Integration tests with test server in GraphQL - Mini Project: Build & Apply

Integration Tests with Test Server

📋 What You'll Learn

💡 Why This Matters

🌍 Real World

Integration tests help developers verify that their GraphQL APIs work correctly before deploying to production. This reduces bugs and improves reliability.

💼 Career

Many software engineering roles require writing tests for APIs. Knowing how to set up test servers and write integration tests is a valuable skill for backend and full-stack developers.

1

Create a simple GraphQL schema with a Book type

Create a GraphQL schema string called typeDefs that defines a Book type with fields id (ID!), title (String!), and author (String!). Also define a Query type with a field book that takes an id argument of type ID! and returns a Book.

GraphQL

# Create the GraphQL schema string called typeDefs
# Your code here

Hint

Use backticks to create a multi-line string. Define the Book type and Query type exactly as described.

2

Create a resolver for the book query

Create a constant called resolvers that defines a Query resolver with a book function. This function takes parent, args, and returns a book object with id, title, and author fields. Return the book with id equal to args.id, title as "Test Book", and author as "John Doe".

GraphQL

const typeDefs = `
  type Book {
    id: ID!
    title: String!
    author: String!
  }

  type Query {
    book(id: ID!): Book
  }
`;

// Create resolvers object with Query.book resolver
// Your code here

Hint

Define the resolvers object with a Query field. The book resolver returns a fixed book object using args.id.

3

Create the test server using ApolloServer

Create a constant called server that is a new ApolloServer instance. Pass typeDefs and resolvers as options to the constructor.

GraphQL

const typeDefs = `
  type Book {
    id: ID!
    title: String!
    author: String!
  }

  type Query {
    book(id: ID!): Book
  }
`;

const resolvers = {
  Query: {
    book(parent, args) {
      return {
        id: args.id,
        title: "Test Book",
        author: "John Doe"
      };
    }
  }
};

// Create ApolloServer instance called server
// Your code here

Hint

Import ApolloServer and create a new instance with the schema and resolvers.

4

Write an integration test to query the book by ID

Write an async function called testBookQuery. Inside, call server.executeOperation with a query string that requests book(id: "1") and asks for id, title, and author. Await the result and assign it to a variable called response. Then check that response.data.book.id equals "1", response.data.book.title equals "Test Book", and response.data.book.author equals "John Doe".

GraphQL

import { ApolloServer } from 'apollo-server';

const typeDefs = `
  type Book {
    id: ID!
    title: String!
    author: String!
  }

  type Query {
    book(id: ID!): Book
  }
`;

const resolvers = {
  Query: {
    book(parent, args) {
      return {
        id: args.id,
        title: "Test Book",
        author: "John Doe"
      };
    }
  }
};

const server = new ApolloServer({ typeDefs, resolvers });

// Write async function testBookQuery to run query and check response
// Your code here

Hint

Use server.executeOperation with a query string. Check the response data fields for expected values.

Practice

1. What is the main purpose of using a test server in GraphQL integration tests?

easy

A. To speed up the production server

B. To run queries and mutations safely without affecting real data

C. To replace the database permanently

D. To generate random data automatically

Solution

1. Step 1: Understand the role of a test server

   A test server is a safe environment that mimics the real server but does not affect actual data.

2. Step 2: Identify the purpose in integration tests

   Integration tests use the test server to check if queries and mutations work together correctly without risk.

3. Final Answer:

   To run queries and mutations safely without affecting real data -> Option B

4. Quick Check:

   Test server = safe testing environment [OK]

Hint: Test server isolates tests from real data changes [OK]

Common Mistakes:

• Thinking test server speeds up production
• Confusing test server with permanent database replacement
• Assuming test server auto-generates data

2. Which of the following is the correct way to start a test server for GraphQL integration tests using Apollo Server?

easy

A. const server = ApolloServer(); server.startServer();

B. const server = ApolloServer(typeDefs, resolvers); server.run();

C. const server = new ApolloServer({ typeDefs, resolvers }); await server.listen();

D. const server = new ApolloServer({ typeDefs, resolvers }); await server.start();

Solution

1. Step 1: Recall Apollo Server setup

   Apollo Server requires creating an instance with typeDefs and resolvers, then calling start() before listen().

2. Step 2: Identify correct method to start server

   The correct method to start the server is await server.start(); before running listen().

3. Final Answer:

   const server = new ApolloServer({ typeDefs, resolvers }); await server.start(); -> Option D

4. Quick Check:

   Use server.start() before listen() [OK]

Hint: Remember to call await server.start() before listen() [OK]

Common Mistakes:

• Calling listen() without starting server
• Using incorrect constructor syntax
• Assuming server.run() or startServer() exist

3. Given this test code snippet for a GraphQL query on a test server:

const result = await server.executeOperation({ query: `query { user(id: 1) { name } }` }); console.log(result.data.user.name);

What will be printed if the user with id 1 has the name "Alice"?

medium

A. undefined

B. null

C. "Alice"

D. Error: user not found

Solution

1. Step 1: Understand executeOperation result

   executeOperation returns an object with data containing the query result if successful.

2. Step 2: Check the query and expected data

   The query requests user with id 1 and its name. If user exists with name "Alice", result.data.user.name will be "Alice".

3. Final Answer:

   "Alice" -> Option C

4. Quick Check:

   Query result matches user name "Alice" [OK]

Hint: executeOperation returns data object with query results [OK]

Common Mistakes:

• Expecting undefined if user exists
• Confusing null with undefined
• Assuming error thrown instead of null result

4. You wrote this test code but it throws an error:

const result = await server.executeOperation({ query: `mutation { addUser(name: "Bob") { id } }` });

What is the most likely cause?

medium

A. The mutation name is incorrect or not defined in schema

B. The query should be a GET request, not mutation

C. executeOperation cannot run mutations

D. Missing await keyword before server.executeOperation

Solution

1. Step 1: Check mutation usage in test

   executeOperation supports mutations, so that is not the issue.

2. Step 2: Verify mutation name and schema

   If mutation name addUser is not defined in the schema, the server throws an error.

3. Final Answer:

   The mutation name is incorrect or not defined in schema -> Option A

4. Quick Check:

   Mutation must exist in schema to run [OK]

Hint: Check mutation name matches schema exactly [OK]

Common Mistakes:

• Thinking executeOperation can't run mutations
• Forgetting to await executeOperation
• Confusing query and mutation types

5. You want to write an integration test that checks if a mutation correctly adds a user and then a query fetches that user. Which sequence correctly tests this on a GraphQL test server?

hard

A. Run mutation with executeOperation, then run query with executeOperation, check query result matches mutation data

B. Run query first, then mutation, then check mutation result

C. Run mutation and query in parallel without waiting, then check results

D. Only run mutation; query testing is unnecessary in integration tests

Solution

1. Step 1: Understand integration test flow

   Integration tests verify that mutations affect data and queries reflect those changes.

2. Step 2: Correct test sequence

   First run mutation to add user, then query to fetch user, then compare results to confirm correctness.

3. Final Answer:

   Run mutation with executeOperation, then run query with executeOperation, check query result matches mutation data -> Option A

4. Quick Check:

   Mutation then query to verify changes [OK]

Hint: Test mutation first, then query to confirm data change [OK]

Common Mistakes:

• Running query before mutation
• Running mutation and query in parallel without order
• Skipping query test after mutation