- Play 2.4
- Swagger (OpenAPI) 2.0
This plugin should be enabled using the play-swagger-service activator template as the version in this repository is under active development. The status of this software is beta, an end-to-end functional release intended to demonstrate the possibility to generate following from a Swagger specification:
- Play route files
- Generators of random test data
- Wrappers for Play route files to convert semantics from http-related to domain-related (controller_base)
- Skeletons for the domain-driven controller implementation
- Model classes and validation rules
- Unit tests for invalid and valid parameter sets
- Security extractors (if needed)
- Skeletons for custom deserializers (if needed)
We benefit from community feedback. All comments are welcome!
This tutorial is based on the play-swagger-service activator template.
$ activator new playground play-swagger-service
The template project contains following:
tutorial
folder with HTML tutorialpublic/swagger
folder containing static files needed for swagger UIproject
folder containing pre-configuredplugins.sbt
file with a definition of all required resolvers and pluginsconf
folder with following customized contents:routes
file with route configuration for Swagger UI, example specification and commented out links to other examplesexample.yaml
, a demo Swagger specification. The specification has a dummy implementation inapp
folder.examples
folder containing other different Swagger specification examples. Each specification in this folder represents some aspect of the Play-Swagger plugin in more details. For the specification to be picked up by the plugin it must be moved into theconf
folder. It is allowed to have multiple Swagger specifications in theconf
folder at the same time.
app
directory with following template implementations:controllers/Swagger.scala
- a backend side of the Swagger UIgenerated_controllers/example.yaml.scala
- a dummy implementation of the example controller. Will be (re)generated if deletedsecurity/example.yaml.scala
- a marshaller for OAuth2 tokens. Will not be regenerated until a) deleted or renamed b) explicitly requested by issuing aapiFirstSecurity
command
Congratulations, you just created a new Play-Swagger application!
The Play Framework with the Play-Swagger plugin make it easy to build RESTful web services from a Swagger API specification as the single source of truth. Play is based on a lightweight, stateless, web-friendly architecture. Built on Akka, Play provides predictable and minimal resource consumption for highly-scalable applications. The Play-Swagger plugin takes Swagger API definitions and treats them as the single source of truth of your REST services.
Play-Swagger supports round-trip regeneration and compilation of:
- Play routes definitions (managed).
- Swagger domain model definitions and parameters onto Scala case classes (managed).
- Swagger domain model constraints onto Play validations (managed).
- Generators for random test data generation of parameter values (managed).
- Unit tests for validating your service at the API boundary (managed).
- Swagger path definitions onto skeletons for Play controller implementations (unmanaged).
In the list above, "(managed)" means that the code is managed by sbt. The code is not controlled and altered by you, the programmer of the REST service. The plugin takes your Swagger API definition as the single source of truth and regenerates these code parts in a consistent manner. You'll instead be focusing on implementing the service business logic in an (unmanaged) Play controller class that is generated once. Subsequent regenerations keep the code that you have added, either by commenting out the parts that are no longer valid, or by adding parts that are needed because you have made a change to the API.
Manual generation and compilation of:
- Security extractors
- Unmarshallers for custom content types
is supported in the case if
a) No security extractor or unmarshaller with the same name already exists
b) The developer issues apiFirstSecurity
or apiFirstMarshallers
sbt command
Before we go any further, let's run the application.
- Open a shell and
cd
into your service project directory. - Start
sbt
andrun
the service. - View the running application at http://localhost:9000.
The service template comes with the Swagger UI frontend included,
run statically from the within Play, which provides a sandbox for your service.
The template is configured with a template Swagger API definition called example.yaml
and located in the conf
directory of the Play application.
The example.yaml
definition provides an example API description
This definition contains three end points:
- the
/token
path, which accept theGET
andPOST
methods - the
/todos/{user_id}
, which accepts theGET
method.
The GET /token
API plays a role of an authentication server and is used by the Swagger UI for OAuth token requests.
The POST /token
API represents an authorization server and is used by the security part of the
generated code to validate OAuth tokens.
The GET /todos/{user_id}
takes a path parameter user_id
and returns a TODO list for given user.
For the client to be allowed to access this endpoint, it must provide an OAuth token with the scope admin:org
.
The token can be requested using the Swagger UI.
Try it out for yourself:
Click the default button to expand the API definition in the Swagger UI.
As a Play application developer, you are used to defining your endpoints in the conf/routes
file.
Not so with the Play-Swagger plugin! Swagger API specifications already define endpoints as path
definitions,
as seen in the example above. So why do the work twice, right? Instead, the Play-Swagger plugin requires you to
link your API definition in the routes file ones—making all Swagger API-defined endpoints available as children
of one single path context location, and generating Play route definitions from them (as shown below):
-> /example example.yaml.Routes
Note that the conf/routes
file provided by this activator template also contains a couple of additional GET
mappings required for the the Swagger UI sandbox.
There are a couple of commented out links to other examples. If you activate some specification by moving it from
the examples
folder into the conf
folder, you'll need to uncomment an appropriate line in the routes
file in
order for play to be able to find it.
Scala domain model definitions are generated for all data types defined as Swagger parameters in an API specification. Swagger parameters can be of path, query, header, form or body types, and consist of either primitive data types or more complex types composed from objects and arrays with primitives as leaves.
Both primitive types and complex types are mapped to scala.
As an example, let's look at the Swagger API specification file simple.petstore.api.yaml
,
which defines the API of a simple pet store. It contains a model definition for a pet.
definitions:
pet:
required:
- id
- name
properties:
id:
type: integer
format: int64
name:
type: string
tag:
type: string
This definition consists of an object pet
containing the required properties id
and name
and the optional property tag
. The Swagger primitive types of these properties are a 64-bit integer
and (twice) a string
, successively. The Play-Swagger plugin will map this definition on to a generated Scala model.
package simple.petstore.api
package object yaml {
type PetTag = Option[String]
case class Pet(id: Long, name: String, tag: PetTag)
}
This generated model contains a type definition PetTag
, which declares a type alias for the optional tag
property,
and a Pet
case class with the properties as named in the Swagger API definition and mapped on the subsequent
Scala primitive or declared types. The case class and type alias are generated in an package object yaml
,
this package object itself is contained in the package simple.petstore.api
so that full object name corresponds
to the API filename.
Note that models are generated within a Play application as managed code in the target folder.
Generated model code is not intended to be altered. We should instead look upon the Swagger definition as the single
source of truth, and as the source code that defines our model.
The Swagger specification file of our API is, in that sense, part of the codebase.
Even though the generated Pet
case class is managed by the plugin, and not us, it can (of course)
be used in our application codebase after being imported.
import simple.petstore.api.yaml._
val pet = Pet(0L, "Tucker", Some("Greyhound"))
A $ref
element of the specification is allowed to contain a name of file as it's part. Because of this, it is possible to split
a single specification into multiple files as shown in cross_spec_references.yaml
example. It is also possible to reference a definition in one specification from another specification.
In this case for each reference an independent copy of the class definition will be created for each referencing specification.
The definition is then placed into the appropriate package for each specification.
Thus, even if multiple classes with the same name and structure might be generated, they all will coexist in their own separate namespaces and won't be interchangeable.
Swagger version 2.0 allows for primitive data types based on the types defined by JSON-Schema.
When generated as Scala, the following mapping applies:
Common Name | Swagger Type | Swagger Format | Scala Type |
---|---|---|---|
integer | integer | int32 | scala.Int |
long | integer | int64 | scala.Long |
float | number | float | scala.Float |
double | number | double | scala.Double |
big int | integer | scala.math.BigInt | |
big decimal | number | scala.math.BigDecimal | |
boolean | boolean | scala.Boolean | |
string | string | scala.String | |
byte | string | byte | de.zalando.play.controllers.Base64String |
binary | string | binary | de.zalando.play.controllers.BinaryString |
date | string | date | org.joda.time.LocalDate |
datetime | string | date-time | org.joda.time.DateTime |
password | string | password | scala.String |
file | file | java.io.File |
Additionally, if a validation of type "enum" is defined for some primitive type, a trait and a set of case objects forming an ADT will be generated for this enum.
Complex types are made up of primitive objects, or nested objects.
Complex object types are defined in Swagger model definitions as either objects or arrays.
Objects are, again, based on the JSON-Schema specification
and defined as Swagger Schema Objects
for parameter definitions of type: "object"
.
For example, given a Swagger API definition file api.yaml
containing a model that defines a person
as an object
with the properties name
and age
of the primitive types string
and integer
subsequently,
this object will be mapped on a Scala case class, and generated in a Scala package object (namespace) with the same name
as the extension of the file the specification is read from and in a package with the same name as the
Swagger definition file in which the model is defined—that is, api
definitions:
person:
type: object
required:
- name
- age
properties:
name:
type: string
age:
type: integer
format: int32
Is generated into:
package api
package object yaml {
case class Person(name: String, age: Int)
}
Nested objects are generated adjourned but referenced hierarchically. E.g.
definitions:
parent:
type: object
required:
- child
properties:
child:
type: object
required:
- name
properties:
name:
type: string
Is generated into:
package api
package object yaml {
case class Parent(child: ParentChild)
case class ParentChild(name: String)
}
Swagger, by default, defines object properties to be optional, which can be overridden by providing a list of required
object properties as already used in the examples above. Optional properties are mapped upon Scala's Option
type,
for which a type alias is generated for each property that is optional. E.g.
definitions:
product:
required:
- name
properties:
name:
type: string
tag:
type: string
Which is generated as:
package api
package object yaml {
type ProductTag = Option[String]
case class Product(name: String, tag: ProductTag)
}
As objects can be nested, so can object property optionality. To facilitate for nested optionality, we generate a nested scala Option
type alias. E.g.
definitions:
Basic:
properties:
optional:
type: object
properties:
nested:
type: string
Which is generated as:
package api
package object yaml {
type BasicOptional = Option[BasicOptionalOpt]
type BasicOptionalNested = Option[String]
case class BasicOptionalOpt(nested: BasicOptionalNested)
case class Basic(optional: BasicOptional)
}
As object properties can be optional, so can be query, header, body or form parameters.
In the case if they are not required, they are mapped to the Scala's Option
type.
Path parameters are must be declared as required.
In the case, if a parameter is not required, it is allowed to have a default value.
Objects can extend other objects via employment of Swagger's allOff
property. In the example below, the ExtendedErrorModel
inherits all of the properties of the ErrorModel
which it refers to—that is, the properties message
and code
—and extends this model with the property rootCause
. Swagger object extension is mapped by duplicating inherited properties in the object that extends. E.g.
definitions:
ErrorModel:
type: object
required:
- message
- code
properties:
message:
type: string
code:
type: integer
ExtendedErrorModel:
allOf:
- $ref: '#/definitions/ErrorModel'
- type: object
required:
- rootCause
properties:
rootCause:
type: string
Which is generated as:
package api
package object yaml {
import scala.math.BigInt
case class ErrorModel(message: String, code: BigInt)
case class ExtendedErrorModel(message: String, code: BigInt, rootCause: String)
}
Polymorphic object definitions are possible through employment of the Swagger discriminator
property.
In the example definition below, an abstract Pet
defines what concrete Cat
and Dog
s have in common.
Swagger object models define data, so a discriminator property is required to distinguish concrete cat and dog
instances as they are serialised to and from the API. In this sense, the discriminator property works
in the same way as a discriminator column works in ORM frameworks when mapping a class hierarchy onto a single table.
It simply contains a value that maps onto one of the concrete types—for example, petType: "Cat"
or petType: "Dog"
.
definitions:
Pet:
discriminator: petType
properties:
name:
type: string
petType:
type: string
required:
- name
- petType
Cat:
allOf:
- $ref: '#/definitions/Pet'
- properties:
huntingSkill:
type: string
default: lazy
enum:
- clueless
- lazy
- adventurous
- aggressive
required:
- huntingSkill
Dog:
allOf:
- $ref: '#/definitions/Pet'
- properties:
packSize:
type: integer
format: int32
required:
- packSize
Which is generated as:
package api
package object yaml {
trait IPet {
def name: String
def petType: String
}
case class Cat(name: String, petType: String, huntingSkill: CatHuntingSkill) extends IPet
case class Dog(name: String, petType: String, packSize: Int) extends IPet
case class Pet(name: String, petType: String) extends IPet
sealed trait CatHuntingSkill { def value: String }
case object Clueless extends CatHuntingSkill { val value = "clueless" }
case object Lazy extends CatHuntingSkill { val value = "lazy" }
case object Adventurous extends CatHuntingSkill { val value = "adventurous" }
case object Aggressive extends CatHuntingSkill { val value = "aggressive" }
implicit def stringToCatHuntingSkill(in: String): CatHuntingSkill = in match {
case "clueless" => Clueless
case "lazy" => Lazy
case "adventurous" => Adventurous
case "aggressive" => Aggressive
}
}
Please note how the enumeration of cat's huntingSkill
's get's translated into the ADT with a sealed trait CatHuntingSkill
and four case objects implementing that trait.
Swagger's model language allows objects' additional properties to be loosely defined employing the additionalProperties
annotation
in order to model dictionaries. These dictionaries are mapped to Scala's Map
type, for which a type alias is
generated following the same (by now) well-known pattern as for optional properties, with the map's key parameter type being a Scala String
.
A Swagger additional property definition takes as its type property the element type of the dictionary,
which can be of primitive or complex type and which is mapped on Scala as the map's value parameter type.
Swagger allows for one additionalProperties
annotation per object definition, so we can generate this Scala parameter
with the static name additionalProperties
.
In the following example we define a Swagger model object definition KeyedArray
that uses the additionalProperties
annotation to provide the object with a set of key value mappings from string to array. E.g.
definitions:
KeyedArrays:
type: object
additionalProperties:
type: array
items:
type: integer
Which is generated as:
package api
package object yaml {
import de.zalando.play.controllers.ArrayWrapper
import scala.math.BigInt
import scala.collection.immutable.Map
type KeyedArraysAdditionalPropertiesCatchAll = ArrayWrapper[BigInt]
type KeyedArraysAdditionalProperties = Map[String, KeyedArraysAdditionalPropertiesCatchAll]
case class KeyedArrays(additionalProperties: KeyedArraysAdditionalProperties)
}
Swagger's array
is used to define properties that hold sets or lists of model values—possibly of a primitive type,
but complex element types are also allowed. Depending on the place where the array definition appears, Swagger array can be mapped to one of two Scala types, parametrised for the element type that it contains:
- if an array only defined inline as a part of the response definition, it is translated to a
Seq
type - otherwise (array appears in the parameter definition or in the
definitions
part of the specification) it is defined as ade.zalando.play.controllers.ArrayWrapper
For example, in the snippet below, an Activity
object definition is referred to as an item element in the
messages
property of type: array
of the containing object definition Example
.
A Scala type alias will be generated for the array type (just as we've seen before with optional properties),
after which the array-containing property can be generated within the case class as being of this alias type.
E.g. in the Swagger definition and code
definitions:
Activity:
type: object
required:
- actions
properties:
actions:
type: string
Example:
type: object
required:
- messages
properties:
messages:
type: array
items:
$ref: '#/definitions/Activity'
Which is generated as:
package api
package object yaml {
import de.zalando.play.controllers.ArrayWrapper
type ExampleMessages = ArrayWrapper[Activity]
case class Activity(actions: String)
case class Example(messages: ExampleMessages)
}
If the description of the same array is inlined as a part of the response definition like that:
paths:
/api:
get:
responses:
200:
schema:
type: object
required:
- messages
properties:
messages:
type: array
items:
$ref: '#/definitions/Activity'
description: array payload
definitions:
Activity:
type: object
required:
- actions
properties:
actions:
type: string
than the Seq
scala type will be used:
package api
package object yaml {
type ApiGetResponses200Messages = Seq[Activity]
case class Activity(actions: String)
case class ApiGetResponses200(messages: ApiGetResponses200Messages)
}
Array definition types can be nested and are possibly optional.
The following (contrived) snippet depicts the generated Scala code when both definition types are
employed in a somewhat non-useful manner. The intent of this example is to show that the case
class definitions are rather concisely generated, even though a stack of type aliases is needed
to make sure that we still refer in Scala code to an aptly named Swagger definition—especially
in conjunction with the object properties being optional. Next to its benefits,
type safety against null
pointers does have an associated cost as well.
definitions:
Activity:
type: object
properties:
actions:
type: string
Example:
type: object
properties:
messages:
type: array
items:
type: array
items:
$ref: '#/definitions/Activity'
nested:
type: array
items:
type: array
items:
type: array
items:
type: array
items:
type: string
Which is generated as:
package api
package object yaml {
import de.zalando.play.controllers.ArrayWrapper
type ExampleMessagesOpt = ArrayWrapper[ExampleMessagesOptArr]
type ExampleMessages = Option[ExampleMessagesOpt]
type ExampleNested = Option[ExampleNestedOpt]
type ExampleMessagesOptArr = ArrayWrapper[Activity]
type ExampleNestedOptArrArrArr = ArrayWrapper[String]
type ExampleNestedOptArrArr = ArrayWrapper[ExampleNestedOptArrArrArr]
type ActivityActions = Option[String]
type ExampleNestedOptArr = ArrayWrapper[ExampleNestedOptArrArr]
type ExampleNestedOpt = ArrayWrapper[ExampleNestedOptArr]
case class Activity(actions: ActivityActions)
case class Example(messages: ExampleMessages, nested: ExampleNested)
}
Swagger API definitions allow for constraints to be put on parameter types.
We have already seen the required
constraint, used to mark a parameter or specific field within
a domain definition to be required upon input. Additional constraints, as defined by the
Parameter Object,
can be added to your API definition. The Play-Swagger plugin will generate validations for these parameter
constraints and make sure that your controller methods are only called if the input of your service
complies to those constraints.
In the example below, the API definition of the token
parameter of
type Base64String
, as the form parameter, contains validation rules for the lenght of the perameter as well as a regexp pattern the value of the parameter must confirm to.
The parameter is also required.
...
parameters:
- name: token
in: formData
description: oauth2 token
type: string
format: byte
pattern: "[A-Za-z0-9]*"
minLength: 5
maxLength: 100
required: true
...
Let's take another example:
...
get:
parameters:
- name: state
in: query
description: Any application state to be forwarded back to the frontend
type: string
minLength: 1
maxLength: 110
required: false
...
The state
parameter is of type string, is not required and has no default value.
It is also only allowed to have a state of length between 1 and 110, otherwise it won't pass validation.
For the demo purposes, let's change it's type to integer
and make it required.
As the parameter is required now, the default
value cannot be present. The maxLength
and maxLength
validations
are not allowed for integer parameters, therefore let's replace them with minimum
and maximum
values:
...
get:
parameters:
- name: state
in: query
description: Any application state to be forwarded back to the frontend
type: integer
format: int32
required: true
minimum: 2000
maximum: 2100
...
As we just changed the parameter type, refreshing Swagger UI will, in addition to generating validations
for that parameter type, also force a regeneration of the model consistent with the validation.
That's nice, but note that it will break the current implementation of the controller class, as the
implementation of the postAction
expects state
to be of type String
.
Let's change the implementation. The second parameter state
is no longer
of type Option[String]
but of type Int
. We change the implementation to take this fact into the account:
...
val tokenGet = tokenGetAction { input: (String, String, String, Int) =>
val (redirect_uri, scope, response_type, state) = input
// ----- Start of unmanaged code area for action TokenService.tokenGet
val statePart = s"""state=$state"""
...
}
Refreshing Swagger UI and trying out a couple of integer values for state
shows that the service
now excepts value within the range [2000..2100]
, but returns a descriptive error when outside. I.e.
[
{
"messages": [
"error.max"
],
"args": [
2100
]
}
]
Having an API definition as the single source of truth in your codebase—with formal type specification of the in- and output values, including their constraints—provides for a powerful feature when it comes to testing. The Play-Swagger plugin automates the creation of test data generators that can drive property checks directly from the API specification. Play-Swagger derives data generators and unit tests directly from your Swagger API specification.
Property-based testing using generator-driven property checks is a cool way to test the validity of your application according to the rules or properties that apply to your application. Properties, in this sense, are high-level specifications that should always hold for a range of data values. The idea is to generate a range of data values for your data types and let (also generated) tests assert that the properties of these data types hold. A Swagger API definition contains formal type definitions and constraints for all data values, and the Play-Swagger plugin maps these types on managed Scala source code that represents the data types, so it is also possible to map these API definitions on test data generators that provide a range of data values for these types. The plugin does exactly that: It creates managed test data generators and unit tests that assert whether your application still complies to your specification. It does so in a single-source-of-truth manner, taking the Swagger API definition as the source.
We employ the ScalaTest property-based testing
functionality as the framework to generate the data values, and map the data types of our API definition on
the test data generators that are created by the plugin. ScalaTest provides
org.scalacheck.Gen
and org.scalacheck.Arbitrary
objects with utility methods that help generate a range of
(possibly arbitrary) data values for common Scala types and primitives. The Play-Swagger plugin uses these
methods to create test data generators specific for the data types of our API definition. When necessary,
it composes generators from primitive types into generators for complex types, so that you end up with a
set of generators that provide test data for your complete API.
As an example, let's take the API definition for the simple pet store—trimmed down to the parts defining parameter types, and (for brevity) omitting any non-data definitions and error definitions:
paths:
/pets:
get:
parameters:
- name: limit
in: query
required: false
type: integer
format: int32
responses:
default:
description: error payload
post:
parameters:
- name: pet
in: body
required: true
schema:
$ref: '#/definitions/newPet'
responses:
default:
description: error payload
/pets/{id}:
get:
parameters:
- name: id
in: path
required: true
type: integer
format: int64
responses:
default:
description: error payload
delete:
parameters:
- name: id
in: path
required: true
type: integer
format: int64
responses:
default:
description: error payload
definitions:
pet:
required:
- id
- name
properties:
id:
type: integer
format: int64
name:
type: string
tag:
type: string
newPet:
required:
- name
properties:
id:
type: integer
format: int64
name:
type: string
tag:
type: string
The get
method on path /pets
takes an optional limit
parameter of common type integer
.
The post
method takes a newPet
body parameter comprising of the primitive attributes id
, name
and tag
,
subsequently of common types long
and string
(twice). Of these, only the name
attribute is mandatory.
The get
method on the path /pets/{id}
takes the path parameter id
of common type long
and returns
an array of pet
s consisting of the same attributes and primitive types as a newPet
- but this time
with both name
and id
being mandatory. This specification maps to the following managed Scala domain model code:
package example
package object yaml {
import de.zalando.play.controllers.PlayPathBindables
type PetsIdDeleteResponsesDefault = Null
type NewPetTag = Option[String]
type PetsIdDeleteId = Long
type PetsGetLimit = Option[Int]
type NewPetId = Option[Long]
case class Pet(id: Long, name: String, tag: NewPetTag)
case class NewPet(name: String, id: NewPetId, tag: NewPetTag)
implicit val bindable_OptionIntQuery = PlayPathBindables.createOptionQueryBindable[Int]
}
We want to have test data generators that generate an arbitrary range of values for the model
code shown above - composed from primitive, and sometimes optional, data definitions.
The Play-Swagger plugin does this by generating two Scala objects: one for the Swagger API definition,
and one for the API path parts. Each object contains generator factory methods for the defined data types,
prefixed by create
, which returns a generator function. A generator function takes a given integer count
and returns a generated amount of test data for the data type it was created for.
Data types are composed from primitive types, Scala optional types, and possibly more complex types.
Test data values for the primitive types are generated arbitrarily, employing the ScalaCheck
org.scalacheck.Arbitrary.arbitrary[T]
method (the type parameter, replaced with Scala's primitive type,
on which the Swagger common type is mapped).
In the code shown below, starting with primitive leaf data values, the pet
parameter's attribute id
of common type long
is arbitrarily generated from a scala.Long
. Note that the id
attribute is optional,
though, for the newPet
definition. As with the generated model, we created a NewPetIdGenerator
value that
takes an arbitrarily generated scala.Long
id value and generates an option value from it, employing the
ScalaCheck org.scalacheck.Gen.option[T]
. This generator will generate test data values comprising of None
and Some
arbitrarily id value. It's probably best to let the Scala generator code speak for itself.
Note how it composes according to the same structure as the Scala model code.
package example.yaml
import org.scalacheck.Gen
import org.scalacheck.Arbitrary
import play.api.libs.json.scalacheck.JsValueGenerators
import Arbitrary._
object Generators extends JsValueGenerators {
def createNullGenerator = _generate(NullGenerator)
def createNewPetTagGenerator = _generate(NewPetTagGenerator)
def createLongGenerator = _generate(LongGenerator)
def createPetsGetLimitGenerator = _generate(PetsGetLimitGenerator)
def createNewPetIdGenerator = _generate(NewPetIdGenerator)
def createPetGenerator = _generate(PetGenerator)
def createNewPetGenerator = _generate(NewPetGenerator)
def NullGenerator = arbitrary[Null]
def NewPetTagGenerator = Gen.option(arbitrary[String])
def LongGenerator = arbitrary[Long]
def PetsGetLimitGenerator = Gen.option(arbitrary[Int])
def NewPetIdGenerator = Gen.option(arbitrary[Long])
def PetGenerator = for {
id <- arbitrary[Long]
name <- arbitrary[String]
tag <- NewPetTagGenerator
} yield Pet(id, name, tag)
def NewPetGenerator = for {
name <- arbitrary[String]
id <- NewPetIdGenerator
tag <- NewPetTagGenerator
} yield NewPet(name, id, tag)
def _generate[T](gen: Gen[T]) = (count: Int) => for (i <- 1 to count) yield gen.sample
}
A PetGenerator
and NewPetGenerator
are created and implemented by the plugin as a for comprehension
that generates data values for each attribute, yielding an instance of a test pet. Other generators follow
the same pattern but, if necessary, delegate to different child generators. From this we acquire a set of
test data generators to implement our property-based testing.
Running the test is as simple as running a test set from sbt. Just type test
from your sbt
prompt.
To build a plugin, do the following:
- Clone the repository to your local filesystem
- Run
sbt +publishLocal
in the Play-Swagger directory. This will publish the plugin into your local ivy repository
To use the plugin in a plain Play project:
- Create a new Play-Swagger project using activator template, for example:
activator new hello-world play-swagger-service
- Take a look at the
project/plugins.sbt
of the generated project and add required plugins and resolvers to theproject/plugins.sbt
of your Play project - Do the same for
build.sbt
- Put a Swagger specification with a
.yaml
or.json
extension into theconf
directory - Add a specification link (
->
) to the play's routes file
Ths Play-Swagger plugin has a three-tier architecture:
- specification - this tier is responsible for finding and parsing a specification and converting it into the raw AST format
- normalisation - this tier performs a couple of optimisations on the AST including type deduplication, flattening and parameter dereferencing
- generation - a final step including transformation of the AST into the source-code related data and generation of source code from it
The separation of the specification and generation tiers allows for plugging in different specification standards and generating source code for different frameworks.
There are a couple of sub-projects:
swagger-model
- A standalone Scala Swagger model and a Jackson parser for it. Can be used by another projectsapi
- This is the project that's automatically added to the runtime classpath of any projects that use this plugin.swagger-parser
- A converter of the Swagger model to the internal AST of the pluginapi-first-core
- This is a core of the plugin with minimal functionality. It includes defining an AST structure and some transformations on AST.play-scala-generator
- The standalone generator for transforming an AST into the skeleton of Play-Scala application.plugin
- A coupble of sbt plugins, one for each tier:ApiFirstSwaggerParser
- a plugin wrapping Swagger parsing partApiFirstCore
- a wrapper for AST-related functionalityApiFirstPlayScalaCodeGenerator
- a wrapper for the Play-Scala generator
Because of the modular plugin architecture, all modules must be enabled separatly in sbt's build.sbt. It is also necessary to configure which parser(s) must be used by the plugin, like that:
lazy val root = (project in file(".")).enablePlugins(PlayScala, ApiFirstCore, ApiFirstPlayScalaCodeGenerator, ApiFirstSwaggerParser)
apiFirstParsers := Seq(ApiFirstSwaggerParser.swaggerSpec2Ast.value).flatten
Please take a look at activator template's configuration for complete example.
The PlayScala generator supports custom templates. In order to override default template for some of the components, please provide your custom template named in accordance to the following list:
* `play_scala_test.mustache` - for unit tests
* `play_validation.mustache` - for validators
* `generators.mustache` - for test data generators
* `model.mustache` - for model classes and query and path bindables
* `play_scala_controller_base.mustache` - for play controller bases
* `play_scala_controller_security.mustache` - for security adapters used by controller bases
* `play_scala_form_parser.mustache` - for form parsers used by the controller bases
* `play_scala_controller.mustache` - for play controller skeletons supposed to be augmented by the programmer
* `play_scala_response_writers.mustache` - for custom serializers to be augmented by the programmer
* `play_scala_security_extractors.mustache` - for custom security extractors to be augmented by the programmer
Please be aware that generated artifacts need to preserve some specific shape in order to be compiled together without errors.
The location where custom templates reside needs to be configured by overriding the plugin setting playScalaCustomTemplateLocation
.
For example following configuration will set this place to be conf/templates
folder of the project:
playScalaCustomTemplateLocation := Some(((resourceDirectory in Compile) / "templates").value)
sbt doesn't allow sub-projects to depend on each other as sbt plugins. To test an sbt plugin, you need a separate
project. This project is swagger-tester
. To test your changes as you're developing the plugin, cd into this
directory, and run sbt. This project uses an sbt ProjectRef
to the sbt plugin, which means you don't need to
publishLocal
the plugin after each change. Just run reload
in the sbt console, and it will pick up your changes.
The play-swagger plugin provides a couple of commands useful for development:
apiFirstPrintDenotations
- outputs a common names of different parts of the AST as they are intended to be used in generated Scala codeapiFirstPrintRawAstTypes
- outputs all type definitions as they read from the specification before type optimisationsapiFirstPrintRawAstParameters
- outputs all parameters definitions before type optimisationsapiFirstPrintFlatAstTypes
- outputs type definitions after type optimisationsapiFirstPrintFlatAstParameters
- outputs parameter definitions after type optimisations
We're using the sbt scripted framework for testing. You can find the tests in plugin/src/sbt-test
, and run them
by running scripted
in the sbt console.
There are some quality checks embedded into the build script:
- the source code is (re)formatted using scalariform each time it is compiled (currently deactivated).
scalastyle
sbt command shall be used to perform code style checks before putting changes into the repository.lint:compile
sbt command shall be used to perform static code analysis before putting changes into the repository.- code coverage for api and compiler modules can be executed by issuing
sbt clean coverage test
command for these projects. Coverage statistics can be generated usingcoverageReport
sbt command.