"A basic example of using Dispatch with Scalatra on Jetty 8.x / AsyncServlet 3.0. It took me a lot of time to connect the dots how to use Dispatch asynchronously and actually process the results (not simply return them) and I could not find examples how to use Scalatra with AsyncServlet either. So here it is for anyone who could find it useful and save themselves a few –or more– hours."
"DynamoDB is a fast and flexible NoSQL database service that can be easily managed, so you don't have to worry about administrative burdens such as operating and scaling your databases. Instead, you can focus on designing your application, and launch it on DynamoDB with a few simple steps.
In this article, we will show you how to build an application with Amazon DynamoDB.
"Dealing with the Java AWS SDK is messy. This library attempts to make it less messy by:
Making it easier to create AWS SDK clients based on configuration and supporting fallback configurations
Providing a nicer syntax for AWS SDK calls by wrapping them in a monad (no thrown exceptions, and sequencing!)
Tries to provide Options where null can be returned
Provides a nice 'ORM' for DynamoDB table access. Dealing with AttributeValues is ugly, real ugly.
Also provide a nice 'ORM' for SQS message marshalling/unmarshalling.
Currently the library has basic support for S3, DynamoDB, CloudFormation and SQS. Feel free to add more as you need it."
The different ways to load data in R for different formats.
"A large fraction of the flaws in software development are due to programmers not fully understanding all the possible states their code may execute in. In a multithreaded environment, the lack of understanding and the resulting problems are greatly amplified, almost to the point of panic if you are paying attention. Programming in a functional style makes the state presented to your code explicit, which makes it much easier to reason about, and, in a completely pure system, makes thread race conditions impossible."
"In this series of posts I’ll explain why Haskell’s data types are called algebraic - without mentioning category theory or advanced math."
"Just as algebra is fundamental to the whole of mathematics, algebraic data types (ADTs) are fundamental to many common functional programming languages. They’re the primitives upon which all of our richer data structures are built, including everything from sets, maps, and queues, to bloom filters and neural networks."
The Selenium pageobject pattern in Scala.
"Scala enables you to define a new construct that lies halfway between an interface and a class, called a trait. Traits are unusual in that a class can incorporate as many of them as desired, like interfaces, but they can also contain behavior, like classes. Also, like both classes and interfaces, traits can introduce new methods. But unlike either, the definition of that behavior isn't checked until the trait is actually incorporated as part of a class. Or, put differently, you can define methods that aren't checked for correctness until they're incorporated into a trait-using class definition.
Traits may sound complex, but they're easier understood once you've seen them in action. To get started, here's the Person POJO redefined in Scala:"
" a thoughtless eventing setup leads to bad control flow issues. In the case of Mixpanel, as some of our front-end reports grew in scope and complexity, patterns which worked at first became unwieldy"
"I started applying React to a tool I built called RxMarbles.com, and spent some time investigating Flux. React turned out to disappoint me in multiple ways, mainly through a poorly designed API which induces the programmer to create complex state machines and to mix multiple concerns in one component. I decided to replace React with the great virtual-dom library, and to build a Reactive MVC alternative heavily based on RxJS. This pattern turned out to be successful and I applied it to other web apps. One of these is a customer project we are glad to say has worked out very well.
The combo React/Flux is clearly inspired by Reactive Programming principles, but the API and architecture are an unjustified mix of Interactive and Reactive patterns. Keep reading and I'll explain what this means, and how we can do better."
"A Support Vector Machine (SVM) is a discriminative classifier formally defined by a separating hyperplane. In other words, given labeled training data (supervised learning), the algorithm outputs an optimal hyperplane which categorizes new examples."