SpaceX Launch Dashboard

Project Objective

To learn how to set up and use a GraphQL server for API experimentation, specifically focusing on free options and creating a working implementation that can query live data.

Process Overview

Step 1: Choose a GraphQL API and Setup Approach

Effective Prompt:

I would like to test GraphQL. What is something I can do for free with GraphQL? Walk me through step by step how I can get started with a GraphQL project, including a free API to use.

Why This Works:

• Clearly states your intention to experiment with GraphQL
• Asks for free options, setting a practical constraint
• Requests a step-by-step guide, indicating the level of detail needed

Step 2: Set Up Your Development Environment

Effective Prompt:

How do I set up a dev environment?

Why This Works:

• Asks for specific guidance on the first implementation step
• Short and direct, focusing on immediate needs

Step 3: Create Your GraphQL Server File

Using Code Provided by AI:

• Create a new file with the GraphQL server code
• Save it with an appropriate name (like graphql_index.js)
• Ensure you understand the code structure (schema definition, resolvers, server setup)

Step 4: Install Required Dependencies

Effective Prompt:

Terminal won’t let me enter password

Why This Works:

• Identifies a specific roadblock
• Provides context for the AI to troubleshoot

Step 5: Run Your GraphQL Server

Effective Prompt:

Is it possible to execute the GraphQL server from Visual Studio Code?

Why This Works:

• Asks about an alternative approach when facing obstacles
• Specifies the preferred tool (VS Code)

Step 6: Troubleshoot Any Issues

Effective Prompt:

I get an error message { “errors”: [ { “message”: “fetch is not a function” … }

Why This Works:

• Shares the complete error message
• Provides enough technical detail for accurate diagnosis

Step 7: Explore GraphQL Queries

Effective Prompt:

What can I do with the outputs from Apollo?

Why This Works:

• Shows interest in expanding knowledge beyond basic setup
• Opens the conversation to application possibilities

Additional Recommended Prompts

For more effective collaboration with AI on API projects, consider these prompts:

For Initial Planning

What are the key differences between GraphQL and REST APIs that would impact my [specific use case]?

For Environment Setup

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What development tools or extensions would you recommend for working with GraphQL in VS Code?

For Project Structure

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Can you explain how I should structure a larger GraphQL project with multiple data sources?

For Understanding the Code

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Can you explain each part of this GraphQL server code and how they work together?

For Learning GraphQL Concepts

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What are the key GraphQL concepts I should understand before building more complex queries?

For Performance Considerations

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What performance considerations should I keep in mind when designing GraphQL queries?

Troubleshooting Guide

Issue: “Command not found” error

Solution:

1. Verify Node.js is installed with node –version
2. If not installed, download and install from nodejs.org
3. Restart terminal after installation
4. Verify installation with node –version

Issue: Navigation to project directory

Solution:

1. Use find ~/ -name “filename.js” -type f to locate your file
2. Use cd /path/to/directory (without the filename) to navigate to the containing folder
3. Verify with ls to confirm you see your file

Issue: “fetch is not a function” error

Solution:

1. Update your code to use the correct import syntax for node-fetch v3:
   javascript
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   const fetch = (…args) => import(‘node-fetch’).then(({default: fetch}) => fetch(…args));
   

Update your package with:

npm uninstall node-fetch

npm install node-fetch@3

Then, restart your server.

Applying This to Other API Projects

To incorporate any API with AI assistance:

1. Identify API Requirements
   • Ask the AI to compare different API options for your specific needs
   • Request explanation of authentication methods and requirements
2. Environment Setup
   • Have the AI guide you through installing necessary tools
   • Ask for code that includes proper error handling
3. Create Minimal Implementation
   • Request a simple working example that demonstrates core functionality
   • Have the AI explain each component of the implementation
4. Handle Security Properly
   • Ask for best practices regarding API keys and authentication
   • Request guidance on secure storage of credentials
5. Scale Your Knowledge
   • Once basic implementation works, ask about more advanced features
   • Request examples of common patterns and best practices
6. Troubleshoot Methodically
   • When errors occur, share the complete error message
   • Ask for explanation of what the error means before implementing fixes

By following this structured approach and using effective prompts, you can successfully incorporate APIs into your projects with AI assistance, learning valuable skills along the way.