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# 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(); ``` ##### Kotlin Lambda DSL ```kotlin newJsonArray { newArray { stringValue("a1") stringValue("a2") } newArray { numberValue(1) numberValue(2) } newArray { newObject { stringValue("foo", "Foo") } } } ```

HockeySDK-Android implements support for using HockeyApp in your Android application. The following features are currently supported: Collect crash reports:If your app crashes, a crash log is written to the device's storage. If the user starts the app again, they will be asked asked to submit the crash report to HockeyApp. This works for both beta and live apps, i.e. those submitted to Google Play or other app stores. Crash logs contain viable information for you to help resolve the issue. Furthermore, you as a developer can add additional information to the report as well. Update Alpha/Beta apps: The app will check with HockeyApp if a new version for your alpha/beta build is available. If yes, it will show a dialog to users and let them see the release notes, the version history and start the installation process right away. You can even force the installation of certain updates. User Metrics: Understand user behavior to improve your app. Track usage through daily and monthly active users. Monitor crash impacted users. Measure customer engagement through session count. Add custom tracking calls to learn which features your users are actually using. This feature requires a minimum API level of 14 (Android 4.x Ice Cream Sandwich). Feedback: Besides crash reports, collecting feedback from your users from within your app is a great option to help with improving your app. You act on and answer feedback directly from the HockeyApp backend. Authenticate: Identify and authenticate users against your registered testers with the HockeyApp backend.

# 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() ```

pact-jvm-consumer-groovy-v3 =========================== Groovy DSL for Pact JVM implementing V3 specification changes. ##Dependency The library is available on maven central using: * group-id = `au.com.dius` * artifact-id = `pact-jvm-consumer-groovy-v3_2.11` * version-id = `2.2.x` or `3.0.x` ##Usage Add the `pact-jvm-consumer-groovy-v3` library to your test class path. This provides a `PactMessageBuilder` class for you to use to define your pacts. If you are using gradle for your build, add it to your `build.gradle`: dependencies { testCompile 'au.com.dius:pact-jvm-consumer-groovy-v3_2.11:2.2.12' } ## Consumer test for a message consumer The `PactMessageBuilder` class provides a DSL for defining your message expectations. It works in much the same way as the `PactBuilder` class for Request-Response interactions. ### Step 1 - define the message expectations Create a test that uses the `PactMessageBuilder` to define a message expectation, and then call `run`. This will invoke the given closure with a message for each one defined in the pact. ```groovy def eventStream = new PactMessageBuilder().call { serviceConsumer 'messageConsumer' hasPactWith 'messageProducer' given 'order with id 10000004 exists' expectsToReceive 'an order confirmation message' withMetaData(type: 'OrderConfirmed') // Can define any key-value pairs here withContent(contentType: 'application/json') { type 'OrderConfirmed' audit { userCode 'messageService' } origin 'message-service' referenceId '10000004-2' timeSent: '2015-07-22T10:14:28+00:00' value { orderId '10000004' value '10.000000' fee '10.00' gst '15.00' } } } ``` ### Step 2 - call your message handler with the generated messages This example tests a message handler that gets messages from a Kafka topic. In this case the Pact message is wrapped as a Kafka `MessageAndMetadata`. ```groovy eventStream.run { Message message -> messageHandler.handleMessage(new MessageAndMetadata('topic', 1, new kafka.message.Message(message.contentsAsBytes()), 0, null, valueDecoder)) } ``` ### Step 3 - validate that the message was handled correctly ```groovy def order = orderRepository.getOrder('10000004') assert order.status == 'confirmed' assert order.value == 10.0 ``` ### Step 4 - Publish the pact file If the test was successful, a pact file would have been produced with the message from step 1.

pact-jvm-consumer-groovy-v3 =========================== Groovy DSL for Pact JVM implementing V3 specification changes. ##Dependency The library is available on maven central using: * group-id = `au.com.dius` * artifact-id = `pact-jvm-consumer-groovy-v3_2.11` * version-id = `2.2.x` or `3.0.x` ##Usage Add the `pact-jvm-consumer-groovy-v3` library to your test class path. This provides a `PactMessageBuilder` class for you to use to define your pacts. If you are using gradle for your build, add it to your `build.gradle`: dependencies { testCompile 'au.com.dius:pact-jvm-consumer-groovy-v3_2.11:2.2.12' } ## Consumer test for a message consumer The `PactMessageBuilder` class provides a DSL for defining your message expectations. It works in much the same way as the `PactBuilder` class for Request-Response interactions. ### Step 1 - define the message expectations Create a test that uses the `PactMessageBuilder` to define a message expectation, and then call `run`. This will invoke the given closure with a message for each one defined in the pact. ```groovy def eventStream = new PactMessageBuilder().call { serviceConsumer 'messageConsumer' hasPactWith 'messageProducer' given 'order with id 10000004 exists' expectsToReceive 'an order confirmation message' withMetaData(type: 'OrderConfirmed') // Can define any key-value pairs here withContent(contentType: 'application/json') { type 'OrderConfirmed' audit { userCode 'messageService' } origin 'message-service' referenceId '10000004-2' timeSent: '2015-07-22T10:14:28+00:00' value { orderId '10000004' value '10.000000' fee '10.00' gst '15.00' } } } ``` ### Step 2 - call your message handler with the generated messages This example tests a message handler that gets messages from a Kafka topic. In this case the Pact message is wrapped as a Kafka `MessageAndMetadata`. ```groovy eventStream.run { Message message -> messageHandler.handleMessage(new MessageAndMetadata('topic', 1, new kafka.message.Message(message.contentsAsBytes()), 0, null, valueDecoder)) } ``` ### Step 3 - validate that the message was handled correctly ```groovy def order = orderRepository.getOrder('10000004') assert order.status == 'confirmed' assert order.value == 10.0 ``` ### Step 4 - Publish the pact file If the test was successful, a pact file would have been produced with the message from step 1.

Axis2 is an effort to re-design and totally re-implement both Axis/Java and (eventually) Axis/C++ on a new architecture. Evolving from the now standard "handler chain" model which Axis1 pioneered, Axis2 is developing a more flexible pipeline architecture which can yet be managed and packaged in a more organized manner. This new design acknowledges the maturing of the Web services space in terms of new protocols such as WS-ReliableMessaging, WS-Security and WS-Addressing that are built on top of the base SOAP system. At the time Axis1 was designed, while it was fully expected that other protocols such as WS-ReliableMessaging would be built on top of it, there was not a proper extension architecture defined to enable clean composition of such layers. Thus, one of the key motivations for Axis2 is to provide a clean and simple environment for like Apache Sandesha and Apache WSS4J to layer on top of the base SOAP system. Another driving force for Axis2 as well as the move away from RPC oriented Web services towards more document-oriented, message style asynchronous service interactions. The Axis2 project is centered on a new representation for SOAP messages called AXIOM (AXIs Object Model). AXIOM consists of two parts: a complete XML Infoset representation and a SOAP Infoset representation on top of that. The XML Infoset representation provides a JDOM-like simple API but is built on a deferred model via a StAX-based (Streaming API for XML) pull parsing API. A key feature of AXIOM is that it allows one to stop building the XML tree and just access the pull stream directly; thus enabling both maximum flexibility and maximum performance. This approach allows us to support multiple levels of abstraction for consuming and offering Web services: using plain AXIOM, using generated code and statically data-bound data types and so on. At the time of Axis1's design, RPC-style, synchronous, request-response interactions were the order of the day for Web services. Today service interactions are much more message -oriented and exploit many different message exchange patterns. The Axis2 engine architecture is careful to not build in any assumptions of request-response patterns to ensure that it can be used easily to support arbitrary message exchange patterns.

This is the main aggregator for all gwt submodules. All gwt-specific code resides here. Submodules should avoid inheriting from each other unless necessary. This goes for maven structure and gwt.xml structure. The super module is where our jre emulation layer and super-source live; all modules should inherit super, and a minimum of other modules. Some modules, like injection, are fulfilling an api in the core module, and should be accessed only through core service interfaces. Other modules, like reflection, are capable of being standalone inherits, but can benefit from core utilities like injection, so, two (or more) .gwt.xml modules may be provided. As XApi nears 1.0, all submodules will be routinely stitched together into an uber-jar, in order to have a single jar with a single gwt module that can provide all of the services at once. Internal projects will never use the uber jar, to help maintain modularity, but external projects that want to use more than one service will certainly prefer inheriting one artifact, instead of twelve. When distributed in uber-jar format, it will likely be necessary for either the uber jar, or just xapi-gwt-api.jar to appear before gwt-dev on your compile-time classpath. If using gwt-maven-plugin, the gwtFirstOnClasspath option may become problematic. If so, we will provide a forked gwt-plugin to make sure our compiler enhancements are included in the build process. There is also work going on to make a super-source-everything plugin, which will use maven to find source files, and generate synthetic .gwt.xml for you, as part of an effort to create a wholly unified programming environment. In addition to java-to-javascript, we intend to compile java-to-java and possibly other languages, like go; imagine implementing gwt deferred binding to eliminate cross-platform differences between server environments, or operating systems, or versions of a platform, or anywhere else a core api needs to bind to multiple implementations, depending on the runtime environment.

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, classfication 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 exisiting 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.