Announcing Krush – idiomatic persistence layer for Kotlin, based on Exposed

We’ve released a persistence library for Kotlin, you can find it on our Github. It’s a JPA-to-Exposed SQL DSL generator.

TL;DR

We’ve released a persistence library for Kotlin, you can find it on our Github. It’s a JPA-to-Exposed SQL DSL generator.

The state of persistence in Kotlin

One of the key decisions that helped Kotlin gain massive popularity was to reuse Java ecosystem instead of inventing it’s own. This means that you can safely use Kotlin as a primary language for a project developed using any popular Java stack like Spring Boot and built with Java build tool like Maven. What this also means is that natural choice for persistence layer in Kotlin is Spring Data with JPA 3 with Hibernate as an implementation.

However, JPA, which highly relies on mutable objects and dirty checking, may not look like pure Kotlin, which tries to embrace functional programming and immutability. The official Spring JPA guide for Kotlin uses mutable classes and properties which is not really idiomatic for Kotlin where you want to use immutable data classes whenever it’s possible.

There are some other options, which can be used safely with Kotlin and data classes, like Spring Data JDBC — interesting approach based on pure JDBC, embracing DDD and aggregate root concepts or Micronaut Data JDBC — if you’re not tied to Spring ecosystem. But they’re both relatively new, not mature yet and miss another idiomatic Kotlin feature — a DSL for making SQL queries.

DSL for SQL queries

Another thing that made Kotlin really powerful and popular is its ability to construct Domain Specific Languages using features like property reference, operators, infix and extension functions. For example, for Android development there is excellent anko library for constructing complex view layouts for Android apps. In Spring/JPA the default approach to SQL queries are query methods, where you use special naming convention of methods in repository interfaces. The method names are parsed at runtime to provide required SQL queries and mapping. The naming convention is supported by IntelliJ Idea and other IDEs and works well in simple cases, but may be not flexible enough when you want complex queries e.g. with some conditions based on dynamic filters. If you want to use a true, type-safe, composable and idiomatic Kotlin SQL DSL, you can try to use other libraries, like Requery or Exposed.

Requery

Requery is a lightweight persistence library for Java and Kotlin with RxJava and Java 8 streams support. It uses annotations (both custom and JPA) to process your entities and generate some infrastructure code called “model”.

So given a Book interface:

@Entity
@Table(name = "books")

interface Book : Persistable {
    @get:Key @get:Generated
    val id: Long

    val isbn: String
    val author: String
    val title: String

    val publishDate: LocalDate
}

 

You can instantiate and persist it by using generated BookEntity class:

//given
val book = BookEntity().apply {
    setIsbn("1449373321")
    setPublishDate(LocalDate.of(2017, Month.APRIL, 11))
    setTitle("Designing Data-Intensive Applications")
    setAutor("Martin Kleppmann")
}

// when
val persistedBook = dataStore.insert(book)

And the use SQL DSL to fetch data and map the results back to entities:

// then
val books = dataStore.select(Book::class).where(Book::id eq  book.id).get().toList()

assertThat(books).containsExactly(persistedBook)

This was really close to our needs! We like the idea of having annotations on the entities combined with the rich SQL DSL. Also the RxJava bindings and lazy Kotlin sequences support looks promising. On the other side, there are few minor issues related to immutable classes support:

  • immutable interface approach needs to be backed up with this generated, mutablexxxEntity class
  • there are some restrictions: e.g. you cannot use them to map relations to other entities (just foreign keys by ids)
  • @Generated also doesn’t work for ids in data classes.

You can check example project using Requery in requery branch of krush-example project on GitHub.

Exposed

Another approach which given you rich SQL DSL support is Exposed — a Kotlin-only persistence layer maintained by the JetBrains team. It comes in two flavors: active-record DAO and lightweight SQL DSL. As we are not the fans of active records, we tried the SQL DSL flavor. It works by creating additional mapping code using Kotlin objects and extension functions:

object  BookTable : Table("books") {
    val id: Column<Long> = long("id").promaryKey().autoIncrement()
    val isbn: Column<String> = varchar("isbn". 255)
    val autor: Column<String> = varchar("author". 255)
    val title: Column<String> = varchar("title". 255)
    val publishDate: Column<LocalDate> = date("publishDate")
}

Then you can refer to these Column properties to create type-safe queries and map results using Kotlin collections API:

val titles: List<String> = BookTable
        .select { BookTable.author like "Martin K%" }
        .map { it[BookTable.title] }

As you can see, Exposed is not a full-blown ORM — there is no direct mapping to/from your domain classes into these Table objects, but it’s not hard to write simple mapping functions for that. You can also benefit from Kotlin null-types support and write bindings for your own types by using Kotlin’s extension functions. We wrote some time ago this article about our approach to using Exposed in our projects.

Krush

We really like the Kotlin-first feeling combined with great flexibility of Exposed, but at some time we were tired of writing these table mappings manually. We thought that it would be nice to generate them from JPA-compatible annotations, in similar way it’s done in Requery. This ended with building a library called Krush, which we’re announcing today ;)

Krush consist of two components:

  • annotation-processor which generates Exposed mappings by reading (a subset of) standard JPA annotations found on entity classes
  • utility functions for persisting entities and mapping from/to Exposed objects

So given this entity:

@Entity
@Table(name = "books")

data class Book(
    @Id @GeneratedValue
    val id: Long? = null,

    val isbn: String,
    val author: String,
    val title: String,
    val publishDate: LocalDate
)

Krush will generate BookTable object which allows to persist it like this:

//given
val book = Book(
        isbn = "1449373321", publishDate = LocalDate.of(2017, Month.APRIL, 11),
        title = "Designing Data-Intensive Applications", author = "Martin Kleppmann"
)
val persistedBook = BookTable.insert(book)
assertThat(persistedBook.id).isNotNull()

And write queries using type-safe DSL just like you were using plain Exposed:

val bookId = book.id ?: throw IllegalargumentException( )
val fetchedBook = BookTable.select { BookTable.id eq bookId }.singleOrNull()?.toBook( )
assertThat(fetchedBook).isEqualTo(book)

val selectedBooks = BookTable
        .select { BookTable.author like "Martin Kx" }
        .toBookList()

assertThat(selectedBooks).containsOnly(book)

That’s it! You can find more details and supported features in the README of Krush repository or in some example projects.

Enjoy! Looking for feedback from the community!

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Using WsLite in practice

TL;DR

There is a example working GitHub project which covers unit testing and request/response logging when using WsLite.

Why Groovy WsLite ?

I’m a huge fan of Groovy WsLite project for calling SOAP web services. Yes, in a real world you have to deal with those - big companies have huge amount of “legacy” code and are crazy about homogeneous architecture - only SOAP, Java, Oracle, AIX…

But I also never been comfortable with XFire/CXF approach of web service client code generation. I wrote a bit about other posibilites in this post. With JAXB you can also experience some freaky classloading errors - as Tomek described on his blog. In a large commercial project the “the less code the better” principle is significant. And the code generated from XSD could look kinda ugly - especially more complicated structures like sequences, choices, anys etc.

Using WsLite with native Groovy concepts like XmlSlurper could be a great choice. But since it’s a dynamic approach you have to be really careful - write good unit tests and log requests. Below are my few hints for using WsLite in practice.

Unit testing

Suppose you have some invocation of WsLite SOAPClient (original WsLite example):

def getMothersDay(long _year) {
    def response = client.send(SOAPAction: action) {
       body {
           GetMothersDay('xmlns':'http://www.27seconds.com/Holidays/US/Dates/') {
              year(_year)
           }
       }
    }
    response.GetMothersDayResponse.GetMothersDayResult.text()
}

How can the unit test like? My suggestion is to mock SOAPClient and write a simple helper to test that builded XML is correct. Example using great SpockFramework:

void setup() {
   client = Mock(SOAPClient)
   service.client = client
}

def "should pass year to GetMothersDay and return date"() {
  given:
      def year = 2013
  when:
      def date = service.getMothersDay(year)
  then:
      1 * client.send(_, _) >> { Map params, Closure requestBuilder ->
            Document doc = buildAndParseXml(requestBuilder)
            assertXpathEvaluatesTo("$year", '//ns:GetMothersDay/ns:year', doc)
            return mockResponse(Responses.mothersDay)
      }
      date == "2013-05-12T00:00:00"
}

This uses a real cool feature of Spock - even when you mock the invocation with “any mark” (_), you are able to get actual arguments. So we can build XML that would be passed to SOAPClient's send method and check that specific XPaths are correct:

void setup() {
    engine = XMLUnit.newXpathEngine()
    engine.setNamespaceContext(new SimpleNamespaceContext(namespaces()))
}

protected Document buildAndParseXml(Closure xmlBuilder) {
    def writer = new StringWriter()
    def builder = new MarkupBuilder(writer)
    builder.xml(xmlBuilder)
    return XMLUnit.buildControlDocument(writer.toString())
}

protected void assertXpathEvaluatesTo(String expectedValue,
                                      String xpathExpression, Document doc) throws XpathException {
    Assert.assertEquals(expectedValue,
            engine.evaluate(xpathExpression, doc))
}

protected Map namespaces() {
    return [ns: 'http://www.27seconds.com/Holidays/US/Dates/']
}

The XMLUnit library is used just for XpathEngine, but it is much more powerful for comparing XML documents. The NamespaceContext is needed to use correct prefixes (e.g. ns:GetMothersDay) in your Xpath expressions.

Finally - the mock returns SOAPResponse instance filled with envelope parsed from some constant XML:

protected SOAPResponse mockResponse(String resp) {
    def envelope = new XmlSlurper().parseText(resp)
    new SOAPResponse(envelope: envelope)
}

Request and response logging

The WsLite itself doesn’t use any logging framework. We usually handle it by adding own sendWithLogging method:

private SOAPResponse sendWithLogging(String action, Closure cl) {
    SOAPResponse response = client.send(SOAPAction: action, cl)
    log(response?.httpRequest, response?.httpResponse)
    return response
}

private void log(HTTPRequest request, HTTPResponse response) {
    log.debug("HTTPRequest $request with content:\n${request?.contentAsString}")
    log.debug("HTTPResponse $response with content:\n${response?.contentAsString}")
}

This logs the actual request and response send through SOAPClient. But it logs only when invocation is successful and errors are much more interesting… So here goes withExceptionHandler method:

private SOAPResponse withExceptionHandler(Closure cl) {
    try {
        cl.call()
    } catch (SOAPFaultException soapEx) {
        log(soapEx.httpRequest, soapEx.httpResponse)
        def message = soapEx.hasFault() ? soapEx.fault.text() : soapEx.message
        throw new InfrastructureException(message)
    } catch (HTTPClientException httpEx) {
        log(httpEx.request, httpEx.response)
        throw new InfrastructureException(httpEx.message)
    }
}
def send(String action, Closure cl) {
    withExceptionHandler {
        sendWithLogging(action, cl)
    }
}

XmlSlurper gotchas

Working with XML document with XmlSlurper is generally great fun, but is some cases could introduce some problems. A trivial example is parsing an id with a number to Long value:

def id = Long.valueOf(edit.'@id' as String)

The Attribute class (which edit.'@id' evaluates to) can be converted to String using as operator, but converting to Long requires using valueOf.

The second example is a bit more complicated. Consider following XML fragment:

<edit id="3">
   <params>
      <param value="label1" name="label"/>
      <param value="2" name="param2"/>
   </params>
   <value>123</value>
</edit>
<edit id="6">
   <params>
      <param value="label2" name="label"/>
      <param value="2" name="param2"/>
   </params>
   <value>456</value>
</edit>

We want to find id of edit whose label is label1. The simplest solution seems to be:

def param = doc.edit.params.param.find { it['@value'] == 'label1' }
def edit = params.parent().parent()

But it doesn’t work! The parent method returns multiple edits, not only the one that is parent of given param

Here’s the correct solution:

doc.edit.find { edit ->
    edit.params.param.find { it['@value'] == 'label1' }
}

Example

The example working project covering those hints could be found on GitHub.

Tomcat: Problemy z requestami zawierającymi polskie znaki diakrytyczne


Jeśli jest problem z pobieraniem plików z polskimi znakami diakrytycznymi, to trzeba dopisać kodowanie do connectora w tomcat/conf/server.xml

URIEncoding="UTF-8"

Typowa konfiguracja connectora będzie wyglądała tak

<Connector port="8080" protocol="HTTP/1.1"
               connectionTimeout="20000"
               redirectPort="8443" URIEncoding="UTF-8" />