decapi

What is decapi?

decapi is set of decorators allowing creating GraphQL APIs quickly and in type-safe way.

• Documentation

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 { Schema, Query, compileSchema } from 'decapi'

@Schema()
class SuperSchema {
  @Query()
  hello(name: string): string {
    return `Hello, ${name}!`
  }
}

const compiledSchema = compileSchema(SuperSchema)

compiledSchema is regular executable schema compatible with graphql-js library.

To use it with express, you'd have to simply:

import express from 'express'
import 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 'decapi'

@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, decapi 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 is Float or Int (GraphQLFloat or GraphQLInt) etc
• Function we use returns type of Promise<SomeType> while field itself is typed as SomeType
• 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, Date.
• 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 decapi 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.

Why forking?

I wanted to contribute to typegql and work on it together with @pie6k, but it soon became obvious that we both have something different in mind. Just to briefly summarise the differences:

• decapi has @DuplexObjectType and @DuplexField
• decapi has interfaces and mixins
• decapi can infer Date type
• InputObjectType argument passed ot your Field/Query is not just a plain object, but an instance of it's class
• decapi allows you to have an empty object type-you can populate it with fields at runtime