Metaprogramming in Scala 2 & 3
In this article, you'll learn more about changes in Scala 3's metaprogramming functionality compared to Scala 2.

In this article, you'll learn more about changes in Scala 3's metaprogramming functionality compared to Scala 2.

This article presents cloud-native solutions that successfully passed evaluation and how you can evaluate cloud-native technology yourself.

We take a look at what a Cloud IDE is, its benefits and challenges, and how you can start using a Cloud IDE.

The Industry 4.0 concept comes with challenges and benefits. In this article, you'll find everything you need to know about I4.

VirtusLab's Scala 3 article series is coming. In this article, you'll learn how t prevent compiler regressions with Community Build.

Scala 3 gives you the tools to design the perfect Spark API. We proved it by creating the open-source library Iskra.

Below article describes the front-end architecture we created. FEEA is the right choice for every scale business. The framework didn’t materialize just now, it’s an output of years of experience with enterprise delivery we’ve managed.

This essay dispels several very substantial myths about #Scala that we have seen circulating the blogosphere. For each debunked myth, we present an alternative viewpoint backed up by data from reliable sources.

What if you could take a look at our code from above – and instead of seeing just text files – go through colorful graph nodes that instantly and clearly?

Nvidia DeepStream is portrayed as a solution to reliably host and serve deep learning models for live video feeds, especially at the edge where latency and efficiency matter most. The article frames DeepStream as a production-ready tool that brings computer vision techniques into mainstream IT systems.

Spark 3.2.0’s support for Scala 2.13 technically allows Scala 3 Spark jobs—but it remains “an uphill path,” requiring workarounds for encoders and data shapes. Using libraries like Iskra smooths the path, yet production readiness is still experimental.

VirtusLab created the pandas‑stubs library to enhance pandas with type information, enabling stronger type‑safety in pandas‑dependent projects. It emerged from challenges integrating pandas and pyspark, where missing stubs led to API conflicts and unchecked code.
