# Apollo GraphQL Best Practices

This document provides a comprehensive guide to best practices and coding standards for developing GraphQL APIs and applications using the Apollo ecosystem.

## Library Information:
- Name: apollo-graphql
- Tags: web, api, graphql, javascript

## 1. Schema Design

- **Clarity and Consistency:**
    - Use descriptive naming conventions for types, fields, and arguments (e.g., `getUserById` instead of `getUser`).
    - Maintain consistency across the schema in terms of naming and structure.
    - Define a clear schema that reflects your business domain and data model.

- **Interfaces and Unions:**
    - Implement interfaces and unions for shared features and common data structures.
    - Use interfaces to define contracts for types that implement shared behaviors.
    - Use unions when a field can return different object types that don't share a common interface.

- **Nullability:**
    - Every field is nullable by default unless explicitly marked as non-null using `!`.  Carefully consider nullability for each field.
    - Use non-null types (`!`) only when you can guarantee that the field will always return a value.
    - Handle potential errors gracefully and return `null` for nullable fields when appropriate.

- **Demand-Driven Schema Design:**
   - Design your schema to serve client use cases and product requirements.
   - Intentionally design your schema to serve client use cases and product requirements.

- **Avoid Autogenerated Schemas:**
    - Avoid autogenerating schemas, especially the fields on the root operation types

## 2. Security

- **Disable Introspection in Production:**
    - Disable introspection in production environments to prevent unauthorized access to your schema.
    - Restrict access to staging environments where introspection is enabled.

- **Input Validation:**
    - Validate all user inputs to prevent injection attacks and data corruption.
    - Use custom scalars or directives to enforce validation rules on input types.
    - Sanitize and escape user inputs before using them in resolvers.

- **Authentication and Authorization:**
    - Implement robust authentication and authorization mechanisms to protect your API.
    - Use industry-standard protocols like OAuth 2.0 or JWT for authentication.
    - Implement fine-grained authorization checks at the field level.
    - Enforcing authentication and authorization in the router protects your underlying APIs from malicious operations

- **Rate Limiting and Depth Limiting:**
    - Implement rate limiting to prevent abuse and denial-of-service attacks.
    - Limit query depth to prevent complex queries from overwhelming your server.

- **Whitelisting Queries:**
    - Consider whitelisting queries to restrict the operations that can be executed against your API.

- **Obfuscate Error Details:**
    - Remove verbose error details from API responses in your production graph.
    - Only selectively expose error details to clients in production.

- **Data Validation and Sanitization:**
    - As a schema design best practice, you should deliberately design your schema to serve client use cases and product requirements.

## 3. Performance Optimization

- **Batching and Caching:**
    - Utilize batching techniques (e.g., DataLoader) to reduce the number of requests to backend data sources.
    - Implement caching at different levels (e.g., server-side, client-side) to improve response times.

- **Pagination:**
    - Implement pagination strategies to manage large datasets effectively.
    - Use cursor-based pagination for efficient retrieval of paginated data.

- **N+1 Problem:**
    - Use tools like DataLoader to address the N+1 query problem and ensure efficient data fetching.

- **Server-Side Batching & Caching:**
    - GraphQL is designed in a way that allows you to write clean code on the server, where every field on every type has a focused single-purpose function for resolving that value.

- **Automatic Persisted Queries (APQ):**
    - Consider implementing automatic persisted queries (APQ) to optimize network usage and improve security

## 4. Code Organization and Structure

- **Directory Structure:**
    
    src/
      schema/
        types/
          *.graphql
        resolvers/
          *.js
      dataSources/
        *.js
      utils/
        *.js
      index.js // Entry point
    

- **File Naming Conventions:**
    - Use PascalCase for type definitions (e.g., `UserType.graphql`).
    - Use camelCase for resolver functions (e.g., `getUserById.js`).

- **Module Organization:**
    - Organize your code into reusable modules based on functionality (e.g., user management, product catalog).
    - Create separate modules for schema definitions, resolvers, and data sources.

- **Component Architecture:**
    - Follow a component-based architecture for building GraphQL applications.
    - Create reusable components for common UI elements and data fetching logic.

- **Code Splitting:**
    - Use code splitting to reduce the initial bundle size and improve page load times.
    - Consider splitting your application into smaller chunks based on routes or features.

## 5. Common Patterns and Anti-patterns

- **Design Patterns:**
    - **Data Source Pattern:** Decouple data fetching logic from resolvers using data sources.
    - **Schema Stitching:** Combine multiple GraphQL APIs into a single, unified schema.

- **Recommended Approaches:**
    - Use a GraphQL client library (e.g., Apollo Client, Relay) for efficient data fetching and caching.
    - Implement custom directives to add additional functionality to your schema.

- **Anti-patterns:**
    - **Over-fetching/Under-fetching:** Avoid returning more or less data than required by the client.
    - **Chatty APIs:** Reduce the number of round trips between the client and the server.
    - **God Objects:** Avoid creating large, monolithic types with too many fields.

- **State Management:**
    - Use a state management library (e.g., Redux, Zustand, Jotai) to manage client-side state.
    - Consider using Apollo Client's local state management features for simple state requirements.

- **Error Handling:**
    - Use a consistent error handling mechanism across your application.
    - Return informative error messages to the client.
    - Log errors on the server for debugging purposes.

## 6. Testing Approaches

- **Unit Testing:**
    - Unit test individual resolvers and data sources.
    - Mock external dependencies to isolate the code under test.

- **Integration Testing:**
    - Integrate test your GraphQL API with your database and other backend services.
    - Use a testing framework like Jest or Mocha for writing integration tests.

- **End-to-End Testing:**
    - Use end-to-end testing to verify the entire application flow.
    - Use a testing tool like Cypress or Puppeteer for writing end-to-end tests.

- **Test Organization:**
    - Organize your tests into separate directories based on functionality.
    - Use descriptive names for your test files and test cases.

- **Mocking and Stubbing:**
    - Use mocking and stubbing techniques to isolate the code under test and simulate external dependencies.

## 7. Common Pitfalls and Gotchas

- **N+1 Problem:** Be aware of the N+1 query problem and use DataLoader or other batching techniques to solve it.
- **Schema Evolution:** Plan for schema evolution and use techniques like adding new fields and deprecating old ones to avoid breaking changes.
- **Performance Bottlenecks:** Monitor your API for performance bottlenecks and use profiling tools to identify slow resolvers.
- **Nullability:** Ensure that non-null fields never return `null` to avoid unexpected errors.

## 8. Tooling and Environment

- **Development Tools:**
    - Use a GraphQL IDE like GraphiQL or Apollo Studio for exploring and testing your API.
    - Use code generation tools to generate types and resolvers from your schema.

- **Build Configuration:**
    - Use a build tool like Webpack or Parcel to bundle your code for production.
    - Configure your build tool to optimize your code and reduce bundle size.

- **Linting and Formatting:**
    - Use a linter like ESLint or Prettier to enforce code style and prevent errors.

- **Deployment:**
    - Deploy your GraphQL API to a production environment like AWS Lambda, Google Cloud Functions, or a Node.js server.
    - Use a serverless platform for easy scaling and management.

- **CI/CD Integration:**
    - Integrate your GraphQL API with a CI/CD pipeline for automated testing and deployment.

## 9. Additional Best Practices

- **Versioning:** While GraphQL promotes continuous evolution, consider versioning your API if you need to make breaking changes.
- **Documentation:** Provide comprehensive documentation for your GraphQL API using tools like GraphQL Docs.
- **Monitoring:** Monitor your GraphQL API for performance and errors using tools like Apollo Studio or New Relic.
- **Error Messages and Notifications:** You can also opt for union types to represent an error and to prompt suggestions to users, though this is a more expensive choice.

## 10. Global Identification

- Another way to organize components, besides Pagination, is by using a global identification. Originally proposed on Relay and similar to URIs, this method has become a more general good practice though it is not considered mandatory — especially if you are not planning on supporting Relay in your application

## 11. Rate Limiting

-  Like any other web API, setting limits is a good strategy to avoid, for example, an overload of requests per minute. There are a few ways this can be done in GraphQL

## 12. Authentication and Authorization

- Often interchanged in their meaning, authentication is the act of determining who a user is and whether they are logged in or not. Authorization, on the other hand, is the act of determining if a user is allowed to do an action or see something.

## 13. Safelisting with Persisted queries

-  Beyond operation limits, GraphOS enables first-party apps to register trusted operations in a persisted query list ( PQL) or safelist.