Programación funcional para desarrolladores de Java, Parte 1

Java 8 introdujo a los desarrolladores de Java a la programación funcional con expresiones lambda. Esta versión de Java notificó eficazmente a los desarrolladores que ya no es suficiente pensar en la programación de Java solo desde la perspectiva imperativa y orientada a objetos. Un desarrollador de Java también debe poder pensar y codificar utilizando el paradigma funcional declarativo.

Este tutorial presenta los conceptos básicos de la programación funcional. Comenzaré con la terminología, luego profundizaremos en los conceptos de programación funcional. Concluiré presentándote cinco técnicas de programación funcional. Los ejemplos de código en estas secciones lo ayudarán a comenzar con funciones puras, funciones de orden superior, evaluación diferida, cierres y currización.

La programación funcional va en aumento

El Instituto de Ingenieros Eléctricos y Electrónicos (IEEE) incluyó lenguajes de programación funcional en sus 25 principales lenguajes de programación para 2018, y Google Trends actualmente clasifica la programación funcional como más popular que la programación orientada a objetos.

Claramente, la programación funcional no se puede ignorar, pero ¿por qué se está volviendo más popular? Entre otras cosas, la programación funcional facilita la verificación de la corrección del programa. También simplifica la creación de programas concurrentes. La concurrencia (o procesamiento paralelo) es vital para mejorar el rendimiento de la aplicación.

descargar Obtener el código Descargar el código fuente, por ejemplo, las aplicaciones de este tutorial. Creado por Jeff Friesen para JavaWorld.

¿Qué es la programación funcional?

Las computadoras generalmente implementan la arquitectura de Von Neumann, que es una arquitectura de computadora ampliamente utilizada basada en una descripción de 1945 del matemático y físico John von Neumann (y otros). Esta arquitectura está sesgada hacia la programación imperativa , que es un paradigma de programación que utiliza declaraciones para cambiar el estado de un programa. C, C ++ y Java son lenguajes de programación imperativos.

En 1977, el distinguido científico informático John Backus (notable por su trabajo en FORTRAN), dio una conferencia titulada "¿Puede la programación liberarse del estilo von Neumann?" Backus afirmó que la arquitectura de Von Neumann y sus lenguajes imperativos asociados son fundamentalmente defectuosos, y presentó un lenguaje de programación de nivel funcional (FP) como solución.

Aclarando Backus

Debido a que la conferencia de Backus se presentó hace varias décadas, algunas de sus ideas pueden ser difíciles de comprender. El blogger Tomasz Jaskuła agrega claridad y notas a pie de página en su publicación de blog de enero de 2018.

Conceptos y terminología de programación funcional

La programación funcional es un estilo de programación en el que los cálculos se codifican como funciones de programación funcional . Estas son construcciones similares a funciones matemáticas (por ejemplo, funciones lambda) que se evalúan en contextos de expresión.

Los lenguajes de programación funcional son declarativos , lo que significa que la lógica de un cálculo se expresa sin describir su flujo de control. En la programación declarativa, no hay declaraciones. En cambio, los programadores usan expresiones para decirle a la computadora lo que debe hacerse, pero no cómo realizar la tarea. Si está familiarizado con SQL o expresiones regulares, entonces tiene cierta experiencia con el estilo declarativo; ambos usan expresiones para describir lo que se debe hacer, en lugar de usar declaraciones para describir cómo hacerlo.

Un cálculo en programación funcional se describe mediante funciones que se evalúan en contextos de expresión. Estas funciones no son las mismas que las funciones utilizadas en la programación imperativa, como un método Java que devuelve un valor. En cambio, una función de programación funcional es como una función matemática, que produce una salida que normalmente depende solo de sus argumentos. Cada vez que se llama a una función de programación funcional con los mismos argumentos, se obtiene el mismo resultado. Se dice que las funciones en la programación funcional exhiben transparencia referencial . Esto significa que puede reemplazar una llamada a función con su valor resultante sin cambiar el significado del cálculo.

La programación funcional favorece la inmutabilidad , lo que significa que el estado no puede cambiar. Este no suele ser el caso en la programación imperativa, donde una función imperativa puede estar asociada con el estado (como una variable de instancia de Java). Llamar a esta función en diferentes momentos con los mismos argumentos puede resultar en diferentes valores de retorno porque en este caso el estado es mutable , lo que significa que cambia.

Efectos secundarios en la programación imperativa y funcional

Los cambios de estado son un efecto secundario de la programación imperativa, impidiendo la transparencia referencial. Hay muchos otros efectos secundarios que vale la pena conocer, especialmente al evaluar si usar el estilo imperativo o funcional en sus programas.

Un efecto secundario común en la programación imperativa es cuando una declaración de asignación muta una variable al cambiar su valor almacenado. Las funciones de la programación funcional no admiten asignaciones de variables. Debido a que el valor inicial de una variable nunca cambia, la programación funcional elimina este efecto secundario.

Otro efecto secundario común ocurre cuando se modifica el comportamiento de una función imperativa en función de una excepción lanzada, que es una interacción observable con la persona que llama. Para obtener más información, consulte la discusión de Stack Overflow, "¿Por qué la creación de una excepción es un efecto secundario?"

Un tercer efecto secundario común ocurre cuando una operación de E / S ingresa texto que no se puede dejar de leer, o genera texto que no se puede escribir. Consulte la discusión de Stack Exchange "¿Cómo puede IO causar efectos secundarios en la programación funcional?" para obtener más información sobre este efecto secundario.

La eliminación de los efectos secundarios hace que sea mucho más fácil comprender y predecir el comportamiento computacional. También ayuda a que el código sea más adecuado para el procesamiento en paralelo, lo que a menudo mejora el rendimiento de la aplicación. Si bien hay efectos secundarios en la programación funcional, generalmente son menores que en la programación imperativa. El uso de la programación funcional puede ayudarlo a escribir código que sea más fácil de entender, mantener y probar, y también más reutilizable.

Orígenes (y creadores) de la programación funcional

La programación funcional se originó en el cálculo lambda, que fue introducido por Alonzo Church. Otro origen es la lógica combinatoria, que fue introducida por Moses Schönfinkel y posteriormente desarrollada por Haskell Curry.

Programación orientada a objetos versus programación funcional

He creado una aplicación Java que contrasta los enfoques de programación funcional imperativos, orientados a objetos y declarativos para escribir código. Estudie el código a continuación y luego señalaré las diferencias entre los dos ejemplos.

Listado 1. Employees.java

import java.util.ArrayList; import java.util.List; public class Employees { static class Employee { private String name; private int age; Employee(String name, int age) { this.name = name; this.age = age; } int getAge() { return age; } @Override public String toString() { return name + ": " + age; } } public static void main(String[] args) { List employees = new ArrayList(); employees.add(new Employee("John Doe", 63)); employees.add(new Employee("Sally Smith", 29)); employees.add(new Employee("Bob Jone", 36)); employees.add(new Employee("Margaret Foster", 53)); printEmployee1(employees, 50); System.out.println(); printEmployee2(employees, 50); } public static void printEmployee1(List employees, int age) { for (Employee emp: employees) if (emp.getAge() < age) System.out.println(emp); } public static void printEmployee2(List employees, int age) { employees.stream() .filter(emp -> emp.age  System.out.println(emp)); } }

El Listado 1 revela una Employeesaplicación que crea algunos Employeeobjetos y luego imprime una lista de todos los empleados menores de 50 años. Este código demuestra estilos de programación funcional y orientados a objetos.

El printEmployee1()método revela el enfoque imperativo, orientado a declaraciones. Como se especifica, este método itera sobre una lista de empleados, compara la edad de cada empleado con el valor de un argumento y (si la edad es menor que el argumento), imprime los detalles del empleado.

El printEmployee2()método revela el enfoque declarativo y orientado a expresiones, en este caso implementado con la API Streams. En lugar de especificar imperativamente cómo imprimir a los empleados (paso a paso), la expresión especifica el resultado deseado y deja los detalles de cómo hacerlo a Java. Piense en filter()como el equivalente funcional de una ifdeclaración y forEach()como funcionalmente equivalente a la fordeclaración.

Puede compilar el Listado 1 de la siguiente manera:

javac Employees.java

Utilice el siguiente comando para ejecutar la aplicación resultante:

java Employees

The output should look something like this:

Sally Smith: 29 Bob Jone: 36 Sally Smith: 29 Bob Jone: 36

Functional programming examples

In the next sections, we'll explore five core techniques used in functional programming: pure functions, higher-order functions, lazy evaluation, closures, and currying. Examples in this section are coded in JavaScript because its simplicity, relative to Java, will allow us to focus on the techniques. In Part 2 we'll revisit these same techniques using Java code.

Listing 2 presents the source code to RunScript, a Java application that uses Java's Scripting API to facilitate running JavaScript code. RunScript will be the base program for all of the forthcoming examples.

Listing 2. RunScript.java

import java.io.FileReader; import java.io.IOException; import javax.script.ScriptEngine; import javax.script.ScriptEngineManager; import javax.script.ScriptException; import static java.lang.System.*; public class RunScript { public static void main(String[] args) { if (args.length != 1) { err.println("usage: java RunScript script"); return; } ScriptEngineManager manager = new ScriptEngineManager(); ScriptEngine engine = manager.getEngineByName("nashorn"); try { engine.eval(new FileReader(args[0])); } catch (ScriptException se) { err.println(se.getMessage()); } catch (IOException ioe) { err.println(ioe.getMessage()); } } }

The main() method in this example first verifies that a single command-line argument (the name of a script file) has been specified. Otherwise, it displays usage information and terminates the application.

Assuming the presence of this argument, main() instantiates the javax.script.ScriptEngineManager class. ScriptEngineManager is the entry-point into Java's Scripting API.

Next, the ScriptEngineManager object's ScriptEngine getEngineByName(String shortName) method is called to obtain a script engine corresponding to the desired shortName value. Java 10 supports the Nashorn script engine, which is obtained by passing "nashorn" to getEngineByName(). The returned object's class implements the javax.script.ScriptEngine interface.

ScriptEngine declares several eval() methods for evaluating a script. main() invokes the Object eval(Reader reader) method to read the script from its java.io.FileReader object argument and (assuming that java.io.IOException isn't thrown) then evaluate the script. This method returns any script return value, which I ignore. Also, this method throws javax.script.ScriptException when an error occurs in the script.

Compile Listing 2 as follows:

javac RunScript.java

I'll show you how to run this application after I have presented the first script.

Functional programming with pure functions

A pure function is a functional programming function that depends only on its input arguments and no external state. An impure function is a functional programming function that violates either of these requirements. Because pure functions have no interaction with the outside world (apart from calling other pure functions), a pure function always returns the same result for the same arguments. Pure functions also have no observable side effects.

Can a pure function perform I/O?

If I/O is a side effect, can a pure function perform I/O? The answer is yes. Haskell uses monads to address this problem. See "Pure Functions and I/O" for more about pure functions and I/O.

Pure functions versus impure functions

The JavaScript in Listing 3 contrasts an impure calculatebonus() function with a pure calculatebonus2() function.

Listing 3. Comparing pure vs impure functions (script1.js)

// impure bonus calculation var limit = 100; function calculatebonus(numSales) { return(numSales > limit) ? 0.10 * numSales : 0 } print(calculatebonus(174)) // pure bonus calculation function calculatebonus2(numSales) { return (numSales > 100) ? 0.10 * numSales : 0 } print(calculatebonus2(174))

calculatebonus() is impure because it accesses the external limit variable. In contrast, calculatebonus2() is pure because it obeys both requirements for purity. Run script1.js as follows:

java RunScript script1.js

Here's the output you should observe:

17.400000000000002 17.400000000000002

Suppose calculatebonus2() was refactored to return calculatebonus(numSales). Would calculatebonus2() still be pure? The answer is no: when a pure function invokes an impure function, the "pure function" becomes impure.

When no data dependency exists between pure functions, they can be evaluated in any order without affecting the outcome, making them suitable for parallel execution. This is one of functional programming's benefits.

More about impure functions

Not all functional programming functions need to be pure. As Functional Programming: Pure Functions explains, it is possible (and sometimes desirable) to "separate the pure, functional, value based core of your application from an outer, imperative shell."

Functional programming with higher-order functions

A higher-order function is a mathematical function that receives functions as arguments, returns a function to its caller, or both. One example is calculus's differential operator, d/dx, which returns the derivative of function f.

First-class functions are first-class citizens

Closely related to the mathematical higher-order function concept is the first-class function, which is a functional programming function that takes other functional programming functions as arguments and/or returns a functional programming function. First-class functions are first-class citizens because they can appear wherever other first-class program entities (e.g., numbers) can, including being assigned to a variable or being passed as an argument to or returned from a function.

The JavaScript in Listing 4 demonstrates passing anonymous comparison functions to a first-class sorting function.

Listing 4. Passing anonymous comparison functions (script2.js)

function sort(a, cmp) { for (var pass = 0; pass 
    
      pass; i--) if (cmp(a[i], a[pass]) < 0) { var temp = a[i] a[i] = a[pass] a[pass] = temp } } var a = [22, 91, 3, 45, 64, 67, -1] sort(a, function(i, j) { return i - j; }) a.forEach(function(entry) { print(entry) }) print('\n') sort(a, function(i, j) { return j - i; }) a.forEach(function(entry) { print(entry) }) print('\n') a = ["X", "E", "Q", "A", "P"] sort(a, function(i, j) { return i 
     
       j; }) a.forEach(function(entry) { print(entry) }) print('\n') sort(a, function(i, j) { return i > j ? -1 : i < j; }) a.forEach(function(entry) { print(entry) })
     
    

In this example, the initial sort() call receives an array as its first argument, followed by an anonymous comparison function. When called, the anonymous comparison function executes return i - j; to achieve an ascending sort. By reversing i and j, the second comparison function achieves a descending sort. The third and fourth sort() calls receive anonymous comparison functions that are slightly different in order to properly compare string values.

Run the script2.js example as follows:

java RunScript script2.js

Here's the expected output:

-1 3 22 45 64 67 91 91 67 64 45 22 3 -1 A E P Q X X Q P E A

Filter and map

Functional programming languages typically provide several useful higher-order functions. Two common examples are filter and map.

  • A filter processes a list in some order to produce a new list containing exactly those elements of the original list for which a given predicate (think Boolean expression) returns true.
  • A map applies a given function to each element of a list, returning a list of results in the same order.

JavaScript supports filtering and mapping functionality via the filter() and map() higher-order functions. Listing 5 demonstrates these functions for filtering out odd numbers and mapping numbers to their cubes.

Listing 5. Filtering and mapping (script3.js)

print([1, 2, 3, 4, 5, 6].filter(function(num) { return num % 2 == 0 })) print('\n') print([3, 13, 22].map(function(num) { return num * 3 }))

Run the script3.js example as follows:

java RunScript script3.js

You should observe the following output:

2,4,6 9,39,66

Reduce

Another common higher-order function is reduce, which is more commonly known as a fold. This function reduces a list to a single value.

Listing 6 uses JavaScript's reduce() higher-order function to reduce an array of numbers to a single number, which is then divided by the array's length to obtain an average.

Listing 6. Reducing an array of numbers to a single number (script4.js)

var numbers = [22, 30, 43] print(numbers.reduce(function(acc, curval) { return acc + curval }) / numbers.length)

Run Listing 6's script (in script4.js) as follows:

java RunScript script4.js

You should observe the following output:

31.666666666666668

You might think that the filter, map, and reduce higher-order functions obviate the need for if-else and various looping statements, and you would be right. Their internal implementations take care of decisions and iteration.

A higher-order function uses recursion to achieve iteration. A recursive function invokes itself, allowing an operation to repeat until it reaches a base case. You can also leverage recursion to achieve iteration in your functional code.

Functional programming with lazy evaluation

Another important functional programming feature is lazy evaluation (also known as nonstrict evaluation), which is the deferral of expression evaluation for as long as possible. Lazy evaluation offers several benefits, including these two:

  • Expensive (timewise) calculations can be deferred until they're absolutely necessary.
  • Unbounded collections are possible. They'll keep delivering elements for as long as they're requested to do so.

Lazy evaluation is integral to Haskell. It won't calculate anything (including a function's arguments before the function is called) unless it's strictly necessary to do so.

Java's Streams API capitalizes on lazy evaluation. A stream's intermediate operations (e.g., filter()) are always lazy; they don't do anything until a terminal operation (e.g., forEach()) is executed.

Although lazy evaluation is an important part of functional languages, even many imperative languages provide builtin support for some forms of laziness. For example, most programming languages support short-circuit evaluation in the context of the Boolean AND and OR operators. These operators are lazy, refusing to evaluate their right-hand operands when the left-hand operand is false (AND) or true (OR).

Listing 7 is an example of lazy evaluation in a JavaScript script.

Listing 7. Lazy evaluation in JavaScript (script5.js)

var a = false && expensiveFunction("1") var b = true && expensiveFunction("2") var c = false || expensiveFunction("3") var d = true || expensiveFunction("4") function expensiveFunction(id) { print("expensiveFunction() called with " + id) }

Run the code in script5.js as follows:

java RunScript script5.js

You should observe the following output:

expensiveFunction() called with 2 expensiveFunction() called with 3

Lazy evaluation is often combined with memoization, an optimization technique used primarily to speed up computer programs by storing the results of expensive function calls and returning the cached result when the same inputs reoccur.

Because lazy evaluation doesn't work with side effects (such as code that produces exceptions and I/O), imperative languages mainly use eager evaluation (also known as strict evaluation), where an expression is evaluated as soon as it's bound to a variable.

More about lazy evaluation and memoization

A Google search will reveal many useful discussions of lazy evaluation with or without memoization. One example is "Optimizing your JavaScript with functional programming."

Functional programming with closures

First-class functions are associated with the concept of a closure, which is a persistent scope that holds onto local variables even after the code execution has left the block in which the local variables were defined.

Crafting closures

Operationally, a closure is a record that stores a function and its environment. The environment maps each of the function's free variables (variables used locally, but defined in an enclosing scope) with the value or reference to which the variable's name was bound when the closure was created. It lets the function access those captured variables through the closure's copies of their values or references, even when the function is invoked outside their scope.

To help clarify this concept, Listing 8 presents a JavaScript script that introduces a simple closure. The script is based on the example presented here.

Listing 8. A simple closure (script6.js)

function add(x) { function partialAdd(y) { return y + x } return partialAdd } var add10 = add(10) var add20 = add(20) print(add10(5)) print(add20(5))

Listing 8 defines a first-class function named add() with a parameter x and a nested function partialAdd(). The nested function partialAdd() has access to x because x is in add()'s lexical scope. Function add() returns a closure that contains a reference to partialAdd() and a copy of the environment around add(), in which x has the value assigned to it in a specific invocation of add().

Because add() returns a value of function type, variables add10 and add20 also have function type. The add10(5) invocation returns 15 because the invocation assigns 5 to parameter y in the call to partialAdd(), using the saved environment for partialAdd() where x is 10. The add20(5) invocation returns 25 because, although it also assigns 5 to y in the call to partialAdd(), it's now using another saved environment for partialAdd() where x is 20. Thus, while add10() and add20() use the same function partialAdd(), the associated environments differ and invoking the closures will bind x to two different values in the two invocations, evaluating the function to two different results.

Run Listing 8's script (in script6.js) as follows:

java RunScript script6.js

You should observe the following output:

15 25

Functional programming with currying

Currying is a way to translate the evaluation of a multi-argument function into the evaluation of an equivalent sequence of single-argument functions. For example, a function takes two arguments: x and y. Currying transforms the function into taking only x and returning a function that takes only y. Currying is related to but is not the same as partial application, which is the process of fixing a number of arguments to a function, producing another function of smaller arity.

Listing 9 presents a JavaScript script that demonstrates currying.

Listing 9. Currying in JavaScript (script7.js)

function multiply(x, y) { return x * y } function curried_multiply(x) { return function(y) { return x * y } } print(multiply(6, 7)) print(curried_multiply(6)(7)) var mul_by_4 = curried_multiply(4) print(mul_by_4(2))

The script presents a noncurried two-argument multiply() function, followed by a first-class curried_multiply() function that receives multiplicand argument x and returns a closure containing a reference to an anonymous function (that receives multiplier argument y) and a copy of the environment around curried_multiply(), in which x has the value assigned to it in an invocation of curried_multiply().

The rest of the script first invokes multiply() with two arguments and prints the result. It then invokes curried_multiply() in two ways:

  • curried_multiply(6)(7) results in curried_multiply(6) executing first. The returned closure executes the anonymous function with the closure's saved x value 6 being multiplied by 7.
  • var mul_by_4 = curried_multiply(4) executes curried_multiply(4) and assigns the closure to mul_by_4. mul_by_4(2) executes the anonymous function with the closure's 4 value and the passed argument 2.

Run Listing 9's script (in script7.js) as follows:

java RunScript script7.js

You should observe the following output:

42 42 8

Why use currying?

In his blog post "Why curry helps," Hugh Jackson observes that "little pieces can be configured and reused with ease, without clutter." Quora's "What are the advantages of currying in functional programming?" describes currying as "a cheap form of dependency injection," that eases the process of mapping/filtering/folding (and higher order functions generally). This Q&A also notes that currying "helps us create abstract functions."

In conclusion

In this tutorial you've learned some basics of functional programming. We've used examples in JavaScript to study five core functional programming techniques, which we'll further explore using Java code in Part 2. In addition to touring Java 8's functional programming capabilities, the second half of this tutorial will help you begin to think functionally, by converting an example of object-oriented Java code to its functional equivalent.

Learn more about functional programming

I found the book Introduction to Functional Programming (Richard Bird and Philip Wadler, Prentice Hall International Series in Computing Science, 1992) helpful in learning the basics of functional programming.

This story, "Functional programming for Java developers, Part 1" was originally published by JavaWorld .