Learn Ionic, Netlify and Polymer

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

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Serverless Function 4

Serverless Function 3

Serverless Function 2

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Netlify Serverless Function 1

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Get started building web applications with Angular and Firebase.

In this course, you'll learn how to set up and use Firebase in your Angular applications using the AngularFire library.

We choose the AngularFire library because it is an official library created by the Firebase and Angular teams to work better with Angular.

It helps you by wrapping everything into observables and helps update zones. 

By the end of this course, you'll be able to build web applications using Cloud Firestore as your database, Firebase Authentication as your Auth system, Cloud Storage to save files, and Firebase Hosting to deploy your applications to the web.

TypeScript is a typed superset of JavaScript that compiles to plain JavaScript.

typescript

Build Full Stack Web Applications with Angular and Firebase

Ionic is the beautiful, free and open source mobile SDK for developing native and progressive web apps with ease.

ionic

Now that file uploading works, we want to actually show that a task has files associated with it. To do this we will need to update the task object with a file property that we'll push files too.

In this lesson, we'll use Cloud Storage methods like getDownloadUrl() to get the file's download URL from our bucket.

Then we'll add that file's information to our task and persist it in the database to show the list of files in a task to the user.

While we do this, you'll see how we can easily add a spinner when files are being uploaded using Ionic loadingController.


Save and Display Tasks Files Utilizing Firebase Cloud Storage getDownloadUrl

A scenario you will inevitably run into is users needing to reset their passwords for security reasons or they lost and forgot their password.

We'll learn how to send our users an email to reset their passwords, after we send the email, we'll display a notification alert with ionic alertController to the user and redirect them to the login page.


Send a Password Reset Email Using Firebase Authentication with sendPasswordResetEmail

Now it's time to create a template for our authentication page using Ionics page generation CLI.

We'll show how to use the same page for all of our authentication operations by reading the parameters from the URL and displaying the right form elements and buttons depending on the parameters present.


Create an Authentication Page Template with Ionic Page Generation

We'll learn how to delete documents from the database. This action is pretty straight forward, we'll add a delete button that will call Firestore `deleteDoc` and pass in the task id.

We'll also explore a good practice when performing destructive operations (__like deleting database objects__) of adding a confirmation step to make sure our users don't delete objects by accident. We'll do this with the Ionic Alert Controller.


Delete a Document with a Confirmation Step from Firestore

We'll evaluate 2 good practices when adding a new task.

First, we'll show the users a toast alert to notify them that their document was saved in the database. We'll do this with a toast component that ionic makes available to us

And second, we'll use Angular's router to navigate the user back to the task list.

Notify Users Their Database Operation Worked with a Toast Alert

We'll create the template for our new page and set everything up so that we can use this page to create new tasks. The first thing we will do is create a BehaviorSubject task variable that we'll store form values in to send to Firebase.

Because we are using the ionic framework we'll lean heavily into this when creating our templates. You'll see how we bind text values to the object we'll send to Firebase as well as a selector component that will use `ion-segment`.

We'll also see a tip on handling the `async` pipe in a top container in our template so that we don't have to manually add it everywhere we'll render a property from an observable


Create a New Task Form Page Template with Ionic

firebase

There are 2 different ways to get a document's ID when using `@angular/fire`.

You can add the parameter `{ idField: 'id' }` to your collection when using the `collectionData()` observable.

You can also use the observable `collectionChanges()` and access the internal metadata of the document to manually get the ID and add it to the resulting object.

Code sample: https://github.com/javebratt/angularfire-idField

Access a Firebase Document's ID Even when It's Not Stored in the Document with angularfire

In this lesson, you'll learn how to set up a new Vite project and configure it to use React with TypeScript.

Set up a Vite project with React and TypeScript

In this lesson, you'll globally install the Netlify CLI and use its dev command to run your site locally. Netlify automatically detects if it's a Vite project!

Set up Vite local dev with the Netlify CLI

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

Netlify has the power to automatically detect serverless functions in your project and run a functions server with hot reloading for you. 

In this lesson, you'll learn how to create serverless functions in your Netlify app using TypeScript

Add TypeScript powered serverless functions to a Netlify project

In this lesson, you will learn how to create a Netlify serverless function, powered by TypeScript, to handle form submissions.

Create a serverless form submission handler with TypeScript

In this lesson, you'll learn how to set up a submit handler that posts your form data to a serverless function.

Submit form data to a Netlify serverless function

 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

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.

Search 100s of Issues with GitHub CLI as Context for AI Studio

I often find myself wondering how to use certain APIs in certain situations, and I have a couple of keywords that I try and search up on Google. 

What you can do in this situation is turn to GitHub and see how other people have actually used this code on public projects. The GitHub CLI enables us to run searches like this, and we can take the results and work on them programmatically.

Inside of Cursor with their Composer AI agent, we can search for the files we want, tell the agent to download them, and inspect them for better understanding of how those things work together.

Search All of GitHub's Code and Pass the Results to AI Agents in Cursor

Implement virtual scrolling to handle large datasets in an HTML table. Start with a basic table that renders 10,000 rows of data. The browser can struggle with this amount of DOM nodes to render at one time, especially on low end devices. 

We implement tanstack react virtual to render only the necessary amount of rows the user is viewing. The implementation includes proper column sizing, accessibility considerations, and convenient scroll controls, resulting in a smooth and performant table experience regardless of the dataset size.

Create a row virtualized HTML table with Tanstack Virtual

Learn how to implement virtual scrolling in React tables using TanStack Table and Tanstack Virtual with the useWindowVirtualizer React hook.

The most difficult tasks will require the strongest AI models. And those models simply aren't available as AI agents inside of your tooling. So the best workflows are to drag and drop the files you need to be changed and analyzed inside of a reasoning model such as OpenAI's O1 Pro, then letting it create a giant plan for your dumber AI agents to work on. The key here is that instead of just copying and pasting the entire plan into Cursors Composer or your AI agent, it's to create a file inside of your project and ask your agent to tackle the plan one step at a time. This allows you ample opportunity between each step to test and verify the micro steps along the way. Otherwise, as I've experienced many times, a session can go way off track and you burn a lot of time and burn a lot of AI requests Cursors Composer and it starts churning through a plan Cursors Composer and making lots of unwanted changes. Cursors Composer and it's to guide an AI agent to hold its hand along the way, especially through the most complex tasks. Cursors Composer and the most complex tasks Cursors Composer and the most complex tasks require a step-by-step plan.

Planning AI Agent Sessions with Reasoning Models

AI agents will inevitably make mistakes—it's just a matter of when. A key tool in your toolbox, once they do make mistakes after working on a problem for a while, is to use **git diff** to capture all of the changes they've made. 

Once you have those changes in a text file, you have a portable document that you can test against other AI models. This allows you to move the problem into smarter reasoning models with smaller context windows, helping you isolate and focus on the issue at hand.

**git diff** has been invaluable when working with AI agents because they'll often make many good changes but also slip in one tiny error. Finding that one small mistake is **git diff**’s superpower.

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