Java 8 Lambdas: Pragmatic Functional Programming by Richard Warburton

By Richard Warburton

If you’re a developer with center Java SE abilities, this hands-on booklet takes you thru the language adjustments in Java eight prompted via the addition of lambda expressions. You’ll examine via code examples, routines, and fluid motives how those nameless capabilities might help you write uncomplicated, fresh, library-level code that solves company problems.
Lambda expressions are a pretty uncomplicated swap to Java, and the 1st a part of the booklet exhibits you ways to exploit them effectively. Later chapters express you the way lambda capabilities assist you increase functionality with parallelism, write less complicated concurrent code, and version your area extra thoroughly, together with development greater DSLs.
Use workouts in each one bankruptcy that can assist you grasp lambda expressions in Java eight quickly
Explore streams, complicated collections, and different Java eight library improvements
Leverage multicore CPUs and increase functionality with info parallelism
Use recommendations to “lambdify” your current codebase or library code
Learn useful ideas for lambda expression unit checking out and debugging
Implement sturdy ideas of object-oriented programming with lambdas
Write concurrent functions that successfully practice message passing and non-blocking I/O

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Extra info for Java 8 Lambdas: Pragmatic Functional Programming

Example text

In the builder pattern, there are a sequence of calls that set up properties or configuration, followed by a single call to a build method. The object being created isn’t created until the call to build occurs. ” By waiting until we know more about what result and operations are needed, we can perform the computations more efficiently. A good example is finding the first number that is > 10. We don’t need to evaluate all the elements to figure this out—only enough to find our first match. It also means that we can string together lots of different operations over our collection and iterate over the collection only once.

It starts by taking a Stream from a List . There is some operation, followed by collecting into a list . Finally, we perform an assert to show you what the results are equal to . You can think of the opening call to stream and the closing call to a collect or other terminal method as bun methods. They aren’t the actual filling of our stream burger, but they do help us see where the operations begin and end. map If you’ve got a function that converts a value of one type into anoth‐ er, map lets you apply this function to a stream of values, producing another stream of the new values.

Example 4-1. debug("Look at this: " + expensiveOperation()); } What we actually want to be able to do is pass in a lambda expression that generates a String to be used as the message. This expression would be called only if the Logger was actually at debug level or above. This approach would allow us to rewrite the pre‐ vious code example to look like the code in Example 4-2. Example 4-2. debug(() -> "Look at this: " + expensiveOperation()); So how do we implement this method from within our Logger class?

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