Events in Polymer

When playing around in Polymer, we encounter iron signals. Besides normal javascript events, this gives us a lot of options for dealing with events. Lets try it all out!

We can catch events using the on-event attribute:

This calls method push1:

Scroll down for the complete code listing. Or see it on github.

Another way to catch it is using a listener:

We can also fire our own events:

We can catch that in the parent component using the on-event attribute or a listener.

These events will always bubble up to parent components. Even when the event is caught. But never sideways.

So in this situation the methods push, push-parent and push-grandparent will be called, but not push-sibling.

So it’s good to not use too generic names, because the parent component might also use that event.
You can prevent that by prefixing your event names with your component name.

you can stop an event from bubbling up by using event.stopPropagation():

You can also use iron-signals to throw events sideways.

Throw them:

and catch them:

You can also catch them in multiple places.

I recommend against using iron-signals, because it can be hard to find out where the even comes from or will be caught. Use the rule of least power and stay with normal javascript events.

Complete code.

This uses subComponent1:

and subComponent2:

Handling YAML format in your REST with Spring Boot

In general a REST service serves JSON document formats. In Spring Boot it is even the standard without having to configure anything.
Over HTTP we have the ability to send a Content-Type as header to instruct the server to return a certain document format (Mime type).
Besides handling JSON, XML is another common document format. But what if we want to serve or read a YAML document format?

This tutorial provides the required steps to be able to handle objects in YAML format. To be able to send a YAML Content-Type with the header, and to be able to serialize and deserialize with the existing ObjectMappers of Jackson. This tutorial will use Spring Boot, Jackson and a YAML dataformat extension library for Jackson.

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Gradle Goodness: Adding Task With Rule Based Model Configuration

Gradle has an incubating feature Rule based model configuration. This is a new way to configure Gradle projects where Gradle has more control of the configuration and the dependencies between configuration objects. This allows Gradle to resolve configuration values before they are used, because Gradle knows there is a dependency. With this new model we don’t need any lazy evaluation “tricks” we had to use. For example there was an internal convention mapping mechanism for tasks to assign values to a task configuration after the task was already created. Also the project.afterEvalute is a mechanism to have late binding for task properties. With the new rule based model Gradle can do without these options, we can rely on Gradle resolving all dependent configuration values when we create a task.

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Awesome Asciidoctor: Using Ruby Extensions With Asciidoctor Gradle Plugin

Asciidoctor is a Ruby tool, but luckily we can use AsciidoctorJ to use Asciidoctor in Java code. The Asciidoctor Gradle plugin relies on AsciidoctorJ to run. AsciidoctorJ allows us to write custom extensions in Java (or Groovy), but we can still use Asciidoctor extensions written in Ruby with the Gradle plugin.

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Gradle Goodness: Custom Plugin Repositories With Plugins DSL

To apply a plugin in our Gradle build script we can use the plugins DSL. The plugins DSL is very concise and allows Gradle to be more efficient and more in control when loading the plugin. Normally the plugin we define is fetched from the Gradle plugin portal. If we have our own repository, for example on the intranet of our company, we have to define that extra repository with a pluginRepositories configuration block in the settings.gradle file of our project.

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AI movie critic – part 1 – Reading the training data

This is the first of a series of posts. Where we will use machine learning to rate movies. For this task we’re not going to watch all the movies. I assume it’s good enough to just read the plot. We’ll use Markov chains to rate the movies and as an added bonus we can also generate new movie plots for awesome (or terrible) movies.

In this first part we’ll get the data and change it into a more usable format.
We can use the data from IMDB, which is published on Of interest are the plots and the ratings.

Plots look like this:

and from ratings.list:

We’ll combine these and output one file with just a title, one plot and a rating in stars (1 to 5).

Now it looks like this:

next time: Markov chains

You can find all the code on github.

Ratpacked: Creating Pairs From Promises

The Pair class in Ratpack is an easy way to create a growing data structure, passed on via Promise methods. A Pair object has a left and right part containing data. These parts can even be other Pair objects. Since Ratpack 1.4.0 the Promise class has methods to set the right or left part of a Pair: left, flatLeft, right and flatRight. The result of these methods is a Promise<Pair> object. The input can be Promise type or a Function that can use a previous Promise.

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Groovy Goodness: Identity Closure

In functional programming we have the concept of an identity function. An identity function returns the same result as the input of the function. Groovy has a lot of functional paradigms including a identity function. Of course in Groovy’s case it is an identity closure. It is defined as a constant in the Closure class: Closure.IDENTITY. If we use this closure we get the same result as the argument we provide.

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