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"Scaldi - is Scala dependency injection library. Basically Scala already have everything you need for dependency injection. But still some things can be made easier. Goal of the project is to provide more standard and easy way to make dependency injection in Scala projects consuming power of the Scala language. "

Arquillian brings the test to the runtime so you don't have to manage the runtime from the test (or the build). Arquillian eliminates this burden by covering all aspects of test execution, which includes: Managing the lifecycle of the container (or containers) Bundling the test case, dependent classes and resources into a ShrinkWrap archive (or archives) Deploying the archive (or archives) to the container (or containers) Enriching the test case by providing dependency injection and other declarative services Executing the tests inside (or against) the container Capturing the results and returning them to the test runner for reporting

Este "patrón" está funcionando muy bien en navrel.

"Spoon allows you to package applications and their dependencies into a lightweight, isolated virtual environment called a "container." Containerized applications can then be run on any Windows machine that has Spoon installed, no matter the underlying infrastructure. This eliminates installs, conflicts, breaks, and missing dependencies."

"Terraform is a tool for building, changing, and versioning infrastructure safely and efficiently. Terraform can manage existing and popular service providers as well as custom in-house solutions. Configuration files describe to Terraform the components needed to run a single application or your entire datacenter. Terraform generates an execution plan describing what it will do to reach the desired state, and then executes it to build the described infrastructure. As the configuration changes, Terraform is able to determine what changed and create incremental execution plans which can be applied. The infrastructure Terraform can manage includes low-level components such as compute instances, storage, and networking, as well as high-level components such as DNS entries, SaaS features, etc. The key features of Terraform are: Infrastructure as Code: Infrastructure is described using a high-level configuration syntax. This allows a blueprint of your datacenter to be versioned and treated as you would any other code. Additionally, infrastructure can be shared and re-used. Execution Plans: Terraform has a "planning" step where it generates an execution plan. The execution plan shows what Terraform will do when you call apply. This lets you avoid any surprises when Terraform manipulates infrastructure. Resource Graph: Terraform builds a graph of all your resources, and parallelizes the creation and modification of any non-dependent resources. Because of this, Terraform builds infrastructure as efficiently as possible, and operators get insight into dependencies in their infrastructure. Change Automation: Complex changesets can be applied to your infrastructure with minimal human interaction. With the previously mentioned execution plan and resource graph, you know exactly what Terraform will change and in what order, avoiding many possible human errors."

Jugoso debate y ejemplos de como reemplazar inyección de dependencias (DI) con patrones comunes de programación funcional.

Me expresé muy mal, muy desde el punto de vista de un programador java... el asunto en realidad no es "cómo reemplazar DI" sino qué patrones de diseño hicieron que nunca fuera necesario el uso de DI en los lenguajes del paradigma funcional y cómo se pueden aplicar en scala.

Muy buena charla de Runar Bjarnasson sobre DI estilo funcional. En alguna charla lo escuché decir algo así como:   Como todos sabemos "Inversion Of Control" es solo otra forma de llamar al "pasaje de parámetros". Y eso marca el approach alternativo al "DI estilo Spring" que tomó el mundo de la programación funcional.

"In this post I would like to make small introduction to Scaldi and show you how easy it is to use it together with Play."

Functional dependencies are a near-standard extension to Haskell (present in GHC and elsewhere) which allow constraints on the type parameters of type classes to be expressed and then enforced by the compiler.

"Insight into why node_modules works the way it does."

"Glock is a command-line tool to lock dependencies to specific revisions, using a version control hook to keep those revisions in sync across a team."

"HDF (Hierarchical Data Format) technologies are relevant when the data challenges being faced push the limits of what can be addressed by traditional database systems, XML documents, or in-house data formats. Leveraging the powerful HDF products and the expertise of The HDF Group, organizations realize substantial cost savings while solving challenges that seemed intractable using other data management technologies. Many HDF adopters have very large datasets, very fast access requirements, or very complex datasets. Others turn to HDF because it allows them to easily share data across a wide variety of computational platforms using applications written in different programming languages. Some use HDF to take advantage of the many open-source and commercial tools that understand HDF. Similar to XML documents, HDF files are self-describing and allow users to specify complex data relationships and dependencies. In contrast to XML documents, HDF files can contain binary data (in many representations) and allow direct access to parts of the file without first parsing the entire contents. HDF, not surprisingly, allows hierarchical data objects to be expressed in a very natural manner, in contrast to the tables of relational database. Whereas relational databases support tables, HDF supports n-dimensional datasets and each element in the dataset may itself be a complex object. Relational databases offer excellent support for queries based on field matching, but are not well-suited for sequentially processing all records in the database or for subsetting the data based on coordinate-style lookup."

"A sbt plugin for creating distributable Scala packages that include dependent jars and launch scripts."

"Scala.Rx is an experimental change propagation library for Scala. Scala.Rx gives you Reactive variables (Rxs), which are smart variables who auto-update themselves when the values they depend on change. The underlying implementation is push-based FRP based on the ideas in Deprecating the Observer Pattern."

One-JAR lets you package a Java application together with its dependency Jars into a single executable Jar file.

Dick Wall explores the state and future of Java, his reasons for switching to programming in Scala, the SubCut Dependency Injection library for Scala, Scala Compiler Plugins and much more.

"Configuration library for JVM languages. Overview implemented in plain Java with no dependencies extensive test coverage supports files in three formats: Java properties, JSON, and a human-friendly JSON superset merges multiple files across all formats can load from files, URLs, or classpath good support for "nesting" (treat any subtree of the config the same as the whole config) users can override the config with Java system properties, java -Dmyapp.foo.bar=10 supports configuring an app, with its framework and libraries, all from a single file such as application.conf parses duration and size settings, "512k" or "10 seconds" converts types, so if you ask for a boolean and the value is the string "yes", or you ask for a float and the value is an int, it will figure it out. JSON superset features: comments includes substitutions ("foo" : ${bar}, "foo" : Hello ${who}) properties-like notation (a.b=c) less noisy, more lenient syntax substitute environment variables This library limits itself to config files. If you want to load config from a database or something, you would need to write some custom code. The library has nice support for merging configurations so if you build one from a custom source it's easy to merge it in."

"shapeless is a type class and dependent type based generic programming library for Scala."