目录
What is Functional Programming
第一部分概念较多, 如果没有耐心看下去的话, 可直接看重点标注的定义
What is side effects
Let's take a look at the first pair with this example
public int square(int x) {
return x * x;
}
Here, the input you're used to thinking about is int x, and the output you're used to is also an int
public void processNext() {
Message message = InboxQueue.popMessage();
if (message != null) {
process(message);
}
}
The second piece of code has hidden inputs and outputs. It requires things, and causes things, but you could never guess what just by looking at the API
These hidden inputs and outputs have an official name: "side-effects"
Are Side Effects Bad?
we have to trust that the the hidden expectations of the original programmer were correct, and will remain correct as time marches on
Can we test this code? Not in isolation. Unlike a circuit board, we can't just plug into its inputs and check its outputs
What is a Pure Function
A function is called 'pure' if all its inputs are declared as inputs - none of them are hidden - and likewise all its outputs are declared as outputs
What is Functional Programming
Functional programming is about writing pure functions, about removing hidden inputs and outputs as far as we can, so that as much of our code as possible just describes a relationship between inputs and outputs
What is a Functional Programming Language
A functional programming language is one that supports and encourages programming without side-effects
Features of functional languages
First-Class Functions - Functional programming requires that functions are first-class, which means that they are treated like any other values and can be passed as arguments to other functions or be returned as a result of a function
Pure Function - 函数的结果只受函数参数影响, 且不影响外部变量 / 函数内部不使用能被外部函数影响的变量
Immutable Data - Purely functional programs typically operate on immutable data. Instead of altering existing values, altered copies are created and the original is preserved
Lazy Evaluation - Since pure computations are referentially transparent they can be performed at any time and still yield the same result. This makes it possible to defer the computation of values until they are needed, that is, to compute them lazily
Recursion
Recursion is heavily used in functional programming as it is the canonical and often the only way to iterate. Functional language implementations will often include tail call optimisation to ensure that heavy recursion does not consume excessive memory
Lazy evaluation avoids unnecessary computations and allows, for example, infinite data structures to be defined and used
In functional programming, programs are executed by evaluating expressions
In contrast with imperative programming where programs are composed of statements which change global state when executed. Functional programming typically avoids using mutable state
Benefits of functional programming
Functional programming is known to provide better support for structured programming than imperative programming. To make a program structured it is necessary to develop abstractions and split it into components which interface each other with those abstractions. Functional languages aid this by making it easy to create clean and simple abstractions. It is easy, for instance, to abstract out a recurring piece of code by creating a higher-order function, which will make the resulting code more declarative and comprehensible
Functional programs are often shorter and easier to understand than their imperative counterparts
Since various studies have shown that the average programmer's productivity in terms of lines of code is more or less the same for any programming language, this translates also to higher productivity
Functional Programming in iOS
Masonry
iOS开发中链式函数编程的典例:
make.centerY.equalTo(self.view).offset(100);
如何实现类似masonry的链式函数编程呢? (引自深入浅出－iOS函数式编程的实现 && 响应式编程概念)
有一个Person类, 它的两个方法如下
- (void)run{
NSLog(@"run");
}
- (void)study {
NSLog(@"study")
}
要实现这样的效果
person.run().study().run();
我们可以这样做
- (Person * (^)())run {
Person * (^block)() = ^() {
NSLog(@"run");
return self;
};
return block;
}
- (Person * (^)())study {
Person * (^block)() = ^() {
NSLog(@"study");
return self;
};
return block;
}
事实上masonry也是这么实现的
- (MASConstraint * (^)(id))equalTo {
return ^id(id attribute) {
return self.equalToWithRelation(attribute, NSLayoutRelationEqual);
};
}
PromiseKit
我们来看看PromiseKit实现UI Animation的例子(更多例子, 请参考PromiseKit官网)
[UIView promiseWithDuration:0.3 animations:^{
view.frame = CGRectOffset(view.frame, 0, -100);
}].then(^{
return [self doWork];
}).catch(^(NSError *error){
[[UIAlertView …] show];
}).finally(^{
view.frame = CGRectOffset(view.frame, 0, +100);
})
Swift
尽管我不认为Swift是一门函数式编程语言(对于语言的讨论可以参考Which Programming Languages Are Functional?), 但是相比于Objective-C来说Swift最大优点就是
Swift为iOS编程世界引入了一个新的范式: 函数式范式
我们来看这样一个例子(代码的含义比较简单, 就不解释了)
var evens = [Int]()
for i in 1...10 {
if i % 2 == 0 {
evens.append(i)
}
}
println(evens)
使用Functional Filtering可以写成这样
func isEven(number: Int) -> Bool {
return number % 2 == 0
}
evens = Array(1...10).filter(isEven)
println(evens)
运用Swift的closures以上代码还可以简化成
evens = Array(1...10).filter { (number) in number % 2 == 0 }
println(evens)
更甚
evens = Array(1...10).filter { $0 % 2 == 0 }
println(evens)
Functional Programming in Android
Glide
Glide作为新生代Android图片库的代表, 和Fresco都是值得推荐的
Glide, Fresco与Picasso的比较可以参考[ Android ] Fresco 与 Picasso 、Glide 的比较和Picasso&Glide&Fresco比较
Glide的使用非常简单和函数式
// For a simple view:
@Override public void onCreate(Bundle savedInstanceState) {
...
ImageView imageView = (ImageView) findViewById(R.id.my_image_view);
Glide.with(this).load("http://goo.gl/gEgYUd").into(imageView);
}
// For a simple image list:
@Override public View getView(int position, View recycled, ViewGroup container) {
final ImageView myImageView;
if (recycled == null) {
myImageView = (ImageView) inflater.inflate(R.layout.my_image_view, container, false);
} else {
myImageView = (ImageView) recycled;
}
String url = myUrls.get(position);
Glide
.with(myFragment)
.load(url)
.centerCrop()
.placeholder(R.drawable.loading_spinner)
.crossFade()
.into(myImageView);
return myImageView;
}
What is Reactive Programming
以下是Wiki Reactive Programming的定义
reactive programming is a programming paradigm oriented around data flows and the propagation of change
其实响应式这个概念很早就有了, 例如
当你操作键盘时, 电脑对按键进行中断响应
当你浏览网站时, 页面对点击页面按钮的响应
那么响应式编程的目的是什么呢? 我们来看这样一个经典的例子(引自Wiki Reactive Programming)
For example, in an imperative programming setting, a b c
a = b + c would mean that a is being assigned the result of b+c in the instant the expression is evaluated
and later, the values of b and c can be changed with no effect on the value of a
However, in reactive programming, the value of a would be automatically updated based on the new values
而响应式编程也是很早就有的了, 例如
iOS开发中的KVC
Android开发中的Broadcast
从中可以看出一点, 所谓的响应式编程很多是基于event bus或observer的, 那么有没有一种更友好, 更强大, 更智能的响应式编程呢?
答案就是本文的主题: Functional Reactive Programming
What is Functional Reactive Programming
按照"国际惯例", 先看下Wiki FRP的定义
Functional reactive programming (FRP) is a programming paradigm for reactive programming (asynchronous dataflow programming) using the building blocks of functional programming (e.g. map, reduce, filter)
简单来说
Functional Reactive Programming = Functional Programming + Reactive Programming
由此, 函数响应式编程集合了两家之所长
那为什么是Functional Programming和Reactive Programming在"一起"了呢? 我认为因为他们两者都最"合适"
函数式编程的这种输入输出特性, 本身就带着些响应式的味道
响应式以往的实现都没有函数式这样的: 简洁, 流畅(想想链式的丝滑)和高度统一(想想filter, map, 再对比下各种广播观察者event bus云云)
Functional Reactive Programming in iOS
ReactiveCocoa
在iOS开发中, 现在一说到函数响应式或MVVM首先想到的应该就是ReactiveCocoa了
我们来看一个ReactiveCocoa的例子(引自ReactiveCocoa Tutorial – The Definitive Introduction: Part 1/2)
[[[self.usernameTextField.rac_textSignal
map:^id(NSString *text) {
return @(text.length);
}]
filter:^BOOL(NSNumber *length) {
return [length integerValue] > 3;
}]
subscribeNext:^(id x) {
NSLog(@"%@", x);
}];
RxSwift
iOS开发中, 如果你已经使用Swift语言开发, 除了ReactiveCocoa还可以考虑RxJava
它的最大优势就是属于ReactiveX旗下的Swift版本, 精通了RxSwift就可以无缝切换至RxJS, RxJava, RxAndroid,Rx.Net, RxRuby...
我们来看一个用RxSwift实现UITableView的例子(引自 【RxSwift系列】用RxSwift实现一个UITableView（一）)
ViewModel的方法看起来应该是这样的
PS: 在真实应用中, 数据应该是通过网络请求解析JSON数据而获得来的
import Foundation
import RxSwift
import RxDataSources
class ViewModel: NSObject {
func getUsers() -> Observable<[SectionModel<String, User>]> {
return Observable.create { (observer) -> Disposable in
let users = [User(followersCount: 19_901_990, followingCount: 1990, screenName: "Marco Sun"),
User(followersCount: 19_890_000, followingCount: 1989, screenName: "Taylor Swift"),
User(followersCount: 250_000, followingCount: 25, screenName: "Rihanna"),
User(followersCount: 13_000_000_000, followingCount: 13, screenName: "Jolin Tsai"),
User(followersCount: 25_000_000, followingCount: 25, screenName: "Adele")]
let section = [SectionModel(model: "", items: users)]
observer.onNext(section)
observer.onCompleted()
return AnonymousDisposable{}
}
}
viewDidLoad()方法是这样的
override func viewDidLoad() {
super.viewDidLoad()
view.addSubview(tableView)
tableView.registerClass(TableViewCell.self, forCellReuseIdentifier: reuseIdentifier)
viewModel.getUsers()
.bindTo(tableView.rx_itemsWithDataSource(dataSource))
.addDisposableTo(disposeBag)
}
Functional Reactive Programming in Android
RxJava
The example below shows what you may already be familiar with:
It calls to the web service, uses a callbacks interface to pass the successful result to the next web service call, define another success callback, and then moves on to the next web service request
As you can see, this results in two nested callbacks
Old Style
// The "Nested Callbacks" Way
public void fetchUserDetails() {
// first, request the users...
mService.requestUsers(new Callback<GithubUsersResponse>() {
@Override
public void success(final GithubUsersResponse githubUsersResponse,
final Response response) {
Timber.i(TAG, "Request Users request completed");
final List<GithubUserDetail> githubUserDetails = new ArrayList<GithubUserDetail>();
// next, loop over each item in the response
for (GithubUserDetail githubUserDetail : githubUsersResponse) {
// request a detail object for that user
mService.requestUserDetails(githubUserDetail.mLogin,
new Callback<GithubUserDetail>() {
@Override
public void success(GithubUserDetail githubUserDetail,
Response response) {
Log.i("User Detail request completed for user : " + githubUserDetail.mLogin);
githubUserDetails.add(githubUserDetail);
if (githubUserDetails.size() == githubUsersResponse.mGithubUsers.size()) {
// we've downloaded'em all - notify all who are interested!
mBus.post(new UserDetailsLoadedCompleteEvent(githubUserDetails));
}
}
@Override
public void failure(RetrofitError error) {
Log.e(TAG, "Request User Detail Failed!!!!", error);
}
});
}
}
@Override
public void failure(RetrofitError error) {
Log.e(TAG, "Request User Failed!!!!", error);
}
});
}
Now, let’s look at the same functionality written with RxJava
public void rxFetchUserDetails() {
//request the users
mService.rxRequestUsers().concatMap(Observable::from)
.concatMap((GithubUser githubUser) ->
//request the details for each user
mService.rxRequestUserDetails(githubUser.mLogin)
)
//accumulate them as a list
.toList()
//define which threads information will be passed on
.subscribeOn(Schedulers.newThread())
.observeOn(AndroidSchedulers.mainThread())
//post them on an eventbus
.subscribe(githubUserDetails -> {
EventBus.getDefault().post(new UserDetailsLoadedCompleteEvent(githubUserDetails));
});
}
RetroFit
现在Android很火的RetroFit结合RxJava就可以写出"动人"的函数响应式实现来
NetworkUtil.getTestObjectRxApi().getTestObjects()
.doOnNext(new Action1<Map<String, List<TestObjectBean>>>() {
@Override
public void call(Map<String, List<TestObjectBean>> stringListMap) {
Logger.e(Thread.currentThread().getName());
TestObjectBean testObjectBean = stringListMap.get("results").get(0);
Logger.d("objectId = " + testObjectBean.getOb());
testObjectBean.setOb("new id");
}
})
.subscribeOn(Schedulers.io())
.observeOn(AndroidSchedulers.mainThread())
.subscribe(new Observer<Map<String, List<TestObjectBean>>>() {
@Override
public void onCompleted() {
Logger.e(Thread.currentThread().getName());
Logger.d("completed");
}
@Override
public void onError(Throwable e) {
Logger.e(e.getMessage());
}
@Override
public void onNext(Map<String, List<TestObjectBean>> stringListMap) {
Logger.e(Thread.currentThread().getName());
for (TestObjectBean testObjectBean : stringListMap.get("results")) {
Logger.d(testObjectBean);
}
}
});
References
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