Learn Eslint, Reactfire and Serverless

The pluggable linting utility for JavaScript and JSX.

eslint

One of the other tools I use is Emmet. It's used for writing HTML much more quickly by using shorthand. It can also be used for JSX. VSCode also supports ESLint which we will use and configure in our VSCode `settings.json`. I will also set up Prettier as my default formatter for TypeScript and TypeScript React files. 

Configure Emmet, ESlint, and Prettier Extensions

We can leverage GitHub Actions to automate the running of all of our accessibility auditing tools as part of a Continuous Integration (CI) workflow. 

Auditing tools will only catch a percentage of potential accessibility issues, it is no replacement for manual testing.  But being able to automate the auditing will add efficiencies to our testing and provide an early warning system that can be run much more frequently than it’s practical to perform manual testing.  Additionally, we can use our CI suite as a safety net to prevent code changes that break accessibility from being able to be merged.

## Resources
* https://app.egghead.io/lessons/react-set-up-eslint-to-audit-accessibility-issues-in-react
* https://docs.cypress.io/guides/continuous-integration/github-actions#Basic-Setup
* https://github.com/cypress-io/github-action

Automate Accessibility Audits with GitHub Actions

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.

javascript

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?

React is one of the web’s most popular frameworks for building JavaScript applications. 

If you know what you’re doing, React can drastically simplify how you build, use, and maintain code.

Whether you’re a React newbie or you’re ready for advanced techniques, you can level-up with egghead. Explore our in-depth courses, lessons, and community resources to build more powerful applications and crack open your career.

react

Nx already comes with a default TypeScript setup. Although you can opt-out of that and generate plain JS based components, especially in a large setup TypeScript can be beneficial in uncovering potential issues early. To add an extra level, Nx also comes with preconfigured eslint for all the apps and libraries. In this lesson we're going to explore the lint setup and how it can be used.

Linting a React app with Nx

In this lesson you will learn how to use the eslint yeoman generator to scaffold a new plugin to provide custom rules for your project. 
You will also be able to check the basic skeleton for an eslint ruleand a working example rule to apply a naming convention for async functions.

Scaffold an eslint Plugin with Yeoman

We have a number of options to use when testing for accessibility issues concerning alternative text for images.  The react-axe library and axe browser extension will both report when an image is missing alternative text.  The tota11y browser extension will annotate any images that are missing alternative text.  Running eslint with the eslint-plugin-jsx-a11y plugin installed will report on any `<img>` elements missing an `alt` attribute.  Finally, we can use a screen reader to actually hear what is read when an image has focus.

Test for Image Alternative Text Accessibility Issues

Images must have text alternatives that describe the information or function 
represented by them so they can be read and understood by those using screen readers.

## Alternative text for images
* All `<img>` elements should have an `alt` attribute provided
    * When not provided many screen readers will fallback to reading the file name instead
* The `alt` value should not include words like _“image”_, _“picture”_ or _“icon”_
    * Screen readers are already announcing that the element is an image
* Images that are decorative only and provide no information or function to the page should be hidden from Assistive Technologies by providing an empty `alt` attribute (`alt=””`)

## References
* https://www.w3.org/WAI/tutorials/images/
* https://www.w3.org/WAI/tutorials/images/decision-tree/
* https://www.w3.org/WAI/tutorials/images/tips/
* https://www.w3.org/WAI/tutorials/images/informative/
* https://www.w3.org/WAI/tutorials/images/functional/
* https://www.w3.org/WAI/tutorials/images/textual/

Define Images with Appropriate Text Alternatives

Our accessibility auditing toolkit makes it very easy for us to test for any form controls that are missing labels or are not correctly associated with their labels.  Running Eslint with the eslint-plugin-jsx-a11y installed will show us any form controls with missing or unassociated labels.  Running react-axe or using axe to audit a web page will similarly list any of these findings.  Finally using tota11y we can annotate any form controls on a page that are missing labels.  This is definitely some of the lower hanging fruit that we can easily find and fix when making our applications accessible!

Test for Form Control Label Accessibility Issues

Labeling inputs, elements, and widgets add context and clarity for assistive technology such as screen readers.  Elements of a `<form>` such as `<input>` or `<textarea>` or `<select>` should be labelled by using a `<label>` element.  Placeholder text can be used in addition to a label but should not be used in place of a label as not all assistive technologies respect placeholder text.

Ensure Form Controls have Accessible Labels

Our first layer of defense when building accessible React applications is to add some auditing tools to our development workflow. This should include adding static analysis checking for common accessibility standards and best practices. We can get this with the latest eslint plugin: "eslint-plugin-jsx-a11y". If you are already linting your projects adding this plugin should fit very smoothly into your workflow.

## Resources
1. [List of all the rules supported by eslint-plugin-jsx-a11y](https://github.com/evcohen/eslint-plugin-jsx-a11y#supported-rules)
2. [Comparison of the difference in rules between recommended and strict mode](https://github.com/evcohen/eslint-plugin-jsx-a11y#difference-between-recommended-and-strict-mode)
3. [Background on how the Accessibility API implemented by browsers interfaces with Assistive Technologies](https://github.com/evcohen/eslint-plugin-jsx-a11y#some-background-on-wai-aria-the-ax-tree-and-browsers)

Set up ESLint to Audit Accessibility Issues in React

JavaScript is great! JavaScript is also full of features and flexible options that can make it easy to introduce bugs. ESLint uses static analysis to check that your code adheres to a list of rules to help you avoid some specific runtime errors. ESLint is highly configurable, so in this lesson, we'll install ESLint and configure some baseline rules for our boilerplate.

Avoid Common JavaScript Errors with ESLint 

Nuclide is the IDE Facebook employees use to write React code. But setting it up to use Flow type checking and Eslint to lint files on the fly is tricky. This video shows you how. 

Setup Nuclide to use Flow and Eslint (Mac)

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

This lesson demonstrates how to utilize DeepSeek's R1 model to access its reasoning capabilities and then seamlessly transition to other models for subsequent tasks. By extracting the reasoning output from DeepSeek R1, you can leverage its powerful reasoning while gaining the speed, cost efficiency, and configuration flexibility of alternative models. This two-phase approach begins with DeepSeek’s new R1 model, praised for its open-source nature and value. You then gain the adaptability to switch to other models depending on your needs or existing workflows. This lesson provides a step-by-step walkthrough of this process, along with demo code to help you implement this technique yourself.

Combine DeepSeek R1 Reasoning with GPT 3.5 Turbo for the Cheapest, Fastest, and Best AI

While much focus in AI has been on optimizing input and generating concise outputs, a new model in Google's AI Studio dramatically expands output possibilities with a capacity of 65,000 tokens. This represents a significant shift, opening doors to new application scenarios, especially for developers and creators. This lesson explores a practical and immediately useful scenario: leveraging this large output capability within Google's AI Studio to generate extensive sample datasets for your projects. Whether you are developing a new application, building a resource, or require robust datasets for testing and validation, this model offers a powerful solution. We'll demonstrate how to move beyond the constraints of short responses and utilize the full potential of large output models to generate the data volume and variety you need, enhancing your development workflow through Google's AI Studio.

AI Studio's New 65k Output Opens Exciting Possibilities

This lesson explores how to use Cursor to generate and maintain English specifications as a form of living documentation. Learn how these automatically created documents can serve as a consistent and up-to-date representation of your code's behavior. The video highlights how reviewing and refining these English specifications can help ensure that code modifications align with the intended purpose and that documentation accurately reflects the current codebase, promoting better long-term code maintainability and clarity.

Here's the "english-spec.md" used in the video:

```markdown
> You are an AI specialized in analyzing source code and producing structured, plain-English representations of its functionality.  
>  
> **Your Task**:  
> 1. Read and interpret the code I provide.  
> 2. Produce a technical, English-only summary of what the code does.  
> 3. Use headings and bullet points to clearly outline the roles of each function, class, variable, or important logic block.  
> 4. **Do not include any actual code** in your final output. Instead, translate the code’s content into an English explanation (like a specification or documentation).  
> 5. Keep the explanation concise but thorough. Focus on explaining the purpose, process, and relationships between functions or modules in the code.  

**User Prompt to the AI**:

> **Instruction**: Convert the following code into a single file of pure English text that outlines exactly what each part of the code does. Use bullet points, headings, and descriptive language. Do not show any code—only explain how the code behaves. This is intended to serve as a human-readable spec or “translation” of the code.  
>  
> **Code**:  
> ~~~  
> [PASTE YOUR CODE HERE]  
> ~~~  

**Example Input/Output #1**:

- **Example Code (Input):**
  ~~~js
  // example1.js
  const greetUser = (userName) => {
    const greeting = `Hello, ${userName}!`;
    console.log(greeting);
  };

  greetUser("Alice");
  ~~~

- **Example Explanation (Output)**:
  ~~~
  # Overview
  - This file defines a single function which greets a user by name and prints a message to the console.
  
  # Function: greetUser
  - Accepts one parameter (`userName`).
  - Constructs a greeting string that combines static text with the `userName`.
  - Outputs the greeting using `console.log`.

  # Behavior Flow
  - The function is called with the argument "Alice".
  - Upon invocation, "Hello, Alice!" is logged to the console.

  # Key Points
  - Shows how to create a greeting with a dynamic name.
  - Demonstrates basic string interpolation and console logging.
  ~~~

**Example Input/Output #2**:

- **Example Code (Input):**
  ~~~py
  # example2.py
  class Calculator:
      def __init__(self, initial=0):
          self.value = initial
      
      def add(self, amount):
          self.value += amount
      
      def subtract(self, amount):
          self.value -= amount
      
      def get_value(self):
          return self.value

  calc = Calculator(10)
  calc.add(5)
  calc.subtract(3)
  result = calc.get_value()
  print(result)
  ~~~

- **Example Explanation (Output):**
  ~~~
  # Overview
  - This file defines a `Calculator` class that keeps track of an internal numerical value and provides methods to modify it.
  
  # Class: Calculator
  - **Constructor** (`__init__`):
    - Accepts an optional initial value (default is 0).
    - Stores the initial value in a `value` property.
  - **Method: add**:
    - Takes an `amount` and increments the internal `value` by that amount.
  - **Method: subtract**:
    - Takes an `amount` and decrements the internal `value` by that amount.
  - **Method: get_value**:
    - Returns the current internal `value`.
  
  # Behavior Flow
  - An instance of `Calculator` is created with an initial value of 10.
  - The `add` method is called with 5, raising the value to 15.
  - The `subtract` method is called with 3, lowering the value to 12.
  - The `get_value` method is called to retrieve the current value (12).
  - The result (12) is printed to the console.

  # Key Points
  - Demonstrates basic OOP with a class that manages state.
  - Showcases constructor, addition, subtraction, and retrieval of a stored value.
  ~~~  

---

## Final Prompt

Below is a full, combined version of the prompt you can provide to an AI to guide it in generating the English-only, bullet-pointed explanation. Feel free to modify or adapt this as needed:

~~~
You are an AI specialized in analyzing source code and producing structured, plain-English representations of its functionality.

Your Task:
1. Read and interpret the code I provide.
2. Produce a technical, English-only summary of what the code does.
3. Use headings (e.g. # Overview, # Functions, # Classes, # Behavior Flow) and bullet points.
4. Do not include any code in your final output—only explain how the code behaves.
5. Keep it concise but thorough, focusing on purpose, process, and relationships between functions or modules.

Below are some examples of how code might be transformed into an English-only explanation:

Example Input:
-------------------
~~~js
// example1.js
const greetUser = (userName) => {
  const greeting = `Hello, ${userName}!`;
  console.log(greeting);
};

greetUser("Alice");
~~~
Example Output:
-------------------
# Overview
- This file defines a single function which greets a user by name and prints a message to the console.

# Function: greetUser
- Accepts one parameter (`userName`).
- Constructs a greeting string that combines static text with the `userName`.
- Outputs the greeting using `console.log`.

# Behavior Flow
- The function is called with the argument "Alice".
- Upon invocation, "Hello, Alice!" is logged to the console.

# Key Points
- Shows how to create a greeting with a dynamic name.
- Demonstrates basic string interpolation and console logging.


Example Input:
-------------------
~~~py
# example2.py
class Calculator:
    def __init__(self, initial=0):
        self.value = initial
    
    def add(self, amount):
        self.value += amount
    
    def subtract(self, amount):
        self.value -= amount
    
    def get_value(self):
        return self.value

calc = Calculator(10)
calc.add(5)
calc.subtract(3)
result = calc.get_value()
print(result)
~~~
Example Output:
-------------------
# Overview
- This file defines a `Calculator` class that keeps track of an internal numerical value and provides methods to modify it.

# Class: Calculator
- **Constructor** (`__init__`):
  - Accepts an optional initial value (default is 0).
  - Stores the initial value in a `value` property.
- **Method: add**:
  - Takes an `amount` and increments the internal `value` by that amount.
- **Method: subtract**:
  - Takes an `amount` and decrements the internal `value` by that amount.
- **Method: get_value**:
  - Returns the current internal `value`.

# Behavior Flow
- An instance of `Calculator` is created with an initial value of 10.
- The `add` method is called with 5, raising the value to 15.
- The `subtract` method is called with 3, lowering the value to 12.
- The `get_value` method is called to retrieve the current value (12).
- The result (12) is printed to the console.

# Key Points
- Demonstrates basic OOP with a class that manages state.
- Showcases constructor, addition, subtraction, and retrieval of a stored value.

---

**Now**: Please apply the same conversion process to the following code. Convert it into a plain-English document that describes what the code does in detail, using bullet points and headings. Create the document next to the original with the filename as `${fileName}.md`. Do not include any source code in the output—only the explanation:

[INSERT YOUR CODE HERE]
```

Programming in English with Cursor

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.