If you write lots of Kotlin code you might have noticed that it is annoying to write the named parameters when calling functions or when creating a new instance of class.
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Last week, on Thursday 6th and Friday 7th of February, I attended DDD Europe 2020 in Amsterdam. In this post I will give a short overview of the talks and workshops I followed and some of my personal takeaways.
I had a great time on the conference. One of the things I like most is the mixture of talks and workshops. In the 2 hour workshops you are expected to actively participate in whatever is happening. Be it discussions or really doing some coding or testing.
I’d like to thank all the speakers and attendees for their input, talks, workshops and discussions during the breaks.
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SQL allows you to do calculations on columns over multiple rows using aggregate functions like COUNT
, SUM
, AVG
etc. This post explains how to use them in Kotlin Exposed. We will also cover arithmetic operations on one or more columns. If you haven’t used Kotlin Exposed before, you can go here for an introduction.
Consider an application containing two tables in an SQL database: Comment and User. A comment is written by a user, and can receive likes/dislikes. The snippet below shows the table definitions:
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This is a blog post that tries to give a pragmatic explanation about what a monad is, and what problem it tries to solve.
This post is written by Ties van de Ven and Justus Brugman.
When I tried to learn about functional programming, I found myself lost in new words and jargon, I did not know about.
Suddenly my vocabulary needed to be extended with terms like Monads, Monoids, Composable, Functors and so on.
When trying to understand these terms, it became clear that I found it hard to understand what a monad is.
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This post explains how to use table aliases using Kotlin Exposed. Aliases are necessary when you want to join the same table multiple times. If you haven’t used Kotlin Exposed before, you can go here for an introduction: Kotlin Exposed - A lightweight SQL library.
In this example we have an application containing two tables: Message and User. The Message table has two references to the User table, one to model the 'fromUser' relationship and one for the 'toUser' relationship. The table definitions look as follows:
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We can use the flatten
method in Groovy to flatten a collection that contains other collections into a single collection with all elements. We can pass a closure as extra argument to the flatten
method to transform each element that is flattened. The argument of the closure is the element from the original collection.
In the following example we first use the flatten
method without a closure argument. Then we pass a closure argument and transform the element:
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I’ve recently had the situation where I deployed a Spring Boot application on OpenShift where a certain dependency needed a properties file that couldn’t be found.
The problem was that this dependency didn’t scan the classpath for the file, but just opened a FileInputStream relative to the current path.
In this blogpost I will guide you through the process of deploying a text file next to a jar in an OpenShift container.
I’ve reproduced an example scenario, but you can skip these steps and go right to the solution if you want to.
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The December 2019 release of Apache Kafka 2.4.0 saw usability improvements in TopologyTestDriver, with the addition of new TestInputTopic
and TestOutputTopic
classes.
These offer typesafe methods to easily produce and consume messages for your Kafka Streams tests.
In this post we’ll explore these new classes in the context of Avro messages, which requires a small trick to get working.
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In a previous post we learned about callouts in Asciidoctor to add explanation to source code. While surfing the Internet I came upon the following blog post by Alex Soto: Auto-numbered Callouts in Asciidoctor. I turns out that since Asciidoctor 1.5.8 we can use a dot (.
) instead of explicit numbers to have automatic increasing numbering for the callouts.
Let’s take our example from the earlier blog post and now use auto numbered callouts:
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When using Springfox you can annotate your endpoints to automatically generate OpenAPI docs for your clients.
This blogpost will show how you can prevent Springfox generating a model on an endpoint with ResponseEntity
as return type.
I’ll also cover how to prevent generating default responses.
Take an endpoint like below.
You want to return ResponseEntity
because you want control over the status and body which is returned within your endpoint code.
Click to see the Spingfox configuration used for this example
Now your generated OpenAPI doc contains responses with a $ref
to ResponseEntity
.
Springfox will also generate default responses for 201
, 202
, 400
, 401
, 403
, 404
, which you may never need.
Click to see the generated definition for ResponseEntity
(it is quite long)
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Adding Spring Security to an existing application can be quite a daunting prospect.
Merely adding the required dependencies to your project sets off a chain of events which can break your application and tests.
Maybe you’re suddenly shown a login prompt which expects a generated password logged on startup.
Maybe your tests now get the dreaded 401 Unauthorized
, or a subsequently a 403 Forbidden
.
Maybe you get a ClassCastException
when trying to use your Authentication#getPrincipal()
.
Either way, this post is here to help!
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In a previous post I’ve shown how to use ZIO environments to provide your program with dependencies, or modules.
While using environments at the customer I’m currently working for, we found out that the logic to get a database session object using a module would run over and again.
This makes sense, since a ZIO[R, E, A] is a prescribed way of getting an A, and the result is not cached.
Our application was reading configuration files and creating SQL sessions on every module call, while the resulting object was obviously constructed from the same underlying values.
There are multiple ways to solve this:
In this post I’ve chosen the latter, because I wanted to show the use of ZIO’s Ref
. Also, I like how semantically the desired data and the logic of retrieving it belong together.
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