a "drawback" with Bind is that if the first input doesn't produce a value 'T there is no way to get the second computation M<'U>. If you are building some kind of validator monad this means that as soon as a valid value can't be produced because the input is invalid then the validation will stop and you won't get a report of the remaining input.
With Applicative Functor you can execute all validators to produce a validation report for the entire document.
So I think it's pretty cool!
I'm starting to doubt I really understand this topic.
Until now, I was understanding a continuation as calling a function with closure (typically returned by another function). But MLton seems to have a non‑standard special structure for this (a structure I'm not sure to understand), and also in some other documents, mention special optimizations (using jumps, as quickly mentioned on page 58, printed page 51) with continuations, namely, instead of naming call to functions with closure. Also, function closures seems to be sometime described as the basis for continuations, but not described as being continuations, while some other times people assert the opposite (that function closures are special case of continuations, not the other way).
As an example, how do continuations differs from this, and what would looks like the same, with continuations instead of function with closure:
datatype next = Next of (unit -> next)
fun f (i:int): next =
(print (Int.toString i);
Next (fn () => f (i + 1)))
val Next g = f 1
val Next g = g ()
val Next g = g ()
val Next g = g ()
…
I wonder about it, in the general computer‑science context, as much as specifically in the practical SML context.
Note: the question may looks the same as “difference between closures and continuations”, but reading this one did not answer my question and does not address a practical case as a basis. Except it drove me to add another question: why are continuations said to be more abstract than closures, if in the end continuations are made of closures as the incomplete (to my eyes) answer in the above link suggest?
Is the difference really important or just a matter of style / syntax / vocabulary?
I feel a similar question arise with monads versus continuations, but that would be too much for a single question post (but if on the opposite, that can be simply answered in the while, feel free…).
Update
Still from MLton's world, a wording which seems to suggest continuations and function closures are the same (unless I'm not understanding correctly).
CommonArg (mlton.org), near the bottom of the page, says:
What I think the common argument optimization shows is that the
dominator analysis does slightly better than the reviewer puts it:
we find more than just constant continuations, we find common
continuations. And I think this is further justified by the fact
that I have observed common argument eliminate some env_X arguments
which would appear to correspond to determining that while the
closure being executed isn’t constant it is at least the same as
the closure being passed elsewhere.
It's talking about the same using both words, isn't it?
Similarly and may be more explicitely, at the bottom on this page: ReturnStatement (mlton.org).
There too, it seems to be the same. Is it?
It seems there is a terminological confusion. 'Continuation' is an abstract concept, which is a meaning of a context of an expression. Closure is a very particular way to realize
values that represent functions (higher-order languages can be implemented without closures at all, for example, using substitution semantics).
Control operator can capture the current continuation and produce a particular representation of it (this is called reification). The particular representation of a captured continuation may indeed be a closure -- or may be not. For example, in OCaml, the continuations captured by the delimcc library are repersented as values of the abstract data type (whose realization is quite different from closures). You might find the introduction part of the following page useful.
Undelimited continuations are not functions
I'm learning Elixir and wonder why it has two types of function definitions:
functions defined in a module with def, called using myfunction(param1, param2)
anonymous functions defined with fn, called using myfn.(param1, param2)
Only the second kind of function seems to be a first-class object and can be passed as a parameter to other functions. A function defined in a module needs to be wrapped in a fn. There's some syntactic sugar which looks like otherfunction(&myfunction(&1, &2)) in order to make that easy, but why is it necessary in the first place? Why can't we just do otherfunction(myfunction))? Is it only to allow calling module functions without parenthesis like in Ruby? It seems to have inherited this characteristic from Erlang which also has module functions and funs, so does it actually comes from how the Erlang VM works internally?
It there any benefit having two types of functions and converting from one type to another in order to pass them to other functions? Is there a benefit having two different notations to call functions?
Just to clarify the naming, they are both functions. One is a named function and the other is an anonymous one. But you are right, they work somewhat differently and I am going to illustrate why they work like that.
Let's start with the second, fn. fn is a closure, similar to a lambda in Ruby. We can create it as follows:
x = 1
fun = fn y -> x + y end
fun.(2) #=> 3
A function can have multiple clauses too:
x = 1
fun = fn
y when y < 0 -> x - y
y -> x + y
end
fun.(2) #=> 3
fun.(-2) #=> 3
Now, let's try something different. Let's try to define different clauses expecting a different number of arguments:
fn
x, y -> x + y
x -> x
end
** (SyntaxError) cannot mix clauses with different arities in function definition
Oh no! We get an error! We cannot mix clauses that expect a different number of arguments. A function always has a fixed arity.
Now, let's talk about the named functions:
def hello(x, y) do
x + y
end
As expected, they have a name and they can also receive some arguments. However, they are not closures:
x = 1
def hello(y) do
x + y
end
This code will fail to compile because every time you see a def, you get an empty variable scope. That is an important difference between them. I particularly like the fact that each named function starts with a clean slate and you don't get the variables of different scopes all mixed up together. You have a clear boundary.
We could retrieve the named hello function above as an anonymous function. You mentioned it yourself:
other_function(&hello(&1))
And then you asked, why I cannot simply pass it as hello as in other languages? That's because functions in Elixir are identified by name and arity. So a function that expects two arguments is a different function than one that expects three, even if they had the same name. So if we simply passed hello, we would have no idea which hello you actually meant. The one with two, three or four arguments? This is exactly the same reason why we can't create an anonymous function with clauses with different arities.
Since Elixir v0.10.1, we have a syntax to capture named functions:
&hello/1
That will capture the local named function hello with arity 1. Throughout the language and its documentation, it is very common to identify functions in this hello/1 syntax.
This is also why Elixir uses a dot for calling anonymous functions. Since you can't simply pass hello around as a function, instead you need to explicitly capture it, there is a natural distinction between named and anonymous functions and a distinct syntax for calling each makes everything a bit more explicit (Lispers would be familiar with this due to the Lisp 1 vs. Lisp 2 discussion).
Overall, those are the reasons why we have two functions and why they behave differently.
I don't know how useful this will be to anyone else, but the way I finally wrapped my head around the concept was to realize that elixir functions aren't Functions.
Everything in elixir is an expression. So
MyModule.my_function(foo)
is not a function but the expression returned by executing the code in my_function. There is actually only one way to get a "Function" that you can pass around as an argument and that is to use the anonymous function notation.
It is tempting to refer to the fn or & notation as a function pointer, but it is actually much more. It's a closure of the surrounding environment.
If you ask yourself:
Do I need an execution environment or a data value in this spot?
And if you need execution use fn, then most of the difficulties become much
clearer.
I may be wrong since nobody mentioned it, but I was also under the impression that the reason for this is also the ruby heritage of being able to call functions without brackets.
Arity is obviously involved but lets put it aside for a while and use functions without arguments. In a language like javascript where brackets are mandatory, it is easy to make the difference between passing a function as an argument and calling the function. You call it only when you use the brackets.
my_function // argument
(function() {}) // argument
my_function() // function is called
(function() {})() // function is called
As you can see, naming it or not does not make a big difference. But elixir and ruby allow you to call functions without the brackets. This is a design choice which I personally like but it has this side effect you cannot use just the name without the brackets because it could mean you want to call the function. This is what the & is for. If you leave arity appart for a second, prepending your function name with & means that you explicitly want to use this function as an argument, not what this function returns.
Now the anonymous function is bit different in that it is mainly used as an argument. Again this is a design choice but the rational behind it is that it is mainly used by iterators kind of functions which take functions as arguments. So obviously you don't need to use & because they are already considered arguments by default. It is their purpose.
Now the last problem is that sometimes you have to call them in your code, because they are not always used with an iterator kind of function, or you might be coding an iterator yourself. For the little story, since ruby is object oriented, the main way to do it was to use the call method on the object. That way, you could keep the non-mandatory brackets behaviour consistent.
my_lambda.call
my_lambda.call()
my_lambda_with_arguments.call :h2g2, 42
my_lambda_with_arguments.call(:h2g2, 42)
Now somebody came up with a shortcut which basically looks like a method with no name.
my_lambda.()
my_lambda_with_arguments.(:h2g2, 42)
Again, this is a design choice. Now elixir is not object oriented and therefore call not use the first form for sure. I can't speak for José but it looks like the second form was used in elixir because it still looks like a function call with an extra character. It's close enough to a function call.
I did not think about all the pros and cons, but it looks like in both languages you could get away with just the brackets as long as you make brackets mandatory for anonymous functions. It seems like it is:
Mandatory brackets VS Slightly different notation
In both cases you make an exception because you make both behave differently. Since there is a difference, you might as well make it obvious and go for the different notation. The mandatory brackets would look natural in most cases but very confusing when things don't go as planned.
Here you go. Now this might not be the best explanation in the world because I simplified most of the details. Also most of it are design choices and I tried to give a reason for them without judging them. I love elixir, I love ruby, I like the function calls without brackets, but like you, I find the consequences quite misguiding once in a while.
And in elixir, it is just this extra dot, whereas in ruby you have blocks on top of this. Blocks are amazing and I am surprised how much you can do with just blocks, but they only work when you need just one anonymous function which is the last argument. Then since you should be able to deal with other scenarios, here comes the whole method/lambda/proc/block confusion.
Anyway... this is out of scope.
I've never understood why explanations of this are so complicated.
It's really just an exceptionally small distinction combined with the realities of Ruby-style "function execution without parens".
Compare:
def fun1(x, y) do
x + y
end
To:
fun2 = fn
x, y -> x + y
end
While both of these are just identifiers...
fun1 is an identifier that describes a named function defined with def.
fun2 is an identifier that describes a variable (that happens to contain a reference to function).
Consider what that means when you see fun1 or fun2 in some other expression? When evaluating that expression, do you call the referenced function or do you just reference a value out of memory?
There's no good way to know at compile time. Ruby has the luxury of introspecting the variable namespace to find out if a variable binding has shadowed a function at some point in time. Elixir, being compiled, can't really do this. That's what the dot-notation does, it tells Elixir that it should contain a function reference and that it should be called.
And this is really hard. Imagine that there wasn't a dot notation. Consider this code:
val = 5
if :rand.uniform < 0.5 do
val = fn -> 5 end
end
IO.puts val # Does this work?
IO.puts val.() # Or maybe this?
Given the above code, I think it's pretty clear why you have to give Elixir the hint. Imagine if every variable de-reference had to check for a function? Alternatively, imagine what heroics would be necessary to always infer that variable dereference was using a function?
There's an excellent blog post about this behavior: link
Two types of functions
If a module contains this:
fac(0) when N > 0 -> 1;
fac(N) -> N* fac(N-1).
You can’t just cut and paste this into the shell and get the same
result.
It’s because there is a bug in Erlang. Modules in Erlang are sequences
of FORMS. The Erlang shell evaluates a sequence of
EXPRESSIONS. In Erlang FORMS are not EXPRESSIONS.
double(X) -> 2*X. in an Erlang module is a FORM
Double = fun(X) -> 2*X end. in the shell is an EXPRESSION
The two are not the same. This bit of silliness has been Erlang
forever but we didn’t notice it and we learned to live with it.
Dot in calling fn
iex> f = fn(x) -> 2 * x end
#Function<erl_eval.6.17052888>
iex> f.(10)
20
In school I learned to call functions by writing f(10) not f.(10) -
this is “really” a function with a name like Shell.f(10) (it’s a
function defined in the shell) The shell part is implicit so it should
just be called f(10).
If you leave it like this expect to spend the next twenty years of
your life explaining why.
Elixir has optional braces for functions, including functions with 0 arity. Let's see an example of why it makes a separate calling syntax important:
defmodule Insanity do
def dive(), do: fn() -> 1 end
end
Insanity.dive
# #Function<0.16121902/0 in Insanity.dive/0>
Insanity.dive()
# #Function<0.16121902/0 in Insanity.dive/0>
Insanity.dive.()
# 1
Insanity.dive().()
# 1
Without making a difference between 2 types of functions, we can't say what Insanity.dive means: getting a function itself, calling it, or also calling the resulting anonymous function.
fn -> syntax is for using anonymous functions. Doing var.() is just telling elixir that I want you to take that var with a func in it and run it instead of referring to the var as something just holding that function.
Elixir has a this common pattern where instead of having logic inside of a function to see how something should execute, we pattern match different functions based on what kind of input we have. I assume this is why we refer to things by arity in the function_name/1 sense.
It's kind of weird to get used to doing shorthand function definitions (func(&1), etc), but handy when you're trying to pipe or keep your code concise.
In elixir we use def for simply define a function like we do in other languages.
fn creates an anonymous function refer to this for more clarification
Only the second kind of function seems to be a first-class object and can be passed as a parameter to other functions. A function defined in a module needs to be wrapped in a fn. There's some syntactic sugar which looks like otherfunction(myfunction(&1, &2)) in order to make that easy, but why is it necessary in the first place? Why can't we just do otherfunction(myfunction))?
You can do otherfunction(&myfunction/2)
Since elixir can execute functions without the brackets (like myfunction), using otherfunction(myfunction)) it will try to execute myfunction/0.
So, you need to use the capture operator and specify the function, including arity, since you can have different functions with the same name. Thus, &myfunction/2.
Why is it that functions in F# and OCaml (and possibly other languages) are not by default recursive?
In other words, why did the language designers decide it was a good idea to explicitly make you type rec in a declaration like:
let rec foo ... = ...
and not give the function recursive capability by default? Why the need for an explicit rec construct?
The French and British descendants of the original ML made different choices and their choices have been inherited through the decades to the modern variants. So this is just legacy but it does affect idioms in these languages.
Functions are not recursive by default in the French CAML family of languages (including OCaml). This choice makes it easy to supercede function (and variable) definitions using let in those languages because you can refer to the previous definition inside the body of a new definition. F# inherited this syntax from OCaml.
For example, superceding the function p when computing the Shannon entropy of a sequence in OCaml:
let shannon fold p =
let p x = p x *. log(p x) /. log 2.0 in
let p t x = t +. p x in
-. fold p 0.0
Note how the argument p to the higher-order shannon function is superceded by another p in the first line of the body and then another p in the second line of the body.
Conversely, the British SML branch of the ML family of languages took the other choice and SML's fun-bound functions are recursive by default. When most function definitions do not need access to previous bindings of their function name, this results in simpler code. However, superceded functions are made to use different names (f1, f2 etc.) which pollutes the scope and makes it possible to accidentally invoke the wrong "version" of a function. And there is now a discrepancy between implicitly-recursive fun-bound functions and non-recursive val-bound functions.
Haskell makes it possible to infer the dependencies between definitions by restricting them to be pure. This makes toy samples look simpler but comes at a grave cost elsewhere.
Note that the answers given by Ganesh and Eddie are red herrings. They explained why groups of functions cannot be placed inside a giant let rec ... and ... because it affects when type variables get generalized. This has nothing to do with rec being default in SML but not OCaml.
One crucial reason for the explicit use of rec is to do with Hindley-Milner type inference, which underlies all staticly typed functional programming languages (albeit changed and extended in various ways).
If you have a definition let f x = x, you'd expect it to have type 'a -> 'a and to be applicable on different 'a types at different points. But equally, if you write let g x = (x + 1) + ..., you'd expect x to be treated as an int in the rest of the body of g.
The way that Hindley-Milner inference deals with this distinction is through an explicit generalisation step. At certain points when processing your program, the type system stops and says "ok, the types of these definitions will be generalised at this point, so that when someone uses them, any free type variables in their type will be freshly instantiated, and thus won't interfere with any other uses of this definition."
It turns out that the sensible place to do this generalisation is after checking a mutually recursive set of functions. Any earlier, and you'll generalise too much, leading to situations where types could actually collide. Any later, and you'll generalise too little, making definitions that can't be used with multiple type instantiations.
So, given that the type checker needs to know about which sets of definitions are mutually recursive, what can it do? One possibility is to simply do a dependency analysis on all the definitions in a scope, and reorder them into the smallest possible groups. Haskell actually does this, but in languages like F# (and OCaml and SML) which have unrestricted side-effects, this is a bad idea because it might reorder the side-effects too. So instead it asks the user to explicitly mark which definitions are mutually recursive, and thus by extension where generalisation should occur.
There are two key reasons this is a good idea:
First, if you enable recursive definitions then you can't refer to a previous binding of a value of the same name. This is often a useful idiom when you are doing something like extending an existing module.
Second, recursive values, and especially sets of mutually recursive values, are much harder to reason about then are definitions that proceed in order, each new definition building on top of what has been already defined. It is nice when reading such code to have the guarantee that, except for definitions explicitly marked as recursive, new definitions can only refer to previous definitions.
Some guesses:
let is not only used to bind functions, but also other regular values. Most forms of values are not allowed to be recursive. Certain forms of recursive values are allowed (e.g. functions, lazy expressions, etc.), so it needs an explicit syntax to indicate this.
It might be easier to optimize non-recursive functions
The closure created when you create a recursive function needs to include an entry that points to the function itself (so the function can recursively call itself), which makes recursive closures more complicated than non-recursive closures. So it might be nice to be able to create simpler non-recursive closures when you don't need recursion
It allows you to define a function in terms of a previously-defined function or value of the same name; although I think this is bad practice
Extra safety? Makes sure that you are doing what you intended. e.g. If you don't intend it to be recursive but you accidentally used a name inside the function with the same name as the function itself, it will most likely complain (unless the name has been defined before)
The let construct is similar to the let construct in Lisp and Scheme; which are non-recursive. There is a separate letrec construct in Scheme for recursive let's
Given this:
let f x = ... and g y = ...;;
Compare:
let f a = f (g a)
With this:
let rec f a = f (g a)
The former redefines f to apply the previously defined f to the result of applying g to a. The latter redefines f to loop forever applying g to a, which is usually not what you want in ML variants.
That said, it's a language designer style thing. Just go with it.
A big part of it is that it gives the programmer more control over the complexity of their local scopes. The spectrum of let, let* and let rec offer an increasing level of both power and cost. let* and let rec are in essence nested versions of the simple let, so using either one is more expensive. This grading allows you to micromanage the optimization of your program as you can choose which level of let you need for the task at hand. If you don't need recursion or the ability to refer to previous bindings, then you can fall back on a simple let to save a bit of performance.
It's similar to the graded equality predicates in Scheme. (i.e. eq?, eqv? and equal?)
I have been trying to explain the difference between switch statements and pattern matching(F#) to a couple of people but I haven't really been able to explain it well..most of the time they just look at me and say "so why don't you just use if..then..else".
How would you explain it to them?
EDIT! Thanks everyone for the great answers, I really wish I could mark multiple right answers.
Having formerly been one of "those people", I don't know that there's a succinct way to sum up why pattern-matching is such tasty goodness. It's experiential.
Back when I had just glanced at pattern-matching and thought it was a glorified switch statement, I think that I didn't have experience programming with algebraic data types (tuples and discriminated unions) and didn't quite see that pattern matching was both a control construct and a binding construct. Now that I've been programming with F#, I finally "get it". Pattern-matching's coolness is due to a confluence of features found in functional programming languages, and so it's non-trivial for the outsider-looking-in to appreciate.
I tried to sum up one aspect of why pattern-matching is useful in the second of a short two-part blog series on language and API design; check out part one and part two.
Patterns give you a small language to describe the structure of the values you want to match. The structure can be arbitrarily deep and you can bind variables to parts of the structured value.
This allows you to write things extremely succinctly. You can illustrate this with a small example, such as a derivative function for a simple type of mathematical expressions:
type expr =
| Int of int
| Var of string
| Add of expr * expr
| Mul of expr * expr;;
let rec d(f, x) =
match f with
| Var y when x=y -> Int 1
| Int _ | Var _ -> Int 0
| Add(f, g) -> Add(d(f, x), d(g, x))
| Mul(f, g) -> Add(Mul(f, d(g, x)), Mul(g, d(f, x)));;
Additionally, because pattern matching is a static construct for static types, the compiler can (i) verify that you covered all cases (ii) detect redundant branches that can never match any value (iii) provide a very efficient implementation (with jumps etc.).
Excerpt from this blog article:
Pattern matching has several advantages over switch statements and method dispatch:
Pattern matches can act upon ints,
floats, strings and other types as
well as objects.
Pattern matches can act upon several
different values simultaneously:
parallel pattern matching. Method
dispatch and switch are limited to a single
value, e.g. "this".
Patterns can be nested, allowing
dispatch over trees of arbitrary
depth. Method dispatch and switch are limited
to the non-nested case.
Or-patterns allow subpatterns to be
shared. Method dispatch only allows
sharing when methods are from
classes that happen to share a base
class. Otherwise you must manually
factor out the commonality into a
separate function (giving it a
name) and then manually insert calls
from all appropriate places to your
unnecessary function.
Pattern matching provides redundancy
checking which catches errors.
Nested and/or parallel pattern
matches are optimized for you by the
F# compiler. The OO equivalent must
be written by hand and constantly
reoptimized by hand during
development, which is prohibitively
tedious and error prone so
production-quality OO code tends to
be extremely slow in comparison.
Active patterns allow you to inject
custom dispatch semantics.
Off the top of my head:
The compiler can tell if you haven't covered all possibilities in your matches
You can use a match as an assignment
If you have a discriminated union, each match can have a different 'type'
Tuples have "," and Variants have Ctor args .. these are constructors, they create things.
Patterns are destructors, they rip them apart.
They're dual concepts.
To put this more forcefully: the notion of a tuple or variant cannot be described merely by its constructor: the destructor is required or the value you made is useless. It is these dual descriptions which define a value.
Generally we think of constructors as data, and destructors as control flow. Variant destructors are alternate branches (one of many), tuple destructors are parallel threads (all of many).
The parallelism is evident in operations like
(f * g) . (h * k) = (f . h * g . k)
if you think of control flowing through a function, tuples provide a way to split up a calculation into parallel threads of control.
Looked at this way, expressions are ways to compose tuples and variants to make complicated data structures (think of an AST).
And pattern matches are ways to compose the destructors (again, think of an AST).
Switch is the two front wheels.
Pattern-matching is the entire car.
Pattern matches in OCaml, in addition to being more expressive as mentioned in several ways that have been described above, also give some very important static guarantees. The compiler will prove for you that the case-analysis embodied by your pattern-match statement is:
exhaustive (no cases are missed)
non-redundant (no cases that can never be hit because they are pre-empted by a previous case)
sound (no patterns that are impossible given the datatype in question)
This is a really big deal. It's helpful when you're writing the program for the first time, and enormously useful when your program is evolving. Used properly, match-statements make it easier to change the types in your code reliably, because the type system points you at the broken match statements, which are a decent indicator of where you have code that needs to be fixed.
If-Else (or switch) statements are about choosing different ways to process a value (input) depending on properties of the value at hand.
Pattern matching is about defining how to process a value given its structure, (also note that single case pattern matches make sense).
Thus pattern matching is more about deconstructing values than making choices, this makes them a very convenient mechanism for defining (recursive) functions on inductive structures (recursive union types), which explains why they are so abundantly used in languages like Ocaml etc.
PS: You might know the pattern-match and If-Else "patterns" from their ad-hoc use in math;
"if x has property A then y else z" (If-Else)
"some term in p1..pn where .... is the prime decomposition of x.." ((single case) pattern match)
Perhaps you could draw an analogy with strings and regular expressions? You describe what you are looking for, and let the compiler figure out how for itself. It makes your code much simpler and clearer.
As an aside: I find that the most useful thing about pattern matching is that it encourages good habits. I deal with the corner cases first, and it's easy to check that I've covered every case.