Learn Graphcms, Jspm and Serverless

In this course, Colby is going to do a deep dive into creating a full store for your products. You'll learn how to set up and use GraphCMS as your content management system. You'll learn about the Cloudinary UI extension and how to use it to host your images. You'll learn about Snipcart and using the useSnipcart hook to handle the cart state and the checkout. You'll learn how to implement Stripe as your payment gateway. And lastly, you'll learn how to deploy a Next js app to vercel from github with environment variables.

snipcart

Ecommerce Product Management & Storefront with GraphCMS, Snipcart, & Next.js

graphcms

Displaying a list of physical locations is helpful, but showing them on a map, giving your potential customers the ability to see how close each store really is to their location is even better.

GraphCMS supports adding coordinates as a field to our data models, where we can dynamically pull those coordinates in and add them to a map.

We'll walk through how we can loop through our store locations and add each one to a new React Leaflet map. We'll also learn about some pitfalls of using React Leaflet in an app framework like Next.js and how we can solve it with dynamic imports and manual image imports.

* [Dynamic Import - nextjs.org](https://nextjs.org/docs/advanced-features/dynamic-import)
* [Leaflet Map Marker Rendering - github.com](https://github.com/Leaflet/Leaflet/issues/4968)

I also have a whole course on how to [Build Maps using React Leaflet](https://egghead.io/courses/build-maps-with-react-leaflet) if you want a further dive on the topic. 

Add All Store Locations to a React Leaflet Map with Location Data From GraphCMS

If our store supports physical locations, we want to give our customers the opportunity to easily find out those locations so they can visit us in person. That means, we need to show them somewhere on our site.

We can take advantage of GraphCMS custom Schema Models to create a new document for each store.

We'll walk through setting up a new model for our stores and how we can query them in our app to list out all of our locations.

List Store Locations on a Page Using a Store GraphCMS Schema and Data

We are going to create a schema as we did in lesson 2, but this one is going to be for our Categories at the bottom of the home page. This will be slightly different because we are going to add a Reference field. This way we can create a reference between our categories and our products. 

Then over in the content tab, we will add our existing products to an Apparel category, an Accessory category, and a Featured category. 

Create a Product Category Graphcms Schema to Manage Product Groupings

We want to set up a schema for the most important part of our store, our products. We set up all the fields that we'll need, including the name, the image, and the price.

We also set up the description, which we'll use later when we're setting up individual product pages. Then we will see how we can easily construct and query for our data inside of GraphCMS and append that products query to the end of our existing query.

There, we will pass along that data, just like our existing home page data to our app, where we dynamically render our first four products inside of GraphCMS.

Manage Product Details with a Custom GraphCMS Schema Model

To manage my product data, I'm going to use [graphCMS](https://graphcms.com/) which is a content management system that's going to give us a content API backed by GraphQL. You'll need to login, or register an account, with just the free version for this course. I will also run you through the initial setup for graphCMS. 

Use GraphCMS Schema Models to Manage Page Content

Set up GraphCMS to Manage Data with a GraphQL API

JavaScript® (often shortened to JS) is a lightweight, interpreted, object-oriented language with first-class functions, most known as the scripting language for Web pages, but used in many non-browser environments as well such as node.js or Apache CouchDB. It is a prototype-based, multi-paradigm scripting language that is dynamic, and supports object-oriented, imperative, and functional programming styles.

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In this video you'll learn how to deploy a React app to AWS using AWS Amplify Hosting's drag and drop folder functionality. The app will also automatically be globally distributed on AWS's global CDN.

Deploy a React App to AWS in 24 seconds

Starting from a prebuilt frontend, Jason Lengstorf guides you through the creation of a "Corgi Up-boop App" that uses Netlify Functions and Hasura. You can view [the deployed final product on Netlify](https://egghead-serverless-functions.netlify.app/).

You'll set up the Netlify CLI, and configure a local development environment before writing and deploying functions with a few different use cases.

The first example function bypasses CORS restrictions to retrieve corgi data from an example third-party API.

Next, you'll configure environmental variables to securely communicate with the Unsplash API without exposing private keys to the client.

Serverless functions don't persist data by themselves, so we will use  Hasura to create a GraphQL API for tracking the number of "boops" each corgi receives.

This course is an excellent illustration of the speed of Serverless functions, and how fast you can implement functionality in your web applications.

An all-in-one workflow that combines global deployment, continuous integration, and automatic HTTPS.

netlify

Build a Corgi Up-boop Web App with Netlify Serverless Functions and Hasura

Environment variables set in a `.env` file can be imported using the Netlify CLI with the following command: `netlify env:import`.

This allows you to manage environment variables directly on Netlify, providing the benefit of security and flexibility of sharing environment variables with your team. 

From inside Netlify, you can access the environment variables in:

`Site settings` > `Build & deploy` > `Environment` > `Environment variables`

Import and Set Environment Variables from a .env file using Netlify CLI

CORS limits websites from communicating with other domains without the full consent of both sites. Consuming data from a 3rd Party REST API makes it difficult since we can't properly configure the appropriate CORS headers. To solve this, we'll set up a proxy server to request the data using a Netlify function that avoids CORS altogether.

The Third-Party API that we'll be working with will provide the following data: `id`, `name`, `favoriteSong` for each corgi. 

[http://no-cors-api.netlify.app/api/corgis](http://no-cors-api.netlify.app/api/corgis)

We will also use `node-fetch` a light-weight module that brings the `fetch` API to fetch the data into our application.

Circumvent CORS when Accessing a Third-Party API using Netlify Functions 

There are a few ways you can run Netlify serverless functions while you are developing them. 

You can: 

- Navigate to the directory under the `/.netlify/functions/` path
- Curl them using the full URL
- Use an app like Postman

Manually Trigger Netlify Serverless Functions Locally

Netlify makes deploying to production a breeze by configuring your Netlify CLI to your Netlify account and integrating with GitHub.

We'll log in to Netlify through the CLI and initialize a site by completing all the options that the CLI runs us through. Once this is done, Netlify will trigger new builds for your site every time you push to GitHub.

Deploy Serverless Functions to Production on Netlify using the Netlify CLI

Netlify makes developing serverless functions easy with the netlify-cli (`ntl` for short). You'll be able to build and test functions locally as well as publish your functions from the CLI. 

We will install netlify-cli globally and create a `netlify.toml` file that will configure where the CLI should look to run functions that we define, in our case `functions/`. When the application is served up, Netlify runs functions under `/.netlify/functions/`.

Set up a Local Development Environment for Serverless Functions Using Netlify

A serverless function is something that is going to allow us to do server-like things without having to manage servers, but an important distinction here is that serverless does not mean that there are **no** servers. 

The environment is actually running on top of an operating system and uses physical servers, but the responsibility for provisioning and managing the infrastructure belongs entirely to the service provider.

Some of the benefits of using serverless functions: 

- **Enhanced scalability.** No need for developers to implement code to scale. It scales automatically.
- **Reduced time to market.** Serverless is an optimized set of tools for building quickly.
- **No boiler code.** A serverless function is just a tiny piece of logic. Reducing the complexity of software.
- **More time for user experience.** Serverless functions allow teams to focus resources on the user experience and not on managing servers.
- **Security.** We can call third-party APIs securely without exposing important data on the client-side.

What Are Serverless Functions?

jspm is a package manager for the SystemJS universal module loader, built on top of the dynamic ES6 module loader.

jspm

JSPM can handle installed packages, transpiling ES6, and bundling all from the command-line. This video gives a quick overview of install JSPM, installing packages with JSPM, writing a very simple app in ES6 that uses those packages, then bundling up for production.

An Introduction to JSPM (JavaScript Package Manager)

Create a serverless application and deploy it in under thirty minutes!

We'll be using Netlify, Vite, TypeScript, and React in our project. This stack synergizes extremely well for rapidly developing professional-quality applications. 

If you haven't heard of Vite, it's the French word for quick! It's also a build tool that consists of a dev-server and an extremely fast bundler. It makes for a rapid development loop.

As for the rest. Netlify makes hosting fast and easy with serverless functions and continuous deployment. React enables you to quickly create reusable components. And TypeScript helps you write cleaner code that is easier to refactor. 

So get started and learn how to use this stack in your own applications!

Deploy a Serverless API React Application with TypeScript

In this lesson, you'll learn how to enhance the accuracy of components generated by Cursor Composer by aligning your project's package.json with Cursor's rules. We'll guide you through extracting the list of installed packages from your package.json and incorporating them into your .cursorrules file, along with brief descriptions of their functionalities. By providing Cursor with this contextual information, you'll enable it to generate components that are more precise and functional on the first attempt. The lesson includes demonstrations of component generation both with and without these enhancements, highlighting the improvements in accuracy and efficiency.

Boost Cursor Composer Accuracy: Integrating package.json with Cursor Rules

Speed up your bug-fixing process dramatically with Cursors Composer. Take a warning from your logs, search for relevant terms, then seamlessly import both the warning and search results into Composer. Add documentation and apply fixes to all search results in one go. This streamlined workflow resolves multiple issues rapidly, saving valuable development time.

Batch Fix Every File in Search Results with Cursor's Composer

 We map over the initial set of results then use `Promise.all` to efficiently fetch the details of each pokemon rendered in the table. This allows us to add more columns to our pokemon table.

Fetch and display row details with Promise.all in Tanstack Table

map over the initial set of results then use `Promise.all` to efficiently fetch the details of each pokemon rendered in the tanstack table

Create a custom hook to fetch remote data by passing a promise to the React 19 `use` hook. Then render this data in Tanstack Table by memoizing the results and passing them to `useReactTable`.

Render remote data in a Tanstack Table with React 19's use hook and a promise

Create a custom hook using React 19’s use to fetch data with a promise. Render it in a Tanstack Table by memoizing and using useReactTable.

You know when you're deep in the code trenches and need someone to challenge your assumptions? That's exactly what this is about.

Instead of waiting for someone to poke holes in your master plan, you can paste that strategy straight into AI Studio and let it pressure test your ideas. We're talking about using this tool to validate everything from your feature proposals to your ambitious refactoring strategies.

The real magic happens when you hit that microphone button. Now you're in a real-time verbal sparring match. It's like rubber duck debugging but the duck actually pushes back and makes you defend every architectural decision you've made.

Here's the workflow:
1. Drop your master plan into the system instructions
2. Tell the AI to challenge every assumption
3. Hit that mic and defend your choices like you mean it
4. Watch your plan either emerge stronger or get rightfully dismantled

This approach is perfect when you're:
- Stuck in your own head with a complex problem
- Need to validate if your approach holds water
- Want to catch edge cases before they catch you
- Looking for opportunities you might have missed because you're too close to the code

It's like having a senior dev on call 24/7, ready to challenge your ideas and push you to think deeper about your solutions.

Now go forth and get your ideas challenged. Your projects will thank you for it.


An Uncomfortable and Challenging Conversation with AI Studio

In this lesson, you'll learn how to effectively brainstorm your project ideas before working with AI agents. We'll cover:

1. The importance of having a clear plan before starting work with AI agents
2. Using traditional brainstorming techniques to gather your thoughts
3. Leveraging video recording to capture your brainstorming session
4. How to review and analyze websites for inspiration
5. Documenting likes, dislikes, and potential features for your project
6. Using AI tools (like AI Studio) to organize and process your recorded brainstorming session

The lesson emphasizes a modern approach to brainstorming that combines traditional techniques with video recording, making it easier to later process your ideas through AI tools. This method helps ensure that no ideas are lost and that your thoughts can be effectively organized by AI for future reference.

How to Brainstorm Your Project Features to Prepare for AI Agents

fast-check allows us to create composite generators that suit our testing needs. We'll generate two numbers to create a point simulating an X and Y and assert that the distance should always be greater than or equal to 0.

Generate composite objects with fast-check fc.record

Just using fast-check by itself can make you tests verbose and tough to read. Lucky for us there are many integrations with fast-check such as the `@fast-check/jest` package that will help remove some boilerplate from our test.

Tidy up your test with @fast-check/jest

Many people share .cursorrules files, but trying to craft your own from scratch is a huge pain. Instead, this lesson shows you how to grab ALL community-created .cursorrules files to build a custom rule set for your projects. We'll use Gitingest and Google AI Studio to gather these examples and generate an awesome starting point customized to your specific project.

Generate Custom .cursorrules for Your Project Based on Community Examples

The GitHub CLI allows you to search issues and filter on different criteria like amount of comments. This allows you to search for real-world situations and pains/solutions people have using different technology. 

With the GitHub CLI in hand we'll drop 100s of issues as context in Googles AI Studio and have Gemini determine the 10 most frequently asked questions. This will give us a sense of how people use a library and where people get hung up.