Learn Angular-material, Lighthouse and Nativescript

Open source framework for building truly native mobile apps with Angular, TypeScript or JavaScript.

nativescript

Learn how to construct sophisticated custom components using UIViewController. Understand how to construct UIButton's programmatically and attach tap events via NativeScript using the static ObjCExposedMethods property. Also learn how to save images to the user's iPhone Camera Roll using native api's. Specifically we will look at creating a custom {N} view component for SwiftyCam (a Snapchat inspired implementation: https://github.com/Awalz/SwiftyCam).

Create iOS custom UIViewController components with NativeScript for Angular

Using the [NativeScript-DrawingPad](https://github.com/bradmartin/nativescript-drawingpad) plugin in a NativeScript app you can create a drawing pad. This is great for capturing signatures or any touch drawing on the device.

Capture Drawings and Signatures in a NativeScript app

We will use the [NativeScript-Email plugin from Eddy Verbruggen](https://github.com/EddyVerbruggen/nativescript-email) to compose email messages from our app that the user can send out.

Composing emails in a NativeScript app

We will use the [nativescript-phone plugin](https://github.com/msywensky/nativescript-phone) which provides a simple API to access the device's default phone and SMS applications. This allows us to dial phone numbers from our app using the device's phone capabilities as well as pre filling SMS messages for your app's users.

Using the device Phone and SMS with NativeScript

We will use the [NativeScript Speech Recognition plugin by Eddy Verbruggen](https://github.com/EddyVerbruggen/nativescript-speech-recognition) to convert speech to text. The plugin provides a clean abstraction over the [Android SpeechRecognizer](https://developer.android.com/reference/android/speech/SpeechRecognizer.html) and the [iOS SFSpeechRecognizer](https://developer.apple.com/reference/speech/sfspeechrecognizer).

Use Speech Recognition with NativeScript

We will use the NativeScript Text-to-Speech plugin to have the iOS and Android speech synthesizers speak a provided text.

Using Text to Speech with NativeScript

NativeScript is a framework that let's you build JavaScript to native applications. In this lesson, we will set up a native app using the NativeScript command-line interface. We will then take a brief look at some of the project it generates.

Set up a native app project with the NativeScript CLI

AngularJS is an open-source JavaScript framework, maintained by Google, that assists with running single-page applications. Its goal is to augment web-based applications with model–view–controller (MVC) capability, in an effort to make both development and testing easier.

angularjs

Themes convey meaning through color, tones, and contrasts. And the theme color palettes, alphas, and shadows deliver a consistent tone to your application and a unified feel for all Angular Material UI components. Theming allows developers to change the intention and meaning of the application by changing the colors and shadows. 

Accessibility is a huge - often overlooked - feature in modern web applications. Angular Material components all implement ARIA features whenever possible. And for usage scenarios where the ARIA attributes are not explicitly provided and cannot be inferred, then Angular Material will provide details console warnings alerting the developer.

Let’s use the Angular Material Theming service to change the background, primary, accent, and warning colors used within the entire application. These will be configured at startup using the $mdThemeProvider.  

Let’s also resolve the two ARIA warnings shown in console. These originate from icon buttons where the ARIA label cannot be inferred. So let’s add a static aria-label and a dynamic, interpolated aria-label to those buttons.

> This course presented by Thomas Burleson and Aaron Frost

Angular Material: Theming and ARIA

Most Angular Material UI components are declarative and used directly in the HTML markup. Some components, however, are programmatic and must be configured and invoked from Javascript. Programmatic components have a short-term, limited DOM lifespan and include Dialogs, Toast, and BottomSheet.

Let’s use the BottomSheet service to configure and display an Angular Material BottomSheet container which in turn will display a nested, custom Contact Sheet view.

> This course presented by by Thomas Burleson & Aaron Frost.

Angular Material: Using a BottomSheet

Both flexbox CSS and the Angular Material Layout allow web applications to `respond` to the size of the browser at any given point. No matter what the browser width may be, the web app adjusts its layout sizing accordingly. Combine responsive functionality with media query support and your web applications will have `adaptive` features to adapt to the width of the browser at a specific points. More than fluidly adjusting the widths and heights of elements, Adaptive applications can change the rendered UX with new positions, new components, and new styles. Angular Material Layout hides the complexities of implementing adaptive features with a singularly unique and simple HTML syntax.
Let’s use the Adaptive extensions of the Angular Material API to hide the SideNav on small devices (like iPhone or Android). We will explore the use of the $mdMedia service to easily lock open the SideNav on larger devices. And we will see how the $mdSideNav service can be used to programmatically close the SideNav after a user is selected.

> This course presented by Thomas Burleson and Aaron Frost.

Angular Material: Adaptive Layouts

Angular Material UI components have been designed from the ground-up to use dynamic, live data. Supporting AngularJS interpolation, expressions, and databindings… each component exposes an intuitive API and fully supports the existing ng-<xxx> directives published in AngularJS.

Let’s replace the hard-coded, static HTML with dynamic, mock data using AngularJS data bindings, ng-repeat, and the ng-click directives. Our UX remains unchanged, yet now we are using custom application logic and dataservices.

> This course has been created by Thomas Burleson & Aaron Frost.

Angular Material: UI Components with Dynamic Data

Angular Material is an Angular-native, UI component framework from Google. It is a reference implementation of Google's Material Design and provides >30 UI components and services essential for mobile and desktop AngularJS applications.

In this course, we will quickly build a real-work application Angular UI application, take a tour of Angular Material, and learn how ngMaterial can be used in your projects.

*presented by Thomas Burleson and Aaron Frost*

Introduction to AngularJS Material

The Angular Material Layout API wraps the flexbox CSS features with an amazingly easy, powerful HTML markup API. The Layout API hides the complexities of the CSS, is intuitive to use, and eliminates the need for developers to become flexbox experts to implement modern page layouts. 

In this lesson we will learn how to use the Angular Material Container components and the Layout API to implement the layouts specified in design wireframe.

> This course has been created by Thomas Burleson and Aaron Frost. 

Angular Material: Containers with the Layout API

Learn how to install Angular Material with `npm install`  and load the required libraries and stylesheets into your blank web page.

> This course has been created by Thomas Burleson and Aaron Frost

Angular Material: Installing with NPM

Angular Material provides over 30 UI components and services. The framework offers a suite of components and containers: from simple Button components with built-in ink and hover effects, theming, and ARIA support… to more complex container components like mdList and Tabs.  

Let’s use some of those components in our SideNav and Content containers. For now we will use hard-coded, HTML markup. This allows us to confirm the UX matches that specified in the design docs before we start working on our application logic.

> This course has been created by Thomas Burleson and Aaron Frost.

Angular Material: Intro to UI Components

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.

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.