Springer Nature
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Keynote: Pushing Types and Gazing at the Stars
Featuring Rob Norris
The hardest thing about functional programming is learning how to think like a functional programmer. Simple questions can lead to very general answers, but it's not always obvious how to get from here to there.
types functional-programming scala -
Functional Composition and the Kleisli
Featuring Alexander Worton
During this talk, we will explore functional composition from the ground up. Find out about the different ways functions can be composed to form larger pieces of software, using both the standard library and the Kleisli from functional libraries scalaz and cats, while looking at the advantages...
scala typelevel testing functional-composition kleisli scalax -
Into the New World
Featuring Sofia Vaughan-Jones
For the last 6 months, Sofia has been working in a team that has been moving from their comfort zone into a 'New World'. Previously, they kept the balance of using the object-orientated features in Scala paired with functional programming concepts where they could. They now use http4s,...
fs2streams http4s fp oop scala cats functional-composition functional-programming -
Typed Actors - Should I Start Using Them?
Featuring Willem Vermeer
Typed actors are finally here and, for all of you lovers of typesafe programming, just their name is enough to get you excited! But here you are, maintaining a large scala/akka codebase – should you immediately migrate all your actors to typed actors? What are the benefits and will your code look...
scala scalax akka typesafe-programming -
Onboarding Scala
Featuring Luis Angel Vicente Sanchez
Since starting to use Scala in late 2011, "Scala is a hard language" is a phrase Luis has heard very often. And yes, it probably is if you don't have the right support when you are learning it. As in any learning process, you need space to explore and learn new things; but with a...
scala teams learning scalax -
Validating Big Data Jobs - Stopping Failures before Production (w/ Spark, BEAM, & friends!)
Featuring Holden Karau
As big data jobs move from the proof-of-concept phase into powering real production services, you will need to consider what will happen when everything eventually goes wrong (such as recommending inappropriate products or other decisions taken on bad data).
scala scalax big-data apache-beam apache-spark