I have been trying to get into functional programming with java for a few weeks now. I have created 2 functions below "validateFileFunctionally" and "validateFileRegularly" which perform same validations. First works in a functional way using predicates(we can assume Suppliers, Consumers also in here) while the second one works in traditional java ways.
In 2018 which way should I go.
And should I try to use functional programming everywhere in my code as being done in "validateFileFunctionally" or only with Streams?
public class Main {
private final String INVALID_FILE_NAME_LENGTH = "INVALID FILE NAME LENGTH";
private final String INVALID_FILE_EXTENSION = "INVALID FILE EXTENSION";
private final String INVALID_FILE_SIZE = "INVALID FILE SIZE";
public static void main(String... args) {
File file = new File("text.pdf");
Main main = new Main();
main.validateFileFunctionally(file);
main.validateFileRegularly(file);
}
private void validateFileFunctionally(File file) {
BiPredicate<File, Integer> validateFileName = (f, maxLength) -> f.getName().length() < maxLength;
BiPredicate<File, String> validateExtension = (f, type) -> f.getName().endsWith(type);
BiPredicate<File, Integer> validateSize = (f, maxSize) -> f.length() <= maxSize;
BiConsumer<Boolean, String> throwExceptionIfInvalid = (isValid, errorMessage) -> {
if(!isValid) {
throw new InvalidFileException(errorMessage);
}
};
throwExceptionIfInvalid.accept(validateFileName.test(file, 20), INVALID_FILE_NAME_LENGTH);
throwExceptionIfInvalid.accept(validateExtension.test(file, ".pdf") || validateExtension.test(file, ".csv"), INVALID_FILE_EXTENSION);
throwExceptionIfInvalid.accept(validateSize.test(file, 20), INVALID_FILE_SIZE);
}
private void validateFileRegularly(File file) {
if (file.getName().length() > 20) {
throw new InvalidFileException("INVALID FILE NAME LENGTH");
} else if (!file.getName().endsWith(".pdf") && !file.getName().endsWith(".csv")) {
throw new InvalidFileException("INVALID FILE NAME LENGTH");
} else if (file.length() > 20) {
throw new InvalidFileException("INVALID FILE NAME LENGTH");
}
}
class InvalidFileException extends RuntimeException {
public InvalidFileException(String message) {
super(message);
}
}
}
Dah, this is a pet peeve of mine I'm afraid. Don't try to cram in functional stuff everywhere just because it's the latest new / cool thing - that just makes your code hard to read and unconventional. The Java 8 functional libraries are just another tool you have available that allow you to write cleaner, more concise code in a number of cases. You certainly shouldn't aim to use them exclusively.
Take your case as an example - the chained if statements still might not be the best way of achieving the above, but I can look at that and know near enough exactly what's going on in a few seconds.
Meanwhile, the functional example is just - rather odd. It's longer, less obvious as to what's going on, and offers no real advantage. I can't see a single case for using it as written in this example.
You should be applying Functional Programming wherever it makes sense, and stay away from bold statements like:
"I should try to use FP everywhere in my code"
"I should code only with Streams"
However, keep in mind that this example is not functional at all - validateFileFunctionally is just an enterprise-grade version of validateFileRegularly
Simply put, you took an imperative piece of code and rewrote it by wrapping it into FP infrastructure which is not what FP is about.
FP is about removing runtime uncertainty by building code from small and predictable building blocks/values, and not by putting lambda expressions wherever possible.
In your example, one could achieve this by abandoning exception handling and representing validation result as a value:
private Result validateFileRegularly(File file) {
if (file.getName().length() > 20) {
return Result.failed("INVALID FILE NAME LENGTH");
} else if (!file.getName().endsWith(".pdf") && !file.getName().endsWith(".csv")) {
return Result.failed("INVALID FILE NAME LENGTH");
} else if (file.length() > 20) {
return Result.failed("INVALID FILE NAME LENGTH");
}
return Result.ok();
}
Naturally, one could use the more sophisticated syntax for that, or a more sophisticated applicative-based validation API, but essentially that's what's all about.
Related
Okay so essentially, I have some code that uses the contains() method to detect the presence of specific characters in two strings. For extra context, this question is a good resource as to what kind of problem I'm having (and the third solution is also something I've looked into for this). Regardless, here is some of my code:
// code up here basically just concatenates different
// characters to Strings: stringX and stringY
if (stringX.contains("!\"#")) {
} else if (stringX.contains("$%&")) {
} else if (stringX.contains("\'()")) {
} else if (stringX.contains("!$\'")) {
} else if (stringX.contains("\"%(")) {
// literally 70+ more else-if statements
}
if (stringY.contains("!\"#")) {
} else if (stringY.contains("$%&")) {
} else if (stringY.contains("\'()")) {
} else if (stringY.contains("!$\'")) {
} else if (stringY.contains("\"%(")) {
// literally 70+ more else-if statements, all of which are
// exactly the same as those working with stringX
}
I'm still pretty new to Java programming, so I'm not sure how I should go about this. Maybe it is a non-issue? Also, if I can remedy this without using RegEx, that would be preferable; I am not very knowledgeable in it at this point it time. But if the only rational solution would be to utilize it, I will obviously do so.
Edit: The code within all of these else-if statements will not be very different from each other at all; basically just a System.out.println() with some information about what characters stringX/stringY contains.
Writing the same code more than once should immediately set off alarm bells in your head to move that code into a function so it can be reused.
As for simplifying the expression, the best approach is probably storing the patterns you're looking for as an array and iterating over the array with your condition.
private static final String[] patterns = new String[] {"!\"#", "$%&", "\'()", "!$\'", "\"%(", ...};
private static void findPatterns(String input) {
for (String pattern : patterns) {
if (input.contains(pattern) {
System.out.println("Found pattern: " + pattern);
}
}
}
// Elsewhere...
findPatterns(stringX);
findPatterns(stringY);
This pattern is especially common in functional and functional-style languages. Java 8 streams are a good example, so you could equivalently do
List<String> patterns = Arrays.asList("!\"#", "$%&", "\'()", "!$\'", "\"%(", ...);
patterns.stream()
.filter(pattern -> stringX.contains(pattern))
.forEach(pattern -> System.out.println("Found pattern: " + pattern));
can simply by make a list of your case. then using java 8 stream filter
List<String> pattems = Arrays.asList("!\"#", "$%&", ...);
Optional<String> matched = pattems.stream().filter(p -> stringX.contains(p));
if(matched.isPresent()) {
System.console().printf(matched.get())
}
java stream could make your peformance slower but not too much
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The question is more general and is not related to pros and cons of both styles.
The question is should I prefer whenever it is possible to use Stream instead of for loops because it is declarative with a good readability?
I was arguing with my colleague about pros and cons of using streams and for loop. I agree that we should prefer streams in 90% of time but I believe there are some cases when it is better to use for loop instead of stream.
For example I needed to perform several operations on collection of elements and these operations could throw Checked Exception. During operating if exception occurres for any element I wanted to quit the execution at all so I used for loop for it and wrapped it in try/catch block. My colleague was not satisfied because result took in two times more lines than If I would use stream instead. I rewrote it by creating own custom functional interfaces that throws checked exception and static methods to convert them into throwing unchecked exception(examples here) and finally it looked like this:
try {
Map<String, String> someResult= elements.stream()
.filter(throwingPredicateWrapper(element-> client.hasValue(element)))
.collect(
Collectors.toMap(Function.identity(),
throwingFunctionWrapper(element -> client.getValue(element))));
return someResult;
} catch (Exception e) {
LOGGER.error("Error while processing", e);
}
He was happy because it took lines of code in two time less.
It is simple example and it does not look so bad but old loop here is more simple and faster way to deal with that case I believe.
Should we tend to use Streams everywhere it is possible?
Joshua Bloch, author of "Effective Java", has a good talk which touches on when to use streams. Start watching around 30:30 for his section on "Use streams judiciously".
Although this is largely opinion based, he argues that you do not want to immediately begin turning all of your procedural loops into streams, but you really want a balanced approach. He provides at least one example method where doing so creates code that is more difficult to understand. He also argues that there is no right answer in many cases whether to write it procedural or in a more functional manner, and it is dependent on the context (and I would argue what the team has decided to do corporately might play a role). He has the examples on GitHub, and all the examples below are from his GitHub repository.
Here is the example he provides of his iterative anagram method,
// Prints all large anagram groups in a dictionary iteratively (Page 204)
public class IterativeAnagrams {
public static void main(String[] args) throws IOException {
File dictionary = new File(args[0]);
int minGroupSize = Integer.parseInt(args[1]);
Map<String, Set<String>> groups = new HashMap<>();
try (Scanner s = new Scanner(dictionary)) {
while (s.hasNext()) {
String word = s.next();
groups.computeIfAbsent(alphabetize(word),
(unused) -> new TreeSet<>()).add(word);
}
}
for (Set<String> group : groups.values())
if (group.size() >= minGroupSize)
System.out.println(group.size() + ": " + group);
}
private static String alphabetize(String s) {
char[] a = s.toCharArray();
Arrays.sort(a);
return new String(a);
}
}
And here it is using Streams,
// Overuse of streams - don't do this! (page 205)
public class StreamAnagrams {
public static void main(String[] args) throws IOException {
Path dictionary = Paths.get(args[0]);
int minGroupSize = Integer.parseInt(args[1]);
try (Stream<String> words = Files.lines(dictionary)) {
words.collect(
groupingBy(word -> word.chars().sorted()
.collect(StringBuilder::new,
(sb, c) -> sb.append((char) c),
StringBuilder::append).toString()))
.values().stream()
.filter(group -> group.size() >= minGroupSize)
.map(group -> group.size() + ": " + group)
.forEach(System.out::println);
}
}
}
He argues for a balanced, third approach that uses both,
// Tasteful use of streams enhances clarity and conciseness (Page 205)
public class HybridAnagrams {
public static void main(String[] args) throws IOException {
Path dictionary = Paths.get(args[0]);
int minGroupSize = Integer.parseInt(args[1]);
try (Stream<String> words = Files.lines(dictionary)) {
words.collect(groupingBy(word -> alphabetize(word)))
.values().stream()
.filter(group -> group.size() >= minGroupSize)
.forEach(g -> System.out.println(g.size() + ": " + g));
}
}
private static String alphabetize(String s) {
char[] a = s.toCharArray();
Arrays.sort(a);
return new String(a);
}
}
So our project back-end is a Java 8 Springboot application, springboot allows you to do some stuff really easily. ex, request validation:
class ProjectRequestDto {
#NotNull(message = "{NotNull.DotProjectRequest.id}")
#NotEmpty(message = "{NotEmpty.DotProjectRequest.id}")
private String id;
}
When this constraint is not meet, spring (springboot?) actually throws a validation exception, as such, we catch it somewhere in the application and construct a 404 (Bad Request) response for our application.
Now, given this fact, we kinda followed the same philosophy throughout our application, that is, on a deeper layer of the application we might have something like:
class ProjectService throws NotFoundException {
DbProject getProject(String id) {
DbProject p = ... // some hibernate code
if(p == null) {
Throw new NotFoundException();
}
return p;
}
}
And again we catch this exception on a higher level, and construct another 404 for the client.
Now, this is causing a few problems:
The most important one: Our error tracing stops being useful, we cannot differentiate (easily) when the exception is important, because they happen ALL the time, so if the service suddenly starts throwing errors we would not notice until it is too late.
Big amount of useless logging, on login requests for example, user might mistyped his password, and we log this and as a minor point: our analytics cannot help us determine what we are actually doing wrong, we see a lot of 4xx's but that is what we expect.
Exceptions are costly, gathering the stack trace is a resource intensive task, minor point at this moment, as the service scales up with would become more of a problem.
I think the solution is quite clear, we need to make an architectural change to not make exceptions part of our normal data flow, however this is a big change and we are short on time, so we plan to migrate over time, yet the problem remains for the short term.
Now, to my actual question: when I asked one of our architects, he suggested the use of monads (as a temporal solution ofc), so we don't modify our architecture, but tackle the most contaminating endpoints (ex. wrong login) in the short term, however I'm struggling with the monad paradigm overall and even more in java, I really have no idea on how to apply it to our project, could you help me with this? some code snippets would be really good.
TL:DR: If you take a generic spring boot application that throws errors as a part of its data flow, how can you apply the monad pattern to avoid login unnecessary amount of data and temporarily fix this Error as part of data flow architecture.
The standard monadic approach to exception handling is essentially to wrap your result in a type that is either a successful result or an error. It's similar to the Optional type, though here you have an error value instead of an empty value.
In Java the simplest possible implementation is something like the following:
public interface Try<T> {
<U> Try<U> flatMap(Function<T, Try<U>> f);
class Success<T> implements Try<T> {
public final T value;
public Success(T value) {
this.value = value;
}
#Override
public <U> Try<U> flatMap(Function<T, Try<U>> f) {
return f.apply(value);
}
}
class Fail<T> implements Try<T> {
// Alternatively use Exception or Throwable instead of String.
public final String error;
public Fail(String error) {
this.error = error;
}
#Override
public <U> Try<U> flatMap(Function<T, Try<U>> f) {
return (Try<U>)this;
}
}
}
(with obvious implementations for equals, hashCode, toString)
Where you previously had operations that would either return a result of type T or throw an exception, they would return a result of Try<T> (which would either be a Success<T> or a Fail<T>), and would not throw, e.g.:
class Test {
public static void main(String[] args) {
Try<String> r = ratio(2.0, 3.0).flatMap(Test::asString);
}
static Try<Double> ratio(double a, double b) {
if (b == 0) {
return new Try.Fail<Double>("Divide by zero");
} else {
return new Try.Success<Double>(a / b);
}
}
static Try<String> asString(double d) {
if (Double.isNaN(d)) {
return new Try.Fail<String>("NaN");
} else {
return new Try.Success<String>(Double.toString(d));
}
}
}
I.e. instead of throwing an exception you return a Fail<T> value which wraps the error. You can then compose operations which might fail using the flatMap method. It should be clear that once an error occurs it will short-circuit any subsequent operations - in the above example if ratio returns a Fail then asString doesn't get called and the error propagates directly through to the final result r.
Taking your example, under this approach it would look like this:
class ProjectService throws NotFoundException {
Try<DbProject> getProject(String id) {
DbProject p = ... // some hibernate code
if(p == null) {
return new Try.Fail<DbProject>("Failed to create DbProject");
}
return new Try.Succeed<DbProject>(p);
}
}
The advantage over raw exceptions is it's a bit more composable and allows, for example, for you to map (e.g. Stream.map) a fail-able function over a collection of values and end up with a collection of Fails and Successes. If you were using exceptions then the first exception would fail the entire operation and you would lose all results.
One downside is that you have to use Try return types all the way down your call stack (somewhat like checked exceptions). Another is that since Java doesn't have built-in monad support (al la Haskell & Scala) then the flatMap'ing can get slightly verbose. For example something like:
try {
A a = f(x);
B b = g(a);
C c = h(b);
} catch (...
where f, g, h might throw, becomes instead:
Try<C> c = f(x).flatMap(a -> g(a))
.flatMap(b -> h(b));
You can generalise the above implementation by making the error type an generic parameter E (instead of String), so it then becomes Try<T, E>. whether this is useful depends on your requirements - I've never needed it.
I have a more fully-implemented version here, alternatively the Javaslang and FunctionalJava libraries offer their own variants.
I'm writing a function where I'm essentially doing the same thing over and over. I have the function listed below
public String buildGarmentsString(List<Garment> garments)
{
StringBuilder garmentString = new StringBuilder(10000);
for(int i=0;i<4;i++)
{
garmentString.append(this.garmentProductId(i,garments.get(i).getProductId()));
garmentString.append(this.garmentColor(i,garments.get(i).getColor()));
for(int j=0;j<garments.get(i).getSizes().size();j++)
{
//check xxsml
if(garments.get(i).getSizes().get(j).getXxsml() >0)
{
garmentString.append(this.garmentSizes(i, Size.xxsml(),garments.get(i).getSizes().get(j).getXxsml()));
}
//check xsml
if(garments.get(i).getSizes().get(j).getXsml() > 0)
{
garmentString.append(this.garmentSizes(i,Size.xsml(),garments.get(i).getSizes().get(j).getXsml()));
}
//check sml
if(garments.get(i).getSizes().get(j).getSml() > 0)
{
garmentString.append(this.garmentSizes(i,Size.sml(),garments.get(i).getSizes().get(j).getSml()));
}
//check med
if(garments.get(i).getSizes().get(j).getMed() > 0)
{
garmentString.append(this.garmentSizes(i,Size.med(),garments.get(i).getSizes().get(j).getMed()));
}
//check lrg
if(garments.get(i).getSizes().get(j).getLrg() > 0)
{
garmentString.append(this.garmentSizes(i,Size.lrg(),garments.get(i).getSizes().get(j).getLrg()));
}
//check xlrg
if(garments.get(i).getSizes().get(j).getXlg() > 0)
{
garmentString.append(this.garmentSizes(i,Size.xlg(),garments.get(i).getSizes().get(j).getXlg()));
}
//check xxlrg
if(garments.get(i).getSizes().get(j).getXxl() >0)
{
garmentString.append(this.garmentSizes(i,Size.xxlg(),garments.get(i).getSizes().get(j).getXxl()));
}
//check xxxlrg
if(garments.get(i).getSizes().get(j).getXxxl() >0)
{
garmentString.append(this.garmentSizes(i,Size.xxxlg(),garments.get(i).getSizes().get(j).getXxxl()));
}
}
}
}
This is my garmentSizes function:
public String garmentSizes(int garmentNumber, String size,int numberToSend)
{
String garmentSizes = "&garment["+garmentNumber+"][sizes]["+size+"]="+numberToSend;
return garmentSizes;
}
I'm trying to figure out how I can get this done with a lot less code. I've read that with functional programming you can do things like pass in functions to parameters to other functions. After doing some reading online, I think I want to do something like this but I'm not sure how or what the best approach would be.
I have done some reading here on stack overflow and I've seen people mention using either the Command pattern or FunctionalJava or LambdaJ for trying to approximate this feature in Java. I've read over the documentation for the two libraries and read the Wikipedia Article on the Command Pattern, but I'm still not sure how I would use any of those to solve my particular problem. Can somebody explain this to me? As somebody that has never done any functional programming this is a bit confusing.
You could use local variables to decrease the amount of repetition. Say bySize = garments.get(i).getSizes().get(j) for example.
instead of size.getXxsml(), size.getXsml() etc. you could use an enum for sizes and loop on sizes.
The whole thing would then look like:
for(int j=0;j<garments.get(i).getSizes().size();j++) {
bySize = garments.get(i).getSizes().get(j);
for (Size s : Size.values()) {
if (bySize.get(s) > 0) {
garmentString.append(garmentSizes(i, s, bySize.get(s)));
}
}
}
The bySize.get(s) method could be implemented either with a switch that directs to the right method or directly in the enum and you could get rid of the getXsml etc. methods.
The only thing which differs between all your checks is this:
getXxsml/xxsml, getXsml/xsml, getSml/sml, etc.
If you could pass these values (as strings) to some upper-level method, and if
that upper-level method could eval i.e. execute these strings, then you can just
have an array of these values and pass that array to that upper-level method.
In Java, you can do something similar with reflection.
All these checks could indeed be simplified to much less
code through the use of reflection.
Look at:
java.lang.Class
java.lang.reflect.Method
java.lang.reflect.Field
java.lang.reflect.Constructor
and you will see what I mean.
From your code it appears that some Class has the following methods:
xxsml(), xsml(), sml(), med(), ..., xxxlg()
to get the amounts (?) available for each size.
You can design your data better, like this:
Have a "Size" type, that enumerates all sizes (could be Enum or some class with attribute String key)
Have a method that returns a List of all known sizes.
replace the above methods with amountFor(Size) This could be backed by a Map<Size, Integer>
For backward compatibility, you could rewrite the old methods along the lines:
int xxsml() {
return amountFor(Size.XXSML); // assuming you have a singleton instance
// for each well known size
}
Of course, in getGarmentString, you would then loop through the List of all known sizes:
for (Size sz : Size.getAllKnownSizes()) {
if (garments.get(i).getSizes().get(j).amountFor(sz) > 0) {
... do whatever must be done here
}
}
I'm a bit new to Guava and it's style. I'm definitely digging it, but one thing I keep tripping over is the order of chained methods. Where I seem to have this problem the most is when using compound Orderings. I have to keep asking myself questions like:
Where does the natural go?
Where does the nullFirst (or last) go?
Which nullsFirst does what? (In the example below, one for host, one for last name, one for first name?)
Here's an example of one that I was just working on. It looks cumbersome, and I'm just not sure if I put it all together right. I have some JUnits to test it, and it seems okay, but there are always those quirky boundary cases.
Ordering<Host> lastNameThenFirstNameOrdering = Ordering.natural().nullsFirst().onResultOf(new Function<Host, String>() {
public String apply(Host host) {
return host.getLastName();
}}).compound(Ordering.natural().nullsFirst().onResultOf(new Function<Host, String>() {
public String apply(Host host) {
return host.getFirstName();
}})).nullsFirst();
As for an actual question: Is there a well-defined rule for how these things get executed? It seems to be last-to-first, but I'm having trouble telling that.
edit: Just wanted to point out the large, ugly code I was trying to replace:
Ordering<Host> ordering2 = new Ordering<Host>() {
public int compare(Host host1, Host host2) {
if (host1 == null || host2 == null) {
return host1 == host2 ? 0 : ((host1 == null) ? -1 : 1);
}
if(host1.getLastName() != null || host2.getLastName() != null){
if (host1.getLastName() == null) {
return -1;
} else if (host2.getLastName() == null) {
return 1;
}
if (host1.getLastName().compareTo(host2.getLastName()) != 0) {
return host1.getLastName().compareTo(host2.getLastName());
}
}
if (host1.getFirstName() == null) {
return -1;
} else if (host2.getFirstName() == null) {
return 1;
}
return host1.getFirstName().compareTo(host2.getFirstName());
}};
I think what you do is correct, but awfully ugly. Try this for readability:
Use an Enum
Move the functions to an enum that implements Function<Host, String>. Each of the enum items can provide it's own implementation.
enum HostFunctions implements Function<Host, String>{
GETFIRSTNAME{
#Override
public String apply(final Host host){
return host.getFirstName();
}
},
GETLASTNAME{
#Override
public String apply(final Host host){
return host.getLastName();
}
}
}
Indent your Code
Now reference those enum functions and indent your code properly. This is what it will look like:
final Ordering<Host> orderingByLastAndFirstName =
Ordering
.natural()
.nullsFirst()
.onResultOf(HostFunctions.GETLASTNAME)
.compound(
Ordering
.natural()
.nullsFirst()
.onResultOf(HostFunctions.GETFIRSTNAME))
.nullsFirst();
I'd say that makes everything much more understandable.
IDE Configuration
Regarding proper indentation (at least if you use Eclipse), see this question:
How to indent the fluent interface
pattern “correctly” with eclipse?
Enums as Functions
Regarding the enum: this is called the enum singleton pattern. The Guava guys use it all over their code base. Read about it on wikipedia or in Effective Java, Item 3. Although those sources both talk about single-item enums, the approach is almost the same here.
Each chaining call is "wrapping" the previous ordering into a new one, so you're right, the execution order can be thought of as "backwards".
I wrote and reviewed the Ordering class and I still regularly have to stop and scratch my head over the correct interleaving of nullsFirst(), and onResultOf() and reverse()!
The following would be my preference for doing this, assuming you must be able to handle null hosts, first names and last names. To me, it seems like a non-null first name and last name ought to be a requirement of the Host class. And you should generally try to avoid allowing collections to contain null objects.
Ordering<Host> lastNameFirstNameOrdering = new Ordering<Host>() {
#Override public int compare(Host left, Host right) {
return ComparisonChain.start()
.compare(left.getLastName(), right.getLastName(), Ordering.natural().nullsFirst())
.compare(left.getFirstName(), right.getFirstName(), Ordering.natural().nullsFirst())
.result();
}
}.nullsFirst();
Alternatively, I'd take an approach similar to Sean's but break things down for readability.
Ordering<Host> lastNameOrder = Ordering.natural().nullsFirst()
.onResultOf(Host.LAST_NAME);
Ordering<Host> firstNameOrder = Ordering.natural().nullsFirst()
.onResultOf(Host.FIRST_NAME);
Ordering<Host> orderingByLastAndFirstName =
lastNameOrder.compound(firstNameOrder).nullsFirst();
Keep in mind that you could also make these individual orderings static final fields of the class, allowing you to easily use them anywhere when sorting like Host.LAST_NAME_ORDER.