 Courses from Vladimir Novick

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

In this video we will understand how you can easily get video insights such as questions, follow ups, action items, topics from Symbl Conversation API

Use Symbl Conversation API to Get a List of Insights From the Processed Video in Next.js

In this video lesson, you will learn the basics of Symbl AI Conversation API and get transcripts of the video. You will render them on the screen along with their timestamps

Render Video Transcripts From Symbl Once Processing Is Complete on a Next.js Screen

Symbl has Job API that gives you an option to check your async tasks process status. You will use this Job API in polling manner, to get an update once video has completed processing.

Check the Status of Processing for Symbl Job API by Polling with a Custom useInterval Hook

In this video lesson, you will learn how to send a video for processing to Symbl Async Video API. As a result you will get some parameters that you can use later on to retrieve insights about the video



Send a Video File From Next.js for Processing Using Symbl AI Video Async API

In order to send video for processing you will add a file input along with the preview of what video you gonna upload. 


> It’s important to note, that even though you are using a file input to send video file to Symbl Async Video API, it’s also possible to send URL instead of the file. You can read more about that [here](https://docs.symbl.ai/docs/async-api/overview/video/post-video-url)

Add Video File Input and Preview in a Next.js App

Storing token in the state is not the best idea, so you will migrate from storing the token in local state to a global state. For that you will use React context. With React Context, your token can be easily access from anywhere in the app. You will need that for API calls to Symbl.ai later on.

Store a Token Globally with React Context for Easier Use Anywhere in a Next.js App

In this video lesson you will implement Login functionality by using Symbl oauth2 endpoint.
You will be able to retrieve an access token, that you can use to authorize your REST API calls when calling Symbl APIs


Implement Login in a Next.js App Functionality by Authorizing with Symbl

In this video lesson, we will build ProtectedPage component, which will let us secure our Video Processing page behind the Login screen. The reason for doing so is because in order to process the video, we will need an access token from Symbl.

Secure a Next.js App with a Login Screen

In this video lesson, you will add Chakra UI component library to ease development of UI components. After all we want to focus mostly not on styling, but on implementing video processing functionality

Style a Next.js App Layout with Chakra UI

In this video lesson, you gonna learn how to get started with the basic NextJS web app from scratch. You will be using NextJS React Framework as it’s a modern standard used nowadays in lots of applications. The main reason of choosing NextJS is the lack of initial configuration we need to set up for things to “just work” 

Create a Basic Next.js App

Add Conversation Intelligence to your video or voice application without training Machine Learning models. Integrate speech to text and all of the below capabilities, out of the box:

- Speaker Diarization
- Sentiment Analysis
- Contextual Insights
- Conversational Analytics
- Topics of Discussion
- Entity and Intent Recognition
- Pre-built UI and Symbl JS Elements

In this course we will use [Symbl.ai](https://symbl.ai/) to get transcripts for the video we will upload as well as more meaningful insights. 

Additionally, you will pick up NextJS for the main stack and will use Symbl's RESTful APIs for processing a conversation from a video and rendering transcripts to screen. Get your Symbl account [here](https://platform.symbl.ai/) and start building.

Create Contextual Video Analysis App with NextJS and Symbl.ai

Node.js is a platform built on Chrome's JavaScript runtime for easily building fast, scalable network applications. Node.js uses an event-driven, non-blocking I/O model that makes it lightweight and efficient, perfect for data-intensive real-time applications that run across distributed devices.

node

YugabyteDB is an open source, high-performance distributed SQL database for powering global, internet-scale applications.YugabyteDB is also a cloud-native database, so it can be deployed across both public and private clouds, including Kubernetes environments. In regards to serving as a backend for microservices, YugabyteDB brings together three must-haves: a PostgreSQL-compatible SQL API, low-latency read performance, and globally distributed write scalability. YugabyteDB with its global data distribution brings data close to users for multi-region and multi-cloud deployments.

In this lesson we will see how we can query YugabyteDB from NodeJS using PostgreSQL driver

Query YugabyteDB from NodeJS using PostgreSQL driver

PostgreSQL is a powerful, open source object-relational database system.

postgres

In this lesson we will see how you can run Hasura GraphQL engine on top of YugabyteDB Distributed SQL

YugabyteDB is an open source, high-performance distributed SQL database for powering global, internet-scale applications.YugabyteDB is also a cloud-native database, so it can be deployed across both public and private clouds, including Kubernetes environments. In regards to serving as a backend for microservices, YugabyteDB brings together three must-haves: a PostgreSQL-compatible SQL API, low-latency read performance, and globally distributed write scalability. YugabyteDB with its global data distribution brings data close to users for multi-region and multi-cloud deployments.

Set up Hasura GraphQL engine with YugabyteDB distributed SQL

YugabyteDB is an open source, high-performance distributed SQL database for powering global, internet-scale applications.YugabyteDB is also a cloud-native database, so it can be deployed across both public and private clouds, including Kubernetes environments. In regards to serving as a backend for microservices, YugabyteDB brings together three must-haves: a PostgreSQL-compatible SQL API, low-latency read performance, and globally distributed write scalability. YugabyteDB with its global data distribution brings data close to users for multi-region and multi-cloud deployments.

In this lesson we will see how you can run YugabyteDB Distributed SQL cluster using docker-compose.

Running YugabyteDB Cluster Locally using docker-compose

Bite-size video tutorials for badass web developers.

egghead

YugabyteDB can automatically handle failures and therefore provides high availability . You will create YSQL tables with a replication factor (RF) of 3 that allows a fault tolerance of 1. This means the cluster will remain available for both reads and writes even if one node fails. However, if another node fails bringing the number of failures to two, then writes will become unavailable on the cluster in order to preserve data consistency.

In this lesson we will see how fault tolerance is tested by using workload sample app and by stopping nodes in the local cluster. 

[Written instructions to get up and running.](https://gist.github.com/vnovick/06881138644641b4909983b5d9356dbc)



Explore YugabyteDB fault tolerance on local database cluster

Bash is a Unix shell and command language written by Brian Fox for the GNU Project as a free software replacement for the Bourne shell. Bash is a command processor that typically runs in a text window, where the user types commands that cause actions. Bash can also read and execute commands from a file, called a shell script.

bash

When we run commands in OSX or Linux terminal which output long lines, these lines are wrapped making output sometimes not readable. This is especially true when dealing with tabular data outputted into console. In this lesson we will see a trick that you can do to disable this line wrapping while still being able to read the data.

Disable line wrapping in OSX or Linux terminal

YugabyteDB is an open source, high-performance distributed SQL database for powering global, internet-scale applications.

The Yugabyte Structured Query Language (YSQL) is the distributed SQL API for YugabyteDB and is compatible with the SQL dialect of PostgreSQL. Currently, YSQL is compatible with PostgreSQL 11.2 version. YugabyteDB and YSQL are optimized for RDBMS workloads that need horizontal write scalability and global data distribution while also using relational modeling features, such as JOINs, distributed transactions, and referential integrity (such as foreign keys).

The main components of YSQL include the data definition language (DDL), the data manipulation language (DML), and the data control language (DCL). A number of elements are used to construct these components, including data types, database objects, names and qualifiers, expressions, and comments. Other components are also provided for different purposes such as system control, transaction control, and performance tuning.

In this lesson we will see how we can connect and work with YugabyteDB YSQL shell on a local cluster running on MacOS.


Explore YugabyteDB YSQL shell in local database cluster

YugabyteDB is an open source, high-performance distributed SQL database for powering global, internet-scale applications.YugabyteDB is also a cloud-native database, so it can be deployed across both public and private clouds, including  Kubernetes environments. In regards to serving as a backend for microservices, YugabyteDB brings together three must-haves: a PostgreSQL-compatible SQL API, low-latency read performance, and globally distributed write scalability. YugabyteDB with its global data distribution brings data close to users for multi-region and multi-cloud deployments. 

In this lesson we will see how we can create YugabyteDB cluster locally on our Mac for dev environment and prototyping 

Set up YugabyteDB Distributed SQL Cluster Locally on MacOS

GraphQL is a query language for APIs and a runtime for fulfilling those queries with your existing data. GraphQL provides a complete and understandable description of the data in your API, gives clients the power to ask for exactly what they need and nothing more, makes it easier to evolve APIs over time, and enables powerful developer tools.

graphql

While creating your GraphQL API with [hasura.io](hasura.io), queries, mutations and subscriptions are auto generated for you. In this video I show an API explorer tool inspired by https://github.com/OneGraph/graphiql-explorer  that will help you to compose GraphQL queries by selecting what data you want to present or how you want to filter your queries.
This tool is also available as stand alone tool at [https://graphiql-online.com](https://graphiql-online.com)


Compose GraphQL Queries and Mutations using Hasura Explorer

In this video you will see how you can easily set up auto-generated GraphQL API for your app with Hasura free and open source engine

To get started with Hasura go to [hasura.io](hasura.io)

Create your GraphQL API auto-generated with Hasura


Using Cursor Chat, you can easily reference an entire directory of files and ask it to generate anything based on those files. This opens up the possibility of using your current code as a reference guide to create new code that follows existing patterns. With this approach, the result can be a polished prompt you can use with any AI to generate consistent and reliable output.

Focus less on crafting the perfect prompt upfront - what matters most is testing and iterating based on the AI's responses. The more results you see from the prompt, the more you can reinforce the good results and prune out the bad results until your prompt is polished enough that you can rely on the prompt to give you consistent quality results.


Create AI Prompts Based on a Directory of Files


With Cursor's "Composer" feature, you can select and entire directory and make changes to every file. This video walks through the process of selecting a folder and refactoring all the files from JavaScript to TypeScript. It also demonstrates other tips around generating terminal commands and customizing your main Cursor "Rules for AI".


Run an AI Refactor on Every File in a Directory with Cursor


This lesson breaks down the concept of asynchronous iterators and generators in JavaScript. Using the Node.js glob function as a practical example, you'll learn how Array.fromAsync facilitates the creation of arrays from asynchronous iterables and how generators can improve performance in file processing tasks.

Efficient File Processing in Node.js with Async Generators and Array.fromAsync

Learn the concept of asynchronous iterators and generators in JavaScript and Node.js Array.fromAsync


With the introduction of Svelte 5, the Svelte team has created a CLI, `sv`, that unifies all the tasks that previously spread across a handful of CLIS (create, add plugins, and migrate).

This lesson will create a Svelte project using the new `sv` CLI and build a counter component to showcase the new `$state`, `$derived`, and `$effect` runes that ship with the new version.



Get Started with Svelte 5 using the sv CLI

You'll create a SvelteKit project using the sv CLI and build a counter component showcasing Svelte $state, $derived, and $effect runes.



pnpm ships with a streamlined, easy way of managing Node.js versions for youself and your team. This video demonstrates why pnpm uses a specific version of Node.js, how to configure it globally, and how to set up your project so that anyone who is running your project will automatically use the same version of Node.js even if that version of Node.js is not installed.


use pnpm as a Node.js version manager

How you build with Angular has changed quite a lot over the years.

For example, the `inject` function was introduced in version 14 but you might still be familiar with Angular's constructor injection.

Similarly, structural directives like `ngif` or `ngfor` have been replaced with `@if` and `@for` blocks since version 17 and beyond.

These are patterns that need to be adjusted if you want to stay up-to-date with the latest Angular has to provide.

Luckily, Angular gives you great tools in the form of a migration CLI for supporting your migration efforts as you incrementally update your App from older version features and patterns. 

When you're done with this course you'll know how to target specific features, folders, and files to migrate to the latest Angular version.

You'll learn how to 'migrate':
- Structural directives with control flow syntax
- Constructor dependency inject to inject function
- Make components standalone
- Lazy load routes
- Input/Output decorators to signal-based API


Angular Migrations in Practice

Migrate old Angular patterns for version 18 and beyond

When we import assets in React components outside of the `public` folder that Nitro reads for assets by default when running the development server we need to tell Nitro how to find them with the `devProxy` configuration option.

```typescript
export default defineNitroConfig({
  renderer: './renderer.ts',
  devProxy: {
    '/app/assets': 'http://localhost:5173/app/assets'
  }
})
```

This is ultimately inadequate in scenarios where you want to import assets arbitrarily and have them "just work" but works in a pinch.



Use devProxy in Nitro Config to Serve Static Imported Assets in Dev Mode via Vite

Learn how to use devProxy in Nitro Config with Vite to serve static assets in React components in dev mode.

Start with a basic Vite React TypeScript app and enhance it for production use by integrating Nitro as the server. 

This requires a custom Vite plugin for nitro as well as a custom renderer and manually creating Nitro config.

The other way to approach this would be to add Vite to a Nitro app instead. Same basic result.

The [Nitro config reference](https://nitro.unjs.io/config) is a great read of you'd like to explore more options.


Configure a Vite React TypeScript Application on a Basic Nitro Server

Configure a Vite React TypeScript app by integrating Nitro for production, using custom plugins, renderers, and configs.

Quick Get Started style introduction to Vite using `pnpm create vite` with the React TypeScript template.

See [more in the official docs](https://vite.dev/guide/).

Create a Vite App with the React TypeScript Preset

Quick guide to start a Vite app using React TypeScript template with pnpm.

Over the years, your application have grown huge. Sometimes, really HUGE.

Many developers have contributed to the codebase. One day they pushed one coding style, a different one another day. Sometimes even different patterns and solutions for similar problems.

You want to keep your codebase consistent. In the Angular ecosystem, there were well established patterns for doing things the right way ™️. But the old solutions are being challenged by signal-based approach.

Eventually, you ask yourself the key question: **Should you integrate with the NEW solutions or stick to the battle-tested ones, but already considered LEGACY**?

That's a very good question indeed. Don't rush with architectural decisions 🤓.

## First, think of what problems you want to solve by introducing the change.

Do you have 1k LoC Angular components? Maybe even 2k? Do you and your team enjoy working with these? 😏

Where does the **domain logic and state management code** belong to - do you have a clear guidance on which code should be put where? Have you spot that different devs implement similar features in totally different ways?

Do you keep on asking the same questions over and over again: **whether this certain piece of code** should be **imperative** (plain old object properties and variables) or **reactive** (streams)? It'd be nice to keep all thinga reactive, but more often than not, it introduces complexity.

## Second, think of long-term consequences.

You are going to have more than one way to **manage the state**. But is that really an issue? If your codebase is modular, separate modules should not depend on each other in any way. Inner abstractions of one should be invisible to the other, etc.

You are going to introduce a **new tool**. On one hand, you need to learn it, and so does your team. But on the other hand, it's a breathe of fresh air. And it's useful to question the way you've been doing things so far. Maybe there's a more effective way?

You are going to embrace signal-based APIs. And that means taking taking advantage of Zoneless Angular. This means using all modern Angular APIs. And you know that signals are the future. Why would you want to stick to the **less performant, less type-safe, less flexible and, objectively, less effective solutions**?

## Finally, plan your INCREMENTAL integration.

INCREMENTAL is the absolute keyword here. You don't want to tell your PM you need to stop delivering features because of a refactor.

Actually, there's no need for a "refactor". Just pick the first new feature to be implemented. Or pick the one that needs to be extended.

NGRX Signal Store allows you to create both very simple & small stores, as well as bigger ones. **Composition** is the key here.

**Start simple**.

Create a `withState` section with the signals that hold the state. That's already reactive. And relatively simple.

```ts
const initialState: CartState = {
  items: ...,
  rebate: ...,
}

export const CartStore = signalStore(
  withState(initialState)
);
```

Create a `withMethods` section to provide ways to change the state:

```ts
export const CartStore = signalStore(
  ...
  withMethods((store) => ({
    addItem(item: ShoppingItem): void {
      patchState(store, (state) => ({ items: [ ...state.items, item ] }));
    },
    ...
);
```

Create a `withComputed` section to provide all derived computations:

```ts
export const CartStore = signalStore(
  ...
  withComputed(({ items }) => ({
    totalPrice: computed(() => items().reduce(...))
    ...
);
```

**Start simple**.

Now you can (literally) **`inject` this code into your existing solution**. All you need is to inject your brand new NGRX Signal Store implementation into a component, or a service:

```ts
@Injectable()
class ExistingBigService {
  cartStore = inject(CartStore)
  //...  
}
```

and that's it! What's beatiful is that NGRX Signal Store should remain an implementation details (of a component, service, etc). It **shouldn't leak outside to the entire application unintentionally**. Small NGRX Signal Stores help us to **keep logic more modular**.

Don't hesitate - give NGRX Signal Store a try! Start with the [_**Scalable Signals Angular Architecture with NGRX Signal Store**_](https://egghead.io/courses/scalable-signals-angular-architecture-with-ngrx-signal-store-a33abd39) course now!

Integrating NGRX Signal Store with an existing Angular application

Integrate NGRX Signal Store into your Angular app incrementally for modular, reactive state management. Improve consistency and performance with modern APIs.

Vladimir Novick

Search Results