Learn Elm, Reactfire and Scss

Sass is the most mature, stable, and powerful professional grade CSS extension language in the world.

scss

Learn the essentials of enabling semantic form validation HTML and styles in preparation to use our form design system with the validation solution of your choice.

We will add an SVG to our form descriptions when the error class is applied and look at a workaround to style the SVG through a Sass function.

Create Accessible Styles for Invalid Form Fields

Let's add a key missing element to our form design system - the submit button! Learn how to reset browser styles, and use our theme system to create accessible styles across `:hover`, `:focus`, and `:disabled` states.

Create Custom CSS Styles for Form Submit Buttons

Often we can improve the user experience by grouping related fields, such as first and last name. In these cases, it's appropriate to include `<fieldset>`. We'll first learn how to semantically create the fieldset HTML. Then, we'll set up a series of scalable classes that are flexible for various layout configurations. The layout classes will also be intrinsically responsive - meaning, they will respond to their parent container _or_ the viewport without the use of media queries!

Define Semantic Fieldset HTML and Create CSS Styles For Responsive Form Layout

In the last two lessons, we set up the initial state styles for radio buttons and checkboxes. Now we'll add styles for the focus and disabled states using our existing Sass mixins. We'll do this by layering box-shadow effects of a white border and blurred primary color.

We'll also learn about an up and coming pseudo selector - `:focus-within` - that will be used to apply styles to the label of a control in a `:focus` state.

Create Custom Radio Button and Checkbox CSS Styles for Focus and Disabled States

We'll setup the layout structure for our custom radio button and checkbox styles using CSS grid. These input types will share the `.form-control` component styles. This lesson will apply the initial styles to prepare for creating custom visual control styles.

Similar to focus states for selects, we will need to add a wrapping span and nested span to our radio buttons and checkboxes to apply visual styles to these native elements.

Create A Layout Structure with CSS Grid For Radio Buttons and Checkboxes

In the previous lesson, we set up the initial state styles for form selects and multi-selects. Now we'll add styles for the focus and disabled states, inclusive of a workaround necessary due to the lack of a parent selector in CSS.

The way we will get around this for our focus styles is to add a sibling span element to apply the styles and position those styles on top of the Select element.

Create Custom Select CSS Styles for Focus and Disabled States

We'll begin to apply our theme styles for our text inputs by creating the `.form-field` component. We'll make use of the Sass feature of "mixins" to create `:focus` and `:disabled` styles that can be reused. While creating the `:focus` and `:disabled` states we'll discuss the importance of contrast and keyboard access for accessibility.

An important take-away is that you need at least a 3:1 contrast ratio between your border and background AS WELL AS a 3:1 contrast ratio between your border and focus state.

Use Sass Mixins to Style Inputs with Accessible Contrast and Keyboard Access

Using modern CSS and in particular CSS grid and `clip-path` we can define cross-browser compatible custom select CSS styles inclusive of the dropdown arrow. We'll continue ensuring all styles are re-themeable by using the Sass functions we've already created within our form design system. We will style both the default single select, and a multi-select using `multiple`.

Create Custom Form Select and Multi-select CSS Styles

Learn how to begin addressing browser inconsistencies by resetting base styles across text inputs, textareas, and selects. We'll also review a few quirks related to mobile browsers and responsive design when dealing with form fields. And we'll uncover how to normalize `<select>` which was formerly one of the trickiest fields but is vastly easier now thanks to modern CSS through the `appearance` property.

Create Reset Styles to Normalize Form Fields Cross-Browser

We'll make a starting point for our form layout styles by creating `.form-group` which will add a bit of `margin` between fields. This will be our first design system component, and we'll also include styles for the `label` contained in this class.

Create the `form-group` Component Styles

We'll define the color palette and create the basic screen styles for our project in addition to Sass helpers for our form design system. 

We will set up Sass variables for the initial them and learn how to use the !default flag to allow our system to be easily overridden from project to project, making our form styles ultra transferable and reusable. You'll also learn how to leverage Sass color functions for ease of theming. We'll map the Sass variables to CSS variables so that as we build up our system we can use CSS variables for the most flexibility in our theming.

Initialize the Form Design System Setup with Sass and CSS Variables

View a preview of the form fields we'll be creating in this course, inclusive of custom CSS styles for text inputs, textareas, selects, multiselects, radio buttons, and checkboxes. Then get an overview of the base project and key parts of the Eleventy build process in regards to compiling with Dart Sass and use of Nunjucks for project template scaffolding. 

Prior experience with Eleventy or Nunjucks is not required, but you may also enjoy learning how to [create an Eleventy site from scratch](https://egghead.io/playlists/build-an-eleventy-11ty-site-from-scratch-bfd3?af=2s65ms) in less than 20 mins in my other egghead collection.

Course Introduction: Accessible Cross-Browser Form Field CSS Styles

`elm-ui` is a language for layout and interface design. This is a novel iteration on declarative styling where you can use Elm types and functions to define your UI in a declarative way.

The novel part is that it does not require you to know CSS to be used. The API is very simple and can be learned quickly!

The approach taken by `elm-ui` is based on two big ideas: 
Getting the compiler to verify as much of the layout and styling as possible by defining them in Elm code
Enabling refactoring capabilities of Elm for UI code


Elm is a programming language that provides a clean functional syntax for writing HTML web applications. It promises zero runtime exceptions, fast rendering, time-travel debugging, and much more.

Declarative UIs without CSS with elm-ui

Now that our beautiful dashboard is complete, is time to produce a production ready build with create-elm-app, one of the biggest benefits of using it. You'll notice that it is running on production mode because the Elm Debugger won't show up anymore.

Create a Production Optimised Build with create-elm-app

We will make all the necessary changes to keep track within our model of the device and orientation that the user is using, and change our UI according with that information, adding responsiveness and multiple columns (at last!) to our dashboard.

To do this, we'll need to modify our app state to track the device height and width (which we expose from JavaScript). Then we can use the `classifyDevice` function to pattern match the devices we want to handle, in our case, `Desktop` and everything else (as mobile). We will add a `Browser.Events` subscription that sends a ResizedApp message to our model that defines what device we are on.

Manually Control Responsiveness with Elm classifyDevice

Up until this point, the 4 cards displayed in our dashboard each repeat the same information, so in this lesson, we will be splitting the state into different parts, showing an algebraic mindset and thinking how best represent the state of our app with our custom types. 

We'll start by modeling the selected options in state as a List of a Menu and String. The next step is to actually update the internal state of our menus. We will update `OptionPicked` to receive a string and when it does receive an option, it will filter for just the selected option and append that to state. Finally we will display the options in the `viewCard` component that will filter for the menu that is being selected and in the case of an option selected display that option as a string.

Split the Business Logic of Elm view Functions By Modeling the State

Since every time we interact with one of the dropdowns the information is shared between the 4 of them, the time as now arrives to give each individual dropdown its own state. We will also add subscriptions to listen to when the user clicks outside each dropdown!

To do this, we'll need to extend our state model to include each instance of our `viewCard`. To determine which dropdown that was clicked we will create a `getDropdownState` function that pattern matches the correct card instance. During this process, you'll see how the Elm compiler guides us through adding this functionality with detailed error messages.

You'll see how adding a subscription to close open dropdowns is convenient as `Dropdown` gives us an `onOutsideClick` function that receives the model and dropdown message.

Give Multiple Dropdowns Their Own Individual State with elm-ui-dropdown

This is the only lesson in which we will fallback to CSS to give our dropdown's scrollbar a fancier look because this is very browser dependent and there is no way (yet) to do this with elm-ui.

Customize My First Checkbox Icon with elm-ui

Now that our dropdown is almost finished lets just drop some shadow in the options selector to make it more visually clear that its over any other element in our page. This is an attribute that we can control the `offset`, `size`, `blur`, and `color`.

We will want to do this to our `viewCard` as well. We will also make the `viewCard` function more flexible by adding additional `Html` attributes from the outside to make each card have a different **height.** That way any time you want to override default attributes, you can pass in a new style.

Add elm-ui Border.shadow to Highlight Any Element

Since there is no select or dropdown component backed in into elm-ui, we will be adding another dependency to our project called `PaackEng/elm-ui-dropdown` and adding to it additional styles and settings so that it looks and behaves exactly as we want to.

To make this works, we need to make a few changes:
- We need to add a `dropdownState : Dropdown.State String` to our `Model`
- Add a couple of extra variants to our `Msg` type: `OptionPicked (Maybe String)`, to be dispatched by our dropdown whenever we click on any option, and `DropdownMsg (Dropdown.Msg String)` to update the internal state of the dropdown from the outside.
- Construct our hardcoded list of options of type `List String`.
- Define a `dropdownConfig : Dropdown.Config String Msg` that is going to contain all our customisation of our dropdown.
- Use `Dropdown.view` to display our custom dropdown wherever we need it.

Customize My Own Dropdown with elm-ui-dropdown

Now that we have our cards more or less looking good lets add a button and style it as well so that it serves as a starting point for our dropdown component, this lesson will also help us to learn how to use the `Element.Input` module from elm-ui.

Work with elm-ui Input Components

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.