Version: 2.0.x

Code Generation

Quill now has a highly customizable code generator. Currently, it only supports JDBC but it will soon be extended to other contexts. With a minimal amount of configuration, the code generator takes schemas like this:

-- Using schema 'public'

create table public.Person (
  id int primary key auto_increment,
  first_name varchar(255),
  last_name varchar(255),
  age int not null
);

create table public.Address (
  person_fk int not null,
  street varchar(255),
  zip int
);

Producing objects like this:

// src/main/scala/com/my/project/public/Person.scala
package com.my.project.public

case class Person(id: Int, firstName: Option[String], lastName: Option[String], age: Int)

// src/main/scala/com/my/project/public/Address.scala
package com.my.project.public

case class Address(personFk: Int, street: Option[String], zip: Option[Int])

Quill Code Generator

This library gives you a few options as to what kind of schema to generate from JDBC metadata for Quill. You can choose to generate simple case classes that are controlled entirely but a Quill Naming Strategy, or a combination of case classes and querySchemas. You can also choose whether they should written to one file, multiple files, or just a list of strings (useful for executing directly into a repl). Thanks to the Slick code generator creators for providing inspiration for this library!

Currently the code generator is only available for JDBC databases but it will be extended in the future for Cassandra as well as others.

You can import the Code Generator using maven:

<dependency>
  <groupId>io.getquill</groupId>
  <artifactId>quill-codegen-jdbc_2.13</artifactId>
  <version>3.10.0</version>
</dependency>

Or using sbt:

libraryDependencies += "io.getquill" %% "quill-codegen-jdbc" % "4.8.4"

SimpleJdbcCodegen

This code generator generates simple case classes, each representing a table in a database. It does not generate Quill querySchema objects. Create one or multiple CodeGeneratorConfig objects and call the .writeFiles or .writeStrings methods on the code generator to generate the code.

Given the following schema:

-- Using schema 'public'

create table public.Person (
  id int primary key auto_increment,
  first_name varchar(255),
  last_name varchar(255),
  age int not null
);

create table public.Address (
  person_fk int not null,
  street varchar(255),
  zip int
);

You can invoke the SimpleJdbcCodegen like so:

// provide DB credentials with a com.typesafe.config.Config object
// (under the hood the credentials are used to create a HikariPool DataSource)
import io.getquill.codegen.jdbc.SimpleJdbcCodegen
import io.getquill.util.LoadConfig

val snakecaseConfig = LoadConfig(configPrefix: String)
val gen = new SimpleJdbcCodegen(snakecaseConfig, "com.my.project") {
    override def nameParser = SnakeCaseNames
}
gen.writeFiles("src/main/scala/com/my/project")

// or, provide an initialized DataSource
import io.getquill.codegen.jdbc.SimpleJdbcCodegen
import org.postgresql.ds.PGSimpleDataSource

val pgDataSource = new PGSimpleDataSource()
pgDataSource.setURL(
  "jdbc:postgresql://127.0.0.1:5432/quill_codegen_example?ssl=false",
)
pgDataSource.setUser("my_user")
pgDataSource.setPassword("my_password")
val gen = new SimpleJdbcCodegen(pgDataSource, "com.my.project") {
    override def nameParser = SnakeCaseNames
}
gen.writeFiles("src/main/scala/com/my/project")

You can parse column and table names using either the SnakeCaseNames or the and the LiteralNames parser which are used with the respective Quill Naming Strategies. They cannot be customized further with this code generator.

The following case classes will be generated

// src/main/scala/com/my/project/public/Person.scala
package com.my.project.public
  
case class Person(id: Int, firstName: Option[String], lastName: Option[String], age: Int)

// src/main/scala/com/my/project/public/Address.scala
package com.my.project.public
  
case class Address(personFk: Int, street: Option[String], zip: Option[Int])

If you wish to generate schemas with custom table or column names, you need to use the ComposeableTraitsJdbcCodegen in order to generate your schemas with querySchema objects.

Composeable Traits Codegen

The ComposeableTraitsJdbcCodegen enables more customized code generation. It allows you to determine the tables to generate entity classes for, their naming strategy, the types for columns in Scala, and generates the necessary querySchema object in order to map the fields. Additionally, it generates a database-independent query schema trait which can be composed with a Context object of your choice.

Given the following schema:

create table public.Person (
  id int primary key auto_increment,
  first_name varchar(255),
  last_name varchar(255),
  age int not null
);

create table public.Address (
  person_fk int not null,
  street varchar(255),
  zip int
);

Here is a example of how you could use the ComposeableTraitsJdbcCodegen in order to replace the first_name and last_name properties with first and last.

val gen = new ComposeableTraitsJdbcCodegen(
  configOrDataSource,
  packagePrefix = "com.my.project",
  nestedTrait = true) {

  override def nameParser: NameParser = CustomNames(
    columnParser = col => col.columnName.toLowerCase.replace("_name", "")
  )


  override def packagingStrategy: PackagingStrategy = PackagingStrategy.ByPackageHeader.TablePerSchema(packagePrefix)
}
gen.writeFiles("src/main/scala/com/my/project")

The following schema should be generated as a result.

package com.my.project.public

case class Person(id: Int, first: Option[String], last: Option[String], age: Int)

case class Address(person_fk: Int, street: Option[String], zip: Option[Int])

// Note that by default this is formatted as "${namespace}Extensions"
trait PublicExtensions[Idiom <: io.getquill.idiom.Idiom, Naming <: io.getquill.NamingStrategy] {
  this:io.getquill.context.Context[Idiom, Naming] =>

  object PublicSchema {
    object PersonDao {
        def query = quote {
            querySchema[Person](
              "public.person",
              _.id -> "id",
              _.first -> "first_name",
              _.last -> "last_name",
              _.age -> "age"
            )

          }

      }

      object AddressDao {
        def query = quote {
            querySchema[Address](
              "public.address",
              _.person_fk -> "person_fk",
              _.street -> "street",
              _.zip -> "zip"
            )

          }

      }
  }
}

Later when declaring your Quill database context you can compose the context with the PublicExtensions like so:

object MyCustomContext extends SqlMirrorContext[H2Dialect, Literal](H2Dialect, Literal)
  with PublicExtensions[H2Dialect, Literal]

ComposeableTraitsJdbcCodegen is designed to be customizable via composition. This is a longer list of customizable strategies:

import io.getquill.codegen.jdbc.ComposeableTraitsJdbcCodegen
import io.getquill.codegen.model._

new ComposeableTraitsJdbcCodegen(...) {

  // whether to generate Scala code for a table
  override def filter(tc: RawSchema[JdbcTableMeta, JdbcColumnMeta]): Boolean = ???

  // how to name table / columns in Scala
  override def nameParser: NameParser = ???

  // how to organize generated code into files / packages
  override def packagingStrategy: PackagingStrategy = ???

  // what JVM types (classes) to use for DB column
  // e.g. one may want to translate Postgres `timestamptz` to java.time.OffsetDateTime
  override def typer: Typer = ???

  // what to do when `typer` above cannot find an appropriate type and returned None
  override def unrecognizedTypeStrategy: UnrecognizedTypeStrategy = ???
}

Stereotyping

Frequently in corporate databases, the same kind of table is duplicated across multiple schemas, databases, etc... for different business units. Typically, all the duplicates of the table will have nearly the same columns with just minor differences. Stereotyped code-generation aims to take the 'lowest common denominator' of all these schemas in order to produce a case class that can be used across all of them.

Examine the following H2 DDL:

create table Alpha.Person (
  id int primary key auto_increment,
  first_name varchar(255),
  last_name varchar(255),
  age int not null,
  foo varchar(255),
  num_trinkets int,
  trinket_type varchar(255) not null
);

create table Bravo.Person (
  id int primary key auto_increment,
  first_name varchar(255),
  bar varchar(255),
  last_name varchar(255),
  age int not null,
  num_trinkets bigint not null,
  trinket_type int not null
);

Firstly, note that Alpha.Person and Bravo.Person have the exact same columns except for foo and bar respectively. If a common table definition Person is desired, these columns must be omitted.
Secondly, note that their columns num_trinkets and trinket_type have different types. If a common table definition Person is desired, these columns must be expanded to the widest datatype of the two which is this case bigint for num_trinkets and varchar(255) for trinket_type.

Both of the above actions are automatically performed by the ComposeableTraitsJdbcCodegen (and SimpleJdbcCodegen) automatically when multiple tables with the same name are detected or if you rename them using a custom namingStrategy causing this to happen. Here is an example of how that is done:

val gen = new ComposeableTraitsJdbcCodegen(twoSchemaConfig, "com.my.project") {
  override def namingStrategy: EntityNamingStrategy = CustomStrategy()
  override val namespacer: Namespacer =
    ts => if (ts.tableSchema.toLowerCase == "alpha" || ts.tableSchema.toLowerCase == "bravo") "common" else ts.tableSchema.toLowerCase
    
  // Be sure to set the querySchemaNaming correctly so that the different
  // querySchemas generated won't all be called '.query' in the common object (which would
  // case an un-compile-able schema to be generated).
  override def querySchemaNaming: QuerySchemaNaming = `[namespace][Table]`
}

gen.writeFiles("src/main/scala/com/my/project")

The following will then be generated. Note how numTrinkets is a Long (i.e. an SQL bigint) type and trinketType is a String (i.e. an SQL varchar),

package com.my.project.common
  
case class Person(id: Int, firstName: Option[String], lastName: Option[String], age: Int, numTrinkets: Option[Long], trinketType: String)
  
trait CommonExtensions[Idiom <: io.getquill.idiom.Idiom, Naming <: io.getquill.NamingStrategy] {
  this:io.getquill.context.Context[Idiom, Naming] =>
  
  object PersonDao {
      def alphaPerson = quote {
          querySchema[Person](
            "ALPHA.PERSON",
            _.id -> "ID",
            _.firstName -> "FIRST_NAME",
            _.lastName -> "LAST_NAME",
            _.age -> "AGE",
            _.numTrinkets -> "NUM_TRINKETS",
            _.trinketType -> "TRINKET_TYPE"
          )
        }
  
      def bravoPerson = quote {
          querySchema[Person](
            "BRAVO.PERSON",
            _.id -> "ID",
            _.firstName -> "FIRST_NAME",
            _.lastName -> "LAST_NAME",
            _.age -> "AGE",
            _.numTrinkets -> "NUM_TRINKETS",
            _.trinketType -> "TRINKET_TYPE"
          )
        }
    }
}

Later when declaring your quill database context you can compose the context with the CommonExtensions like so:

object MyCustomContext extends SqlMirrorContext[H2Dialect, Literal](H2Dialect, Literal)
  with CommonExtensions[H2Dialect, Literal]

Quill Code Generator​

SimpleJdbcCodegen​

Composeable Traits Codegen​

Stereotyping​

ZIO Chat

Quill Code Generator

SimpleJdbcCodegen

Composeable Traits Codegen

Stereotyping