Learn Ember, Reactfire and Turborepo

Turborepo is a fast build system for JavaScript and TypeScript.

turborepo

Turborepo is a task runner that helps speed up and manage your Monorepos. It's not a dependency management tool. It knows nothing about your dependencies. 

It speeds up Monorepos by using local and remote caching as well as incremental builds. It helps to manage your repo with very handy and easy-to-use scripts. 

Here is the [npm-workspaces repo](https://github.com/alejandronanez/npm-workspaces)

So let's hop in and learn about Turborepo!

Note: This course is a continuation of the course [Introduction to Monorepos with NPM Workspaces](https://egghead.io/courses/introduction-to-monorepos-with-npm-workspaces-c03f500b) where we initially build out the Monorepo that is used in this course. It is highly suggested to watch that course first before jumping into this one. 

What is Turborepo?

At the root of our project, we'll run `npm install turbo --save-dev` to install Turborepo.

We'll also look at how to configure Turborepo in the `turbo.json` file. We'll look into the [$schema](https://turborepo.org/schema.json) and how it affects our configuration. 

Install Turborepo in an Existing Monorepo

With our npm scripts, if utils can't build, then the dashboard and blog can't build or run their tests. Turborepo Pipelines changes that. Using the pipeline, we can set up caching, what our scripts depend on, and where we want our logs to be output. 

Also since we now have Turborepo installed and configured our pipelines, we can remove concurrently from our scripts and dependencies. 

Migrate NPM Scripts to Turborepo Pipelines

We are going to be going through Turborepo speeds up your builds and testing with caching. When a command is first run in Turborepo, it gets cached. This way if something has changed in one of your repos in your Monorepo, it will detect that change. For the repos that haven't changed, it will pull their info from the cache inside of `node_modules` instead of fully re-running that command. For the repo that has changed, it will run that command solely on that repo. 

Understand Turborepo Local Cache

It's fairly straight forward to create repo specific pipelines with Turborepo. The script goes like this: `{monorepo-name}/{repository}#{script-name}`. For example, if we wanted to run the typecheck command in just the dashboard repo, it would look like this: `@monorepo/dashboard#typecheck`. Lastly, we will make sure that it `dependsOn` the `utils#typecheck` pipeline. 

Create Repository Specific Turborepo Pipelines

A dependency graph is exactly what it sounds like! A visual graph created by Turborepo to show you your dependencies and what dependencies the projects rely on. For our Monorepo, we'll run `npx turbo run build --graph` in the root of our project and that will build the dependency graph for all of our projects.

We can also do one with a graphic but that requires the [Graphviz](https://graphviz.org/download/) library. We can edit our command to have some arguments: `npx turbo run build --graph=graph.pdf` and it will create a graphic in a .pdf file. 

Generate a Dependency Graph for Monorepos Using Turborepo

You can set up all of your specific pipelines in the turbo.json file, or you can filter through your pipelines in the terminal. If we wanted to run the `typecheck` command in just the `utils` package, our command would look like this: `npx turbo run typecheck --filter=@monorepo/utils`. You can remove `@monorepo` as long as the `utils` package is unique. 

Turborepo also gives you the option to filter your commands based on what files have changed on your branch using `--filter="[HEAD^1]". 

Now that we know a bit more about Turborepo, we can edit all of the scripts that we build in the previous course to use `turbo` instead of `npm`. 

Filter Pipeline Tasks Using Turborepo

By default, Turborepo will stop its execution if it runs into an error. We may not want that if we want Turborepo to continue in the projects that don't have an error. We can do this by adding the `--continue` flag to the end of our command. 

Prevent Turborepo Exiting Early on Failing Tasks

Another really good tool that Turborepo offers is the `--dry` flag. The `dry` flag will display details about the affected workspaces and tasks that would be run. It will help you to know what Turborepo is doing under the hood. 

Preview Turborepo Tasks at the Pipeline Level

The logs produced by Turborepo can get really really long. Turborepo give us a flag, `--output-logs` and if we add on the argument `new-only`, it shortens the logs to just the new information for the repositories that have changed. 

Shorten Turborepo Logs using --output-logs

Remote caching is key when coworking on a project. Using Turborepo, you can upload your cache to the cloud and use it everywhere else. For example, if your coworker switches to your branch and runs the build, they can have your most recent cache saving them time. 

We will start off by logging into Vercel and Turborepo then linking our Turborepo account to our Vercel account. Once that is done, we run `npx turbo link` to connect to our remote cache. Then in our Vercel dashboard, we will need to do some configuring to finish it up. 

Enable Remote Caching in Vercel

Now that we have Turborepo installed, configured, and we have some knowledge about it, let's deploy our two client-side applications, dashboard and blog, to Vercel. We'll link our Github to Vercel and point it towards our Monorepo. We'll then run through all of the configurations and commands needed to get our apps deployed. 

Deploy the Client-Side Apps in a Turborepo Monorepo to Vercel

Github Actions helps to automate the building, testing, and deploying of your applications. We'll configure our actions in the `ci.yml` file in a new directory called `.github/workflows`. When that file is configured, we can update our scripts in our package.json to run off of those. We will also need to make/set up our `TURBO_TOKEN` and our `TURBO_TEAM` which we will create on Vercel and Github. 

Enable Github Actions with Turbporepo Remote Caching

Now you might have a project that currently isn't in your Monorepo that you want to add to it. We can copy that project over into our `apps` folder and then update the `package.json` to update the name to make it consistent across our apps. We'll update the dev port to make sure it's not going to run on the same port as one of our other applications. Lastly, we'll update the build pipeline to include our new application. 

Migrate a VueJS Application to an Existing Turborepo Monorepo

A JavaScript framework for creating ambitious web applications.

ember

In this lesson we will create an `updateContent` method that sets the value of our `content` property to the current epoch timestamp. We need to call `toString()` on the `Date.now()` method in order to make TypeScript happy.

```
updateContent() {
  this.content = Date.now().toString()
}
```

We create a constructor that takes the options parameter, call `super(options)` and call into our `this.updateContent()` method.

```
constructor(options) {
  super(options)
  this.updateContent()
}
```

When we refresh our page we can see that the value of `content` is set to the epoch timestamp. 

To make the content really dynamic we use `setInterval()` to call into `updateContent` each second: `setInterval(() => this.updateContent(), 1000)`.

When we save our file we see that our content does not get updated anymore and when we check the console we see that we get an error telling us that: The 'content' property on the my-component component was changed after it had been rendered. The error also informs us that we should Use the @tracked decorator to mark this as a tracked property.

We add the @tracked decorator to our property, we import tracked from @glimmer/component and we refresh the page. We verify that `content` gets updated each second.

We change our `updateContent` to add our the timestamp to the array. When we use `this.items.push(this.content)` to achieve this we see that the list does not get updated. This is because the `@tracked` decorator only tracks the re-assignment of properties.

The way to get this working is by re-assigning our `items` array inside `updateContent`. We assign a new array, de-structure the current items array and add the new content.

```
this.items = [...this.items, this.content]
```



Use dynamic data in a GlimmerJS component

In this lesson we will add a variable called `content` to our component class, initialize it as a string and display the variable in our class using the double curly braces syntax, which is the handlebars expression for expressions, `{ {content }}`. 

After this we create a new class variable called `items`, initialize it as an array with strings. To display this list in our template we add a `<ul></ul>` and inside this unordered list we use the handlebars `each` helper to display the list items.

And inside our each statement we will print a `<li>` tag and render `{{ item}}` inside it.

```
<ul>
  {{#each items key="@index" as |item| }}
    <li>{{item}}</li> 
  {{/each}}
</ul>
```



Use template variables in a GlimmerJS component

In this lesson we will use the ember cli to generate a new component. Running `ember g glimmer-component my-component` generates the template and component class. We change the content of our component and add it to the main template in order to show it on the page.

Create a new GlimmerJS component

[GlimmerJS](https://glimmerjs.com/) is a UI component library built by the Ember.js team. It is fast and lightweight and uses a combination of TypeScript and Handlebars to build the components.   

In this lesson we will use the Ember CLI to initialize a new GlimmerJS project.

We will start by installing Ember CLI globally by running `npm install -g ember-cli/ember-cli`.

Next we will use the `ember` command to create our new project by running `ember new egghead-glimmer -b @glimmer/blueprint` . 

When our project is created we `cd` into the project directory and start the development server. We will view the page in the browser and change the base template.

Initialize a project using Glimmer.js

Monorepos are an amazing way to collaborate on a multitude of projects with other team members. The ability to share code seamlessly between projects and have a single source of truth is paramount when working on projects with multiple moving wheels. 

One of the tradeoffs of a Monorepo is all of the management you have to do to make your projects run flawlessly and simultaneously. Each project has it’s own linting, building, testing, and deploying that it runs whenever code in that project changes.

This becomes a real problem when each of your projects lints, builds, tests, and deploys on every PR into your monorepo. You might be fine with a handful of projects but as your applications scale and you accrue more projects, you will need a way to scale. 

Turborepo is the tool that solves your monorepo’s needs.

Turborepo is a task runner for Monorepos. Turborepo caches the results of your CI tasks, schedules those tasks to run at maximum speed, and only runs tasks on the affected code in your PRs.  And because of remote caching, your coworkers, wherever they are, will have the most up-to-date code possible. 

One of the greatest things about it is that it's easy to use and can be incrementally adopted. Turborepo is a thin layer on top of your Monorepo. 

Turborepo doesn't get in the way as it is only a task runner. You don't have to modify your application code or anything to make it work. 

You’ll learn about

- How to set up caching for both local and remote
- CLI-commands and how they enhance your Monorepo
- Parallel execution of your tasks

So hop in and learn about Turborepo today!

Prerequisite: This course is a continuation of Introduction to [Monorepos with NPM Workspaces](https://egghead.io/courses/introduction-to-monorepos-with-npm-workspaces-c03f500b). To get the most out of this course, watch [Monorepos with NPM Workspaces](https://egghead.io/courses/introduction-to-monorepos-with-npm-workspaces-c03f500b) first. 

A Monorepo is where you have multiple projects inside a singular repository.

monorepo

Migrate a Monorepo from NPM Workspaces to Turborepo

<p>Today Joel catches up with Iheanyi Ekechukwu. Iheanyi is a Product Engineer currently working at DigitalOcean. He previously worked at IBM on Watson. They also talk about Iheanyi's education, stack, and side projects</p><p>Iheanyi started out majoring in Computer Engineering, but switched to Computer Science after he figured out hardware just wasn't for him. He now lives and works in Brooklyn and spends most of his time coding (though he always brings his design skills to the table).</p><p>Iheanyi's design comes from a dual degree program at Notre Dame, the college where he graduated. He noticed a lot of subpar interfaces coming from pure programmers, and he was frustrated with that, so he took his school's opportunity to learn design and apply it to his work. Even if he isn't a designer, he uses his skills daily to communicate with designers and make whatever he works on that much better.</p><p>Iheanyi started using Ember back during college. He was frustrated by his school's class search interface, and he set out to improve it. Ember and Rails were like a match made in heaven for him, Ember having been authored by ex-Rails core team member, Yehuda Katz.</p><p>Joel discusses with Iheanyi what he's currently using in his work. They get into GO, and how Iheanyi has enjoyed working with a statically typed language when doing back-end work. Not having to worry about full test coverage when refactoring has been great!</p><p>Lastly, they talk about the various side projects Iheanyi has going. Such as Interface Lovers, a blog where top designers are interviewed and share their work music playlists. Also, Seeker, a job-board app that allows you to connect your strip account to it and have companies submit jobs.</p><hr /><h3>Transcript</h3><p><a href="https://egghead.simplecast.com/episodes/47aebd17/transcript">"Iheanyi Ekechukwu on education, programming, and managing side projects" Transcript</a></p><h3>Resources</h3><ul><li><a href="https://seeker.company">seeker</a></li><li><a href="https://interfacelovers.com/">Interface Lovers</a></li><li><a href="http://creative.black/">Creative Black</a></li><li><a href="https://www.ibmchefwatson.com/">Chef Watson</a></li></ul><h3>Iheanyi Ekechukwu</h3><ul><li><a href="https://iheanyi.com/">Website</a></li><li><a href="http://www.twoblacknerds.com/">Podcast</a></li><li><a href="https://twitter.com/kwuchu">Twitter</a></li><li><a href="https://github.com/iheanyi">Github</a></li><li><a href="https://egghead.io/instructors/iheanyi-ekechukwu">egghead.io</a></li></ul><h3>Joel Hooks:</h3><ul><li><a href="https://twitter.com/jhooks">Twitter</a></li><li><a href="https://joelhooks.com/">Website</a></li></ul>

Today Joel catches up with Iheanyi Ekechukwu. Iheanyi is a Product Engineer currently working at DigitalOcean. He previously worked at IBM on Watson. They also talk about Iheanyi's education, stack, and side projects

Iheanyi Ekechukwu on education, programming, and managing side projects

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.