I'm kind of new to reactive programing and currently working on a spring webflux based application. I'm stuck between few questions.
public class FooServiceImpl {
#Autowired
private FooDao fooDao;
#Autowired
private AService aService;
#Autowired
private BService bService;
public long calculateSomething(long fooId) {
Foo foo = fooDao.findById(fooId); // Blocking call one
if (foo == null) {
foo = new Foo();
}
Long bCount = bService.getCountBByFooId(fooId); // Blocking call two
AEntity aEntity = aService.getAByFooId(fooId); // Blocking call three
// Do some calculation using foo, bCount and aEntity
// ...
// ...
return someResult;
}
}
This is the way we write a blocking code which uses three external API call results (let's consider as DB calls). I'm struggling to convert this into a reactive code, If all three becomes mono and if I subscribe all three will the outer subscriber get blocked?
public Mono<Long> calculateSomething(long fooId) {
return Mono.create(sink -> {
Mono<Foo> monoFoo = fooDao.findById(fooId); // Reactive call one
monoFoo.subscribe(foo -> {
if (foo == null) {
foo = new Foo();
}
Mono<Long> monoCount = bService.getCountBByFooId(fooId); // Reactive call two
monoCount.subscribe(aLong -> {
Mono<AEntity> monoA = aService.getAByFooId(fooId); // Reactive call three
monoA.subscribe(aEntity -> {
//...
//...
sink.success(someResult);
});
});
});
};
}
I saw there is a function called zip, but it only works with two results, So is there a way to apply it here?
Also what will happen if we get subscribe for something inside create method, Will it block the thread?
Would be very thankful if you could help me.
If you gave me the calculation you want you do with those values, it would be easier for me to show the reactor way of doing it. But lets suppose you want to read a value from database and then use that value for another thing. Use flatmaps and make a unique Flux reducing the lines of code and complexity, no need to use subscribe() as told by the other people. Example:
return fooDao.findById(fooId)
.flatmap(foo -> bService.getCountBByFooId(foo))
.flatmap(bCount -> aService.getAByFooId(fooId).getCount()+bCount);
Related
so I have a question on OOP class design. I have read that we should "Tell, don't ask" and not use Exceptions for "Flow control". However in this particular case I see some redundant code being executed!
Lets assume Person have a list of events that he will be attending, and it must be enforced that he cannot attend an event that overlaps with his current schedule. So I have the following Java code
public class Person {
// this arraylist of events must not have overlapping events!
ArrayList<Events> eventsToAttend;
// checks if a person is free to attend a new event by viewing all events he is attending
public boolean canAttendEvent(Event newEvent) {
for(int i = 0; i < eventsToAttend.size(); i++) {
if (newEvent.isSameDayAndTime(eventsToAttend.get(i))) {
return false;
}
}
return true;
}
public void attendEvent(Event newEvent) {
// enforce the validity of the newEvent
if (!canAttendEvent(newEvent)) {
// throw exception and return
}
eventsToAttend.add(newEvent);
}
public static main(String[] args) {
// just an example usage!
Person person = somePersonWithEventsAlready;
Event event = new Event();
if (person.canAttendEvent(event)) {
// !!!
// Notice that canAttendEvent() is called twice!! how do you prevent this?
// !!!
person.attendEvent(event);
}
// Alternatively I could just try - catch around person.attendEvent(), but is that bad practise?
}
}
The issue I am facing in general with this way of doing things, is that "canAttendEvent()" is being called twice. However it is good practice according to OOP design patterns?
What would be a better way to do something like this? Thank you for reading this.
try - catch in the main is the best way to achieve what you are trying to avoid: call twice the function canAttendEvent
I'm trying to understand RxJava and I'm sure this question is a nonsense... I have this code using RxJava:
public Observable<T> getData(int id) {
if (dataAlreadyLoaded()) {
return Observable.create(new Observable.OnSubscribe<T>(){
T data = getDataFromMemory(id);
subscriber.onNext(data);
});
}
return Observable.create(new Observable.OnSubscribe<T>(){
#Override
public void call(Subscriber<? super String> subscriber) {
T data = getDataFromRemoteService(id);
subscriber.onNext(data);
}
});
}
And, for instance, I could use it this way:
Action1<String> action = new Action<String>() {
#Override
public void call(String s) {
//Do something with s
}
};
getData(3).subscribe(action);
and this another with callback that implements Runnable:
public void getData(int id, MyClassRunnable callback) {
if (dataAlreadyLoaded()) {
T data = getDataFromMemory(id);
callback.setData(data);
callback.run();
} else {
T data = getDataFromRemoteService(id);
callback.setData(data);
callback.run();
}
}
And I would use it this way:
getData(3, new MyClassRunnable()); //Do something in run method
Which are the differences? Why is the first one better?
The question is not about the framework itself but the paradigm. I'm trying to understand the use cases of reactive.
I appreciate any help. Thanks.
First of all, your RxJava version is much more complex than it needs to be. Here's a much simpler version:
public Observable<T> getData(int id) {
return Observable.fromCallable(() ->
dataAlreadyLoaded() ? getDataFromMemory(id) : getDataFromRemoteService(id)
);
}
Regardless, the problem you present is so trivial that there is no discernible difference between the two solutions. It's like asking which one is better for assigning integer values - var = var + 1 or var++. In this particular case they are identical, but when using assignment there are many more possibilities (adding values other than one, subtracting, multiplying, dividing, taking into account other variables, etc).
So what is it you can do with reactive? I like the summary on reactivex's website:
Easily create event streams or data streams. For a single piece of data this isn't so important, but when you have a stream of data the paradigm makes a lot more sense.
Compose and transform streams with query-like operators. In your above example there are no operators and a single stream. Operators let you transform data in handy ways, and combining multiple callbacks is much harder than combining multiple Observables.
Subscribe to any observable stream to perform side effects. You're only listening to a single event. Reactive is well-suited for listening to multiple events. It's also great for things like error handling - you can create a long sequence of events, but any errors are forwarded to the eventual subscriber.
Let's look at a more concrete with an example that has more intrigue: validating an email and password. You've got two text fields and a button. You want the button to become enabled once there is a email (let's say .*#.*) and password (of at least 8 characters) entered.
I've got two Observables that represent whatever the user has currently entered into the text fields:
Observable<String> email = /* you figure this out */;
Observable<String> password = /* and this, too */;
For validating each input, I can map the input String to true or false.
Observable<Boolean> validEmail = email.map(str -> str.matches(".*#.*"));
Observable<Boolean> validPw = password.map(str -> str.length() >= 8);
Then I can combine them to determine if I should enable the button or not:
Observable.combineLatest(validEmail, validPw, (b1, b2) -> b1 && b2)
.subscribe(enableButton -> /* enable button based on bool */);
Now, every time the user types something new into either text field, the button's state gets updated. I've setup the logic so that the button just reacts to the state of the text fields.
This simple example doesn't show it all, but it shows how things get a lot more interesting after you get past a simple subscription. Obviously, you can do this without the reactive paradigm, but it's simpler with reactive operators.
I'm using a PublishSubject along with map operator:
#Test
public void testMapWithMultipleObservers() {
PublishSubject<Integer> subject = PublishSubject.create();
Func1 action = spy(new Func1<Integer, Integer>() {
#Override
public Integer call(Integer integer) {
return integer;
}
});
Observable<Integer> observable = subject.asObservable().map(action);
observable.subscribe(mock(Observer.class));
observable.subscribe(mock(Observer.class));
subject.onNext(1);
verify(action, times(2)).call(anyInt());
// however, I need it to be times(1)
}
The desired behaviour is to perform an action after the subject produces a value. I've tried doOnEach,doOnNext, map and in each case the action is performed for each present observer (for 100 observers action would be performed 100 times), while I need it to perform per emission.
Could you suggest anything?
Thanks.
The quickest option would be to use share()
Observable<Integer> observable =
subject
.map(action)
.share();
You don't need the asObservable() call. It is used to return a Subject from an API and prevent the caller from casting it back to a Subject. For example:
Observable<Integer> getSubjectAsObservable() {
return subject.asObservable();
}
I have read dozens of posts about PROs and CONs of trying to mock \ fake EF in the business logic.
I have not yet decided what to do - but one thing I know is - I have to separate the queries from the business logic.
In this post I saw that Ladislav has answered that there are 2 good ways:
Let them be where they are and use custom extension methods, query views, mapped database views or custom defining queries to define reusable parts.
Expose every single query as method on some separate class. The method
mustn't expose IQueryable and mustn't accept Expression as parameter =
whole query logic must be wrapped in the method. But this will make
your class covering related methods much like repository (the only one
which can be mocked or faked). This implementation is close to
implementation used with stored procedures.
Which method do you think is better any why ?
Are there ANY downsides to put the queries in their own place ? (maybe losing some functionality from EF or something like that)
Do I have to encapsulate even the simplest queries like:
using (MyDbContext entities = new MyDbContext)
{
User user = entities.Users.Find(userId); // ENCAPSULATE THIS ?
// Some BL Code here
}
So I guess your main point is testability of your code, isn't it? In such case you should start by counting responsibilities of the method you want to test and than refactor your code using single responsibility pattern.
Your example code has at least three responsibilities:
Creating an object is a responsibility - context is an object. Moreover it is and object you don't want to use in your unit test so you must move its creation elsewhere.
Executing query is a responsibility. Moreover it is a responsibility you would like to avoid in your unit test.
Doing some business logic is a responsibility
To simplify testing you should refactor your code and divide those responsibilities to separate methods.
public class MyBLClass()
{
public void MyBLMethod(int userId)
{
using (IMyContext entities = GetContext())
{
User user = GetUserFromDb(entities, userId);
// Some BL Code here
}
}
protected virtual IMyContext GetContext()
{
return new MyDbContext();
}
protected virtual User GetUserFromDb(IMyDbContext entities, int userId)
{
return entities.Users.Find(userId);
}
}
Now unit testing business logic should be piece of cake because your unit test can inherit your class and fake context factory method and query execution method and become fully independent on EF.
// NUnit unit test
[TestFixture]
public class MyBLClassTest : MyBLClass
{
private class FakeContext : IMyContext
{
// Create just empty implementation of context interface
}
private User _testUser;
[Test]
public void MyBLMethod_DoSomething()
{
// Test setup
int id = 10;
_testUser = new User
{
Id = id,
// rest is your expected test data - that is what faking is about
// faked method returns simply data your test method expects
};
// Execution of method under test
MyBLMethod(id);
// Test validation
// Assert something you expect to happen on _testUser instance
// inside MyBLMethod
}
protected override IMyContext GetContext()
{
return new FakeContext();
}
protected override User GetUserFromDb(IMyContext context, int userId)
{
return _testUser.Id == userId ? _testUser : null;
}
}
As you add more methods and your application grows you will refactor those query execution methods and context factory method to separate classes to follow single responsibility on classes as well - you will get context factory and either some query provider or in some cases repository (but that repository will never return IQueryable or get Expression as parameter in any of its methods). This will also allow you following DRY principle where your context creation and most commonly used queries will be defined only once on one central place.
So at the end you can have something like this:
public class MyBLClass()
{
private IContextFactory _contextFactory;
private IUserQueryProvider _userProvider;
public MyBLClass(IContextFactory contextFactory, IUserQueryProvider userProvider)
{
_contextFactory = contextFactory;
_userProvider = userProvider;
}
public void MyBLMethod(int userId)
{
using (IMyContext entities = _contextFactory.GetContext())
{
User user = _userProvider.GetSingle(entities, userId);
// Some BL Code here
}
}
}
Where those interfaces will look like:
public interface IContextFactory
{
IMyContext GetContext();
}
public class MyContextFactory : IContextFactory
{
public IMyContext GetContext()
{
// Here belongs any logic necessary to create context
// If you for example want to cache context per HTTP request
// you can implement logic here.
return new MyDbContext();
}
}
and
public interface IUserQueryProvider
{
User GetUser(int userId);
// Any other reusable queries for user entities
// Non of queries returns IQueryable or accepts Expression as parameter
// For example: IEnumerable<User> GetActiveUsers();
}
public class MyUserQueryProvider : IUserQueryProvider
{
public User GetUser(IMyContext context, int userId)
{
return context.Users.Find(userId);
}
// Implementation of other queries
// Only inside query implementations you can use extension methods on IQueryable
}
Your test will now only use fakes for context factory and query provider.
// NUnit + Moq unit test
[TestFixture]
public class MyBLClassTest
{
private class FakeContext : IMyContext
{
// Create just empty implementation of context interface
}
[Test]
public void MyBLMethod_DoSomething()
{
// Test setup
int id = 10;
var user = new User
{
Id = id,
// rest is your expected test data - that is what faking is about
// faked method returns simply data your test method expects
};
var contextFactory = new Mock<IContextFactory>();
contextFactory.Setup(f => f.GetContext()).Returns(new FakeContext());
var queryProvider = new Mock<IUserQueryProvider>();
queryProvider.Setup(f => f.GetUser(It.IsAny<IContextFactory>(), id)).Returns(user);
// Execution of method under test
var myBLClass = new MyBLClass(contextFactory.Object, queryProvider.Object);
myBLClass.MyBLMethod(id);
// Test validation
// Assert something you expect to happen on user instance
// inside MyBLMethod
}
}
It would be little bit different in case of repository which should have reference to context passed to its constructor prior to injecting it to your business class.
Your business class can still define some queries which are never use in any other classes - those queries are most probably part of its logic. You can also use extension methods to define some reusable part of queries but you must always use those extension methods outside of your core business logic which you want to unit test (either in query execution methods or in query provider / repository). That will allow you easy faking query provider or query execution methods.
I saw your previous question and thought about writing a blog post about that topic but the core of my opinion about testing with EF is in this answer.
Edit:
Repository is different topic which doesn't relate to your original question. Specific repository is still valid pattern. We are not against repositories, we are against generic repositories because they don't provide any additional features and don't solve any problem.
The problem is that repository alone doesn't solve anything. There are three patterns which have to be used together to form proper abstraction: Repository, Unit of Work and Specifications. All three are already available in EF: DbSet / ObjectSet as repositories, DbContext / ObjectContext as Unit of works and Linq to Entities as specifications. The main problem with custom implementation of generic repositories mentioned everywhere is that they replace only repository and unit of work with custom implementation but still depend on original specifications => abstraction is incomplete and it is leaking in tests where faked repository behaves in the same way as faked set / context.
The main disadvantage of my query provider is explicit method for any query you will need to execute. In case of repository you will not have such methods you will have just few methods accepting specification (but again those specifications should be defined in DRY principle) which will build query filtering conditions, ordering etc.
public interface IUserRepository
{
User Find(int userId);
IEnumerable<User> FindAll(ISpecification spec);
}
The discussion of this topic is far beyond the scope of this question and it requires you to do some self study.
Btw. mocking and faking has different purpose - you fake a call if you need to get testing data from method in the dependency and you mock the call if you need to assert that method on dependency was called with expected arguments.
I have a rather complex bit of resolving going on in Autofac. Basically I want all the objects in the container which implement a specifically named method with a specific argument type. I have implemented some somewhat insane code to get it for me
var services = (from registrations in _componentContext.ComponentRegistry.Registrations
from service in registrations.Services
select service).Distinct();
foreach (var service in services.OfType<Autofac.Core.TypedService>())
{
foreach (var method in service.ServiceType.GetMethods().Where(m => m.Name == "Handle"
&& m.GetParameters().Where(p => p.ParameterType.IsAssignableFrom(implementedInterface)).Count() > 0))
{
var handler = _componentContext.Resolve(service.ServiceType);
method.Invoke(handler, new Object[] { convertedMessage });
}
}
My problem arises in that the handler returned the the resolution step is always the same handler and I cannot see a way to resolve a collection of the the registrations which are tied to the service as one might normally do with container.Resolve>().
I feel like I'm pushing pretty hard against what AutoFac was designed to do and might do better with a MEF based solution. Is there an easy AutoFac based solution to this issue or should I hop over to a more composition based approach?
G'day,
In MEF you could use 'Method Exports' for this (http://mef.codeplex.com/wikipage?title=Declaring%20Exports) but that might be a bit drastic. There are a couple of ways to achieve what you want in Autofac.
You can make the above code work by searching for registrations rather than services:
var implementorMethods = _componentContext.ComponentRegistry.Registrations
.Select(r => new {
Registration = r,
HandlerMethod = r.Services.OfType<TypedService>()
.SelectMany(ts => ts.ServiceType.GetMethods()
.Where(m => m.Name == "Handle" && ...))
.FirstOrDefault()
})
.Where(im => im.HandlerMethod != null);
foreach (var im in implementorMethods)
{
var handler = _componentContext.ResolveComponent(im.Registration, new List<Parameter>());
im.HandlerMethod.Invoke(handler, new object[] { convertedMessage });
}
I.e. implementorMethods is a list of the components implementing a handler method, along with the method itself. ResolveComponent() doesn't rely on a service to identify the implementation, so there's no problem with the service not uniquely identifying a particular implementor.
This technique in general will probably perform poorly (if perf is a concern here) but also as you suspect will work against the design goals of Autofac (and MEF,) eliminating some of the benefits.
Ideally you need to define a contract for handlers that will let you look up all handlers for a message type in a single operation.
The typical recipe looks like:
interface IHandler<TMessage>
{
void Handle(TMessage message);
}
Handlers then implement the appropriate interface:
class FooHandler : IHandler<Foo> { ... }
...and get registered at build-time like so:
var builder = new ContainerBuilder();
builder.RegisterAssemblyTypes(typeof(FooHandler).Assembly)
.AsClosedTypesOf(typeof(IHandler<>));
To invoke the handlers, define a message dispatcher contract:
interface IMessageDispatcher
{
void Dispatch(object message);
}
...and then its implementation:
class AutofacMessageDispatcher : IMessageDispatcher
{
static readonly MethodInfo GenericDispatchMethod =
typeof(AutofacMessageDispatcher).GetMethod(
"GenericDispatch", BindingFlags.NonPublic | BindingFlags.Instance);
IComponentContext _cc;
public AutofacMessageDispatcher(IComponentContext cc)
{
_cc = cc;
}
public void Dispatch(object message)
{
var dispatchMethod = GenericDispatchMethod
.MakeGenericMethod(message.GetType());
dispatchMethod.Invoke(this, new[] { message });
}
void GenericDispatch<TMessage>(TMessage message)
{
var handlers = _cc.Resolve<IEnumerable<IHandler<TMessage>>>();
foreach (var handler in handlers)
handler.Handle(message);
}
}
...which is registered like so:
builder.RegisterType<AutofacMessageDispatcher>()
.As<IMessageDispatcher>();
The component that feeds in the messages will then resolve/use IMessageDispatcher to get the messages to the handlers.
var dispatcher = _cc.Resolve<IMessageDispatcher>();
dispatcher.Dispatch(message);
There are still ways to do this without the interface, but all rely on creating some kind of contract that uniquely defines handlers for a particular message (e.g. a delegate.)
In the long run the generic handler pattern will be the easiest to maintain.
Hope this helps, Nick.