TypeScript and GraphQL: Building Strongly Typed APIs

TypeScript and GraphQL have become essential tools for modern web development, empowering developers to build reliable and scalable applications. TypeScript adds static typing to JavaScript, while GraphQL introduces a schema-based approach to managing APIs, ensuring that clients and servers communicate seamlessly. Together, they create a powerhouse for crafting strongly typed APIs, improving developer productivity and reducing errors.

This blog explores how TypeScript and GraphQL complement each other, the benefits of using them together, and best practices for building strongly-typed APIs.

Why TypeScript?

TypeScript is a superset of JavaScript that introduces static typing to the language. It provides:

1. Type Safety: Detects type-related errors during development rather than at runtime.
2. Enhanced IDE Support: Features like autocomplete, code navigation, and refactoring make development faster and less error-prone.
3. Scalability: Strong typing ensures that code remains maintainable as applications grow.

Why GraphQL?

GraphQL is a query language and runtime for APIs that allows clients to request only the data they need. Its key features include:

1. Strongly Typed Schema: GraphQL APIs are defined by schemas written in SDL (Schema Definition Language), ensuring the API is self-documenting and type-safe.
2. Flexibility: Clients can query multiple resources in a single request, optimising API calls.
3. Introspection: GraphQL APIs expose their schema, enabling tools like GraphiQL or Apollo Explorer to provide insights into available queries, mutations, and types.

The Building Blocks of Strongly Typed APIs

• Schema-First Design
  GraphQL’s schema-first approach allows developers to define the structure of the API, including the types of data it provides, in a declarative way. This schema acts as a contract between the client and the server, ensuring that both sides are aligned. In a TypeScript-based project, this schema becomes the foundation for generating TypeScript types.

1. Type Generation
   To eliminate manual synchronization between GraphQL schemas and TypeScript types, tools like GraphQL Code Generator can automatically generate TypeScript definitions from the schema. This process creates a single source of truth, ensuring that the API implementation matches the schema exactly.

2. Resolvers with Type Safety
   GraphQL resolvers connect the schema to the data sources, handling requests and returning responses. When using TypeScript, resolvers are strongly typed, which means that developers can detect mismatches or errors at compile time rather than at runtime.

GraphQL vs Traditional CMS Configuration

Traditional CMS Configuration

Traditional CMS platforms (like WordPress or Drupal) typically operate with REST APIs or direct database queries. Configurations are often rigid and may require:

• Manual setup for endpoint connections.
• Custom code for mapping CMS data to frontend data structures.

Example Workflow:

1. Backend developer exposes an endpoint (e.g., /api/users).
2. Frontend developer fetches data with REST API using libraries like Axios or Fetch.
3. Adjustments to the CMS require changes in both backend and frontend.

Drawbacks:

• Lack of strong typing: Developers often rely on documentation or manual testing to ensure data consistency.
• Over-fetching or under-fetching: REST APIs return fixed data sets, which may include unnecessary fields or miss required ones.

Benefits of TypeScript with GraphQL

• Early Error Detection
  By leveraging TypeScript’s static analysis, developers can catch type-related bugs during the development phase, long before the code is deployed. For instance, if the server expects a string but the client sends a number, TypeScript will flag this mismatch immediately.
  
  Example:

GraphQL Schema:

type Query {
	user(id: ID!): User
}
type User {
	id: ID!
	name: String!
	age: Int!
}

TypeScript Code:

import { gql } from 'graphql-tag';
import { useQuery } from '@apollo/client';

const GET_USER = gql`
	query GetUser($id: ID!) {
		user(id: $id) {
			id
			name
			age
		}
	}
`;

interface User {
	id: string;
	name: string;
	age: number;
}

const UserProfile: React.FC<{ userId: string }> = ({ userId }) => {
	const { data, error } = useQuery<{ user: User }>(GET_USER, {
		variables: { id: userId },
	});
	
	if (error) {
		console.error("Error fetching user:", error);
		return <div>Error loading user data.</div>;
	}
	
	return (
		<div>
			<h1>{data?.user.name}</h1>
			<p>Age: {data?.user.age}</p>
		</div>
	);
};

In this example:

• If the id variable is not a string, or if user.age is not a number, TypeScript will raise errors.
• The GraphQL query and TypeScript interface work together to ensure type consistency between the frontend and the API.

1. 1. Improved Collaboration
      With a strongly typed schema and TypeScript definitions, teams working on different parts of the application (e.g., frontend and backend) can collaborate more effectively. Developers know exactly what data structures to expect, reducing miscommunication and guesswork.

   2. Enhanced Refactoring
      As applications grow, changes to the data model are inevitable. With TypeScript, making these changes becomes safer and more efficient because the compiler identifies all affected areas in the codebase, minimizing the risk of introducing errors.

• Better Developer Experience
  Integrated development environments (IDEs) like Visual Studio Code provide autocompletion, inline documentation, and error hints for TypeScript and GraphQL. This speeds up development and helps developers understand the API without needing to consult external documentation.

Real-World Applications

• API Response Validation
  TypeScript and GraphQL ensure that API responses match the defined schema. This is particularly useful when working with dynamic data, as developers can confidently handle responses without worrying about unexpected values.

1. Frontend and Backend Alignment
   For frontend teams, consuming APIs becomes easier and safer with TypeScript-generated types. These types provide a clear understanding of the data structure, reducing the likelihood of misinterpreting the API.

2. Self-Documenting APIs
   GraphQL’s introspection capabilities, combined with TypeScript’s type definitions, create APIs that are essentially self-documenting. Tools like GraphQL Playground or Apollo Studio can display the schema in real time, helping developers quickly grasp the available queries, mutations, and types.

Best Practices for Integration

1. Automate Type Generation: Use tools to generate TypeScript types from your GraphQL schema to avoid manual errors.
2. Use Enums for Constants: Replace string literals with GraphQL enums to ensure consistency across the application.
3. Adopt a Schema-First Approach: Start with a well-defined GraphQL schema and let it drive the implementation to maintain a single source of truth.
4. Enable Strict TypeScript Settings: Use TypeScript’s strict mode to catch subtle type errors, especially when dealing with optional or nullable fields.
5. Organize Types Centrally: Keep all generated and custom types in a single directory for easy management and access.

Conclusion

TypeScript and GraphQL are a match made in heaven for developers who value type safety, maintainability, and efficiency. Together, they create a seamless development experience, ensuring that APIs are strongly typed, well-documented, and easy to use.

By adopting best practices and leveraging tools like GraphQL Code Generator, developers can unlock the full potential of this integration, building APIs that are not only robust but also future-proof. Whether you’re a frontend developer consuming APIs or a backend developer designing them, combining TypeScript and GraphQL is a step toward more reliable and scalable applications.