Oftentimes, we are faced with a situation where we need to split a string at some specific character or substring, to derive some useful information from it.
For example, we might want to split a phone number on the country code or data imported from a CSV file.
In
With Spring, we map requests to request handlers via the @RequestMapping annotation. Spring Boot introduced us to derived types of this annotation - @GetMapping, @PostMapping, @DeleteMapping, etc.
These requests contain different types of information and data - and depending on what our endpoint does with the request, we may
In Java, working with files and directories is rather common. We are also often interested in the contents of those files and directories.
Depending on the contents of the file, we might want to behave differently. We might be writing some data into a file and we first want
Redis is an in-memory data store, which can be used as a NoSQL database, cache, or as a typical message broker. It's written in ANSI C, which compiles into significantly efficient machine code and its ability to store data as key-value pairs makes in-memory caching an attractive use-case for
In this article, we'll convert a JSON array into a Java Array and Java List using Jackson.
Since we're using Jackson, you'll have to add it to your project. If you're using Maven, it's as easy as adding the dependency:
<dependency>
<groupId>com.fasterxml.jackson.In this tutorial, we'll be converting a Java Array into a Java Stream for primitive types, as well as objects. This can be done either via Arrays.stream(), as well as Stream.of().
A good way to turn an array into a stream is to use the
In this tutorial, we'll be converting a Java Stream into a Java Array for primitive types, as well as objects.
The toArray() method is a built-in method from the Stream class which is really convenient to use when converting from a Stream to an array. It works
This tutorial will go through some common techniques for removing elements from Java arrays. Manipulating array elements is an extremely common task as discussions about it can be found on many forums, particularly on StackOverflow.
Here's a list of the techniques and methods we'll go over in this article:
Understand your data better with visualizations! With over 275+ pages, you'll learn the ins and outs of visualizing data in Python with popular libraries like Matplotlib, Seaborn, Bokeh, and more.
