In the ever-evolving landscape of web development, GraphQL has emerged as a powerful query language and runtime for APIs. With its flexibility and efficiency, GraphQL introduces new opportunities and challenges in building robust and reliable APIs. As developers navigate this space, the significance of automated testing becomes increasingly evident.

This blog post explores the pivotal role of automated testing in ensuring the stability and functionality of GraphQL APIs. By the end of this journey, you'll gain a comprehensive understanding of the importance of automated testing in GraphQL. Let's embark on an exploration of automated GraphQL testing to uncover the key practices for ensuring the resilience and efficacy of our GraphQL APIs.

Setting up a Testing Environment

To kickstart our journey into automated testing for GraphQL, it's essential to establish a well-configured testing environment.

1. Install Node.js and npm:

Ensure you have Node.js and npm (Node Package Manager) installed on your system. You can download and install them from the official Node.js website.

2. Create a New Project:

Initiate a new JavaScript project by running the following commands in your terminal:

                                     
mkdir graphql-testing-project
cd graphql-testing-project
npm init -y
                    

This will create a package.json file with default configurations.

3. Install Testing Dependencies:

Now that we've set up our project, let's install the necessary testing dependencies. Open your terminal and run the following command:

                                     
npm install --save-dev jest @types/jest ts-jest babel-jest
                    

This command installs Jest as our testing framework, along with the TypeScript support (ts-jest), the Jest typings (@types/jest), and Babel integration for JavaScript files (babel-jest).

Since we are doing testing around GraphQL, we will need the following dependencies, too:

                                     
npm install @graphql-tools/schema @apollo/server graphql
                    

4. Configure Jest:

Once the testing dependencies are installed, we need to configure Jest to work with TypeScript and Babel. Create a jest.config.js file in the root of your project with the following content:

                                     
export default {
    preset: "ts-jest",
    transform: {
        "^.+\\.(ts|tsx)?$": "ts-jest",
        "^.+\\.(js|jsx)$": "babel-jest",
    },
};
                    

This configuration specifies the TypeScript preset for Jest and tells Jest to use the ts-jest transformer for TypeScript files and the babel-jest transformer for JavaScript files.

We will also add a babel.config.cjs file with the following content:

                                     
module.exports = { presets: ["@babel/preset-env"] };
                    

This configuration tells Babel to use the @babel/preset-env preset, which is a widely used preset for transpiling modern JavaScript code to an older version that is compatible with a specified set of environments.

5. Ready to Go:

Our testing environment is now set up. We can start writing and running tests for our GraphQL APIs using the tools and configurations we've installed. In case you don't have a testing API, I will provide the one used in this blog example on our GitHub repository.

Unit Testing with Jest

Now that our testing environment is set up, let's dive into the world of unit testing for GraphQL resolvers using Jest. Unit testing allows us to scrutinize individual components of our GraphQL server, ensuring they behave as expected in isolation.

Writing a Simple Resolver Test

First we import the necessary functions and data for testing GraphQL resolvers and queries:

                                     
import { graphql } from "graphql";
import { makeExecutableSchema } from "@graphql-tools/schema";
import db from "./db";
import { typeDefs } from "./schema";
import { resolvers } from "./resolvers";
                    

Then, we use makeExecutableSchema to combine our type definitions (typeDefs) and resolvers (resolvers) into a single executable schema named schema.

                                     
const schema = makeExecutableSchema({
    typeDefs,
    resolvers,
});
                    

The next block is the start of a Jest test suite titled "Movie Resolver." Jest uses describe to group tests together.

                                     
describe("Movie Resolver", () => {
    // ...
});
                    

This following block is a specific test case within the "Movie Resolver" suite. Jest uses test to define individual test cases.

                                     
test("Movie resolver returns correct movie by ID", async () => {
    // ...
});
                    

Now, we create a variable called source that contains a GraphQL query requesting information about a movie with ID "1." graphql({ schema, source }) executes the query against the schema, returning the data from the response:

                                     
const source = `
    query {
        movie(id: "1") {
            id
            title
            genre
        }
    }
`;
                  
const { data } = await graphql({ schema, source });
                    

expectedMovie is determined by finding the movie with ID "1" in our mock database (db.movies). The assertion checks if the data returned by the GraphQL query matches the expected movie data.

Following this pattern, a test case that is focused on retrieving reviews for a movie would look something like this:

                                     
test("Movie resolver returns reviews for the movie", async () => {

    const source = `
        query {
            movie(id: "1") {
                id
                title
                reviews {
                    id
                    rating
                    content
                }
            }
        }
    `;
                        
    const { data } = await graphql({ schema, source });

    const expectedReviews = db.movieReviews.filter(
        (review) => review.movie_id === "1"
    );

    const filteredReviews = expectedReviews.map((obj) => {
        const { director_id, movie_id, ...rest } = obj;
        return rest;
    });
                        
    expect(data.movie.reviews).toEqual(filteredReviews);
});
                    

Unit testing GraphQL resolvers with Jest allows us to verify the correctness of our individual resolver functions. As we continue building our GraphQL schema and resolvers, we create unit tests to ensure each component behaves as intended. This practice contributes to the overall reliability and maintainability of our GraphQL API.

Integration Testing

Integration testing involves verifying the collaboration between various components in a system. For GraphQL APIs, this typically includes testing the interaction between the schema, resolvers, and data sources.

If we would break this process down into steps, it would look something like this:

• Setup Testing Environment: Set up a testing environment where you can instantiate your GraphQL server with a mock database or test-specific data.
• Test GraphQL Queries and Mutations: Write tests to validate the behavior of GraphQL queries and mutations by executing them against the instantiated GraphQL server.
• Verify Resolvers: Ensure that resolvers are correctly resolving data and handling business logic. Check that they interact appropriately with the mock database or test-specific data.
• Mock External Dependencies: If your resolvers interact with external services (e.g., authentication, third-party APIs), use mocks or stubs to simulate these interactions without relying on the actual external services during tests.
• Test Error Handling: Create tests to verify that your GraphQL server handles errors gracefully. This includes testing scenarios where queries or mutations may result in errors, and your server responds appropriately.
• Check Data Consistency: Validate the consistency of data returned by queries and mutations. Ensure that the server returns the expected data based on the provided inputs.
• Evaluate Performance: If performance is a concern, consider including tests to evaluate the response time and overall performance of your GraphQL server under varying loads.

Example Integration Test (using Jest):

                                     
import { graphql } from "graphql";
import { makeExecutableSchema } from "@graphql-tools/schema";
import db from "./db";
import { typeDefs } from "./schema";
import { resolvers } from "./resolvers";
                        
const schema = makeExecutableSchema({
    typeDefs,
    resolvers,
});
                        
test("Integration Test: Adding a Movie", async () => {
    const mutation = `
        mutation {
            addMovie(movie: { title: "New Movie", genre: ["Action", "Adventure"] }) {
                id
                title
                genre
            }
        }
    `;
                        
    const initialMoviesCount = db.movies.length;
                        
    const { data } = await graphql({ schema, source: mutation });
    expect(data.addMovie.id).toEqual(expect.any(String));
    expect(data.addMovie.title).toEqual("New Movie");
    expect(data.addMovie.genre).toEqual(["Action", "Adventure"]);
                        
    // Check if the new movie is added to the mock database
    expect(db.movies.length).toBe(initialMoviesCount + 1);
    const newMovie = db.movies.find((movie) => movie.title === "New Movie");
    expect(newMovie).toBeTruthy();
});
                    

In this example, we're testing the interaction between a mutation (addMovie) and the corresponding resolver. The test checks whether the mutation successfully adds a new movie to the mock database and whether the response matches the expected data structure.

End-to-End Testing with Jest and Supertest

End-to-end testing involves testing the complete flow of an application, simulating real user interactions. In the context of a GraphQL API, this includes sending HTTP requests to the server and validating the responses.

1. Setup Testing Environment:

First, we need to configure Jest to handle end-to-end tests. Then, we need to ensure that our GraphQL server is running in the testing environment and the database is in a known state before each test.

2. Install Dependencies:

The next step is to install the necessary packages (jest, supertest, and any other dependencies) for end-to-end testing.

                                     
npm install --save-dev supertest
                    

3. Write End-to-End Tests:

Finally, we create Jest test files for our end-to-end tests. For this blog, we will use supertest to make HTTP requests to our GraphQL endpoint and validate the responses.

First things first, we need to import necessary libraries and modules, including Express, Apollo Server, GraphQL schema tools, type definitions, resolvers, database representation, and Supertest for testing HTTP requests.

                                     
import express from "express";
import { ApolloServer } from "apollo-server-express";
import { makeExecutableSchema } from "@graphql-tools/schema";
import { typeDefs } from "./schema";
import { resolvers } from "./resolvers";
import db from "./db";
const request = require("supertest");
                    

Similarly, as with the previous examples, we use makeExecutableSchema to combine GraphQL type definitions and resolvers into a schema.

                                     
const schema = makeExecutableSchema({
    typeDefs,
    resolvers,
});
                    

Now, we create a new instance of Apollo Server with the defined schema.

                                     
const server = new ApolloServer({ schema });
                    

The startServer function initializes and starts the Apollo Server. The Express app is created, and middleware is applied for GraphQL handling. The server is started, and the function returns a promise with the resolved app.

                                     
const startServer = async () => {
    await server.start();
    const app = express();
    server.applyMiddleware({ app });
                          
    const port = process.env.PORT || 4000; // Use environment variable or default port
                          
    return new Promise((resolve) => {
        app.listen(port, () => {
            console.log(`Server ready at http://localhost:${port}/graphql`);
            resolve(app);
        });
    });
};
                    

Jest test suite is defined for end-to-end tests. The beforeAll hook starts the server before running tests. The afterAll hook stops the server after all tests have been executed.

                                     
describe("End-to-End Tests", () => {
    let app;
                          
    beforeAll(async () => {
        app = await startServer();
    });
                          
    // ... Individual test cases ...
                          
    afterAll(async () => {
        await server.stop();
    });
});
                    

Individual test cases are using Jest's test function. HTTP requests are made using supertest to test GraphQL queries and mutations. Assertions are made to check the expected behavior and outcomes of the queries/mutations.

                                     
test("Query: Get Movies", async () => {
    const response = await request(app)
        .post("/graphql")
        .send({
            query: `
                query {
                    movies {
                        id
                        title
                        genre
                    }
                }
            `,
        });
                        
    expect(response.status).toBe(200);
    expect(response.body).toHaveProperty("data.movies");
    expect(response.body.data.movies).toHaveLength(db.movies.length);
});
                    

In the end, we need to ensure the server stops even if the tests fail or exit unexpectedly.

                                     
process.on("exit", () => {
    server.stop();
});
                    

Conclusion

In conclusion, as we navigate the dynamic landscape of web development, GraphQL has emerged as a potent tool for building flexible and efficient APIs. However, harnessing its full potential requires a robust approach to testing, particularly automated testing. In this blog post, we delved into the pivotal role of automated testing in ensuring the stability and functionality of GraphQL APIs.

We began our journey by establishing a well-configured testing environment, walking through the steps of installing Node.js, npm, and essential testing dependencies such as Jest, ts-jest, and babel-jest. With the environment set up, we explored unit testing for GraphQL resolvers using Jest, emphasizing the importance of scrutinizing individual components to ensure they behave as expected in isolation.

The integration testing section demonstrated how to verify the collaboration between different components, including the schema, resolvers, and data sources.

Furthermore, we delved into end-to-end testing with Jest and Supertest, covering the setup of the testing environment, installation of necessary dependencies, and writing end-to-end tests to simulate real user interactions with the GraphQL server.

In summary, automated testing is an integral part of GraphQL development, contributing to the resilience and efficacy of APIs. Whether through unit testing, integration testing, or end-to-end testing, adopting a comprehensive testing strategy ensures that GraphQL APIs not only meet but exceed the expectations of developers and end-users alike. By embracing automated testing, developers can confidently navigate the evolving landscape of web development, building GraphQL APIs that are reliable, maintainable, and performant.