I want my code to repeat a certain asynchronous operation until this operation is successful (i.e. until it returns true).
At the moment I'm using the following workaround:
Supplier<Observable<Boolean>> myOperation = () -> {
// do something useful and return 'true' if it was successful
// NOTE: GENERATING A RANDOM NUMBER IS JUST AN EXAMPLE HERE
// I WANT TO RUN AN ASYNCHRONOUS OPERATION (LIKE PINGING A SERVER
// OR THE LIKE) AND RETRY IT UNTIL IT SUCCEEDS.
System.out.println("Try");
return Observable.just(Math.random() > 0.9);
};
final Throwable retry = new IllegalStateException();
Observable.<Boolean>create(subscriber -> {
myOperation.get().subscribe(subscriber);
}).flatMap(b -> b ? Observable.just(b) : Observable.error(retry))
.retryWhen(exceptions -> exceptions.flatMap(exception -> {
if (exception == retry) {
return Observable.timer(1, TimeUnit.SECONDS);
}
return Observable.error(exception);
}))
.toBlocking()
.forEach(b -> {
System.out.println("Connected.");
});
It works well and prints out something like this:
Try
Try
...
Try
Connected.
The code does what I want, but it doesn't look very elegant. I'm sure there must be a better way. Maybe by using a custom Operator?
Does anybody know how to achieve the same thing in RxJava but in a more readable manner and without the artificial Throwable?
Not enough time, so this is going to be by memory...
public class Randomizer implements Iterable<Double>, Iterator<Double> {
public Iterator<Double> getIterator() {return this;}
public boolean hasNext() {return true;}
public Double next() {return Math.random();}
}
...
Observable.from(new Randomizer())
.takeWhile(value -> value < 0.99);
// or takeUntil(value -> value > 0.99); can't remember their differences.
OTOH if you need to do something more complex, look into Observable.defer() and / or a BehaviorSubject.
Edit: Now there's a bit more time to read your post, you could try something like this:
Observable.defer(() -> createConnectionObservable())
.retry((count, err) -> {
if(count>9) return false;
if(!(err instanceof IOException)) return false;
return true;
})
Keep in mind that if you use Retrofit you shouldn't need defer(), as retrofit will re-initiate the call when a new subscription happens.
Related
I try to make a code more compact by coding a helper method, because the code is very repetitive.
The code consists of:
call a command (remote ssh, or local command, this part is not interesting for my question)
check if it was a success
if not, stop here and return the return code to the calling method (i.e. return cr;)
if success, continue with another command
I tried to create a helper method that do all that. If the command execution is a failure, it will return an Optional<Integer> of the return code. If it works as expected, it returns a Optional.empty().
My question is how to do something like that:
public void topMethod()
{
int cr = execCmds();
... do stuff with cr ...
}
private int execCmds()
{
executeCmd("my command").ifPresent(cr -> return cr);
executeCmd("my next command").ifPresent(cr -> return cr);
....
return 0;
}
As you can see, I want to stop the flow if the return code is meaningful. If not it must continue. Is there a way to do that? (Something concise.)
For information, the return cr is invalid in the ifPresent lambda method.
Use Optional.or()
Optional.or() was introduced with JDK 9, and expects a Supplier of Optional.
In a nutshell, method or() checks whether the Optional on which it is applied is empty, and if that's the case it replaces it with another optional. otherwise, if value is present, it would return the same optional (i.e. Supplier passed as an argument wouldn't be executed, functions are evaluated lazily).
public void topMethod() {
int cr = execCmds();
// do something with cr
}
private int execCmds() {
return executeCmd("my command")
.or(() -> executeCmd("my next command"))
.or(...) // more alternatives
.orElse(0);
}
public Optional<Integer> executeCmd(String command) {
return // something;
}
Stream of Suppliers
Another option would be to create a Stream of Supplier of Optional.
It can be useful if you're using JDK 8 (and therefor can't use or), or if executeCmd() returns an OptionalInt which lacks method or().
Stream would process each Supplier lazily, one at a time, and As well as in the previous solution each executeCmd() invocation would occur only if needed (if the previous command failed to provide the result).
Here's how it can be implemented:
public void topMethod() {
int cr = execCmds();
// do something with cr
}
private int execCmds() {
return Stream.<Supplier<OptionalInt>>of(
() -> executeCmd("my command"),
() -> executeCmd("my next command")
// ...
) // Stream<Supplier<OptionalInt>>>
.map(Supplier::get) // Stream<<OptionalInt>>
.filter(OptionalInt::isPresent) // Stream<<OptionalInt>>
.mapToInt(OptionalInt::getAsInt) // IntStream
.findFirst() // OptionalInt
.orElse(0);
}
public OptionalInt executeCmd(String command) {
return // something;
}
Would chaining your commands with or work? Something like
private int execCmds()
{
return executeCmd("command one")
.or(() -> executeCmd("command two")
.or(() -> executeCmd("command three")
.orElse(0);
}
I have these two methods which call an async API and return a Mono<Boolean> if a value exists. I am returning a random boolean value for the sake of this example,
private Mono<Boolean> checkFirstExists() {
// Replacing actual API call here
return Mono.just(Boolean.FALSE);
}
private Mono<Boolean> checkSecondExists() {
// Replacing actual API call here
return Mono.just(Boolean.TRUE);
}
Now, I have another method that should combine the results of these two methods and simply return a boolean if either checkFirstExists or checkSecondExists is true.
private boolean checkIfExists() {
// Should return true if any of the underlying method returns true
final Flux<Boolean> exists = Flux.concat(checkFirstExists(), checkSecondExists());
return exists.blockFirst();
}
What's the best way of doing this? Mono.zip maybe? Any help would be great.
Mono.zip is the correct approach for awaiting completion of multiple async operations before continuing. Something like this should work:
return Mono.zip(checkFirstExists(), checkSecondExists(), (first, second) -> first && second);
Or if a list is provided instead:
private boolean checkIfExists()
{
return allTrue(Arrays.asList(checkFirstExists(), checkSecondExists())).blockOptional().orElseThrow(() -> new IllegalStateException("Invalid State"));
}
private Mono<Boolean> allTrue(List<Mono<Boolean>> toAggregate)
{
return mergeMonos(toAggregate).map(list -> list.stream().allMatch(val -> val));
}
#SuppressWarnings("unchecked")
private <T> Mono<List<T>> mergeMonos(List<Mono<T>> toAggregate)
{
return Mono.zip(toAggregate, array -> Stream.of(array).map(o -> (T) o).collect(Collectors.toList()));
}
Unrelated Note:
In general, it is worth keeping the operation async as long as possible when constructing reactive flows. It may be worth having the 'checkIfExists' function return a Mono instead of blocking.
I understand you can't return from a ifPresent() so this example does not work:
public boolean checkSomethingIfPresent() {
mightReturnAString().ifPresent((item) -> {
if (item.equals("something")) {
// Do some other stuff like use "something" in API calls
return true; // Does not compile
}
});
return false;
}
Where mightReturnAString() could return a valid string or an empty optional. What I have done that works is:
public boolean checkSomethingIsPresent() {
Optional<String> result = mightReturnAString();
if (result.isPresent()) {
String item = result.get();
if (item.equals("something") {
// Do some other stuff like use "something" in API calls
return true;
}
}
return false;
}
which is longer and does not feel much different to just checking for nulls in the first place. I feel like there must be a more succinct way using Optional.
I think all you're looking for is simply filter and check for the presence then:
return result.filter(a -> a.equals("something")).isPresent();
How about mapping to a boolean?
public boolean checkSomethingIfPresent() {
return mightReturnAString().map(item -> {
if (item.equals("something")) {
// Do some other stuff like use "something" in API calls
return true; // Does not compile
}
return false; // or null
}).orElse(false);
}
While #nullpointer and #Ravindra showed how to merge the Optional with another condition, you'll have to do a bit more to be able to call APIs and do other stuff as you asked in the question. The following looks quite readable and concise in my opinion:
private static boolean checkSomethingIfPresent() {
Optional<String> str = mightReturnAString();
if (str.filter(s -> s.equals("something")).isPresent()) {
//call APIs here using str.get()
return true;
}
return false;
}
A better design would be to chain methods:
private static void checkSomethingIfPresent() {
mightReturnFilteredString().ifPresent(s -> {
//call APIs here
});
}
private static Optional<String> mightReturnFilteredString() {
return mightReturnAString().filter(s -> s.equals("something"));
}
private static Optional<String> mightReturnAString() {
return Optional.of("something");
}
The ideal solution is “command-query separation”: Make one method (command) for doing something with the string if it is present. And another method (query) to tell you whether it was there.
However, we don’t live an ideal world, and perfect solutions are never possible. If in your situation you cannot separate command and query, my taste is for the idea already presented by shmosel: map to a boolean. As a detail I would use filter rather than the inner if statement:
public boolean checkSomethingIfPresent() {
return mightReturnAString().filter(item -> item.equals("something"))
.map(item -> {
// Do some other stuff like use "something" in API calls
return true; // (compiles)
})
.orElse(false);
}
What I don’t like about it is that the call chain has a side effect, which is not normally expected except from ifPresent and ifPresentOrElse (and orElseThrow, of course).
If we insist on using ifPresent to make the side effect clearer, that is possible:
AtomicBoolean result = new AtomicBoolean(false);
mightReturnAString().filter(item -> item.equals("something"))
.ifPresent(item -> {
// Do some other stuff like use "something" in API calls
result.set(true);
});
return result.get();
I use AtomicBoolean as a container for the result since we would not be allowed to assign to a primitive boolean from within the lambda. We don’t need its atomicity, but it doesn’t harm either.
Link: Command–query separation on Wikipedia
By the way if you really want to get value from Optional, use:
Optional<User> user = service.getCurrentUset();
return user.map(User::getId);
With Java 8, I have this code:
if(element.exist()){
// Do something
}
I want to convert to lambda style,
element.ifExist(el -> {
// Do something
});
with an ifExist method like this:
public void ifExist(Consumer<Element> consumer) {
if (exist()) {
consumer.accept(this);
}
}
But now I have else cases to call:
element.ifExist(el -> {
// Do something
}).ifNotExist(el -> {
// Do something
});
I can write a similar ifNotExist, and I want they are mutually exclusive (if the exist condition is true, there is no need to check ifNotExist, because sometimes, the exist() method takes so much workload to check), but I always have to check two times. How can I avoid that?
Maybe the "exist" word make someone misunderstand my idea. You can imagine that I also need some methods:
ifVisible()
ifEmpty()
ifHasAttribute()
Many people said that this is bad idea, but:
In Java 8 we can use lambda forEach instead of a traditional for loop. In programming for and if are two basic flow controls. If we can use lambda for a for loop, why is using lambda for if bad idea?
for (Element element : list) {
element.doSomething();
}
list.forEach(Element::doSomething);
In Java 8, there's Optional with ifPresent, similar to my idea of ifExist:
Optional<Elem> element = ...
element.ifPresent(el -> System.out.println("Present " + el);
And about code maintenance and readability, what do you think if I have the following code with many repeating simple if clauses?
if (e0.exist()) {
e0.actionA();
} else {
e0.actionB();
}
if (e1.exist()) {
e0.actionC();
}
if (e2.exist()) {
e2.actionD();
}
if (e3.exist()) {
e3.actionB();
}
Compare to:
e0.ifExist(Element::actionA).ifNotExist(Element::actionB);
e1.ifExist(Element::actionC);
e2.ifExist(Element::actionD);
e3.ifExist(Element::actionB);
Which is better? And, oops, do you notice that in the traditional if clause code, there's a mistake in:
if (e1.exist()) {
e0.actionC(); // Actually e1
}
I think if we use lambda, we can avoid this mistake!
As it almost but not really matches Optional, maybe you might reconsider the logic:
Java 8 has a limited expressiveness:
Optional<Elem> element = ...
element.ifPresent(el -> System.out.println("Present " + el);
System.out.println(element.orElse(DEFAULT_ELEM));
Here the map might restrict the view on the element:
element.map(el -> el.mySpecialView()).ifPresent(System.out::println);
Java 9:
element.ifPresentOrElse(el -> System.out.println("Present " + el,
() -> System.out.println("Not present"));
In general the two branches are asymmetric.
It's called a 'fluent interface'. Simply change the return type and return this; to allow you to chain the methods:
public MyClass ifExist(Consumer<Element> consumer) {
if (exist()) {
consumer.accept(this);
}
return this;
}
public MyClass ifNotExist(Consumer<Element> consumer) {
if (!exist()) {
consumer.accept(this);
}
return this;
}
You could get a bit fancier and return an intermediate type:
interface Else<T>
{
public void otherwise(Consumer<T> consumer); // 'else' is a keyword
}
class DefaultElse<T> implements Else<T>
{
private final T item;
DefaultElse(final T item) { this.item = item; }
public void otherwise(Consumer<T> consumer)
{
consumer.accept(item);
}
}
class NoopElse<T> implements Else<T>
{
public void otherwise(Consumer<T> consumer) { }
}
public Else<MyClass> ifExist(Consumer<Element> consumer) {
if (exist()) {
consumer.accept(this);
return new NoopElse<>();
}
return new DefaultElse<>(this);
}
Sample usage:
element.ifExist(el -> {
//do something
})
.otherwise(el -> {
//do something else
});
You can use a single method that takes two consumers:
public void ifExistOrElse(Consumer<Element> ifExist, Consumer<Element> orElse) {
if (exist()) {
ifExist.accept(this);
} else {
orElse.accept(this);
}
}
Then call it with:
element.ifExistOrElse(
el -> {
// Do something
},
el -> {
// Do something else
});
The problem
(1) You seem to mix up different aspects - control flow and domain logic.
element.ifExist(() -> { ... }).otherElementMethod();
^ ^
control flow method business logic method
(2) It is unclear how methods after a control flow method (like ifExist, ifNotExist) should behave. Should they be always executed or be called only under the condition (similar to ifExist)?
(3) The name ifExist implies a terminal operation, so there is nothing to return - void. A good example is void ifPresent(Consumer) from Optional.
The solution
I would write a fully separated class that would be independent of any concrete class and any specific condition.
The interface is simple, and consists of two contextless control flow methods - ifTrue and ifFalse.
There can be a few ways to create a Condition object. I wrote a static factory method for your instance (e.g. element) and condition (e.g. Element::exist).
public class Condition<E> {
private final Predicate<E> condition;
private final E operand;
private Boolean result;
private Condition(E operand, Predicate<E> condition) {
this.condition = condition;
this.operand = operand;
}
public static <E> Condition<E> of(E element, Predicate<E> condition) {
return new Condition<>(element, condition);
}
public Condition<E> ifTrue(Consumer<E> consumer) {
if (result == null)
result = condition.test(operand);
if (result)
consumer.accept(operand);
return this;
}
public Condition<E> ifFalse(Consumer<E> consumer) {
if (result == null)
result = condition.test(operand);
if (!result)
consumer.accept(operand);
return this;
}
public E getOperand() {
return operand;
}
}
Moreover, we can integrate Condition into Element:
class Element {
...
public Condition<Element> formCondition(Predicate<Element> condition) {
return Condition.of(this, condition);
}
}
The pattern I am promoting is:
work with an Element;
obtain a Condition;
control the flow by the Condition;
switch back to the Element;
continue working with the Element.
The result
Obtaining a Condition by Condition.of:
Element element = new Element();
Condition.of(element, Element::exist)
.ifTrue(e -> { ... })
.ifFalse(e -> { ... })
.getOperand()
.otherElementMethod();
Obtaining a Condition by Element#formCondition:
Element element = new Element();
element.formCondition(Element::exist)
.ifTrue(e -> { ... })
.ifFalse(e -> { ... })
.getOperand()
.otherElementMethod();
Update 1:
For other test methods, the idea remains the same.
Element element = new Element();
element.formCondition(Element::isVisible);
element.formCondition(Element::isEmpty);
element.formCondition(e -> e.hasAttribute(ATTRIBUTE));
Update 2:
It is a good reason to rethink the code design. Neither of 2 snippets is great.
Imagine you need actionC within e0.exist(). How would the method reference Element::actionA be changed?
It would be turned back into a lambda:
e0.ifExist(e -> { e.actionA(); e.actionC(); });
unless you wrap actionA and actionC in a single method (which sounds awful):
e0.ifExist(Element::actionAAndC);
The lambda now is even less 'readable' then the if was.
e0.ifExist(e -> {
e0.actionA();
e0.actionC();
});
But how much effort would we make to do that? And how much effort will we put into maintaining it all?
if(e0.exist()) {
e0.actionA();
e0.actionC();
}
If you are performing a simple check on an object and then executing some statements based on the condition then one approach would be to have a Map with a Predicate as key and desired expression as value
for example.
Map<Predicate<Integer>,Supplier<String>> ruleMap = new LinkedHashMap <Predicate<Integer>,Supplier<String>>(){{
put((i)-> i<10,()->"Less than 10!");
put((i)-> i<100,()->"Less than 100!");
put((i)-> i<1000,()->"Less than 1000!");
}};
We could later stream the following Map to get the value when the Predicate returns true which could replace all the if/else code
ruleMap.keySet()
.stream()
.filter((keyCondition)->keyCondition.test(numItems,version))
.findFirst()
.ifPresent((e)-> System.out.print(ruleMap.get(e).get()));
Since we are using findFirst() it is equivalent to if/else if /else if ......
How can I express this with java8 streaming-API?
I want to perform itemConsumer for every item of a stream. If there
are no items I want to perform emptyAction.
Of course I could write something like this:
Consumer<Object> itemConsumer = System.out::println;
Runnable emptyAction = () -> {System.out.println("no elements");};
Stream<Object> stream = Stream.of("a","b"); // or Stream.empty()
List<Object> list = stream.collect(Collectors.toList());
if (list.isEmpty())
emptyAction.run();
else
list.stream().forEach(itemConsumer);
But I would prefer to avoid any Lists.
I also thought about setting a flag in a peek method - but that flag would be non-final and therefore not allowed. Using a boolean container also seems to be too much of a workaround.
You could coerce reduce to do this. The logic would be to reduce on false, setting the value to true if any useful data is encountered.
The the result of the reduce is then false then no items have been encountered. If any items were encountered then the result would be true:
boolean hasItems = stream.reduce(false, (o, i) -> {
itemConsumer.accept(i);
return true;
}, (l, r) -> l | r);
if (!hasItems) {
emptyAction.run();
}
This should work fine for parallel streams, as any stream encountering an item would set the value to true.
I'm not sure, however, that I like this as it's a slightly obtuse use of the reduce operation.
An alternative would be to use AtomicBoolean as a mutable boolean container:
final AtomicBoolean hasItems = new AtomicBoolean(false);
stream.forEach(i -> {
itemConsumer.accept(i);
hasItems.set(true);
});
if (!hasItems.get()) {
emptyAction.run();
}
I don't know if I like that more or less however.
Finally, you could have your itemConsumer remember state:
class ItemConsumer implements Consumer<Object> {
private volatile boolean hasConsumedAny;
#Override
public void accept(Object o) {
hasConsumedAny = true;
//magic magic
}
public boolean isHasConsumedAny() {
return hasConsumedAny;
}
}
final ItemConsumer itemConsumer = new ItemConsumer();
stream.forEach(itemConsumer::accept);
if (!itemConsumer.isHasConsumedAny()) {
emptyAction.run();
}
This seems a bit neater, but might not be practical. So maybe a decorator pattern -
class ItemConsumer<T> implements Consumer<T> {
private volatile boolean hasConsumedAny;
private final Consumer<T> delegate;
ItemConsumer(final Consumer<T> delegate) {
this.delegate = delegate;
}
#Override
public void accept(T t) {
hasConsumedAny = true;
delegate.accept(t);
}
public boolean isHasConsumedAny() {
return hasConsumedAny;
}
}
final ItemConsumer<Object> consumer = new ItemConsumer<Object>(() -> /** magic **/);
TL;DR: something has to remember whether you encountered anything during the consumption of the Stream, be it:
the Stream itself in case of reduce;
AtomicBoolean; or
the consumer
I think the consumer is probably best placed, from a logic point of view.
A solution without any additional variables:
stream.peek(itemConsumer).reduce((a, b) -> a).orElseGet(() -> {
emptyAction.run();
return null;
});
Note that if the stream is parallel, then itemConsumer could be called simultaneously for different elements in different threads (like in forEach, not in forEachOrdered). Also this solution will fail if the first stream element is null.
There’s a simple straight-forward solution:
Spliterator<Object> sp=stream.spliterator();
if(!sp.tryAdvance(itemConsumer))
emptyAction.run();
else
sp.forEachRemaining(itemConsumer);
You can even keep parallel support for the elements after the first, if you wish:
Spliterator<Object> sp=stream.parallel().spliterator();
if(!sp.tryAdvance(itemConsumer))
emptyAction.run();
else
StreamSupport.stream(sp, true).forEach(itemConsumer);
In my opinion, it is much easier to understand as a reduce based solution.
You could do this:
if(stream.peek(itemConsumer).count() == 0){
emptyAction.run();
}
But it seems that count may be changed to skip the peek if it knows the size of the Stream in Java 9 (see here), so if you want it to work in the future you could use:
if(stream.peek(itemConsumer).mapToLong(e -> 1).sum() == 0){
emptyAction.run();
}
Another attempt to use reduce:
Stream<Object> stream = Stream.of("a","b","c");
//Stream<Object> stream = Stream.empty();
Runnable defaultRunnable = () -> System.out.println("empty Stream");
Consumer<Object> printConsumer = System.out::println;
Runnable runnable = stream.map(x -> toRunnable(x, printConsumer)).reduce((a, b) -> () -> {
a.run();
b.run();
}).orElse(defaultRunnable);
runnable.run(); // prints a, b, c (or empty stream when it is empty)
// for type inference
static <T> Runnable toRunnable(T t, Consumer<T> cons){
return ()->cons.accept(t);
}
This approach does not use peek() which according to Javadoc "mainly exists to support debugging"