Signatures and Hiding Things

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來自 University of Washington 的課程

程序设计语言

798 個評分

University of Washington

程序设计语言

798 個評分

This course is an introduction to the basic concepts of programming languages, with a strong emphasis on functional programming. The course uses the languages ML, Racket, and Ruby as vehicles for teaching the concepts, but the real intent is to teach enough about how any language “fits together” to make you more effective programming in any language -- and in learning new ones. This course is neither particularly theoretical nor just about programming specifics -- it will give you a framework for understanding how to use language constructs effectively and how to design correct and elegant programs. By using different languages, you will learn to think more deeply than in terms of the particular syntax of one language. The emphasis on functional programming is essential for learning how to write robust, reusable, composable, and elegant programs. Indeed, many of the most important ideas in modern languages have their roots in functional programming. Get ready to learn a fresh and beautiful way to look at software and how to have fun building it. The course assumes some prior experience with programming, as described in more detail in the first module. The course is divided into three Coursera courses: Part A, Part B, and Part C. As explained in more detail in the first module of Part A, the overall course is a substantial amount of challenging material, so the three-part format provides two intermediate milestones and opportunities for a pause before continuing. The three parts are designed to be completed in order and set up to motivate you to continue through to the end of Part C. The three parts are not quite equal in length: Part A is almost as substantial as Part B and Part C combined.

從本節課中

Section 4 and Part-A Exam

We finish Part A of the course with this module. As explained in more detail in the welcome message, we discuss type inference, ML's module system, and the fundamental idea in computing of two computations being equivalent. There is no programming assignment -- instead there is an exam covering all of Part A. Finally, there is a brief wrap-up video for the end of Part A that also looks ahead to Part B and Part C -- we have put it after the exam, so don't overlook it.

Section Introduction1:45

What is Type Inference5:37

ML Type Inference6:09

Type Inference Examples10:27

Polymorphic Examples10:52

Optional: The Value Restriction and Other Type-Inference Challenges9:53

Mutual Recursion9:45

Modules for Namespace Management6:25

Signatures and Hiding Things7:02

A Module Example11:06

Signatures for Our Example11:03

Signature Matching4:03

An Equivalent Structure6:38

Another Equivalent Structure9:01

Different Modules Define Different Types3:32

Equivalent Functions8:41

Standard Equivalences10:01

Equivalence Versus Performance6:00

與講師見面

Dan Grossman
Professor
Computer Science & Engineering

[MUSIC] In this segment, we're going to give types to modules.

We'll call those types signatures. We'll start with the basic idea, and

then, show the most important thing signatures are used for,

which is to hide things inside of modules from all the code outside the module.

So, I really do want you to think of a signature as a type for a module,

but the same way we call modular structures, we will call their types

signatures, we're just using different english words.

And what a signature indicates about a module, is what bindings are defined in

there and what type do they have. So, we can define a signature, actually,

separately from any particular module, and then, we can say that module has the

signature. So let's see how this works with the

example we used in the previous segment. So we can define a signature, as you see

here at the top, we use the keyword signature.

It's somewhat conventional to use all capital letters.

You don't have to do that. Say this is the MATHLIB signature,

then, sig, which is a key word, although, it's not an English word. The types of

bindings just like we've been seeing the RPL print out,

so we would write val fact:int->int to say any module with the MATHLIB signature

must have a variable fact of type int->int, however it's defined.

It doesn't matter if it's defined via a function binding, or a variable binding

or any other way. The point is that it has such a thing

that it defines, similarly half_pi, and doubler, and then

the keyword end. Now, our structure that we defined in the

previous segment, my MATHLIB, could have this signature.

It defines all the things that the MATHLIB signature requires.

And in such a situation you can write :> and the name of the signature in your

structure definition between the structure name and the =.

And now, the structure will only type check if you provide everything at an

appropriate type. So if this signature had something that

the structure did not provide, we would get a nice error message from the type

checker reminding us that we didn't provide it, and similarly, if we provided

something, but not at the correct type. Okay?

so, in general, the way we do signatures, is you just write signature, name of your

signature, equal sig, the types for your bindings very much like the REPL has been

printing things out for us in N. And in fact, one way you can get a start

to your signature is paste in what the REPL says a structure has. in this

signature, you can have things for a variable, types data type and exceptions,

we'll see examples of that in future segment and then when you want to ascribe

a ignature. to a structure, you do it like this.

So the advantage of having this, as we will see, so we can define a signature

once, and then, have different structures in our program that all have that

signature and we can could reuse the signature name.

And as I mentioned the module simply won't type-check unless it has everything

at the right types. So if we see that over in our file here,

I have the same structure I had before, but now I have the signature as you've

seen from the, on the slides, then my structure, and then, later here,

in the file, the same uses, and if I load all this up in the rebel we now see that

it defined the signature. Having done so, all it's going to tell us about the

structure of my MATHLIB is that it has that signature.

And then we have pi and 28 and everything works great.

Alright? So that's the basics of signatures, but now let me show you what

they're actually good for and that is hi-, hiding things.

The real value of signatures is not to document and write down the type of

everything in the module. It's to hide implementation details,

which is the most important strategy for writing correct, robust, reusible

software, is to say to the outside world, I don't want you using eveything defined

in this module. I want control over what's public and

what's private, what you can use, and what you should not assume even exists.

So we actually have ways to do this already in ML, whether it's with local

helper functions or what not. you know, here are three versions of a

double function and there are all sorts of reasons why clients of this function

have no idea how it's implemented. It doesn't matter whether you write x*2

or x+x or x*y where y happens to be equal to two where the function is defined.

We also know that if we define helper functions locally, no one outside of the

let expression where the function is defined, even knows that function exist.

What module systems are giving us, in addition to other things, is the ability

to do this for a sequence of bindings at the top level of the module.

It would be really convenient to have some functions that are private and some

are public. In a lot of programming languages, we do

this by actually marking the the functions, private or public.

In ML, we do it a little differently. It's nice to see something different.

what we do in ML, is we just write our module how we want, and then in the

signature, we leave things out and anything not in the signature cannot be

used outside the module. So here's how that works.

If I just go back to my example, and I take out one of the bindings from the

signature, the module, the structure can still have that type.

The module is allowed to have things not in the signature, it just has to have

everything that is in the signature. And whatever is not in the signature

cannot be used outside the module, it can still be used inside the module.

So let me show that over here with the code.

So let me go back up here, and let me comment out from my signature, the

doubler function, so no one on the outside can know that doubler exists.

but I can still use it inside, so I could have a value eight here that would be a

doubler of four, that would work just fine.

And, then, if I go over here and recompile everything, I'm actually going

to get an error message. And, we will see that the error message

is, on line 27 there is an unbound variable, MyMathLib.doubler,

and indeed there is. Right here on line 28, there is no such

thing as MyMathLib.doubler outside of the module and so I simply cannot use it.

Alright? So having fixed that, everything should now work.

I still have my val pi, I still have my structure, MyMathLib that has the

signature, MATHLIB. Okay. So that is hiding for us,

and that is one of the ways we are going to use modules to hide things from the

rest of the program. We'll see that signatures have even more

power that will let us code up neat things in the upcoming segment.

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