Union Type in GraphQL
In GraphQL, a union type is used to represent a type that can be one of several possible types. It allows a field to return different types of objects based on a condition. Union types are declared using the union
keyword in the schema definition language (SDL).
Here’s an example of how to define a union type in GraphQL:
union SearchResult = Book | Movie type Book { title: String author: String } type Movie { title: String director: String } type Query { search(query: String): [SearchResult] }
In the above example, the SearchResult
union type can represent either a Book
or a Movie
object. The search
query returns an array of SearchResult
objects, which can be of either type.
Here’s how you can query for a union type in GraphQL:
query { search(query: "GraphQL") { ... on Book { title author } ... on Movie { title director } } }
In the above query, we use the ... on
syntax to specify the fields we want to retrieve for each possible type of the SearchResult
union. Depending on the actual type of the returned object, the corresponding fields will be populated.
Related Article: Achieving Production-Ready GraphQL
Interface Type in GraphQL
In GraphQL, an interface type is used to define a common set of fields that can be implemented by multiple object types. It allows for polymorphism in the schema, where a field can return different types of objects that share a common interface. Interface types are declared using the interface
keyword in SDL.
Here’s an example of how to define an interface type in GraphQL:
interface Animal { name: String age: Int makeSound: String } type Dog implements Animal { name: String age: Int makeSound: String breed: String } type Cat implements Animal { name: String age: Int makeSound: String color: String } type Query { getAnimal(name: String): Animal }
In the above example, the Animal
interface defines a common set of fields that all implementing types (Dog
and Cat
) must have. The getAnimal
query returns an Animal
object, which can be of either type.
Here’s how you can query for an interface type in GraphQL:
query { getAnimal(name: "Fluffy") { name age makeSound ... on Dog { breed } ... on Cat { color } } }
In the above query, we use the ... on
syntax to specify the fields we want to retrieve for each possible type of the Animal
interface. Depending on the actual type of the returned object, the corresponding fields will be populated.
Schema Stitching in GraphQL
Schema stitching is a technique in GraphQL that allows you to combine multiple schemas into a single, unified schema. It enables you to create a schema that represents the entire API surface area of your application, even if the underlying data sources have separate schemas.
There are different approaches to schema stitching, but one common way is to use the mergeSchemas
function from the graphql-tools
library. This function takes an array of schemas and merges them together to create a new schema.
Here’s an example of how to use mergeSchemas
to stitch two schemas together:
const { mergeSchemas } = require('graphql-tools'); const { makeExecutableSchema } = require('graphql-tools'); // Schema 1 const typeDefs1 = ` type Query { hello: String } `; const resolvers1 = { Query: { hello: () => 'Hello from Schema 1', }, }; const schema1 = makeExecutableSchema({ typeDefs: typeDefs1, resolvers: resolvers1 }); // Schema 2 const typeDefs2 = ` type Query { goodbye: String } `; const resolvers2 = { Query: { goodbye: () => 'Goodbye from Schema 2', }, }; const schema2 = makeExecutableSchema({ typeDefs: typeDefs2, resolvers: resolvers2 }); // Stitched Schema const stitchedSchema = mergeSchemas({ schemas: [schema1, schema2] });
In the above example, we define two separate schemas (schema1
and schema2
) with their respective types and resolvers. Then, we use mergeSchemas
to combine them into a single stitchedSchema
.
Now, you can execute queries against the stitched schema and it will resolve fields from both underlying schemas:
query { hello goodbye }
The above query will return:
{ "data": { "hello": "Hello from Schema 1", "goodbye": "Goodbye from Schema 2" } }
Schema stitching allows you to modularize your GraphQL schemas and combine them as needed, making it easier to manage and extend your API surface area.
Enum Type in GraphQL
In GraphQL, an enum type is used to define a list of possible values for a field. It restricts the possible values that can be assigned to a field to a specific set of options. Enum types are declared using the enum
keyword in SDL.
Here’s an example of how to define an enum type in GraphQL:
enum DayOfWeek { MONDAY TUESDAY WEDNESDAY THURSDAY FRIDAY SATURDAY SUNDAY } type Event { name: String day: DayOfWeek } type Query { getEvents: [Event] }
In the above example, the DayOfWeek
enum type defines a set of possible values representing the days of the week. The Event
type has a day
field of type DayOfWeek
, which can only be assigned one of the defined enum values.
Here’s how you can query for an enum type in GraphQL:
query { getEvents { name day } }
The above query will return a list of events with their names and the corresponding day of the week.
Enums provide a way to enforce a specific set of options for a field, making the schema more explicit and self-documenting.
Related Article: AEM GraphQL: A Critical Component in Modern Programming
Input Type in GraphQL
In GraphQL, an input type is used to represent the input arguments of a field or the input types of mutations. They are similar to object types, but they cannot have fields that return object types. Input types are declared using the input
keyword in SDL.
Here’s an example of how to define an input type in GraphQL:
input UserInput { name: String age: Int email: String } type User { id: ID name: String age: Int email: String } type Mutation { createUser(input: UserInput): User }
In the above example, the UserInput
input type represents the input arguments for the createUser
mutation. It has fields for the name, age, and email of the user. The createUser
mutation takes a UserInput
as an argument and returns a User
object.
Here’s how you can use an input type in a mutation:
mutation { createUser(input: { name: "John Doe", age: 30, email: "john.doe@example.com" }) { id name age email } }
The above mutation creates a new user with the specified input and returns the created user object.
Input types allow you to pass complex data structures as arguments to fields or mutations, making it easier to define and handle input data in your GraphQL schema.
Schema Composition in GraphQL
Schema composition in GraphQL refers to the process of combining multiple GraphQL schemas together to create a single, unified schema. It allows you to modularize your schema definition and reuse existing schemas across different parts of your application.
There are different approaches to schema composition, but one common way is to use the mergeSchemas
function from the graphql-tools
library. This function takes an array of schemas and merges them together to create a new schema.
Here’s an example of how to use mergeSchemas
to compose two schemas together:
const { mergeSchemas } = require('graphql-tools'); const { makeExecutableSchema } = require('graphql-tools'); // Schema 1 const typeDefs1 = ` type Query { hello: String } `; const resolvers1 = { Query: { hello: () => 'Hello from Schema 1', }, }; const schema1 = makeExecutableSchema({ typeDefs: typeDefs1, resolvers: resolvers1 }); // Schema 2 const typeDefs2 = ` type Query { goodbye: String } `; const resolvers2 = { Query: { goodbye: () => 'Goodbye from Schema 2', }, }; const schema2 = makeExecutableSchema({ typeDefs: typeDefs2, resolvers: resolvers2 }); // Composed Schema const composedSchema = mergeSchemas({ schemas: [schema1, schema2] });
In the above example, we define two separate schemas (schema1
and schema2
) with their respective types and resolvers. Then, we use mergeSchemas
to combine them into a single composedSchema
.
Now, you can execute queries against the composed schema and it will resolve fields from both underlying schemas:
query { hello goodbye }
The above query will return:
{ "data": { "hello": "Hello from Schema 1", "goodbye": "Goodbye from Schema 2" } }
Schema composition allows you to build a unified GraphQL schema from modular components, making it easier to manage and extend your API surface area.
Query Type in GraphQL
In GraphQL, the query type is a special type that defines the entry point for all read operations. It represents the root of the query execution tree and provides the structure for retrieving data from the GraphQL server.
Here’s an example of how to define a query type in GraphQL:
type Query { hello: String user(id: ID!): User users: [User] } type User { id: ID name: String age: Int email: String }
In the above example, the Query
type defines three fields: hello
, user
, and users
. The hello
field returns a string, while the user
field takes an ID
argument and returns a User
object. The users
field returns an array of User
objects.
Here’s how you can query for a field on the query type in GraphQL:
query { hello user(id: "123") { id name age email } users { id name age email } }
The above query will return the value of the hello
field, the user with the specified id
, and the list of all users.
The query type serves as the starting point for retrieving data in a GraphQL schema and defines the available fields and their return types.
Related Article: Exploring Default Values in GraphQL Programming
Mutation Type in GraphQL
In GraphQL, the mutation type is a special type that defines the entry point for all write operations. It represents the root of the mutation execution tree and provides the structure for modifying data on the GraphQL server.
Here’s an example of how to define a mutation type in GraphQL:
type Mutation { createUser(input: CreateUserInput!): User updateUser(id: ID!, input: UpdateUserInput!): User deleteUser(id: ID!): Boolean } input CreateUserInput { name: String! age: Int! email: String! } input UpdateUserInput { name: String age: Int email: String } type User { id: ID name: String age: Int email: String }
In the above example, the Mutation
type defines three fields: createUser
, updateUser
, and deleteUser
. The createUser
field takes a CreateUserInput
as an argument and returns a User
object. The updateUser
field takes an ID
and an UpdateUserInput
as arguments and returns a User
object. The deleteUser
field takes an ID
as an argument and returns a boolean.
Here’s how you can execute a mutation in GraphQL:
mutation { createUser(input: { name: "John Doe", age: 30, email: "john.doe@example.com" }) { id name age email } updateUser(id: "123", input: { name: "Jane Doe" }) { id name age email } deleteUser(id: "123") }
The above mutation creates a new user, updates an existing user’s name, and deletes a user with the specified id
.
The mutation type allows you to define operations that modify data on the GraphQL server, providing a way to create, update, and delete resources.
Subscription Type in GraphQL
In GraphQL, the subscription type is a special type that defines the entry point for real-time updates. It represents the root of the subscription execution tree and provides the structure for subscribing to data changes on the GraphQL server.
Here’s an example of how to define a subscription type in GraphQL:
type Subscription { newMessage: Message } type Message { id: ID content: String createdAt: DateTime }
In the above example, the Subscription
type defines a single field newMessage
that returns a Message
object. Subscribers can listen to the newMessage
field to receive real-time updates whenever a new message is created.
Here’s how you can subscribe to a field on the subscription type in GraphQL:
subscription { newMessage { id content createdAt } }
The above subscription will establish a real-time connection with the GraphQL server and receive updates whenever a new message is created.
The subscription type allows you to define real-time capabilities in your GraphQL schema, enabling clients to receive real-time updates from the server.
Introspection in GraphQL
Introspection in GraphQL refers to the ability to query the schema itself to retrieve information about the available types, fields, and directives. It allows clients to dynamically discover the capabilities of a GraphQL server and interact with it in a more flexible way.
GraphQL provides a built-in __schema
field that can be used to perform introspection queries. This field returns a representation of the schema as a JSON object.
Here’s an example of how to perform an introspection query in GraphQL:
query { __schema { types { name kind description fields { name type { name kind } } } } }
The above query retrieves information about all the types in the schema, including their names, kinds, descriptions, and fields.
Related Article: Exploring Directus GraphQL
Additional Resources
– Defining a Union Type in GraphQL
– Advantages of Using Interfaces in GraphQL