Scalar 2020
who it's for
Scala developers, functional programmers, backend engineers, distributed systems engineers, data engineers, library authors, frontend developers
topics
type class based CSV decoding; custom test frameworks and quarantining; monad transformer patterns (OptionT); async/await generation for arbitrary monads; Kafka microservices with Greyhound and ZIO; deep learning with DeepLearning4J and Akka Streams; stack-safe functional interpreters and trampolines; Scala.js integration into TypeScript/Node stacks; JMH and JIT assembly performance analysis; split-brain resolver for Akka Cluster (Lithium); fiber supervision and scopes in ZIO; tapir + http4s + doobie + OpenAPI
| title | author | length |
|---|---|---|
| TYPE CLASSES FROM THE GROUND UP | Nicolas Rinaudo | 33m |
Builds a CSV parser then a decoding library that turns rows of strings into business types by defining CellDecoder and RowDecoder type classes and registering… | ||
| PROBING THE UNPROVABLE AND PROVING THE IMPROBABLE | Jon Pretty | 48m |
Two new Scala libraries appear: Probably is a tiny orthogonal test library that treats tests as ordinary expressions or statement assertions, runs them inline… | ||
| HOW I UNDERSTOOD MONAD TRANSFORMERS | Jacek Kunicki | 45m |
Mixing Future[Option[A]] in for-comprehensions becomes concrete: code shows a custom wrapper that maps and flatMaps the inner Option rather than the outer… | ||
| CAN WE FREE CONCURRENT PROGRAMMING FROM THE MONADIC STYLE | Ruslan Shevchenko | 44m |
Claim: explicit monadic plumbing disappears by using continuation/CPS transform and Dotty tasty reflection to generate await/async code that composes with… | ||
| 10 LESSONS LEARNED FROM USING KAFKA IN 1000 SCALA MICROSERVICES | Natan Silnitsky | 52m |
Wix runs ~1,400 Scala microservices on Kafka ingesting ~1 billion messages/day and built an internal library called Greyhound to standardize… | ||
| FROM ZERO TO DEEP LEARNING WITH SCALA | Fabio Tiriticco | 53m |
Raspberry Pi camera collects ~14,000 labeled images cropped to 171x25 pixels; model built in Scala with DeepLearning4J and pipeline implemented with Akka… | ||
| 10 TIPS TO WRITE FAST STACK-SAFE FUNCTIONAL CODE IN SCALA | Christophe Calvès | 47m |
10 concrete tips for fast, stack-safe Scala: production-built Auto-Batch automatically batches per-leg API calls to remove redundant requests and restore… | ||
| A FUNCTIONAL SCALA STACK FOR 2020 | Adam Warski | 50m |
Builds a tiny backend that records likes for programming languages with a simple schema (languages, likes) and a working HTTP endpoint bound on port 8080. Uses… | ||
| FROM SCALA TO ASSEMBLY THE COST OF ABSTACTION REVISITED | Jarek Ratajski | 53m |
Claims that high-level Scala constructs are always slow get tested with real numbers: code examples compile to bytecode and assembly and are profiled with JMH… | ||
| LITHIUM: AN OSS SPLIT-BRAIN RESOLVER FOR AKKA-CLUSTER | Dennis van der Bij | 44m |
Lithium is an open source split‑brain resolver for Akka‑Cluster that implements four strategies (keep‑majority, configurable quorum, keep‑oldest, keep‑ref) and… | ||
| FIBER SUPERVISION IN ZIO | Wiem Zine El Abidine, Adam Fraser | 49m |
ZIO provides lightweight tens of thousands of fibers running on a small thread pool and concrete operations: fork, join, interrupt, ensuring, bracket… | ||
| INTEGRATING SCALA.JS INTO AN EXISTING FULL STACK APP | Devon Miller | 45m |
A runnable demo integrates Scala.js into a Node/Express + Apollo GraphQL + TypeScript SPA that lists books and authors, with roughly half the client UI… | ||
| A TRACE TO REMEMBER: COMPOSITIONAL TRACING | Ayush Mittal | 54m |
Shows concrete tracing code for Scala: uses OpenTelemetry Java SDK with a tracer provider, Zipkin/Jaeger exporters and span processors to emit spans with… | ||
| TYPE-SAFE ERROR HANDLING IN THE AGE OF DOTTY | Kim Covaci, Jordan Coll | 25m |
Claim: using Dotty union types on the left side of Either lets methods declare exact, unrelated error sets (e.g. NoPotatoes | BurntFries) and preserves… | ||
| SPARK-CYPHER: HOW WE WILL BE DOING GRAPH ANALYTICS FROM 2020 ONWARDS | Kamil Owczarek | 45m |
Spark 3 promises up to 17× faster execution (Alibaba’s GTPc benchmarks) and built‑in features like adaptive execution and GPU support, but the planned unified… | ||
| nothing matches | ||