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Reusable framework for daemon applications based on Commons Daemon Jsvc and Procrun. A small installation layout pattern combined with some utility classes allows applications to be come UNIX daemons or Windows NT services. Reusable bootstrappers along with an installer plugin allow for the rapid creation of standalone daemon applications.

Reusable framework for daemon applications based on Commons Daemon Jsvc and Procrun. A small installation layout pattern combined with some utility classes allows applications to be come UNIX daemons or Windows NT services. Reusable bootstrappers along with an installer plugin allow for the rapid creation of standalone daemon applications.

Nuun Kernel is a software kernel for framework creation. It brings a powerful plugin design plus a JSR 330 compliant injection mechanism backed by Guice. Plugin benefits from kernel capabilities by sending requests to it : - kernel params request : - Classpath scans request :on class by name, annotation, meta annotation or more generally Predicate - Binding Request : Nuun Kernel provides an SPI in order to bring IOC from other vendors. Nuun Kernel come with 2 plugins: - Configuration Plugin : a plugin that inject the good property based on @Property annotation. - Log plugin : a Log handler that inject the good Log implementation

The crypto4j library provides a simple and pluggable crypto abstraction library for Java, including both cryptographic primitives and the artifacts defined in the JOSE standard. This library separates the cryptographic primitives from the JOSE artifacts. The library uses the algorithms available through JCA (JCE). The implementations of the cryptographic primitives provided in this library rely on the standard JCA implementation, and can be configured and extended through the JCA mechanisms. The JOSE portion of the library allows custom extensions by either replacing the provided JOSE artifact implementations with custom implementations, or by adding new JOSE artifacts, for instance in form of additional algorithms, which is particularly useful in case that the JOSE standard is updated or in case custom extensions to the JOSE standard should be implemented. The implementations available in this library generally come in two variants: a standard implementation of the primitives and advanced algorithms, and a high-performance implementation that takes advantage of implementation patterns that do not compromise cryprographic security, but speed up the overall processing time.

Nuun Kernel is a software kernel for framework creation. It brings a powerful plugin design plus a JSR 330 compliant injection mechanism backed by Guice. Plugin benefits from kernel capabilities by sendings request to it : - kernel params request : - Classpath scans request :on class by name, annotation, meta annotation or more generally Predicate - Binding Request : Nuun Kernel provides an SPI in order to bring IOC from other vendors. Nuun Kernel come with 2 plugins: - Configuration Plugin : a plugin that inject the good property based on @Property annotation. - Log plugin : a Log handler that inject the good Log implementation

Nuun Kernel is a software kernel for framework creation. It brings a powerful plugin design plus a JSR 330 compliant injection mechanism backed by Guice. Plugin benefits from kernel capabilities by sendings request to it : - kernel params request : - Classpath scans request :on class by name, annotation, meta annotation or more generally Predicate - Binding Request : Nuun Kernel provides an SPI in order to bring IOC from other vendors. Nuun Kernel come with 2 plugins: - Configuration Plugin : a plugin that inject the good property based on @Property annotation. - Log plugin : a Log handler that inject the good Log implementation

All Gwt jre emulation code goes in this module, as well as any gwt-compiler overrides. xapi-gwt-api.jar must come before gwt-dev.jar on your compile classpath. A plugin is being built to automatically adjust maven runtime dependencies, but users of ant or IDEs will need to ensure the super jar comes before gwt-dev. We will petition gwt to accept our mods, but, until then, if you want bleeding edge features, you gotta do bleeding edge configuration. Code that ties directly into other modules, like java.lang.reflect for the reflection submodule, have their super-source here, and generators or other implementations in their own modules. This is to maintain consistency in what is or isn't whitelisted in XApi GWT. Some modules, like appengine, provide dependency-specific super-source in their own packages. This module is for jre, junit and core XApi services.

Mahout's goal is to build scalable machine learning libraries. With scalable we mean: Scalable to reasonably large data sets. Our core algorithms for clustering, classification and batch based collaborative filtering are implemented on top of Apache Hadoop using the map/reduce paradigm. However we do not restrict contributions to Hadoop based implementations: Contributions that run on a single node or on a non-Hadoop cluster are welcome as well. The core libraries are highly optimized to allow for good performance also for non-distributed algorithms. Scalable to support your business case. Mahout is distributed under a commercially friendly Apache Software license. Scalable community. The goal of Mahout is to build a vibrant, responsive, diverse community to facilitate discussions not only on the project itself but also on potential use cases. Come to the mailing lists to find out more. Currently Mahout supports mainly four use cases: Recommendation mining takes users' behavior and from that tries to find items users might like. Clustering takes e.g. text documents and groups them into groups of topically related documents. Classification learns from existing categorized documents what documents of a specific category look like and is able to assign unlabelled documents to the (hopefully) correct category. Frequent itemset mining takes a set of item groups (terms in a query session, shopping cart content) and identifies, which individual items usually appear together.

# pact-jvm-consumer-java8 Provides a Java8 lambda based DSL for use with Junit to build consumer tests. # A Lambda DSL for Pact This is an extension for the pact DSL provided by [pact-jvm-consumer](../pact-jvm-consumer). The difference between the default pact DSL and this lambda DSL is, as the name suggests, the usage of lambdas. The use of lambdas makes the code much cleaner. ## Why a new DSL implementation? The lambda DSL solves the following two main issues. Both are visible in the following code sample: ```java new PactDslJsonArray() .array() # open an array .stringValue("a1") # choose the method that is valid for arrays .stringValue("a2") # choose the method that is valid for arrays .closeArray() # close the array .array() # open an array .numberValue(1) # choose the method that is valid for arrays .numberValue(2) # choose the method that is valid for arrays .closeArray() # close the array .array() # open an array .object() # now we work with an object .stringValue("foo", "Foo") # choose the method that is valid for objects .closeObject() # close the object and we're back in the array .closeArray() # close the array ``` ### The existing DSL is quite error-prone Methods may only be called in certain states. For example `object()` may only be called when you're currently working on an array whereas `object(name)` is only allowed to be called when working on an object. But both of the methods are available. You'll find out at runtime if you're using the correct method. Finally, the need for opening and closing objects and arrays makes usage cumbersome. The lambda DSL has no ambiguous methods and there's no need to close objects and arrays as all the work on such an object is wrapped in a lamda call. ### The existing DSL is hard to read When formatting your source code with an IDE the code becomes hard to read as there's no indentation possible. Of course, you could do it by hand but we want auto formatting! Auto formatting works great for the new DSL! ```java array.object((o) -> { o.stringValue("foo", "Foo"); # an attribute o.stringValue("bar", "Bar"); # an attribute o.object("tar", (tarObject) -> { # an attribute with a nested object tarObject.stringValue("a", "A"); # attribute of the nested object tarObject.stringValue("b", "B"); # attribute of the nested object }) }); ``` ## Installation ### Maven ``` <dependency> <groupId>au.com.dius</groupId> <artifactId>pact-jvm-consumer-java8_2.12</artifactId> <version>${pact.version}</version> </dependency> ``` ## Usage Start with a static import of `LambdaDsl`. This class contains factory methods for the lambda dsl extension. When you come accross the `body()` method of `PactDslWithProvider` builder start using the new extensions. The call to `LambdaDsl` replaces the call to instance `new PactDslJsonArray()` and `new PactDslJsonBody()` of the pact library. ```java io.pactfoundation.consumer.dsl.LambdaDsl.* ``` ### Response body as json array ```java import static io.pactfoundation.consumer.dsl.LambdaDsl.newJsonArray; ... PactDslWithProvider builder = ... builder.given("some state") .uponReceiving("a request") .path("/my-app/my-service") .method("GET") .willRespondWith() .status(200) .body(newJsonArray((a) -> { a.stringValue("a1"); a.stringValue("a2"); }).build()); ``` ### Response body as json object ```java import static io.pactfoundation.consumer.dsl.LambdaDsl.newJsonBody; ... PactDslWithProvider builder = ... builder.given("some state") .uponReceiving("a request") .path("/my-app/my-service") .method("GET") .willRespondWith() .status(200) .body(newJsonBody((o) -> { o.stringValue("foo", "Foo"); o.stringValue("bar", "Bar"); }).build()); ``` ### Examples #### Simple Json object When creating simple json structures the difference between the two approaches isn't big. ##### JSON ```json { "bar": "Bar", "foo": "Foo" } ``` ##### Pact DSL ```java new PactDslJsonBody() .stringValue("foo", "Foo") .stringValue("bar", "Bar") ``` ##### Lambda DSL ```java newJsonBody((o) -> { o.stringValue("foo", "Foo"); o.stringValue("bar", "Bar"); }).build(); ``` #### An array of arrays When we come to more complex constructs with arrays and nested objects the beauty of lambdas become visible! ##### JSON ```json [ ["a1", "a2"], [1, 2], [{"foo": "Foo"}] ] ``` ##### Pact DSL ```java new PactDslJsonArray() .array() .stringValue("a1") .stringValue("a2") .closeArray() .array() .numberValue(1) .numberValue(2) .closeArray() .array() .object() .stringValue("foo", "Foo") .closeObject() .closeArray(); ``` ##### Lambda DSL ```java newJsonArray((rootArray) -> { rootArray.array((a) -> a.stringValue("a1").stringValue("a2")); rootArray.array((a) -> a.numberValue(1).numberValue(2)); rootArray.array((a) -> a.object((o) -> o.stringValue("foo", "Foo"))); }).build(); ``` `object` is a reserved word in Kotlin. To allow using the DSL without escaping, a Kotlin extension `newObject` is available: ```kotlin newJsonArray { rootArray -> rootArray.array { a -> a.stringValue("a1").stringValue("a2") } rootArray.array { a -> a.numberValue(1).numberValue(2) } rootArray.array { a -> a.newObject { o -> o.stringValue("foo", "Foo") } } }.build(); ```