Maps API

Pact provider ============= sub project of https://github.com/DiUS/pact-jvm The pact provider is responsible for verifying that an API provider adheres to a number of pacts authored by its clients This library provides the basic tools required to automate the process, and should be usable on its own in many instances. Framework and build tool specific bindings will be provided in separate libraries that build on top of this core functionality. ### Running Pacts Main takes 2 arguments: The first is the root folder of your pact files (all .json files in root and subfolders are assumed to be pacts) The second is the location of your pact config json file. ### Pact config The pact config is a simple mapping of provider names to endpoint url's paths will be appended to endpoint url's when interactions are attempted for an example see: https://github.com/DiUS/pact-jvm/blob/master/pact-jvm-provider/src/test/resources/pact-config.json ### Provider State Before each interaction is executed, the provider under test will have the opportunity to enter a state. Generally the state maps to a set of fixture data for mocking out services that the provider is a consumer of (they will have their own pacts) The pact framework will instruct the test server to enter that state by sending: POST "${config.stateChangeUrl.url}/setup" { "state" : "${interaction.stateName}" } ### An example of running provider verification with junit This example uses java, junit and hamcrest matchers to run the provider verification. As the provider service is a DropWizard application, it uses the DropwizardAppRule to startup the service before running any test. Warning: It only grabs the first interaction from the pact file with the consumer, where there could be many. (This could possibly be solved with a parameterized test) ```java public class PactJVMProviderJUnitTest { @ClassRule public static TestRule startServiceRule = new DropwizardAppRule<DropwizardAppConfig>(DropwizardApp.class, "config.yml"); private static ProviderInfo serviceProvider; private static Pact testConsumerPact; @BeforeClass public static void setupProvider() { serviceProvider = new ProviderInfo("Dropwizard App"); serviceProvider.setProtocol("http"); serviceProvider.setHost("localhost"); serviceProvider.setPort(8080); serviceProvider.setPath("/"); ConsumerInfo consumer = new ConsumerInfo(); consumer.setName("test_consumer"); consumer.setPactFile(new File("target/pacts/ping_client-ping_service.json")); // serviceProvider.getConsumers().add(consumer); testConsumerPact = (Pact) new PactReader().loadPact(consumer.getPactFile()); } @Test @SuppressWarnings("unchecked") public void runConsumerPacts() { //grab the first interaction from the pact with consumer List<Interaction> interactions = scala.collection.JavaConversions.seqAsJavaList(testConsumerPact.interactions()); Interaction interaction1 = interactions.get(0); //setup any provider state //setup the client and interaction to fire against the provider ProviderClient client = new ProviderClient(); client.setProvider(serviceProvider); client.setRequest(interaction1.request()); Map<String, Object> clientResponse = (Map<String, Object>) client.makeRequest(); Map<String, Object> result = (Map<String, Object>) ResponseComparison.compareResponse(interaction1.response(), clientResponse, (int) clientResponse.get("statusCode"), (Map) clientResponse.get("headers"), (String) clientResponse.get("data")); //assert all good assertThat(result.get("method"), is(true)); // method type matches Map headers = (Map) result.get("headers"); //headers match headers.forEach( (k, v) -> assertThat(format("Header: [%s] does not match", k), v, org.hamcrest.Matchers.equalTo(true)) ); assertThat((Collection<Object>)((Map)result.get("body")).values(), org.hamcrest.Matchers.hasSize(0)); // empty list of body mismatches } } ``` ### An example of running provider verification with spock This example uses groovy and spock to run the provider verification. Again the provider service is a DropWizard application, and is using the DropwizardAppRule to startup the service. This example runs all interactions using spocks Unroll feature ```groovy class PactJVMProviderSpockSpec extends Specification { @ClassRule @Shared TestRule startServiceRule = new DropwizardAppRule<DropwizardAppConfig>(DropwizardApp.class, "config.yml"); @Shared ProviderInfo serviceProvider @Shared Pact testConsumerPact def setupSpec() { serviceProvider = new ProviderInfo("Dropwizard App") serviceProvider.protocol = "http" serviceProvider.host = "localhost" serviceProvider.port = 8080; serviceProvider.path = "/" def consumer = serviceProvider.hasPactWith("ping_consumer", { pactFile = new File('target/pacts/ping_client-ping_service.json') }) testConsumerPact = (Pact) new PactReader().loadPact(consumer.getPactFile()); } def cleanup() { //cleanup provider state //ie. db.truncateAllTables() } def cleanupSpec() { //cleanup provider } @Unroll def "Provider Pact - With Consumer"() { given: //setup provider state // ie. db.setupRecords() // serviceProvider.requestFilter = { req -> // req.addHeader('Authorization', token) // } when: ProviderClient client = new ProviderClient(provider: serviceProvider, request: interaction.request()) Map clientResponse = (Map) client.makeRequest() Map result = (Map) ResponseComparison.compareResponse(interaction.response(), clientResponse, clientResponse.statusCode, clientResponse.headers, clientResponse.data) then: // method matches result.method == true // headers all match, spock needs the size checked before // asserting each result if (result.headers.size() > 0) { result.headers.each() { k, v -> assert v == true } } // empty list of body mismatches result.body.size() == 0 where: interaction << scala.collection.JavaConversions.seqAsJavaList(testConsumerPact.interactions()) } } ```

Routes API Routes API is the next generation, performance optimized version of the existing Directions API and Distance Matrix API. It helps you find the ideal route from A to Z, calculates ETAs and distances for matrices of origin and destination locations, and also offers new features.

Address Validation API The Address Validation API allows developers to verify the accuracy of addresses. Given an address, it returns information about the correctness of the components of the parsed address, a geocode, and a verdict on the deliverability of the parsed address.

WebSphere Distributed Map API, version 2.0

The Google API Libraries for Google Web Toolkit is a collection of libraries that provide Java language bindings for popular Google JavaScript APIs. These libraries make it quick and easy for developers to use these Google JavaScript APIs with Google Web Toolkit. The libraries are supported by the Google Web Toolkit team.

Restcomm :: Parent pom for 2.x releases

Liferay Layout Dynamic Data Mapping Form Field Type API

Liferay Journal Article Dynamic Data Mapping Form Field Type API

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Liferay Dynamic Data Mapping Form Field Type API

odlparent-lite

GWT library to access Google Maps javascript API

JMapper is a framework that permits to write dynamic mapping, bringing several advantages as: create and enrich target objects, apply a specific logic to the mapping (only valued fields, only null fields, etc..), automated management of the XML file, possibility of implementing the 1 to N and N to 1 relationships, define explicit conversions, define inherited configurations,

JSefa (Java Simple exchange format api) is a simple library for stream-based serialization of java objects to XML, CSV, FLR or any other format and back again using an iterator-style interface independent of the serialization format. The mapping between java object types and types of the serialization format (e. g. xml complex element types) can be defined either by annotating the java classes or programmatically using a simple API. The current implementation supports XML, CSV and FLR - for XML it is based on JSR 173.

Coherent Map Reduce API

GS Collections is a collections framework for Java. It has JDK-compatible List, Set and Map implementations with a rich API and set of utility classes that work with any JDK compatible Collections, Arrays, Maps or Strings. The iteration protocol was inspired by the Smalltalk collection framework.

pact-jvm-consumer-groovy ========================= Groovy DSL for Pact JVM ## Dependency The library is available on maven central using: * group-id = `au.com.dius` * artifact-id = `pact-jvm-consumer-groovy_2.11` * version-id = `3.5.x` ## Usage Add the `pact-jvm-consumer-groovy` library to your test class path. This provides a `PactBuilder` class for you to use to define your pacts. For a full example, have a look at the example JUnit `ExampleGroovyConsumerPactTest`. If you are using gradle for your build, add it to your `build.gradle`: dependencies { testCompile 'au.com.dius:pact-jvm-consumer-groovy_2.11:3.5.0' } Then create an instance of the `PactBuilder` in your test. ```groovy import au.com.dius.pact.consumer.PactVerificationResult import au.com.dius.pact.consumer.groovy.PactBuilder import groovyx.net.http.RESTClient import org.junit.Test class AliceServiceConsumerPactTest { @Test void "A service consumer side of a pact goes a little something like this"() { def alice_service = new PactBuilder() // Create a new PactBuilder alice_service { serviceConsumer "Consumer" // Define the service consumer by name hasPactWith "Alice Service" // Define the service provider that it has a pact with port 1234 // The port number for the service. It is optional, leave it out to // to use a random one given('there is some good mallory') // defines a provider state. It is optional. uponReceiving('a retrieve Mallory request') // upon_receiving starts a new interaction withAttributes(method: 'get', path: '/mallory') // define the request, a GET request to '/mallory' willRespondWith( // define the response we want returned status: 200, headers: ['Content-Type': 'text/html'], body: '"That is some good Mallory."' ) } // Execute the run method to have the mock server run. // It takes a closure to execute your requests and returns a PactVerificationResult. PactVerificationResult result = alice_service.runTest { def client = new RESTClient('http://localhost:1234/') def alice_response = client.get(path: '/mallory') assert alice_response.status == 200 assert alice_response.contentType == 'text/html' def data = alice_response.data.text() assert data == '"That is some good Mallory."' } assert result == PactVerificationResult.Ok.INSTANCE // This means it is all good } } ``` After running this test, the following pact file is produced: { "provider" : { "name" : "Alice Service" }, "consumer" : { "name" : "Consumer" }, "interactions" : [ { "provider_state" : "there is some good mallory", "description" : "a retrieve Mallory request", "request" : { "method" : "get", "path" : "/mallory", "requestMatchers" : { } }, "response" : { "status" : 200, "headers" : { "Content-Type" : "text/html" }, "body" : "That is some good Mallory.", "responseMatchers" : { } } } ] } ### DSL Methods #### serviceConsumer(String consumer) This names the service consumer for the pact. #### hasPactWith(String provider) This names the service provider for the pact. #### port(int port) Sets the port that the mock server will run on. If not supplied, a random port will be used. #### given(String providerState) Defines a state that the provider needs to be in for the request to succeed. For more info, see https://github.com/realestate-com-au/pact/wiki/Provider-states. Can be called multiple times. #### given(String providerState, Map params) Defines a state that the provider needs to be in for the request to succeed. For more info, see https://github.com/realestate-com-au/pact/wiki/Provider-states. Can be called multiple times, and the params map can contain the data required for the state. #### uponReceiving(String requestDescription) Starts the definition of a of a pact interaction. #### withAttributes(Map requestData) Defines the request for the interaction. The request data map can contain the following: | key | Description | Default Value | |----------------------------|-------------------------------------------|-----------------------------| | method | The HTTP method to use | get | | path | The Path for the request | / | | query | Query parameters as a Map<String, List> | | | headers | Map of key-value pairs for the request headers | | | body | The body of the request. If it is not a string, it will be converted to JSON. Also accepts a PactBodyBuilder. | | | prettyPrint | Boolean value to control if the body is pretty printed. See note on Pretty Printed Bodies below | For the path, header attributes and query parameters (version 2.2.2+ for headers, 3.3.7+ for query parameters), you can use regular expressions to match. You can either provide a regex `Pattern` class or use the `regexp` method to construct a `RegexpMatcher` (you can use any of the defined matcher methods, see DSL methods below). If you use a `Pattern`, or the `regexp` method but don't provide a value, a random one will be generated from the regular expression. This value is used when generating requests. For example: ```groovy .withAttributes(path: ~'/transaction/[0-9]+') // This will generate a random path for requests // or .withAttributes(path: regexp('/transaction/[0-9]+', '/transaction/1234567890')) ``` #### withBody(Closure closure) Constructs the body of the request or response by invoking the supplied closure in the context of a PactBodyBuilder. ##### Pretty Printed Bodies [Version 2.2.15+, 3.0.4+] An optional Map can be supplied to control how the body is generated. The option values are available: | Option | Description | |--------|-------------| | mimeType | The mime type of the body. Defaults to `application/json` | | prettyPrint | Boolean value controlling whether to pretty-print the body or not. Defaults to true | If the prettyPrint option is not specified, the bodies will be pretty printed unless the mime type corresponds to one that requires compact bodies. Currently only `application/x-thrift+json` is classed as requiring a compact body. For an example of turning off pretty printing: ```groovy service { uponReceiving('a request') withAttributes(method: 'get', path: '/') withBody(prettyPrint: false) { name 'harry' surname 'larry' } } ``` #### willRespondWith(Map responseData) Defines the response for the interaction. The response data map can contain the following: | key | Description | Default Value | |----------------------------|-------------------------------------------|-----------------------------| | status | The HTTP status code to return | 200 | | headers | Map of key-value pairs for the response headers | | | body | The body of the response. If it is not a string, it will be converted to JSON. Also accepts a PactBodyBuilder. | | | prettyPrint | Boolean value to control if the body is pretty printed. See note on Pretty Printed Bodies above | For the headers (version 2.2.2+), you can use regular expressions to match. You can either provide a regex `Pattern` class or use the `regexp` method to construct a `RegexpMatcher` (you can use any of the defined matcher methods, see DSL methods below). If you use a `Pattern`, or the `regexp` method but don't provide a value, a random one will be generated from the regular expression. This value is used when generating responses. For example: ```groovy .willRespondWith(headers: [LOCATION: ~'/transaction/[0-9]+']) // This will generate a random location value // or .willRespondWith(headers: [LOCATION: regexp('/transaction/[0-9]+', '/transaction/1234567890')]) ``` #### PactVerificationResult runTest(Closure closure) The `runTest` method starts the mock server, and then executes the provided closure. It then returns the pact verification result for the pact run. If you require access to the mock server configuration for the URL, it is passed into the closure, e.g., ```groovy PactVerificationResult result = alice_service.runTest() { mockServer -> def client = new RESTClient(mockServer.url) def alice_response = client.get(path: '/mallory') } ``` ### Note on HTTP clients and persistent connections Some HTTP clients may keep the connection open, based on the live connections settings or if they use a connection cache. This could cause your tests to fail if the client you are testing lives longer than an individual test, as the mock server will be started and shutdown for each test. This will result in the HTTP client connection cache having invalid connections. For an example of this where the there was a failure for every second test, see [Issue #342](https://github.com/DiUS/pact-jvm/issues/342). ### Body DSL For building JSON bodies there is a `PactBodyBuilder` that provides as DSL that includes matching with regular expressions and by types. For a more complete example look at `PactBodyBuilderTest`. For an example: ```groovy service { uponReceiving('a request') withAttributes(method: 'get', path: '/') withBody { name(~/\w+/, 'harry') surname regexp(~/\w+/, 'larry') position regexp(~/staff|contractor/, 'staff') happy(true) } } ``` This will return the following body: ```json { "name": "harry", "surname": "larry", "position": "staff", "happy": true } ``` and add the following matchers: ```json { "$.body.name": {"regex": "\\w+"}, "$.body.surname": {"regex": "\\w+"}, "$.body.position": {"regex": "staff|contractor"} } ``` #### DSL Methods The DSL supports the following matching methods: * regexp(Pattern re, String value = null), regexp(String regexp, String value = null) Defines a regular expression matcher. If the value is not provided, a random one will be generated. * hexValue(String value = null) Defines a matcher that accepts hexidecimal values. If the value is not provided, a random hexidcimal value will be generated. * identifier(def value = null) Defines a matcher that accepts integer values. If the value is not provided, a random value will be generated. * ipAddress(String value = null) Defines a matcher that accepts IP addresses. If the value is not provided, a 127.0.0.1 will be used. * numeric(Number value = null) Defines a matcher that accepts any numerical values. If the value is not provided, a random integer will be used. * integer(def value = null) Defines a matcher that accepts any integer values. If the value is not provided, a random integer will be used. * decimal(def value = null) Defines a matcher that accepts any decimal numbers. If the value is not provided, a random decimal will be used. * timestamp(String pattern = null, def value = null) If pattern is not provided the ISO_DATETIME_FORMAT is used ("yyyy-MM-dd'T'HH:mm:ss") . If the value is not provided, the current date and time is used. * time(String pattern = null, def value = null) If pattern is not provided the ISO_TIME_FORMAT is used ("'T'HH:mm:ss") . If the value is not provided, the current date and time is used. * date(String pattern = null, def value = null) If pattern is not provided the ISO_DATE_FORMAT is used ("yyyy-MM-dd") . If the value is not provided, the current date and time is used. * uuid(String value = null) Defines a matcher that accepts UUIDs. A random one will be generated if no value is provided. * equalTo(def value) Defines an equality matcher that always matches the provided value using `equals`. This is useful for resetting cascading type matchers. * includesStr(def value) Defines a matcher that accepts any value where its string form includes the provided string. * nullValue() Defines a matcher that accepts only null values. * url(String basePath, Object... pathFragments) Defines a matcher for URLs, given the base URL path and a sequence of path fragments. The path fragments could be strings or regular expression matchers. For example: ```groovy url('http://localhost:8080', 'pacticipants', regexp('[^\\/]+', 'Activity%20Service')) ``` Defines a matcher that accepts only null values. #### What if a field matches a matcher name in the DSL? When using the body DSL, if there is a field that matches a matcher name (e.g. a field named 'date') then you can do the following: ```groovy withBody { date = date() } ``` ### Ensuring all items in a list match an example (2.2.0+) Lots of the time you might not know the number of items that will be in a list, but you want to ensure that the list has a minimum or maximum size and that each item in the list matches a given example. You can do this with the `eachLike`, `minLike` and `maxLike` functions. | function | description | |----------|-------------| | `eachLike()` | Ensure that each item in the list matches the provided example | | `maxLike(integer max)` | Ensure that each item in the list matches the provided example and the list is no bigger than the provided max | | `minLike(integer min)` | Ensure that each item in the list matches the provided example and the list is no smaller than the provided min | For example: ```groovy withBody { users minLike(1) { id identifier name string('Fred') } } ``` This will ensure that the user list is never empty and that each user has an identifier that is a number and a name that is a string. __Version 3.2.4/2.4.6+__ You can specify the number of example items to generate in the array. The default is 1. ```groovy withBody { users minLike(1, 3) { id identifier name string('Fred') } } ``` This will create an example user list with 3 users. __Version 3.2.13/2.4.14+__ The each like matchers have been updated to work with primitive types. ```groovy withBody { permissions eachLike(3, 'GRANT') } ``` will generate the following JSON ```json { "permissions": ["GRANT", "GRANT", "GRANT"] } ``` and matchers ```json { "$.body.permissions": {"match": "type"} } ``` and now you can even get more fancy ```groovy withBody { permissions eachLike(3, regexp(~/\w+/)) permissions2 minLike(2, 3, integer()) permissions3 maxLike(4, 3, ~/\d+/) } ``` You can also match arrays at the root level, for instance, ```groovy withBody PactBodyBuilder.eachLike(regexp(~/\w+/)) ``` or if you have arrays of arrays ```groovy withBody PactBodyBuilder.eachLike([ regexp('[0-9a-f]{8}', 'e8cda07e'), regexp(~/\w+/, 'sony') ]) ``` __Version 3.5.9+__ A `eachArrayLike` method has been added to handle matching of arrays of arrays. ```groovy { answers minLike(1) { questionId string("books") answer eachArrayLike { questionId string("title") answer string("BBBB") } } ``` This will generate an array of arrays for the `answer` attribute. ### Matching any key in a map (3.3.1/2.5.0+) The DSL has been extended for cases where the keys in a map are IDs. For an example of this, see [#313](https://github.com/DiUS/pact-jvm/issues/313). In this case you can use the `keyLike` method, which takes an example key as a parameter. For example: ```groovy withBody { example { one { keyLike '001', 'value' // key like an id mapped to a value } two { keyLike 'ABC001', regexp('\\w+') // key like an id mapped to a matcher } three { keyLike 'XYZ001', { // key like an id mapped to a closure id identifier() } } four { keyLike '001XYZ', eachLike { // key like an id mapped to an array where each item is matched by the following id identifier() // example } } } } ``` For an example, have a look at [WildcardPactSpec](src/test/au/com/dius/pact/consumer/groovy/WildcardPactSpec.groovy). **NOTE:** The `keyLike` method adds a `*` to the matching path, so the matching definition will be applied to all keys of the map if there is not a more specific matcher defined for a particular key. Having more than one `keyLike` condition applied to a map will result in only one being applied when the pact is verified (probably the last). **Further Note: From version 3.5.22 onwards pacts with wildcards applied to map keys will require the Java system property "pact.matching.wildcard" set to value "true" when the pact file is verified.** ### Matching with an OR (3.5.0+) The V3 spec allows multiple matchers to be combined using either AND or OR for a value. The main use of this would be to either be able to match a value or a null, or to combine different matchers. For example: ```groovy withBody { valueA and('AB', includeStr('A'), includeStr('B')) // valueA must include both A and B valueB or('100', regex(~/\d+/), nullValue()) // valueB must either match a regular expression or be null valueC or('12345678', regex(~/\d{8}/), regex(~/X\d{13}/)) // valueC must match either 8 or X followed by 13 digits } ``` ## Changing the directory pact files are written to (2.1.9+) By default, pact files are written to `target/pacts` (or `build/pacts` if you use Gradle), but this can be overwritten with the `pact.rootDir` system property. This property needs to be set on the test JVM as most build tools will fork a new JVM to run the tests. For Gradle, add this to your build.gradle: ```groovy test { systemProperties['pact.rootDir'] = "$buildDir/custom-pacts-directory" } ``` ## 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`. # Publishing your pact files to a pact broker If you use Gradle, you can use the [pact Gradle plugin](https://github.com/DiUS/pact-jvm/tree/master/provider/pact-jvm-provider-gradle#publishing-pact-files-to-a-pact-broker) to publish your pact files. # Pact Specification V3 Version 3 of the pact specification changes the format of pact files in the following ways: * Query parameters are stored in a map form and are un-encoded (see [#66](https://github.com/DiUS/pact-jvm/issues/66) and [#97](https://github.com/DiUS/pact-jvm/issues/97) for information on what this can cause). * Introduces a new message pact format for testing interactions via a message queue. * Multiple provider states can be defined with data parameters. ## Generating V3 spec pact files (3.1.0+, 2.3.0+) To have your consumer tests generate V3 format pacts, you can pass an option into the `runTest` method. For example: ```groovy PactVerificationResult result = service.runTest(specificationVersion: PactSpecVersion.V3) { config -> def client = new RESTClient(config.url) def response = client.get(path: '/') } ``` ## Consumer test for a message consumer For testing a consumer of messages from a message queue, 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, but will generate a V3 format message pact file. The following steps demonstrate how to use it. ### 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. # Having values injected from provider state callbacks (3.6.11+) You can have values from the provider state callbacks be injected into most places (paths, query parameters, headers, bodies, etc.). This works by using the V3 spec generators with provider state callbacks that return values. One example of where this would be useful is API calls that require an ID which would be auto-generated by the database on the provider side, so there is no way to know what the ID would be beforehand. The DSL method `fromProviderState` allows you to set an expression that will be parsed with the values returned from the provider states. For the body, you can use the key value instead of an expression. For example, assume that an API call is made to get the details of a user by ID. A provider state can be defined that specifies that the user must be exist, but the ID will be created when the user is created. So we can then define an expression for the path where the ID will be replaced with the value returned from the provider state callback. ```groovy service { given('User harry exists') uponReceiving('a request for user harry') withAttributes(method: 'get', path: fromProviderState('/api/user/${id}', '/api/user/100')) withBody { name(fromProviderState('userName', 'harry')) // looks up the value using the userName key } } ```

Shades is an Object/Relational Mapping (ORM) framework that works in conjunction with JDBC APIs. Instead of relying on XML or annotations for configuration, Shades relies on an interface called ORMapping. This makes shades simple and flexible. Shades has no new transaction model nor Connection management which you must learn. You control the transactions, and the Connection that Shades uses, through plain JDBC interfaces. Shades is designed to work well with modern web development frameworks like Tapestry and Wicket.

Mapping, persistence, and code generation API for reading and writing POJOs to an LDAP directory

Easy Redis Java client and Real-Time Data Platform. Valkey compatible. Sync/Async/RxJava3/Reactive API. Client side caching. Over 50 Redis based Java objects and services: JCache API (JSR-107), Hibernate Cache, MyBatis Cache, Quarkus Cache, Micronaut Cache, Apache Tomcat Session, Spring Session, Micronaut Session, Hibernate, Spring Boot Starter, Spring Cache, Spring Session, Spring Transaction Manager, Spring Cloud Stream, Spring Data Redis, JSON, Set, Multimap, Geo, SortedSet, Map, List, Queue, Deque, Semaphore, ReadWriteLock, FairLock, Lock, AtomicLong, AtomicDouble, LongAdder, DoubleAdder, Map Reduce, Bloom filter, Scheduler, RPC

Isotrol Port@l 3.0 Portal Management Platform

Liferay Frontend JS Import Maps Extender API

Liferay Object Dynamic Data Mapping Form Field Type API

Liferay Dynamic Data Mapping Demo Data Creator API

Easy Redis Java client and Real-Time Data Platform. Valkey compatible. Sync/Async/RxJava3/Reactive API. Client side caching. Over 50 Redis based Java objects and services: JCache API (JSR-107), Hibernate Cache, MyBatis Cache, Quarkus Cache, Micronaut Cache, Apache Tomcat Session, Spring Session, Micronaut Session, Hibernate, Spring Boot Starter, Spring Cache, Spring Session, Spring Transaction Manager, Spring Cloud Stream, Spring Data Redis, JSON, Set, Multimap, Geo, SortedSet, Map, List, Queue, Deque, Semaphore, ReadWriteLock, FairLock, Lock, AtomicLong, AtomicDouble, LongAdder, DoubleAdder, Map Reduce, Bloom filter, Scheduler, RPC

A Java API for using Google Maps within a JavaFX application.

Easy Redis Java client and Real-Time Data Platform. Valkey compatible. Sync/Async/RxJava3/Reactive API. Client side caching. Over 50 Redis based Java objects and services: JCache API (JSR-107), Hibernate Cache, MyBatis Cache, Quarkus Cache, Micronaut Cache, Apache Tomcat Session, Spring Session, Micronaut Session, Hibernate, Spring Boot Starter, Spring Cache, Spring Session, Spring Transaction Manager, Spring Cloud Stream, Spring Data Redis, JSON, Set, Multimap, Geo, SortedSet, Map, List, Queue, Deque, Semaphore, ReadWriteLock, FairLock, Lock, AtomicLong, AtomicDouble, LongAdder, DoubleAdder, Map Reduce, Bloom filter, Scheduler, RPC

Easy Redis Java client and Real-Time Data Platform. Valkey compatible. Sync/Async/RxJava3/Reactive API. Client side caching. Over 50 Redis based Java objects and services: JCache API (JSR-107), Hibernate Cache, MyBatis Cache, Quarkus Cache, Micronaut Cache, Apache Tomcat Session, Spring Session, Micronaut Session, Hibernate, Spring Boot Starter, Spring Cache, Spring Session, Spring Transaction Manager, Spring Cloud Stream, Spring Data Redis, JSON, Set, Multimap, Geo, SortedSet, Map, List, Queue, Deque, Semaphore, ReadWriteLock, FairLock, Lock, AtomicLong, AtomicDouble, LongAdder, DoubleAdder, Map Reduce, Bloom filter, Scheduler, RPC

Permazen classes that map Java model classes onto the core API.

The internal API module for Virtual Data Set modules. Each module that provides mapping functions should only have to depend on this module to get all the dependencies it needs.

The DriverAdapter API for nosqlbench; Provides the interfaces needed to build drivers that can be loaded by nosqlbench core, using a minimal and direct API for op mapping.

Easy Redis Java client and Real-Time Data Platform. Valkey compatible. Sync/Async/RxJava3/Reactive API. Client side caching. Over 50 Redis based Java objects and services: JCache API (JSR-107), Hibernate Cache, MyBatis Cache, Quarkus Cache, Micronaut Cache, Apache Tomcat Session, Spring Session, Micronaut Session, Hibernate, Spring Boot Starter, Spring Cache, Spring Session, Spring Transaction Manager, Spring Cloud Stream, Spring Data Redis, JSON, Set, Multimap, Geo, SortedSet, Map, List, Queue, Deque, Semaphore, ReadWriteLock, FairLock, Lock, AtomicLong, AtomicDouble, LongAdder, DoubleAdder, Map Reduce, Bloom filter, Scheduler, RPC

Easy Redis Java client and Real-Time Data Platform. Valkey compatible. Sync/Async/RxJava3/Reactive API. Client side caching. Over 50 Redis based Java objects and services: JCache API (JSR-107), Hibernate Cache, MyBatis Cache, Quarkus Cache, Micronaut Cache, Apache Tomcat Session, Spring Session, Micronaut Session, Hibernate, Spring Boot Starter, Spring Cache, Spring Session, Spring Transaction Manager, Spring Cloud Stream, Spring Data Redis, JSON, Set, Multimap, Geo, SortedSet, Map, List, Queue, Deque, Semaphore, ReadWriteLock, FairLock, Lock, AtomicLong, AtomicDouble, LongAdder, DoubleAdder, Map Reduce, Bloom filter, Scheduler, RPC

OpenDaylight is leading the transformation to Open Software Defined Networking (SDN). For more information, please see https://www.opendaylight.org

Legato is a configurable, lightweight web mapping client that can be easily embedded into web pages and portals, CMS and individual web applications. Legato is implemented in JavaScript and based on the popular open source library OpenLayers.

Eclipse Collections is a collections framework for Java. It has JDK-compatible List, Set and Map implementations with a rich API and set of utility classes that work with any JDK compatible Collections, Arrays, Maps or Strings. The iteration protocol was inspired by the Smalltalk collection framework.

Eclipse JNoSQL Mapping, Artemis API, core engine

A Java API for using Google Maps within a JavaFX application.

Handy extensions to the Google Maps Android API.

Handy extensions to the Google Maps Android API.

JSimpleDB classes that map Java model classes onto the core API.

Easy Redis Java client and Real-Time Data Platform. Valkey compatible. Sync/Async/RxJava3/Reactive API. Client side caching. Over 50 Redis based Java objects and services: JCache API (JSR-107), Hibernate Cache, MyBatis Cache, Quarkus Cache, Micronaut Cache, Apache Tomcat Session, Spring Session, Micronaut Session, Hibernate, Spring Boot Starter, Spring Cache, Spring Session, Spring Transaction Manager, Spring Cloud Stream, Spring Data Redis, JSON, Set, Multimap, Geo, SortedSet, Map, List, Queue, Deque, Semaphore, ReadWriteLock, FairLock, Lock, AtomicLong, AtomicDouble, LongAdder, DoubleAdder, Map Reduce, Bloom filter, Scheduler, RPC

Easy Redis Java client and Real-Time Data Platform. Valkey compatible. Sync/Async/RxJava3/Reactive API. Client side caching. Over 50 Redis based Java objects and services: JCache API (JSR-107), Hibernate Cache, MyBatis Cache, Quarkus Cache, Micronaut Cache, Apache Tomcat Session, Spring Session, Micronaut Session, Hibernate, Spring Boot Starter, Spring Cache, Spring Session, Spring Transaction Manager, Spring Cloud Stream, Spring Data Redis, JSON, Set, Multimap, Geo, SortedSet, Map, List, Queue, Deque, Semaphore, ReadWriteLock, FairLock, Lock, AtomicLong, AtomicDouble, LongAdder, DoubleAdder, Map Reduce, Bloom filter, Scheduler, RPC

Easy Redis Java client and Real-Time Data Platform. Valkey compatible. Sync/Async/RxJava3/Reactive API. Client side caching. Over 50 Redis based Java objects and services: JCache API (JSR-107), Hibernate Cache, MyBatis Cache, Quarkus Cache, Micronaut Cache, Apache Tomcat Session, Spring Session, Micronaut Session, Hibernate, Spring Boot Starter, Spring Cache, Spring Session, Spring Transaction Manager, Spring Cloud Stream, Spring Data Redis, JSON, Set, Multimap, Geo, SortedSet, Map, List, Queue, Deque, Semaphore, ReadWriteLock, FairLock, Lock, AtomicLong, AtomicDouble, LongAdder, DoubleAdder, Map Reduce, Bloom filter, Scheduler, RPC

Easy Redis Java client and Real-Time Data Platform. Valkey compatible. Sync/Async/RxJava3/Reactive API. Client side caching. Over 50 Redis based Java objects and services: JCache API (JSR-107), Hibernate Cache, MyBatis Cache, Quarkus Cache, Micronaut Cache, Apache Tomcat Session, Spring Session, Micronaut Session, Hibernate, Spring Boot Starter, Spring Cache, Spring Session, Spring Transaction Manager, Spring Cloud Stream, Spring Data Redis, JSON, Set, Multimap, Geo, SortedSet, Map, List, Queue, Deque, Semaphore, ReadWriteLock, FairLock, Lock, AtomicLong, AtomicDouble, LongAdder, DoubleAdder, Map Reduce, Bloom filter, Scheduler, RPC

Easy Redis Java client and Real-Time Data Platform. Valkey compatible. Sync/Async/RxJava3/Reactive API. Client side caching. Over 50 Redis based Java objects and services: JCache API (JSR-107), Hibernate Cache, MyBatis Cache, Quarkus Cache, Micronaut Cache, Apache Tomcat Session, Spring Session, Micronaut Session, Hibernate, Spring Boot Starter, Spring Cache, Spring Session, Spring Transaction Manager, Spring Cloud Stream, Spring Data Redis, JSON, Set, Multimap, Geo, SortedSet, Map, List, Queue, Deque, Semaphore, ReadWriteLock, FairLock, Lock, AtomicLong, AtomicDouble, LongAdder, DoubleAdder, Map Reduce, Bloom filter, Scheduler, RPC

This package enables the Linked Data Client to access the metadata of YouTube Videos as if they were published as Linked Data (RDF) by mapping the YouTube API to the Ontology for Media Resources.

OpenDaylight is leading the transformation to Open Software Defined Networking (SDN). For more information, please see https://www.opendaylight.org

REST SPI Mappings for SOS Series Database.

Coherent Map Reduce API