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Extract all True properties and add to a list

I have a java class with 3 boolean property like this
boolean isActive;
boolean isEnable;
boolean isNew;
every property is related to an enum (e.g. ACTIVE,ENABLE,NEW).
I want to have 2 lists of enum. One which has only the enums related to true property value and one for the false one.
just to be clear. using if-else statement I could have
Set<FlagEnum> flagSet = new HashSet<>();
Set<FlagEnum> falseFlagSet = new HashSet<>();
if (object.isActive()) {
flagSet.add(ACTIVE);
} else {
falseFlagSet.add(ACTIVE);
}
if (object.isEnable()) {
flagSet.add(ENABLE);
} else {
falseFlagSet.add(ENABLE);
}
if (object.isNew()) {
flagSet.add(NEW);
} else {
falseFlagSet.add(NEW);
}
is there a way to avoid all these if-else?
I tried with something like
Map<boolean, List<Pair<boolean, FlagEnum>>> res = Stream.of(
new Pair<>(object.isActive(), ACTIVE),
new Pair<>(object.isNew(), NEW),
new Pair<>(object.isEnable(), ENABLE))
.collect(Collectors.partitioningBy(Pair::getKey));
but the resulted structure is an additional complexity which I would like to avoid.
In my real case, I have more than 15 boolean properties...

You can simplify this in various ways. Which of them make sense, depends on your exact requirements.
You can derive the falseFlagSet trivially from the flagSet using EnumSet.complementOf after populating the flagSet:
EnumSet<FlagEnum> falseFlagSet = EnumSet.complementOf(flagSet);
This assumes that all FlagEnum values have corresponding flags. If that's not the case then you need to construct a EnumSet with all enums that have flags and subtract flagSet from that using removeAll.
#1 already removes the need for the else in your cascade, simplifying the code to
if (object.isActive()) {
flagSet.add(ACTIVE);
}
if (object.isEnable()) {
flagSet.add(ENABLE);
}
if (object.isNew()) {
flagSet.add(NEW);
}
If you have enough different flags, then you can create a mapping from getter method to FlagEnum value like this:
Map<Function<YourClass,Boolean>,FlagEnum> GETTERS = Map.of(
YourClass::isActive, FlagEnum.ACTIVE,
YourClass::isNew, FlagEnum.NEW,
YourClass::isEnable, FlagEnum.ENABLE);
Then you can use this to make the whole process data-driven:
EnumSet<FlagEnum> getFlagSet(YourClass yourObject) {
EnumSet<FlagEnum> result = EnumSet.noneOf(FlagEnum.class);
for (Map.Entry<Function<YourClass,Boolean>, FlagEnum> getter : GETTERS.entrySet()) {
if (getter.getKey().apply(yourObject)) {
result.add(getter.getValue());
}
}
return result;
}
If the number of flags is very big, then you could switch entirely to reflection and detect the flags and matching getters dynamically using string comparison, but I would not suggest that approach. If you need something like that then you probably should switch to a framework that supports that kind of feature and not implement it yourself.
That last two obviously only makes sense when the number of flags is big. If it's actually just 3 flags, then I wouldn't mind and just have 3 simple if statements.
As a slight tangent: GETTERS above should definitely be an immutable map (wrap it in Collections.unmodifiableMap or use something like Guava ImmutableMap) and it could be argued that the same applies to the return value of the getFlagSet method. I've left those out for succinctness.

You can use a private helper method for this.
private void addFlagSet(boolean condition, FlagEnum flagEnum,
Set<FlagEnum> flagSet, Set<FlagEnum> falseFlagSet) {
Set<FlagEnum> chosenFlagSet = condition ? flagSet: falseFlagSet;
chosenFlagSet.add(flagEnum);
}
Call it as:
addFlagSet(object.isActive(), FlagEnum.ACIVE, flagSet, falseFlagSet);
addFlagSet(object.isNew(), FlagEnum.NEW, flagSet, falseFlagSet);
addFlagSet(object.isEnable(), FlagEnum.ENABLE, flagSet, falseFlagSet);

You could probably use Reflection to get all methods, then check if a getReturnType() == boolean.class. Problem is the connection between the method's name and the enum. If every single one is named like the method without the 'is', you could use FlagEnum.valueOf() to retrieve the enum value from the method name and use it.

I think this could be the easiest and clearest way to do what I need
Map<Boolean, Set<FlagEnum>> flagMap = new HashMap<>();
flagMap.computeIfAbsent(object.isActive(), h -> new HashSet()).add(ACTIVE);
flagMap.computeIfAbsent(object.isEnabled(), h -> new HashSet()).add(ENABLE);
flagMap.computeIfAbsent(object.isNew(), h -> new HashSet()).add(NEW);
//to get TRUE set simply :
flagMap.get(true);
what do you think?

Is there a clearer way to deal with short-lived optionals?

I love Optional in Java. It has, in one simple class, allowed me to clearly identify return types and arguments which may or may not be available.
One thing that I struggle with is the necessity of assigning it to a short-lived variable which is then inherited into every subsequent scope.
I like to use the simple variable name opt when using optionals like this:
Optional<ThingA> opt = maybeGetThing();
if (opt.isPresent()) {
ThingA usefulVariableName = opt.get();
...
But when I then need a variable name to use in this scope...
void method() {
Optional<ThingA> opt = maybeGetThing();
if (opt.isPresent()) {
ThingA usefulVariableName = opt.get();
usefulVariableName.doA();
usefulVariableName.doB();
usefulVariableName.doC();
// Duplicate local variable opt
Optional<ThingB> opt = usefulVariableName.maybeAnotherThing();
}
}
I can use things like optA and optB and so on. But I wonder if there is another way to write this code without having to enumerate my temporary variables. This just smacks of lazy variable names like a aaaa aaaaaabbb or something.
I don't want to name all of my optionals explicitly like this:
Optional<ThingA> optUsefulVariableName = maybeGetThing();
if (optUsefulVariableName.isPresent()) {
ThingA usefulVariableName = optUsefulVariableName.get();
...
While accurate, it is extremely verbose. I also try to use throwaway names like opt and i to indicate that these are in fact only temporary and should serve no purpose beyond their immediate scope (even though they will be inherited).
UPDATE:
I have seen suggestions for using ifPresent() but I don't see how I can use this for instances where I also need to perform an action if the optional is empty:
void method() {
Optional<ThingA> opt = maybeGetThing();
if (!opt.isPresent()) {
doSomethingOnlyHere();
return;
}
if (opt.isPresent()) {
ThingA usefulVariableName = opt.get();
usefulVariableName.doA();
usefulVariableName.doB();
usefulVariableName.doC();
// Duplicate local variable opt
Optional<ThingB> opt = usefulVariableName.maybeAnotherThing();
}
}
When I try to refactor with ifPresent():
void method() {
// Doesn't handle instance where I need side effects on an empty optional
maybeGetThing().ifPresent(usefulVariableName -> {
...
}
}

The most basic way to eliminate the variable and the need to call Optional#get is to use Optional.ifPresent which calls a function if the Optional has a value.
maybeGetThing().ifPresent(val -> {
// do stuff with side effects here
});
This is still quite a limited way to use Optional, as one of Optionals key purposes is to facilitate programming in a functional style. If you are a beginner this may be a little lost on you, but the idea is to have functions that return something and not functions that rely on side effects. Functions relying on side effects cannot be chained together and are generally harder to reason about.
Technically Optional is something called a Functor (from category theory). It is a wrapper around a value (Whatever T is) and it allows the value to be passed through a series of operations to operate on it and pass it to the next operation until we have what we want, then the chain of operations ends with a terminal (i.e. final) operation. The terminal operation may return the unwrapped value if it exists or it could throw or return some default value if it doesn't.
For Optional it will skip any subsequent operations if the value becomes not present.
There are common operations like map, filter, flatMap (ok that's a Monad operation) and other more java specific operations like Optional#orElse and Optional#orElseThrow.
To refactor your example code you could do this.
void method() {
return maybeGetThing().flatMap(val -> {
// eek side effects
val.doA();
val.doB();
val.doC();
return val.maybeAnotherThing();
});
}
flatMap is a way of converting an Optional of one type to an Optional of another type. If the return value weren't Optional you would use map.
You can see we have eliminated the need for names of return values in favour of naming the parameters of lambda functions. The lambda functions are scoped so you can reuse the names if that's what you want to.
I generally like to provide runnable code, so here is a contrived example of what I mean which is runnable.
import java.util.Optional;
class DummyClass {
private int val = 0;
public void doA(){ val += 1; }
public void doB(){ val += 2; }
public void doC(){ val += 3; }
public Optional<String> maybeAnotherThing(){
return Optional.of(Integer.toString(val));
}
}
public class UseOptional5 {
Optional<DummyClass> maybeGetThing(){
return Optional.of(new DummyClass());
}
String method() {
return maybeGetThing()
// you can put other operations here
.flatMap(val -> {
// eek side effects
val.doA();
val.doB();
val.doC();
return val.maybeAnotherThing();
})
// you can put other operations here too
.orElseThrow(() -> new IllegalArgumentException("fail!!"));
}
public static void main(String args[]) {
UseOptional5 x = new UseOptional5();
System.out.println(x.method());
}
}

Since Java 9 I’d do
void method() {
maybeGetThing().ifPresentOrElse(
usefulVariableName -> {
usefulVariableName.doA();
usefulVariableName.doB();
usefulVariableName.doC();
// No duplicate local variable opt
Optional<ThingB> opt = usefulVariableName.maybeAnotherThing();
},
this::doSomethingOnlyHere
);
}
My rule of thumb is you seldom need or want to use isPresent and/or get, they are low-level. For basic things ifPresent (with f) and ifPresetnOrElse are fine. Others are correct that map and flatMap are very useful too.

Business logic validation patterns & advices

I have two layers of validation in my application. First is entity validation performed by bean validation API (e.g. required fields).
The second level is business logic validation. For example, user has a post. User can delete a post only if he is a creator of this post and post rating < 50. So I have to do something like this:
if (post.getCreator().equals(session.getUser())) {
if (post.getRating() < 50) {
postRepository.delete(post);
} else errors.add(400, "Cant delete post with rating 50 or higher")
} else errors add (400, "You should be owner of the post")
I don't like this way as this conditionals are reused and I have to duplicate code. Moreover, if number of conditionals is greater than 5 or so it becomes unreal to read and understand the code.
Moreover, standard Spring Validator won't be very helpful as I have to maker different validation for one entity on different actions (delete and update for example)
So I'm looking for a way to do this in a smarter way (pattern maybe) and I would be very grateful if someone could give me a hint.
Thank in advance!

You can use the strategy pattern.
Each condition can be modelled as a function that takes a post and a session context and might return an error:
Post -> Session -> Optional<String>
You could represent this with an interface:
#FunctionalInterface
public interface ValidationCondition {
Optional<String> validate(final Post post, final Session session);
}
So for example:
public class CreatorValidation implements ValidationCondition {
public Optional<String> validate(final Post post, final Session session) {
if (post.getCreator().equals(session.getUser()) {
return Optional.empty();
}
return Optional.of("You should be the owner of the post");
}
}
You can then store every validation in a list:
final List<ValidationCondition> conditions = new ArrayList<>();
conditions.add(new CreatorValidation());
conditions.add(new ScoreValidation());
// etc.
Using the list, validations can be applied in bulk:
final List<String> errors = new ArrayList<>();
for (final ValidationCondition condition : conditions) {
final Optional<String> error = condition.validate(post, session);
if (error.isPresent()) {
errors.add(error.get());
}
}
Using Java 8 lambdas, you could declare these inline:
final ValidationCondition condition = (post, session) -> {
// Custom logic
});

Strategy pattern is the solution in my opinion.
I will give you a very simple example. Lets say we have two kinds of credit cards, Visa and Mastercard. The logic to perform payment operation is the same for both cards, but card number validation is different. So, by passing VisaStrategy object through a workflow does the same logic and operations as we would pass MastercardStrategy, except one thing - card number validation, which is done inside each defined Strategy class, so you do not have any "if else" stuff in your code at all. Each Strategy class is now responsible for one and only one type of card validation.
If you look for flexible and easy to maintain code structure - use Strategy design pattern.

Why does my RxJava Observable emit only to the first consumer?

Can someone explain why the below test fails?
public class ObservableTest {
#Test
public void badObservableUsedTwiceDoesNotEmitToSecondConsumer() {
// Any simpler observable makes the test pass
Observable<Integer> badObservable = Observable.just(1)
.zipWith(Observable.just(2), (one, two) -> Observable.just(3))
.flatMap(observable -> observable);
ObservableCalculator calc1 = new ObservableCalculator(badObservable);
ObservableCalculator calc2 = new ObservableCalculator(badObservable);
// zipping causes the failure
// Calling calculate().toBlocking().subscribe() on each calc passes
// Observable.from(listOfCalcs).flatMap(calc -> calc.calculate()) passes
Observable.zip(ImmutableList.of(calc1.calculate(), calc2.calculate()), results -> results)
.toBlocking()
.subscribe();
assertThat(calc1.hasCalculated).isTrue();
assertThat(calc2.hasCalculated).isTrue(); // this fails
}
private static class ObservableCalculator {
private final Observable<?> observable;
public boolean hasCalculated = false;
public ObservableCalculator(Observable<?> observable) {
this.observable = observable;
}
public Observable<Void> calculate() {
return observable.concatMap(o -> {
hasCalculated = true;
// returning Observable.just(null) makes the test pass
return Observable.empty();
});
}
}
}
I've tried to simplify the "bad" observable further, but can't find anything I can remove to make it simpler.
My current understanding, though, is that it's an Observable which (regardless of how it's constructed), should emit a single value and then complete. We then make two similar instances of an object based on that Observable, and call a method on those objects which consumes the Observable, makes a note of having done so, and then returns Observable.empty().
Can anyone explain why using this observable causes the test the fail (when using a simpler observable causes the test to pass)?
It's also possible to make the test pass by either serially calling calculate().toBlocking().subscribe() rather than using zip, or making calculate return Observable.just(null) instead. That makes some sense to me (zip won't subscribe to calc2 if calc1 is empty, since it in that case zip could never yield anything), but not complete sense (I don't understand why zip doesn't behave like that for a simpler version of badObservable - the calculate() methods still return empty, regardless of that input).

If you zip an empty source with something, the operator detects it can't produce any value anymore and unsubscribes from all of its sources. There is a mix of zip and merge involved and merge takes unsubscription seriously: it doesn't emit the value 3 at all thus concatMap doesn't call the mapping function for the second source either.

How should I implement Guava cache when I plan to cache multiple values efficiently?

I have a Java class that has a Guava LoadingCache<String, Integer> and in that cache, I'm planning to store two things: the average time active employees have worked for the day and their efficiency. I am caching these values because it would be expensive to compute every time a request comes in. Also, the contents of the cache will be refreshed (refreshAfterWrite) every minute.
I was thinking of using a CacheLoader for this situation, however, its load method only loads one value per key. In my CacheLoader, I was planning to do something like:
private Service service = new Service();
public Integer load(String key) throws Exception {
if (key.equals("employeeAvg"))
return calculateEmployeeAvg(service.getAllEmployees());
if (key.equals("employeeEff"))
return calculateEmployeeEff(service.getAllEmployees());
return -1;
}
For me, I find this very inefficient since in order to load both values, I have to invoke service.getAllEmployees() twice because, correct me if I'm wrong, CacheLoader's should be stateless.
Which made me think to use the LoadingCache.put(key, value) method so I can just create a utility method that invokes service.getAllEmployees() once and calculate the values on the fly. However, if I do use LoadingCache.put(), I won't have the refreshAfterWrite feature since it's dependent on a cache loader.
How do I make this more efficient?

It seems like your problem stems from using strings to represent value types (Effective Java Item 50). Instead, consider defining a proper value type that stores this data, and use a memoizing Supplier to avoid recomputing them.
public static class EmployeeStatistics {
private final int average;
private final int efficiency;
// constructor, getters and setters
}
Supplier<EmployeeStatistics> statistics = Suppliers.memoize(
new Supplier<EmployeeStatistics>() {
#Override
public EmployeeStatistics get() {
List<Employee> employees = new Service().getAllEmployees();
return new EmployeeStatistics(
calculateEmployeeAvg(employees),
calculateEmployeeEff(employees));
}});
You could even move these calculation methods inside EmployeeStatistics and simply pass in all employees to the constructor and let it compute the appropriate data.
If you need to configure your caching behavior more than Suppliers.memoize() or Suppliers.memoizeWithExpiration() can provide, consider this similar pattern, which hides the fact that you're using a Cache inside a Supplier:
Supplier<EmployeeStatistics> statistics = new Supplier<EmployeeStatistics>() {
private final Object key = new Object();
private final LoadingCache<Object, EmployeeStatistics> cache =
CacheBuilder.newBuilder()
// configure your builder
.build(
new CacheLoader<Object, EmployeeStatistics>() {
public EmployeeStatistics load(Object key) {
// same behavior as the Supplier above
}});
#Override
public EmployeeStatistics get() {
return cache.get(key);
}};

However, if I do use LoadingCache.put(), I won't have the refreshAfterWrite feature since it's dependent on a cache loader.
I'm not sure, but you might be able to call it from inside the load method. I mean, compute the requested value as you do and put in the other. However, this feels hacky.
If service.getAllEmployees is expensive, then you could cache it. If both calculateEmployeeAvg and calculateEmployeeEff are cheap, then recompute them when needed. Otherwise, it looks like you could use two caches.
I guess, a method computing both values at once could be a reasonable solution. Create a tiny Pair-like class aggregating them and use it as the cache value. There'll be a single key only.
Concerning your own solution, it could be as trivial as
class EmployeeStatsCache {
private long validUntil;
private List<Employee> employeeList;
private Integer employeeAvg;
private Integer employeeEff;
private boolean isValid() {
return System.currentTimeMillis() <= validUntil;
}
private synchronized List<Employee> getEmployeeList() {
if (!isValid || employeeList==null) {
employeeList = service.getAllEmployees();
validUntil = System.currentTimeMillis() + VALIDITY_MILLIS;
}
return employeeList;
}
public synchronized int getEmployeeAvg() {
if (!isValid || employeeAvg==null) {
employeeAvg = calculateEmployeeAvg(getEmployeeList());
}
return employeeAvg;
}
public synchronized int getEmployeeEff() {
if (!isValid || employeeAvg==null) {
employeeAvg = calculateEmployeeEff(getEmployeeList());
}
return employeeAvg;
}
}
Instead of synchronized methods you may want to synchronize on a private final field. There are other possibilities (e.g. Atomic*), but the basic design is probably simpler than adapting Guava's Cache.
Now, I see that there's Suppliers#memoizeWithExpiration in Guava. That's probably even simpler.