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A small Java-based toolset to gather event data from a Camunda BPM engine and store it in Apache Kafka. Repository contains the camunda-kafka-polling-client and the camunda-kafka-model, to make reuse of the data structures easy. This tooling is meant to be used as a part of the viadee Process Warehouse or the bpmn.ai concepts. This is the model module, i.e. it contains the data model classes for reuse by Java-based, downstream analysis components.

A small Java-based toolset to gather event data from a Camunda BPM engine and store it in Apache Kafka. Repository contains the camunda-kafka-polling-client and the camunda-kafka-model, to make reuse of the data structures easy. This tooling is meant to be used as a part of the viadee Process Warehouse or the bpmn.ai concepts.

As its name indicates, Core module gather all "kernel" functionalities that will be use by other modules. More precisely, this module defines the whole types used by PowerAPI to define its architecture. This module also defines the essential Clock class, responsible of the periodically sending of the Tick message, itself responsible of the process of the PowerAPI business part.

Babylon is a tool to gather messages, and their translations from property files. It performs a round-trip consisting of two phases: export phase and import phase. In the export phase the messages are written to a Google Sheets spreadsheet. A translator will then fill in the missing translations. In the import phase, the spreadsheet (with the missing translations filled out by a translator) is examined, and the newly translated messages are used to update the respective translation property files. Also, the state of the translation, snapshot, is written out to a disk in the form of JSON file. Babylon can be run as a Maven plugin or as a standalone console application.

This library is the the backend for the Fitzhì solution. Fitzhì aims to gather all technical data regarding your application portfolio into ONE single portal. Fitzhì provides also analysis and assessments at the project scope, but its main target is the portfolio. The main ambition is to provide a global, and dynamic vision of the technical risk for your IT. The dream functionality for Fitzhì should be the ONE single dashboard, one Single Point Point Of Quality, available for the CTO, or CIO, and ready to resume in one second, one view, the current situation and the historic trend.

This library is the the backend for the Fitzhì solution. Fitzhì aims to gather all technical data regarding your application portfolio into ONE single portal. Fitzhì provides also analysis and assessments at the project scope, but its main target is the portfolio. The main ambition is to provide a global, and dynamic vision of the technical risk for your IT. The dream functionality for Fitzhì should be the ONE single dashboard, one Single Point Point Of Quality, available for the CTO, or CIO, and ready to resume in one second, one view, the current situation and the historic trend.

Babylon is a tool to gather messages, and their translations from property files. It performs a round-trip consisting of two phases: export phase and import phase. In the export phase the messages are written to a Google Sheets spreadsheet. A translator will then fill in the missing translations. In the import phase, the spreadsheet (with the missing translations filled out by a translator) is examined, and the newly translated messages are used to update the respective translation property files. Also, the state of the translation, snapshot, is written out to a disk in the form of JSON file. Babylon can be run as a Maven plugin or as a standalone console application.

EasyConfig provides simple way to overview and apply settings to file or folder based collections of files. Synonyms to "setting" are property, attribute, value while throughout application "setting" is used. The settings are groupped in "configuration" that is collection of settings from various sources. Main design concepts are: * minimalistic way to describe configuration * pluggable support for data types (validation), setting sources, source handlers Sample use case: An application is deployed in multiple locations. We need to quickly check key settings/parameters and optionally modify some of them. These values are located in different places: - in files directly in file structure - in files inside archive files (optionally nested archives) - values in DB tables - values accessible via URLs - other sources (just guessed: SSH/telnet connection+some command(s), UPnP devices, proprietary protocols, etc) We gather info from any supported (extendable) source and can modify and apply changes if supported by source (e.g. we can't update value that is count of rows in DB table, but we can read that value).

pact-jvm-consumer-specs2 ======================== ## Specs2 Bindings for the pact-jvm library ## Dependency In the root folder of your project in build.sbt add the line: ```scala libraryDependencies += "au.com.dius.pact.consumer" %% "specs2" % "4.0.1" ``` or if you are using Gradle: ```groovy dependencies { testCompile "au.com.dius.pact.consumer:specs2_2.13:4.0.1" } ``` __*Note:*__ `PactSpec` requires spec2 3.x. Also, for spray users there's an incompatibility between specs2 v3.x and spray. Follow these instructions to resolve that problem: https://groups.google.com/forum/#!msg/spray-user/2T6SBp4OJeI/AJlnJuAKPRsJ ## Usage To author a test, mix `PactSpec` into your spec First we define a service client called `ConsumerService`. In our example this is a simple wrapper for `dispatch`, an HTTP client. The source code can be found in the test folder alongside the `ExamplePactSpec`. Here is a simple example: ``` import au.com.dius.pact.consumer.PactSpec class ExamplePactSpec extends Specification with PactSpec { val consumer = "My Consumer" val provider = "My Provider" override def is = uponReceiving("a request for foo") .matching(path = "/foo") .willRespondWith(body = "{}") .withConsumerTest { providerConfig => Await.result(ConsumerService(providerConfig.url).simpleGet("/foo"), Duration(1000, MILLISECONDS)) must beEqualTo(200, Some("{}")) } } ``` This spec will be run along with the rest of your specs2 unit tests and will output your pact json to ``` /target/pacts/<Consumer>_<Provider>.json ``` # Forcing pact files to be overwritten (3.6.5+) By default, when the pact file is written, it will be merged with any existing pact file. To force the file to be overwritten, set the Java system property `pact.writer.overwrite` to `true`. # Test Analytics We are tracking anonymous analytics to gather important usage statistics like JVM version and operating system. To disable tracking, set the 'pact_do_not_track' system property or environment variable to 'true'.

# pact-jvm-consumer-java8 Provides a Java8 lambda based DSL for use with Junit to build consumer tests. ## Dependency The library is available on maven central using: * group-id = `au.com.dius.pact.consumer` * artifact-id = `java8` * version-id = `4.1.x` # A Lambda DSL for Pact This is an extension for the pact DSL provided by [consumer](../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.pact.consumer</groupId> <artifactId>java8</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") } } } ``` # Test Analytics We are tracking anonymous analytics to gather important usage statistics like JVM version and operating system. To disable tracking, set the 'pact_do_not_track' system property or environment variable to 'true'.