Frameless is an open source Scala library for using more expressive types with Spark. This talk will discuss the benefits to using Frameless, why some businesses might be hesitant to utilize it and how it can add business value.

In the last few years, one of the leading new areas of development in JetBrains has been AI assistance. It started with simple access to an external large language model within IntelliJ IDEA—but we didn’t stop there. Today, JetBrains offers a wide range of new features and plugins that can make software developers work more quickly and productively. During this talk, we will go through the most important of them – AI Assistant, local and cloud completion, connecting to local LLMs, and more. We will discuss how these tools can boost your productivity and improve your coding experience. We will also delve into… sorry, I mean, we will talk about JetBrains Junie, AI agents in general, and the future of AI tooling. The talk will consist of animated infographics and live coding examples.

Feedback on a first book writing: how did it happen? Why did I accept? Which depression steps have I experienced? I'll talk about relationships with the editorial team, delays, steps to finalize a book from day one, with the first lines until the delivery. I won't stop here, I'll mention marketing, advertising, printing, official release and why I will never do this again.

Practicing functional programming inside a Fortune 100 enterprise can feel like flying the Starship Enterprise through asteroid fields of legacy code and bureaucracy. This talk shares hard-earned lessons from the Information Engineering team at JPMorganChase, which runs a production Scala codebase powering a novel metadata platform. We'll explore the political, cultural, and technical friction of pushing functional programming in a Java and Python dominated environment. We'll introduce the domain we work in, the techniques that have worked (and those that haven't), the compromises we've made, and why - despite it all - we still think it's worth it. If you've never tried to run cats-effect in a place where Spring Boot is king, add this talk to your battle log.

Errors are part of life - But how best to work with them in our code? In this talk, I'll take you on a tour of various typed error handling approaches within the Scala ecosystem, as well introduce a new one for cats/cats-effect ecosystem!

Functional streams are a vital tool in any ecosystem. They can simplify the code for webservers, event loops, and data-intensive applications. But they are notoriously difficult to understand. In this talk, we'll explore a mental model of stream execution in fs2, a functional stream processing library in Scala. We'll use our model to draw simple diagrams for complex streaming scenarios, and see how these diagrams can be generated automatically using the aquascape library. Finally, we'll bring our model to the masses. We'll use Scala.js to create interactive, browser-based diagrams that can be integrated into fs2's online documentation. By the end, we'll have a solid understanding of functional streams. With aquascape, you'll see that streams are not only easy to read, but easy to reason with too.

Kannupriya Kalra and Rory Graves discuss GenAI in Scala with LLM4S, walking through live demos—from basic LLM calls and RAG search to image processing and AI-driven code writing. The talk covers building powerful GenAI-powered Scala applications and tools, with practical guidance on architectures, integration, and scalability.

We’ll navigate the rich waters of streaming using fs2, exploring how streams underpin a wide range of Scala applications—from event-based systems to time-based concurrency challenges. We’ll learn what streams are for, when to use them, and how to put a streaming framework to work in your codebase.

Due to popular demand, Anton is back with more Scala Native! He'll be taking us on a journey of working with C libraries, marrying C code with SN interop, and maybe writing some assembly.

⭐ Anton Sviridov ⭐ Scala enthusiast, open source contributor, and blog author. Worked in Data Science, distributed systems, and programming language tooling. Recently I have been diving deeper into systems programming languages and the lessons we can learn from them to be applicable to Scala Native.

Capture checking is an experimental Scala feature and one of the building blocks of the very trendy direct style programming. It’s also, not to put too fine a point on it, a little confusing. In this live coding session, we will explore the aspects that most Scala users will be exposed to, as understood by a regular developer after poring over the very academic documentation and experimenting with nightly builds.

💻 Hands On Session with Creative Scala 💻 Bring your laptops for this event because we'll be getting hands on! In this session, we'll be programming with Creative Scala - a fun way to explore and practise functional programming with Scala. Whether you are completely new to Scala or experienced with functional programming, all levels of experience are welcome! Perhaps you're looking for some help getting set up as a beginner. Perhaps you want to practise your programming skills with peers. Perhaps you want to take a break from your day job and flex your curiosity in a fun environment! Sit back, relax, explore, and learn by doing... ✨

Learning a new programming language can feel overwhelming—so can learning to play a musical instrument. Around the same time I picked up Scala at work, I picked up a pair of drumsticks at home. I didn’t expect these experiences to have anything in common, but I was wrong. In both, I struggled to unlearn old habits, to think in new patterns, and to find rhythm—literal and metaphorical. This talk is a reflection on that dual learning curve. Along the way, I’ll walk through how functional programming in Scala shares some surprising traits with drumming: recursion and rhythm, muscle memory and syntax, constraints as creative tools. I’ll also talk about the differences—where programming relies on precision, music often embraces feel—and how navigating both worlds helped me become more intentional in how I learn anything new. This is not a talk about mastering Scala or music theory. It’s a talk about being a beginner, being frustrated, making progress, and discovering unexpected joy in the process. I hope to share relatable stories, visual and mental metaphors for programming concepts, and reflections that apply whether you’re learning Scala, drums, or just trying to get better at getting better.

Auteur de logiciel chez JPMorgan. Intrigué par le \"capture checking\", incontournable du style direct en Scala 3, il a décidé de creuser le sujet à fond. Il proposera une session de live coding où il expliquera ce qu’il a compris, entre pédagogie, exploration et auto-dérision. Parfait pour celles et ceux qui veulent comprendre ce qui se passe vraiment sous le capot.

Démonstration du monad le plus simple, le plus à jour, et le plus dans le Futur pour représenter tous les effets en Scala. Avec Kyo, on explore les effets dits algébriques, les handlers modulaires et la composition juste assez typée. Pour celles et ceux qui veulent écrire des programmes \"corrects\", ou qui se demandent pourquoi en 2025, on parle encore de burritos, il y a des réponses.

Join this session for a concise tour of Apache Spark™ 4.0’s most notable enhancements: SQL features: ANSI by default, scripting, SQL pipe syntax, SQL UDF, session variable, view schema evolution, etc. Data type: VARIANT type, string collation Python features: Python data source, plotting API, etc. Streaming improvements: State store data source, state store checkpoint v2, arbitrary state v2, etc. Spark Connect improvements: More API coverage, thin client, unified Scala interface, etc. Infrastructure: Better error message, structured logging, new Java/Scala version support, etc. Whether you’re a seasoned Spark user or new to the ecosystem, this talk will prepare you to leverage Spark 4.0’s latest innovations for modern data and AI pipelines.

Building a custom Spark data source connector once required Java or Scala expertise, making it complex and limiting. This left many proprietary data sources without public SDKs disconnected from Spark. Additionally, data sources with Python SDKs couldn't harness Spark’s distributed power. Spark 4.0 changes this with a new Python API for data source connectors, allowing developers to build fully functional connectors without Java or Scala. This unlocks new possibilities, from integrating proprietary systems to leveraging untapped data sources. Supporting both batch and streaming, this API makes data ingestion more flexible than ever. In this talk, we’ll demonstrate how to build a Spark connector for Excel using Python, showcasing schema inference, data reads/writes and streaming support. Whether you're a data engineer or Spark enthusiast, you’ll gain the knowledge to integrate Spark with any data source — entirely in Python.

In this episode, Conor interviews Andor, Stephen and an attendee from Lambda World 2024. Link to Episode 204 on WebsiteDiscuss this episode, leave a comment, or ask a question (on GitHub)Twitter ADSP: The PodcastConor HoekstraGuests Interviewed Andor PénzesStephen TaylorShow Notes Date Recorded: 2024-10-04 Date Released: 2024-10-18 Lambda WorldADSP Episode 133: 🇵🇱 Lambda Days Live 🇵🇱 José Valim, Alexis King & More!Lambda World 2024 - The Butcherbird Combinator - Chris FordLambda World 2024 - Scala Sampler for Functional Soundscapes - Johanna OderskyUnite 2024 Barcelone (Unity Conference)Examples of easy dependently typed programming (in Idris) by Andor Penzes | Lambda Days 2023Dependently-Typed Python by Andor Penzes | Lambda Days 2024DepPy (Dependently Typed Python)CORECURSIVE #065 From Competitive Programming to APL With Conor HoekstraY CombinatorCategory Theory for Programmers - Bartosz MilewskiDevWorld ConferenceQCon ConferenceScala Days ConferenceLambda World 2024 - Stephen Taylor TalkAbove Average in APLDon't Be Mean in APLAPL Wiki MerchCan Programming Be Liberated from the von Neumann Style? John Backus Turing Award PaperLambda World 2024 - The Power of Function Composition - Conor HoekstraLambda World 2024 - Kamila Szewczyk TalkIntro Song Info Miss You by Sarah Jansen https://soundcloud.com/sarahjansenmusic Creative Commons — Attribution 3.0 Unported — CC BY 3.0 Free Download / Stream: http://bit.ly/l-miss-you Music promoted by Audio Library https://youtu.be/iYYxnasvfx8

Jupyter Notebooks are widely used by data scientists and engineers to prototype and experiment with data. However these engineers are often required to work with other data or platform engineers to productionize these experiments due to the complexity in navigating infrastructure and systems. In this talk, we will deep dive into this PR https://github.com/apache/airflow/pull/34840 and share how airflow can be leveraged as a platform to execute notebook pipelines (python, scala or spark) in dynamic environments like Kubernetes for various heterogeneous use cases. We will demonstrate how data scientists can use a Jupyter extension to easily build and manage such pipelines which are executed using Airflow streamlining data science workflow development and supercharging productivity

Sujet du BoF: Loom a introduit les premières fonctionnalités et les threads virtuels dans Java 19 et 21 (LTS). Discussion sur la perception du projet Loom côté Scala, les changements opérationnels et l'intégration dans les projets. Après une courte présentation rappelant le contexte et l'historique des travaux dans Scala autour de Loom, échange sur les approches, les usages et les perspectives futures. BoF destiné à tous les niveaux d'expérience et à ceux qui s'intéressent à l'impact de Loom sur l'écosystème JVM.