# graphql-crystal [![Build Status](https://api.travis-ci.org/ziprandom/graphql-crystal.svg)](https://travis-ci.org/ziprandom/graphql-crystal)


An implementation of [GraphQL](http://graphql.org/learn/) for the crystal programming language inspired by [graphql-ruby](https://github.com/rmosolgo/graphql-ruby) & [go-graphql](https://github.com/playlyfe/go-graphql) & [graphql-parser](https://github.com/graphql-dotnet/parser).

The library is in beta state atm. Should already be usable but expect to find bugs (and open issues about them). pull-requests, suggestions & criticism are very welcome!

Find the api docs [here](https://ziprandom.github.io/graphql-crystal/).

## Installation

Add this to your application's `shard.yml`:

```yaml
dependencies:
  graphql-crystal:
    github: ziprandom/graphql-crystal
```

## Usage

Complete source [here](example/simple_example.cr).

Given this simple domain model of users and posts

```cr
class User
  property name
  def initialize(@name : String); end
end

class Post
  property :title, :body, :author
  def initialize(@title : String, @body : String, @author : User); end
end

POSTS = [] of Post
USERS = [User.new("Alice"), User.new("Bob")]
```

We can instantiate a GraphQL schema directly from a graphql schema definition string

```cr
schema = GraphQL::Schema.from_schema(
  %{
    schema {
      query: QueryType,
      mutation: MutationType
    }

    type QueryType {
      posts: [PostType]
      users: [UserType]
      user(name: String!): UserType
    }

    type MutationType {
      post(post: PostInput) : PostType
    }

    input PostInput {
      author: String!
      title: String!
      body: String!
    }

    type UserType {
      name: String
      posts: [PostType]
    }

    type PostType {
      author: UserType
      title: String
      body: String
    }
  }
)
```

Then we create the backing types by including the ```GraphQL::ObjectType``` and defining the fields using the ```field``` macro

```cr
# reopening User and Post class
class User
  include GraphQL::ObjectType

  # defaults to the method of
  # the same name without block
  field :name

  field :posts do
    POSTS.select &.author.==(self)
  end
end

class Post
  include GraphQL::ObjectType
  field :title
  field :body
  field :author
end
```

Now we define the top level queries

```cr
# extend self when using a module or a class (not an instance)
# as the actual Object

module QueryType
  include GraphQL::ObjectType
  extend self

  field :users do
    USERS
  end

  field :user do |args|
    USERS.find( &.name.==(args["name"].as(String)) ) || raise "no user by that name"
  end

  field :posts do
    POSTS
  end
end

module MutationType
  include GraphQL::ObjectType
  extend self

  field :post do |args|

    user = USERS.find &.name.==(
      args["post"].as(Hash)["author"].as(String)
    )
    raise "author doesn't exist" unless user

    (
      POSTS << Post.new(
        args["post"].as(Hash)["title"].as(String),
        args["post"].as(Hash)["body"].as(String),
        user
      )
    ).last
  end
end
```

Finally set the top level Object Types on the schema

```cr
schema.query_resolver = QueryType
schema.mutation_resolver = MutationType
```

And we are ready to run some tests

```cr
describe "my graphql schema" do
  it "does queries" do
    schema.execute("{ users { name posts } }")
      .should eq ({
                    "data" => {
                      "users" => [
                        {
                          "name" => "Alice",
                          "posts" => [] of String
                        },
                        {
                          "name" => "Bob",
                          "posts" => [] of String
                        }
                      ]
                    }
                  })
  end

  it "does mutations" do

    mutation_string = %{
      mutation post($post: PostInput) {
        post(post: $post) {
          author {
            name
            posts { title }
          }
          title
          body
        }
      }
    }

    payload = {
      "post" => {
        "author" =>  "Alice",
        "title" => "the long and windy road",
        "body" => "that leads to your door"
      }
    }

    schema.execute(mutation_string, payload)
      .should eq ({
                    "data" => {
                      "post" => {
                        "title" => "the long and windy road",
                        "body" => "that leads to your door",
                        "author" => {
                          "name" => "Alice",
                          "posts" => [
                            {
                              "title" => "the long and windy road"
                            }
                          ]
                        }
                      }
                    }
                  })
  end
end
```

### Automatic Parsing of JSON Query & Mutation Variables into InputType Structs

To ease working with input parameters custom structs can be registered to be instantiated from the json params of query and mutation requests. Given the schema from above one can define a PostInput struct as follows

```cr
struct PostInput < GraphQL::Schema::InputType
  JSON.mapping(
    author: String,
    title: String,
    body: String
  )
end
```

and register it in the schema like:

```cr
schema.add_input_type("PostInput", PostInput)
```

Now the argument `post` which is expected to be a GraphQL InputType `PostInput` will be automatically parsed into a crystal `PostInput`-struct. Thus the code in the `post` mutation callback becomes more simple:

```cr
module MutationType
  include GraphQL::ObjectType
  extend self

  field :post do |args|
    input = args["post"].as(PostInput)

    author = USERS.find &.name.==(input.author) ||
           raise "author doesn't exist"

    POSTS << Post.new(input.title, input.body, author)
    POSTS.last
  end
end
```

### Custom Context Types

Custom context types can be used to pass additional information to the object type's field resolves. An example can be found [here](spec/support/custom_context_schema.cr).

A custom context type should inherit from `GraphQL::Schema::Context` and therefore be initialized with the served schema and a max_depth.

```cr
GraphQL::Schema::Schema#execute(query_string, query_arguments = nil, context = GraphQL::Schema::Context.new(self, max_depth))
```
accepts a context type as its third argument.

Field resolver callbacks on object types (including top level query & mutation types) get called with the context as their second argument:
```cr
field :users do |args, context|
  # casting to your custom type
  # is necessary here
  context = context.as(CustomContext)
  unless context.authenticated
    raise "Authentication Error"
  end
  ...
end
```

### Serving over HTTP

For an example of how to serve a schema over a webserver([kemal](https://github.com/kemalcr/kemal)) see [kemal-graphql-example](https://github.com/ziprandom/kemal-graphql-example).

## Development

run tests with

```
crystal spec
```

## Contributing

1. Fork it ( https://github.com/ziprandom/graphql-crystal/fork )
2. Create your feature branch (git checkout -b my-new-feature)
3. Commit your changes (git commit -am 'Add some feature')
4. Push to the branch (git push origin my-new-feature)
5. Create a new Pull Request

## Contributors

- [ziprandom](https://github.com/ziprandom)  - creator, maintainer