In The Joy of Clojure (TJoC) destructuring is described as a mini-language within Clojure. It's not essential to learn this mini-language; however, as the authors of TJoC point out, destructuring facilitates concise, elegant code. Making Code More Understandable One of the scariest things for those who are just now learning how to do some coding is the fact that they have to try to figure out what a seemingly impossible set of rules and structures means for the work that they are trying to do. It is not easy at all, and many people struggle with it in big ways. Fortunately, there are some people who are going about the process of destructuring code so that it may be broken into smaller and more manageable chunks. If this is to happen, then one can easily see how they can potentially get a lot more value from the process of coding, and even how they can contribute to it for themselves in the future. We need to be as encouraging of the next generation of coders as we possibly can because there is no question that they will ultimately have an outsized impact on how the future of coding is decided. If they are best set up to understand coding and to make sense of its many intricacies, then they will be able to handle it without problems. However, we need to support and encourage them along the way, and that all begins by making coding easier to understand in general. What is destructuring? Clojure supports abstract structural binding, often called destructuring, in let binding lists, fn parameter lists, and any macro that expands into a let or fn. -- http://clojure.org/special_forms The simplest example of destructuring is assigning the values of a vector. user=> (def point [5 7]) #'user/point user=> (let [[x y] point] (println "x:" x "y:" y)) x: 5 y: 7 note: I'm using let for my examples of destructuring; however, in practice, I tend to use destructuring in function parameter lists at least as often, if not more often. I'll admit that I can't remember ever using destructuring like the first example, but it's a good starting point. A more realistic example is splitting a vector into a head and a tail. When defining a function with an arglist** you use an ampersand. The same is true in destructuring. user=> (def indexes [1 2 3]) #'user/indexes user=> (let [[x & more] indexes] (println "x:" x "more:" more)) x: 1 more: (2 3) It's also worth noting that you can bind the entire vector to a local using the :as directive. user=> (def indexes [1 2 3]) #'user/indexes user=> (let [[x & more :as full-list] indexes] (println "x:" x "more:" more "full list:" full-list)) x: 1 more: (2 3) full list: [1 2 3] Vector examples are the easiest; however, in practice I find myself using destructuring with maps far more often. Simple destructuring on a map is as easy as choosing a local name and providing the key. user=> (def point {:x 5 :y 7}) #'user/point user=> (let [{the-x :x the-y :y} point] (println "x:" the-x "y:" the-y)) x: 5 y: 7 As the example shows, the values of :x and :y are bound to locals with the names the-x and the-y. In practice we would never prepend "the-" to our local names; however, using different names provides a bit of clarity for our first example. In production code you would be much more likely to want locals with the same name as the key. This works perfectly well, as the next example shows. user=> (def point {:x 5 :y 7}) #'user/point user=> (let [{x :x y :y} point] (println "x:" x "y:" y)) x: 5 y: 7 While this works perfectly well, creating locals with the same name as the keys become tedious and annoying (especially when your keys are longer than one letter). Clojure anticipates this frustration and provides :keys directive that allows you to specify keys that you would like as locals with the same name. user=> (def point {:x 5 :y 7}) #'user/point user=> (let [{:keys [x y]} point] (println "x:" x "y:" y)) x: 5 y: 7 There are a few directives that work while destructuring maps. The above example shows the use of :keys. In practice I end up using :keys the most; however, I've also used the :as directive while working with maps. The following example illustrates the use of an :as directive to bind a local with the entire map. user=> (def point {:x 5 :y 7}) #'user/point user=> (let [{:keys [x y] :as the-point} point] (println "x:" x "y:" y "point:" the-point)) x: 5 y: 7 point: {:x 5, :y 7} We've now seen the :as directive used for both vectors and maps. In both cases, the locale is always assigned to the entire expression that is being destructured. For completeness I'll document the :or directive; however, I must admit that I've never used it in practice. The :or directive is used to assign default values when the map being destructured doesn't contain a specified key. user=> (def point {:y 7}) #'user/point user=> (let [{:keys [x y] :or {x 0 y 0} point] (println "x:" x "y:" y)) x: 0 y: 7 Lastly, it's also worth noting that you can destructure nested maps, vectors and a combination of both. The following example destructures a nested map user=> (def book {:name "SICP" :details {:pages 657 :isbn-10 "0262011530"}) #'user/book user=> (let [{name :name {pages :pages isbn-10 :isbn-10} :details} book] (println "name:" name "pages:" pages "isbn-10:" isbn-10)) name: SICP pages: 657 isbn-10: 0262011530 As you would expect, you can also use directives while destructuring nested maps. user=> (def book {:name "SICP" :details {:pages 657 :isbn-10 "0262011530"}) #'user/book user=> user=> (let [{name :name {:keys [pages isbn-10]} :details} book] (println "name:" name "pages:" pages "isbn-10:" isbn-10)) name: SICP pages: 657 isbn-10: 0262011530 Destructuring nested vectors is also very straight-forward, as the following example illustrates user=> (def numbers [[1 2][3 4]]) #'user/numbers user=> (let [[[a b][c d]] numbers] (println "a:" a "b:" b "c:" c "d:" d)) a: 1 b: 2 c: 3 d: 4 Since binding forms can be nested within one another arbitrarily, you can pull apart just about anything -- http://clojure.org/special_forms The following example destructures a map and a vector at the same time. user=> (def golfer {:name "Jim" :scores [3 5 4 5]}) #'user/golfer user=> (let [{name :name [hole1 hole2] :scores} golfer] (println "name:" name "hole1:" hole1 "hole2:" hole2)) name: Jim hole1: 3 hole2: 5 The same example can be rewritten using a function definition to show the simplicity of using destructuring in parameter lists. user=> (defn print-status [{name :name [hole1 hole2] :scores}] (println "name:" name "hole1:" hole1 "hole2:" hole2)) #'user/print-status user=> (print-status {:name "Jim" :scores [3 5 4 5]}) name: Jim hole1: 3 hole2: 5 There are other (less used) directives and deeper explanations available on http://clojure.org/special_forms and in The Joy of Clojure. I recommend both. **(defn do-something [x y & more] ... )

In Jonathan Giles's post An FX Experience Retrospective, he starts by looking at the history of JavaFX and focuses on "what has happened in the world of JavaFX" in 2011. I was highly skeptical of JavaFX prior to JavaOne 2010 (see here and here for examples), but started to think more positively about it after the JavaOne 2010 and JavaOne 2011 announcements related to JavaFX. One thing that has been a little tricky about learning JavaFX since JavaOne 2011's big announcements have been knowing for certain whether a particular resource on JavaFX applies to JavaFX 1.x or JavaFX 2.x. Reading the An FX Experience Retrospective post provided a different perspective on the risks and challenges Oracle and the JavaFX team has faced in making this major overhaul. A JavaFX Reboot is Going to be a Challenge It is absolutely the case that a JavaFx Reboot will be an extreme challenge in that most people haven’t given the idea of rebooting this system much thought at all. They assume that the JavaFx system will work just as well for them today as it has in the past, but they may be making a big mistake in making such a sweeping judgment. There are many who feel that JavaFx is in need of an update/upgrade, but it is not clear how that is going to be possible. So many of the elements of JavaFX were built with a specific purpose in mind, and it is far from easy to change course on that idea at this stage of the game. Thus, it seems likely that JavaFx will largely continue to exist as it has for all of these years and not receive the upgrade that it needs at this time. However, there are at least some people who are working around the edges to see what they can do about putting the JavaFx train back on the tracks that were designed for it. Giles writes in his post, "Another vivid recollection I have from JavaOne 2010 is the various reactions that people had of this news. It varied from those in shock at losing their favorite language, to those who said it was long overdue and was the right way to proceed with JavaFX." I was in the latter group, welcoming this change and I would have liked to see it happen even sooner. The ability to use JavaFX with standard Java language and APIs was a huge benefit in my opinion and finally gave credence to the pro-JavaFX argument to Java developers that "JavaFX is Java." The JavaOne 2011 announcements of making JavaFX open source and making it part of standard Java SE were likely less controversial for Java developers (who wouldn't want these characteristics?) and are also important to me in my renewed interest in JavaFX. For developers just learning JavaFX, it can be a bit tricky to know if an online resource is for JavaFX 1.x or 2.x without delving into the article. The changes in JavaFX from 1.x to 2.x are significant enough that I generally don't want to risk confusion by reading JavaFX 1.x resources (though some have found value in reading JavaFX 1.x resources in preparation for using JavaFX 2.0). However, there are some clues that can help make it quicker and easier to identify which version of JavaFX is applicable. It is most obvious that an article is about JavaFX 2.0 when it explicitly states so. I try to do this with my blog posts on JavaFX 2.0, though I'm sure I occasionally forget to do so. When an article or blog post does not state the version of JavaFX specifically, another good clue is the date of the resource. In general, it is usually safe to assume that anything written about JavaFX before late 2010 is about JavaFX 1.x and it is similarly safe to assume that most things written about JavaFX in 2011 or later are about JavaFX 2.x. Another clue to watch for is discussion in a resource that includes JavaFX Script or FXML references. The former (JavaFX Script) was exclusive to JavaFX 1.x and the latter (FXML) is exclusive to JavaFX 2.x. Some really good documentation on JavaFX 2.x has been made available recently. The JavaFX 2.0 documentation states the following about JavaFX 2.0 versus JavaFX 1.3: JavaFX 2.0 is the latest major update release for JavaFX. Many of the new features introduced in JavaFX 2.0 are incompatible with JavaFX 1.3. If you are developing a new application in JavaFX, it is recommended that you start with JavaFX 2.0. The JavaFX 2.0 documentation contains many newly written or updated articles and posts on JavaFX 2.0. This set of documentation includes What is JavaFX?, Getting Started with JavaFX, Working with the JavaFX Scene Graph, Introduction to FXML, Getting Started with FXML, and Using JavaFX Charts. Books on JavaFX provide another perspective on the challenges associated with the major shift in JavaFX's vision. Most JavaFX books that are currently available were written for JavaFX 1.x. berry120 (who has also blogged on JavaFX 2) recently asked, Any decent books on JavaFX 2? As far as I can tell, the only JavaFX 2.x book currently available is Carl Dea's JavaFX 2.0: Introduction by Example (I hope to write a review of this short, recipe-oriented book in the near future). This book has a publication date (2011) and JavaFX 2.0 in its title, making it clear that it's on JavaFX 2.0. With books, which typically have a longer time between writing and publishing, even early 2011 publication dates might still mean a book on JavaFX 1.x. Another good clue with books is the price of used books on the Amazon Marketplace. Books on old and/or deprecated language versions tend to be very cheap. Other books on JavaFX 2.0 are likely to come. Pro JavaFXTM 2 Platform A Definitive Guide to Script, Desktop and Mobile RIA with JavaTM Technology has an advertised publication date of 12 February 2012. Carefully wading through online resources and selecting books to purchase is tricky for developers because of the major shift in JavaFX's long-term vision. Giles's post provides some insight into the even greater effort required within Oracle and the JavaFX team to make this major shift. As painful as the shift is, I believe this shift in vision coming at the cost of short-term pain provides JavaFX a fighting chance for a prosperous long-term future.

This article presents an introduction to the Querydsl series with the goal to highlight the difference from JPA Criteria.

This article compares two authentication service providers: Auth0 and Amazon Cognito. Both of them are cloud-based identity management services.

For today’s adventure, we want to build a Java microservice that connects to, and interacts with, graph data in a Neo4j AuraDB Free database.

How to set up a service that hosts the Spring Cloud Config server and to wire an existing microservice as the config client service.

In this Selenium tutorial, you will learn how to use Expected Conditions in Selenium to fix timing-related issues due to the dynamic loading of WebElements.

This article will show you the major features of the plugin (and some of the minor ones) and how they can be useful when working with Mockito test code.

Learn more about class loading in Java and its performance impact.

In this article, explore details on code, especially inside the Jakarta EE world, mainly to answer the questions: should we have a constructor on JPA, and why?

Learn how to take advantage of this API and combine it to create a better, maintainable code design for your Java projects.

The main differences between JSP and servlet, as well as describe the definitions of servlet and JSP, along with their advantages.

The two languages compete with one another as each provides excellent opportunities for developers — all you need to know about Java and Python.

This article explains the notion of happens-before in Java, including ways to install it, what guarantee it gives, advantages it brings, and how to use it.

For those occasions when one storage account just won't do

JavaScript is one of the most important languages today. Let's take a look at how JavaScript has evolved in its short history and where it is headed next.

Bogged down with Java errors? This series presents the 50 most common compiler errors and runtime exceptions that Java devs face, and how to conquer them.

Java is changing the world around us in major ways. Here is how.

Automated deployment doesn't have to be difficult. Learn how to use the Mule management console and Maven to achieve automated deployment.

If you wonder what a JMF player is, you are in the right spot. We've noticed that many aspiring developers want to try it out but are unsure how it works. Hence, we decided to put together this guide to make things a tad easier for you. package org.jmf.example; import javax.swing.JDialog; import javax.swing.JFrame; import javax.swing.UIManager; import javax.swing.UnsupportedLookAndFeelException; import javax.swing.plaf.metal.MetalLookAndFeel; public class ExampleJMF { public static void main(String[] args) { JFrame.setDefaultLookAndFeelDecorated(true); JDialog.setDefaultLookAndFeelDecorated(true); try { UIManager.setLookAndFeel(new MetalLookAndFeel()); } catch(UnsupportedLookAndFeelException e) { e.printStackTrace(); } new exampleFrame(); } } But before we dive into it, let's answer this crucial question: What is Java? Java is a high-level language that programmers use to develop projects with few implementation dependencies. Java has transformed the web in many ways. A vast majority of online tools that we use today were built on Java. That includes websites mobile apps and multimedia playback platforms. This programming language has come a long way. This year it will be 27 years since James Gosling developed it. What is a Java Media Framework JMF is an API that enables you to play, process, and capture media audio and video. Whether you want to transmit or receive live media broadcasts and conduct videoconferences, you can easily do it thanks to this API. All thanks to RTP ”Real-time Transport Protocol of the JMF. A JMF is a straightforward player that encapsulates your multimedia component and allows you to control your player. It also offers methods that enable you to acquire necessary resources and query the current state. These are tools you will use to build page objects. For instance, if you want to scan the page and create a class. Here is what Java Media Framework can do: A multifunctional tool A JMF comes in handy, especially if you're looking for a tool that can scan a page and build a class. You can also use it to create prototype code and later build a robust application. Instrumentalization A lot of what you read about the topic of Observability mentions the benefits and potential of analyzing data, but little about how you collect it. This process is called “instrumentation” and broadly involves collecting events in infrastructure and code that include metrics, logs, and traces. There are of course dozens of methods, frameworks, and tools to help you collect the events that are important to you, and this post begins a series looking at some of those. This post focuses on introductory concepts, setting up the dependencies needed, and generating some basic metrics. Later posts will take these concepts further. An Introduction to Metrics Data Different vendors and open source projects created their own ways to represent the event data they collect. While this remains true, there are increased efforts to create portable standards that everyone can use and add their features on top of but retain interoperability. The key project is OpenTelemetry from the Cloud Native Computing Foundation (CNCF). This blog series will use the OpenTelemetry specification and SDKs, but collect and export a variety of the formats it handles. The Application Example The example for this post is an ExpressJS application that serves API endpoints and exports Prometheus-compatible metrics. The tutorial starts by adding basic instrumentation and sending metrics to a Prometheus backend, then adds more, and adds the Chronosphere collector. You can find the full and final code on GitHub. Install and Setup ExpressJS ExpressJS provides a lot of boilerplate for creating a JavaScript application that serves HTTP endpoints, so it is a great starting point. Add it to a new project by following the install steps. Capture media streams Not only does the JMF allows you to play music, but you can use it to capture media content as well. And all this will happen while you process and capture it from a source to a destination. You'll then identify each media stream by its content format. From there, the JMF will present the content of that specific video stream. Each media stream will have at least one or more tracks that you can play. Identify each media stream by location You can either identify your media stream by using uniform resource locators (URLs) or media locators. It doesn't matter how you locate them. What matters most is that you wouldn't struggle to identify each media stream. Process Time Bases and Clocks You can also play time-based media, or capture them at an accurate time. To achieve this, JMF requires time-bases and clocks. So, without a thorough understanding of time bases and clocks, you won't be able to work with JMF. While at it, use the below 1. Eliminate Unused Tables Usually, when you remove or deactivate a plugin, all the database tables remain. This can be a good thing, as you retain all the user information, preferences, and other data. However, in most cases, you’re left with a cumbersome dataset that may bring your server’s performance down. If you’re using WordPress, you can get rid of leftover tables by installing a plugin called Plugins Garbage Collector. It scans your database for any unused tables, and you can delete the ones that you know aren’t needed. A more hands-on approach is finding inactive tables using the UPDATE_TIME string. 2. Create an Execution Plan The execution plan’s main goal is to display the various methods of retrieving data by containing the operation's type and order when creating a query. If you’re not familiar with execution plans, here’s a video going through the basics. The typical execution plan includes the following: Types of operations Order of operations Indexes to use Row count estimates from stats Row count actual from results 3. Use Proper Indexing Indexing allows for faster access to the database and speeds up the queries. If you don’t use indexes at all, then processing the queries becomes painfully slow. Yet, over-indexing your database is also ineffective. Unfortunately, there isn’t a golden rule for optimizing your database the right way. However, with some trial and error, your database benefits from an index system. 4. Avoid Coding Loops A SQL query that runs more than once is inefficient and can cause unnecessary performance issues, which pile up quickly, especially with large datasets. In essence, moving a query outside a loop with the goal of it executing only once is the way to go. There are a couple of nifty solutions to achieve this. Use JOIN and GROUP BY to select data from multiple tables and have the database perform the counting with a single query. This is especially effective for multiple queries, including COUNT and MAX clauses. 5. Get Rid of Correlated Subqueries Correlated subqueries are essentially coding loops. The subquery runs row-by-row until it satisfies the parent statement. This method of processing is useful when the outcome relies on multi-part answer validation. You can avoid the correlated subqueries by using JOIN clauses, which makes the query run more efficiently. Essentially, this method replaces WHERE and removes the necessity to execute the subquery for each row separa 6. Avoid * Queries The ultimate goal of every query is to retrieve relevant data for maximum efficiency. However, it’s relatively common to use SELECT * clauses when creating a query resulting in unnecessary data. While it doesn’t play a massive role in the performance of small datasets, it can leave a significant dent in larger ones. Selecting the data sparingly helps with optimizing the query speed and reduces resource usage. A quick way to turn this issue around is using the LIMIT clause instead of SELECT *. This way, you limit the output of the query results unless you do need the entire dataset retrieved by the query.