Getting started
What is typegql
?
typegql is set of decorators allowing creating GraphQL APIs quickly and in type-safe way.
Creating very simple schema
Schema is main building block of any graphql
schema. It'll join all parts of our api together.
In typegql
to create schema, we need to pass class decorated with @Schema
to compileSchema
function
import { Schema, compileSchema} from 'typegql
@Schema()
class SuperSchema {
// fields implementation
}
const compiledSchema = compileSchema(SuperSchema);
compiledSchema
from example above is standard, regular graphql
schema.
Adding Query and Mutation fields
Any working schema requires at least one Query field. There are special decorators - @Query
and @Mutation
used to register root fields of schema.
Very simple fully working schema like
{
hello # will resolve to 'world'
}
Could be implemented as:
import { Schema, Query, compileSchema} from 'typegql
@Schema()
class SuperSchema {
@Query()
hello(): string {
return 'world'
}
}
const compiledSchema = compileSchema(SuperSchema);
Adding parameters
Let's add some customization to our schema:
{
hello(name: "Bob") # will resolve to 'Hello, Bob!'
}
With tiny change in our code:
import { Schema, Query, compileSchema} from 'typegql
@Schema()
class SuperSchema {
@Query()
hello(name: string): string {
return `Hello, ${name}!`;
}
}
const compiledSchema = compileSchema(SuperSchema);
Adding nested types
For now, our query field returned scalar (string). Let's return something more complex. Schema will look like:
mutation {
createProduct(name: "Chair", price: 99.99) {
name
price
isExpensive
}
}
Such query will have a bit more code and here it is:
import { Schema, Query, ObjectType, Field, Mutation, compileSchema} from 'typegql;
@ObjectType({ description: 'Simple product object type' })
class Product {
@Field()
name: string;
@Field()
price: number;
@Field()
isExpensive() {
return this.price > 50;
}
}
@Schema()
class SuperSchema {
@Mutation()
createProduct(name: string, price: number): Product {
const product = new Product();
product.name = name;
product.price = price;
return product;
}
}
const compiledSchema = compileSchema(SuperSchema);
Forcing field type.
Since now, typegql
was able to guess type of every field from typescript type definitions.
There are, however, some cases where we'd have to define them explicitly.
- We want to strictly tell if field is nullable or not
- Function we use returns type of
Promise<SomeType>
while field itself is typed asSomeType
- List (Array) type is used. (For now, typescript
Reflect
api is not able to guess type of single array item. This might change in the future)
Let's modify our Product
so it has additional categories
field that will return array of strings. For sake of readibility, I'll ommit all fields we've defined previously.
@ObjectType()
class Product {
@Field({ type: [String] }) // note we can use any native type like GraphQLString!
categories(): string[] {
return ['Tables', 'Furniture'];
}
}
We've added { type: [String] }
as @Field
options. Type can be anything that is resolvable to GraphQL
type
- Native JS scalars:
String
,Number
,Boolean
. - Any type that is already compiled to
graphql
eg.GraphQLFloat
or any type from external graphql library etc - Every class decorated with
@ObjectType
- One element array of any of above for list types eg.
[String]
or[GraphQLFloat]
Writing Asynchroniously
Every field function we write can be async
and return Promise
. Let's say, instead of hard-coding our categories, we want to fetch it from some external API:
@ObjectType()
class Product {
@Field({ type: [String] }) // note we can use any native type like GraphQLString!
async categories(): Promise<string[]> {
const categories = await api.fetchCategories();
return categories.map(cat => cat.name);
}
}
Adding to your project
Important! setup steps are simple, but required. Make sure to check setup section.