Awesome
What is typegql
?
typegql is set of decorators allowing creating GraphQL APIs quickly and in type-safe way.
Examples:
- Basic Express example
- Typeorm integration example
- Forward resolution - eg. query only needed db fields
- Nested mutations or queries
- Custom decorators / Higher order decorators
- Serverless eg. AWS Lambda
- Merge schemas
Basic example
Example below is able to resolve such query
query {
hello(name: "Bob") # will resolve to 'Hello, Bob!'
}
import { compileSchema, SchemaRoot, Query } from 'typegql';
@SchemaRoot()
class SuperSchema {
@Query()
hello(name: string): string {
return `Hello, ${name}!`;
}
}
const compiledSchema = compileSchema({ roots: [SuperSchema] });
compiledSchema
is regular executable schema compatible with graphql-js
library.
To use it with express
, you'd have to simply:
import * as express from 'express';
import * as graphqlHTTP from 'express-graphql';
const app = express();
app.use(
'/graphql',
graphqlHTTP({
schema: compiledSchema,
graphiql: true,
}),
);
app.listen(3000, () => console.log('Graphql API ready on http://localhost:3000/graphql'));
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.
Until 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
- We want to be explicit about if some
number
type isFloat
orInt
(GraphQLFloat
orGraphQLInt
) etc - 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 Asynchronously
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);
}
}
Before 1.0.0
Before version 1.0.0
consider APIs of typegql
to be subject to change. We encourage you to try this library out and provide us feedback so we can polish it to be as usable and efficent as possible.