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Reactive-web is a new framework for writing highly interactive and dynamic web applications. It's written in Scala , sits on top of Lift, and uses the Functional Reactive Programming library reactive-core (it's in the same repository). As in GWT, you can code the user interface in the same language as the rest of your application (except in Scala instead of Java), rather than writing JavaScript. Unlike GWT, however, you don't need an extra build step to convert your code to JavaScript. You can easily combine code that runs on the browser with code that runs on the server. And, you can declare dynamic relationships between components, like binding in Flex/JavaFX/etc. (only much more powerful).

"These are the major new features added since Slick 1.0.1: A code generator that reverse-engineers the database schema and generates all code required for working with Slick. New driver architecture to allow support for non-SQL, non-JDBC databases. Table definitions in the Lifted Embedding use a new syntax which is slightly more verbose but also more robust and logical, avoiding several pitfalls from earlier versions. Table definitions (and their * projections) are not restricted to flat tuples of columns anymore. They can use any type that would be valid as the return type of a Query. The old projection concatenation methods ~ and ~: are still supported but not imported by default. In addition to Scala tuples, Slick supports its own HList abstraction for records of arbitrary size. You can also add support for your own record types with only a few lines of code. All record types can be used everywhere (including table definitions and mapped projections) and they can be mixed and nested arbitrarily. Soft inserts are now the default, i.e. AutoInc columns are automatically skipped when inserting with +=, ++=, insert and insertAll. This means that you no longer need separate projections (without the primary key) for inserts. There are separate methods forceInsert and forceInsertAll in JdbcProfile for the old behavior. A new model for pre-compiled queries replaces the old QueryTemplate abstraction. Any query (both, actual collection-valued Query objects and scalar queries) or function from Column types to such a query can now be lifted into a Compiled wrapper. Lifted functions can be applied (without having to recompile the query), and you can use both monadic composition of Compiled values or just get the underlying query and use that for further composition. Pre-compiled queries can now be used for update and delete operations in addition to querying. threadLocalSession has been renamed to dynamicSession and the corresponding methods have distinct names (e.g. w

"HPaste unlocks the rich functionality of HBase for a Scala audience. In so doing, it attempts to achieve the following goals: Provide a strong, clear syntax for querying and filtration Perform as fast as possible while maintaining idiomatic Scala client code -- the abstractions should not show up in a profiler! Re-articulate HBase's data structures rather than force it into an ORM-style atmosphere. A rich set of base classes for writing MapReduce jobs in hadoop against HBase tables. Provide a maximum amount of code re-use between general Hbase client usage, and operation from within a MapReduce job. Use Scala's type system to its advantage--the compiler should verify the integrity of the schema. Be a verbose DSL--minimize boilerplate code, but be human readable!"

Interesante para probar de ponerlo en práctica y ver qué resulta, ¿no?

En github funciona muy muy bien el mecanismo, lo vengo usando bastante. El análisis, comprensión y diálogo que se genera a partir de los pull requests (y los reviews implícitos que esto produce, sumado a que la herramienta es muy muy buena, permitiendo cosas como poder poner comentarios y responderlos directamente en las lineas de código) son sumamente beneficiosos, ágiles y los resultados son muy buenos. Nosotros, localmente, venimos trabajando de manera similar a lo que se propone (y se acostumbra en github), tenemos branches por temas y se hace review y refactoring de las mismas antes de mergear al tronco de avance. Obviamente en este caso se extrañan MUCHO las herramientas de comunicación que provee github y que NO tenemos localmente.

"Abstract algebra for Scala. This code is targeted at building aggregation systems (via Scalding or Storm). It was originally developed as part of Scalding's Matrix API, where Matrices had values which are elements of Monoids, Groups, or Rings. Subsequently, it was clear that the code had broader application within Scalding and on other projects within Twitter."

"On-premises source code management for Git that's secure, fast, and enterprise grade. Create and manage repositories, set up fine-grained permissions, and collaborate on code - all with the flexibility of your servers."

"Buck is a build system for Android that encourages the creation of small, reusable modules consisting of code and resources. Because Android applications are predominantly written in Java, Buck also functions as a Java build system. Learn more about the strategies Buck uses to build Java code so quickly."

"Build and debug modern web and cloud applications. Code is free and available on your favorite platform - Linux, Mac OSX, and Windows."

"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."

"Athens provides a server for Go Modules that you can run. It serves public code and your private code for you, so you don't have to pull directly from a version control system (VCS) like GitHub or GitLab."

A collection of MapReduce tasks translated (from Pig, Hive, MapReduce streaming, etc.) into Scalding for comparison.

Idea interesante para implementar usos del patrón "ask" (request-reply) con mayor seguridad de tipos.

"ScalaTags is a small XML/HTML construction library for Scala. The core functionality of Scalatags is less than 200 lines of code, and yet it provides all the functionality of large frameworks like Python's Jinja2 or C#'s Razor. It does this by leveraging the functionality of the Scala language to do almost everything. A lot of different language constructs can be used to help keep your templates concise and DRY, and why re-invent them all yourself when you have someone else who has done it before you."