Written by Alexander Nnakwue✏️
Introduction
TypeScript, a typed superset of JavaScript, comes with design features that aim to solve the many pain points of writing applications in JavaScript. With its numerous feature sets and functionalities, including interfaces, generics, optional type-checking, and type inference, it shines majorly when it comes to developer productivity.
With the latest features from ES6, including decorators, async/await, etc., it’s backwards-compatible, with a few edge cases. It compiles down to plain JavaScript and is therefore a great target for older environments.
On the other hand, GraphQL, as we know, is a query language for APIs. Using its type system to describe data fields, it aids in fetching the exact data we queried for without over-fetching or under-fetching. Also, it can greatly help in the area of API versioning. To learn more about the benefits of GraphQL, please take a peek at its awesome documentation.
Prerequisites
In order to follow along with this tutorial, it would be best to have a basic or foundational knowledge of TypeScript and GraphQL. To run our code, it is advisable to have Node.js installed on your machine. Instructions to do so are available in the documentation.
Also, you should have TypeScript installed globally on your machine. To do so, you can run the following command on your terminal or command prompt using npm
or yarn
. Below, we are using npm
:
npm install -g typescript
Note : This command installs the latest TypeScript compiler on our system path, useful when compiling and running our code. The compiler known as
tsc
takes a TypeScript file ending with the.ts
extension and outputs an equivalent JavaScript file, with the.js
extension. Not to worry — as we proceed, we will be learning more about this command.
Introducing TypeGraphQL and bootstrapping our application
In this tutorial, we are going to learn how to integrate TypeScript with GraphQL using the TypeGraphQL library by building an API.
TypeGraphQL makes developing GraphQL APIs in Node an awesome experience by automatically creating GraphQL schema definitions from TypeScript classes with decorators. Decorators (and reflection) were introduced to avoid the need for schema definition files and interfaces describing these schemas.
More details about the library’s motivation can be found in this section of the documentation. Note that we can write custom decorators to suit our specific needs based on a project’s requirements. However, for this tutorial, the provided decorators for TypeGraphQL would suffice.
Without further ado, let us get to the meat of our learning. First of all, we can go ahead and create a new directory and give it any name we want. We can then initialize a new package.json
file with the npm init
command. After we are done installing all of our project’s dependencies, our package.json
file should look like this:
{
"name": "typscript-graphql-logrocket-tutorial",
"version": "1.0.0",
"description": "A typscript and graphql Tutorial",
"main": "server.js",
"scripts": {
"start": "npm run serve",
"serve": "node dist/server.js",
"watch-node": "nodemon dist/server.js",
"build-ts": "tsc",
"watch-ts": "tsc -w",
"test": "echo \"Error: no test specified\" && exit 1"
},
"keywords": [
"Tyscript",
"Graphql",
"node",
"javascript"
],
"author": "Alexander Nnakwue",
"license": "MIT",
"devDependencies": {
"@types/express": "^4.17.3",
"@types/graphql": "^14.5.0",
"@types/node": "^13.9.0",
"nodemon": "^2.0.2",
"ts-node": "^8.6.2",
"typescript": "^3.8.3"
},
"dependencies": {
"@typegoose/typegoose": "^6.4.0",
"apollo-server-express": "^2.11.0",
"class-validator": "^0.11.0",
"express": "^4.17.1",
"graphql": "^14.6.0",
"reflect-metadata": "^0.1.13",
"type-graphql": "^0.17.6"
}
}
Bootstrapping our application
Installation and setup
Before we proceed, we need to install all the required dependencies for our project. We can go ahead and run the following command in our terminal:
npm install type-graphql reflect-metadata graphql express class-validator apollo-server-express mongoose @typegoose/typegoose --save
Like we mentioned earlier, type-graphql
is the framework we will be using for building our API with TypeScript and GraphQL. It comes with a lot of advanced features, like automatic validation, dependency injection, authorization, inheritance, and so on. The library also allows us to define our GraphQL schema types and interfaces using TypeScript classes and decorators.
Discussion
From the dependencies installed above, reflect-metadata
adds a polyfill for the experimental Metadata API support for TypeScript.
Currently, TypeScript includes experimental support for emitting certain types of metadata for declarations that have decorators. This means we must enable support for this library in our tsConfig.json
file, as we will see later. More details about the reflect-metadata package can be found here.
The apollo-server-express
library is the Express and Connect integration of a GraphQL server. Here, we will be using this library to bootstrap a simple GraphQL server with Express. It depends on express
to work. More details can be found here.
The class-validator
library allows the use of decorator- and non-decorator-based validation with TypeGraphQL. We will be using it here to validate our schema fields.
The mongoose
package, as we know, is the MongoDB object data mapper (ODM), while the @types/mongoose
package provide TypScript definitions for it. Lastly, @typegoose/typegoose
allows us to define Mongoose models using TypeScript classes. More details can be found here.
We should also go ahead and install these TypeScript definitions types as dev dependencies: types/express
, @types/graphql
, and @types/node
. Additionally, we should add typescript
, ts-node
(TypeScript execution environment for Node.js), and nodemon
as dev dependencies. Run the following:
npm install types/express @types/graphql @types/node typescript ts-node @types/mongoose nodemon --save-dev
After we complete the above, we then need to set up our tsConfig.json
file, which provides instructions on how our TypeScript project should be configured. For TypeGraphQL, the required TS configuration is shown here.
In this file, we can specify compiler options to compile our .ts
files as well as the root files for our project. So, whenever we run the tsc
command (npm run build
, in our case, based on our package.json
file setup), the compiler will check this file first for special instructions and then proceed with compilation based on those instructions.
To create one, we can run the tsc --init
command. This command creates a new config file with a lot of defaults and comments, which has been stripped here for brevity. Here is how our tsConfig
file looks:
{
"compilerOptions": {
"module": "commonjs",
"esModuleInterop": true,
"allowSyntheticDefaultImports": true,
"target": "es2016", // or newer if your node.js version supports this
"strictNullChecks": true,
"strictFunctionTypes": true,
"noImplicitThis": true,
"noUnusedLocals": true,
"noUnusedParameters": true,
"noImplicitReturns": true,
"skipLibCheck": true,
"declaration": false,
"noFallthroughCasesInSwitch": true,
"composite": false,
"noImplicitAny": true,
"moduleResolution": "node",
"lib": ["dom", "es2016", "esnext.asynciterable"],
"sourceMap": true,
"emitDecoratorMetadata": true,
"strict": false,
"experimentalDecorators": true,
"outDir": "dist",
"rootDir": "app",
"baseUrl": ".",
"paths": {
"*": [
"node_modules/*",
"app/types/*"
]
}
},
"include": [
"app/**/*", "./app/**/*.ts", "./app/**/*.tsx"
]
}
Note : Detailed interpretations and meanings of these configuration options can be found in the documentation here.
Setting up our GraphQL server
Now we can go ahead and set up an Apollo server with the apollo-server-express
package we installed earlier. But before we do so, we’ll create a new app directory in our project directory. The contents of the directory should look like this:
In our server.js
file, we are going to set up our Apollo server with Express. The contents of the file, with all the imports, should look like this:
import { ApolloServer } from "apollo-server-express";
import Express from "express";
import "reflect-metadata";
import { buildSchema } from "type-graphql";
import { connect } from "mongoose";
// resolvers
import {UserResolver} from "./resolvers/User";
import {ProductResolver} from "./resolvers/Product";
import {CategoriesResolver} from "./resolvers/Categories";
import {CartResolver} from "./resolvers/Cart";
import {OrderResolver} from "./resolvers/Order";
const main = async () => {
const schema = await buildSchema({
resolvers: [CategoriesResolver, ProductResolver, UserResolver, CartResolver, OrderResolver ],
emitSchemaFile: true,
validate: false,
});
// create mongoose connection
const mongoose = await connect('mongodb://localhost:27017/test', {useNewUrlParser: true});
await mongoose.connection;
const server = new ApolloServer({schema});
const app = Express();
server.applyMiddleware({app});
app.listen({ port: 3333 }, () =>
console.log(`🚀 Server ready and listening at ==> http://localhost:3333${server.graphqlPath}`))
};
main().catch((error)=>{
console.log(error, 'error');
})
Discussion
Here we are importing the dependencies needed to set up our server.
Earlier, we talked about the apollo-server-express
package, mongoose
for our database connection, and the reflect-metadata
package. The buildSchema
package from TypeGraphQL allows us to use this method to build our schema from TypeGraphQL’s definition. This is the usual signature of the buildSchema
method:
const schema = await buildSchema({
resolvers: [Resolver],
});
As we can see above, we are importing our resolvers from the app/resolver
folder and passing them into the array of the resolvers field
inside the function definition. The emitSchemaFile
field allows us to spit out our GraphQL schema into a schema.gql
file when we run the npm run build-tsc
command. The content of the file looks like this:
# -----------------------------------------------
# !!! THIS FILE WAS GENERATED BY TYPE-GRAPHQL !!!
# !!! DO NOT MODIFY THIS FILE BY YOURSELF !!!
# -----------------------------------------------
"""The Cart model"""
type Cart {
id: ID!
products: String!
product: Product!
}
input CartInput {
products: ID!
}
"""The Categories model"""
type Categories {
id: ID!
name: String!
description: String!
}
input CategoriesInput {
name: String!
description: String!
}
"""
The javascript `Date` as string. Type represents date and time as the ISO Date string.
"""
scalar DateTime
type Mutation {
createUser(data: UserInput!): User!
deleteUser(id: String!): Boolean!
createProduct(data: ProductInput!): Product!
deleteProduct(id: String!): Boolean!
createCategory(data: CategoriesInput!): Categories!
deleteCategory(id: String!): Boolean!
createCart(data: CartInput!): Cart!
deleteCart(id: String!): Boolean!
createOrder(data: OrderInput!): Order!
deleteOrder(id: String!): Boolean!
}
"""The Order model"""
type Order {
id: ID!
user_id: String!
payde: Boolean!
date: DateTime!
products: Product!
}
input OrderInput {
user_id: String!
payde: Boolean!
date: DateTime!
}
"""The Product model"""
type Product {
id: ID!
name: String!
description: String!
color: String!
stock: Int!
price: Int!
category_id: String!
category: Categories!
}
input ProductInput {
name: String!
description: String!
color: String!
stock: Float!
price: Float!
category_id: String!
}
type Query {
returnSingleUser(id: String!): User!
returnAllUsers: [User!]!
returnSingleProduct(id: String!): Order!
returnAllProduct: [Product!]!
returnSingleCategory(id: String!): Categories!
returnAllCategories: [Categories!]!
returnSingleCart(id: String!): Cart!
returnAllCart: [Cart!]!
returnAllOrder: [Order!]!
}
"""The User model"""
type User {
id: ID!
username: String!
email: String!
cart_id: String!
cart: Cart!
}
input UserInput {
username: String!
email: String!
cart_id: ID!
}
Note : The content of this file is based on what we have in the schema fields for our different database entities, which are contained in the
entities
folder. In the next section, we are going to be looking at the contents of these files.
Creating our database schema fields/entities with TypeGraphQL
As we can see in the app folder above, we have a folder called entities
. Inside that folder, we have files that represents all the database entities we need. The contents of these files are shown below:
Categories.ts
import { ObjectType, Field, ID } from "type-graphql";
import { prop as Property, getModelForClass } from "@typegoose/typegoose";
@ObjectType({ description: "The Categories model" })
export class Categories {
@Field(()=> ID)
id: string;
@Field()
@Property()
name: String;
@Field()
@Property()
description: String;
}
export const CategoriesModel = getModelForClass(Categories);
Product.ts
import { ObjectType, Field, ID, Int } from "type-graphql";
import { prop as Property, getModelForClass } from "@typegoose/typegoose";
import { Ref } from "../types";
import {Categories} from "./Categories";
import { __Type } from "graphql";
@ObjectType({ description: "The Product model" })
export class Product {
@Field(() => ID)
id: String;
@Field()
@Property()
name: String;
@Field()
@Property()
description: String;
@Field()
@Property()
color: String;
@Field(_type => Int)
@Property()
stock: number;
@Field(_type => Int)
@Property()
price: number;
@Field(_type => String)
@Property({ref: Categories})
category_id: Ref<Categories>;
_doc: any;
}
export const ProductModel = getModelForClass(Product);
Cart.ts
import { ObjectType, Field, ID} from "type-graphql";
import { prop as Property, getModelForClass } from "@typegoose/typegoose";
import { Ref } from "../types";
import {Product} from "./Product";
@ObjectType({ description: "The Cart model" })
export class Cart {
@Field(() => ID)
id: string;
@Field(_type => String)
@Property({ ref: Product, required: true })
products: Ref<Product>;
_doc: any;
}
export const CartModel = getModelForClass(Cart);
Users.ts
import { ObjectType, Field, ID } from "type-graphql";
import { prop as Property, getModelForClass } from "@typegoose/typegoose";
import { Ref } from "../types";
import {Cart} from "./Cart";
@ObjectType({ description: "The User model" })
export class User {
@Field(() => ID)
id: number;
@Field()
@Property({ required: true })
username: String;
@Field()
@Property({ required: true })
email: String;
@Field(_type => String)
@Property({ ref: Cart, required: true})
cart_id: Ref<Cart>
}
export const UserModel = getModelForClass(User);
Order.ts
import { ObjectType, Field, ID } from "type-graphql";
import { prop as Property, getModelForClass} from "@typegoose/typegoose";
import { Ref } from "../types";
import {Product} from "./Product";
@ObjectType({ description: "The Order model" })
export class Order {
@Field(()=> ID)
id: String;
@Field()
@Property({ nullable: true })
user_id: String;
@Field()
@Property({ required: true })
payde: Boolean;
@Field()
@Property({ default: new Date(), required: true, nullable: true })
date: Date;
// @Field(_type => Product)
@Property({ ref: Product, required: true })
products: Ref<Product>
_doc: any;
}
export const OrderModel = getModelForClass(Order);
Discussion
As we can see in the files above, we are importing the ObjectType
, Field
, ID
, and Int
from type-graphql
. The @Field
decorator is used to declare which class properties should be mapped to the GraphQL fields. It is also used to collect metadata from the TypeScript reflection system.
The @ObjectType
decorator marks the class as the type
known as GraphQLObjectType from graphql-js
. Int
and ID
are aliases for three basic GraphQL scalars. More details can be found here.
Also, from the @typegoose/typegoose
package, we are importing both the Property
decorator and the getModelForClass
method. The Property
decorator is used for setting properties in a class, without which is just a type and will not be in the final model. Details can be found here.
The getModelForClass
method is used to get a model for a given class. More details can be found here.
Lastly, we are importing Refs
from the types.ts
file in the app folder. The content of the file is shown below:
import { ObjectId } from "mongodb";
export type Ref<T> = T | ObjectId;
Here we are importing [ObjectId](https://docs.mongodb.com/manual/reference/method/ObjectId/)
from MongoDB.
Note : The type
Ref<T>
is the type used for References. It also comes with typeguards for validating these references. More details can be found here.
Resolvers and input types for our entities
Here, we can go ahead and create a new folder called resolver
. This folder contains another folder called types
, which contains the types for our different resolver inputs. The input files are shown below:
categories-input.ts
import { InputType, Field } from "type-graphql";
import { Length } from "class-validator";
import { Categories } from "../../entities/Categories";
@InputType()
export class CategoriesInput implements Partial<Categories> {
@Field()
name: string;
@Field()
@Length(1, 255)
description: String;
}
categories-input.ts
import { InputType, Field } from "type-graphql";
import { Length } from "class-validator";
import { Product } from "../../entities/Product";
import { ObjectId } from "mongodb";
@InputType()
export class ProductInput implements Partial<Product> {
@Field()
name: String;
@Field()
@Length(1, 255)
description: String;
@Field()
color: String;
@Field()
stock: number;
@Field()
price: number;
@Field(()=> String)
category_id: ObjectId;
}
cart-input.ts
import { InputType, Field, ID } from "type-graphql";
import { Cart } from "../../entities/Cart";
import { ObjectId } from "mongodb";
@InputType()
export class CartInput implements Partial<Cart> {
@Field(()=> ID)
products?: ObjectId;
}
user-input.ts
import { InputType, Field, ID } from "type-graphql";
import { Length, IsEmail } from "class-validator";
import { User } from "../../entities/User";
import { ObjectId } from "mongodb";
@InputType()
export class UserInput implements Partial<User> {
@Field()
@Length(1, 255)
username: String;
@Field()
@IsEmail()
email: String;
@Field(()=> ID)
cart_id: ObjectId;
}
order-input.ts
import { InputType, Field } from "type-graphql";
import { Order } from "../../entities/Order";
@InputType()
export class OrderInput implements Partial<Order> {
@Field()
user_id: String;
@Field()
payde: Boolean;
@Field()
date: Date;
}
Discussion
As we can see in the input files above, we are importing the InputType
and Field
decorators from type-graphql
. The inputType
decorator is used by TypeGraphQL to automatically validate our inputs and arguments based on their definitions.
We can also see we are using the class-validator
library for field-level validation. Note that TypeGraphQL has built-in support for argument and input validation based off this library.
Moving on, let’s examine the resolvers for these inputs and entities. For the category resolver in the categories.ts
file, the content is shown below:
import { Resolver, Mutation, Arg, Query } from "type-graphql";
import { Categories, CategoriesModel } from "../entities/Categories";
import { CategoriesInput } from "./types/category-input"
@Resolver()
export class CategoriesResolver {
@Query(_returns => Categories, { nullable: false})
async returnSingleCategory(@Arg("id") id: string){
return await CategoriesModel.findById({_id:id});
};
@Query(() => [Categories])
async returnAllCategories(){
return await CategoriesModel.find();
};
@Mutation(() => Categories)
async createCategory(@Arg("data"){name,description}: CategoriesInput): Promise<Categories> {
const category = (await CategoriesModel.create({
name,
description
})).save();
return category;
};
@Mutation(() => Boolean)
async deleteCategory(@Arg("id") id: string) {
await CategoriesModel.deleteOne({id});
return true;
}
}
This resolver performs basic CRUD operations using the Resolver
, Mutation
, Arg
, and Query
decorators from type-graphql
. We can also see that we are importing the input types to be used for the mutation field.
For the product resolver file, we have:
import { Resolver, Mutation, Arg, Query, FieldResolver, Root } from "type-graphql";
import { Product, ProductModel } from "../entities/Product";
import { ProductInput } from "./types/product-input"
import { Categories, CategoriesModel } from "../entities/Categories";
@Resolver(_of => Product)
export class ProductResolver {
@Query(_returns => Product, { nullable: false})
async returnSingleProduct(@Arg("id") id: string){
return await ProductModel.findById({_id:id});
};
@Query(() => [Product])
async returnAllProduct(){
return await ProductModel.find();
};
@Mutation(() => Product)
async createProduct(@Arg("data"){name,description, color, stock, price, category_id}: ProductInput): Promise<Product> {
const product = (await ProductModel.create({
name,
description,
color,
stock,
price,
category_id
})).save();
return product;
};
@Mutation(() => Boolean)
async deleteProduct(@Arg("id") id: string) {
await ProductModel.deleteOne({id});
return true;
}
@FieldResolver(_type => (Categories))
async category(@Root() product: Product): Promise<Categories> {
console.log(product, "product!")
return (await CategoriesModel.findById(product._doc.category_id))!;
}
}
Note : The product resolver above contains a field resolver decorator for relational entity data. In our case, the product schema has a
category-id
field for fetching details about a particular category, which we have to resolve by fetching that data from another node in our data graph.
To learn more about resolvers and how they work, check out the documentation for resolvers. More details about our other resolver files can be found in the GitHub repo here.
Running our application
To start our application, we first run npm run build-tsc
, which compiles our code, then npm start
, which starts up our server. Note that TypeScript catches any compile-time errors when we build our code with the compiler (.tsc
).
After we are done, we can navigate to the GraphQL playground at [http://localhost:3333/graphql
(http://localhost:3333/graphql) to test our API 🙂.
Let’s create a new category:
Let’s get a category by ID:
Awesome, right? More details on the capabilities of the API can be found when we click on the schema tab in the playground. The details are shown below:
type Cart {
id: ID!
products: String!
product: Product!
}
input CartInput {
products: ID!
}
type Categories {
id: ID!
name: String!
description: String!
}
input CategoriesInput {
name: String!
description: String!
}
scalar DateTime
type Mutation {
createUser(data: UserInput!): User!
deleteUser(id: String!): Boolean!
createProduct(data: ProductInput!): Product!
deleteProduct(id: String!): Boolean!
createCategory(data: CategoriesInput!): Categories!
deleteCategory(id: String!): Boolean!
createCart(data: CartInput!): Cart!
deleteCart(id: String!): Boolean!
createOrder(data: OrderInput!): Order!
deleteOrder(id: String!): Boolean!
}
type Order {
id: ID!
user_id: String!
payde: Boolean!
date: DateTime!
products: Product!
}
input OrderInput {
user_id: String!
payde: Boolean!
date: DateTime!
}
type Product {
id: ID!
name: String!
description: String!
color: String!
stock: Int!
price: Int!
category_id: String!
category: Categories!
}
input ProductInput {
name: String!
description: String!
color: String!
stock: Float!
price: Float!
category_id: String!
}
type Query {
returnSingleUser(id: String!): User!
returnAllUsers: [User!]!
returnSingleProduct(id: String!): Order!
returnAllProduct: [Product!]!
returnSingleCategory(id: String!): Categories!
returnAllCategories: [Categories!]!
returnSingleCart(id: String!): Cart!
returnAllCart: [Cart!]!
returnAllOrder: [Order!]!
}
type User {
id: ID!
username: String!
email: String!
cart_id: String!
cart: Cart!
}
input UserInput {
username: String!
email: String!
cart_id: ID!
}
To learn more, we can test the queries and the mutations in the schema tab shown above.
Conclusion
The main idea of TypeGraphQL is to create GraphQL types based on TypeScript classes. TypeScript makes writing class-based OOP code intuitive. It provides us with classes, interfaces, etc. out of the box, which then afford us the opportunity to properly structure our code in a reusable manner, making it easy to maintain and scale.
This has led to the creation of tools and libraries that make it easier and faster to write applications that meet these expectations. TypeScript greatly benefits our productivity and experience as engineers.
Combining both TypeScript features and the benefits of GraphQL with the TypeGraphQL library, we are able to build resilient and strongly typed APIs that fulfill our needs in terms of maintenance, technical debt down the line, and so on.
As a final note, it would be great to explore other advanced guides and features in the documentation to learn more about other aspects not covered in this tutorial. Also, it is an open-source project, which means you can have a peek at the source code as well 🙂.
Thanks for reading and reach out to me on my Twitter if you have any questions.
200's only ✅: Monitor failed and show GraphQL requests in production
While GraphQL has some features for debugging requests and responses, making sure GraphQL reliably serves resources to your production app is where things get tougher. If you’re interested in ensuring network requests to the backend or third party services are successful, try LogRocket.
LogRocket is like a DVR for web apps, recording literally everything that happens on your site. Instead of guessing why problems happen, you can aggregate and report on problematic GraphQL requests to quickly understand the root cause. In addition, you can track Apollo client state and inspect GraphQL queries' key-value pairs.
LogRocket instruments your app to record baseline performance timings such as page load time, time to first byte, slow network requests, and also logs Redux, NgRx, and Vuex actions/state. Start monitoring for free.
The post Integrating TypeScript with GraphQL appeared first on LogRocket Blog.
Top comments (1)
Great article and thank you for sharing, it would be great an article with the same content by following the clean Architecture principles.