Learn Angular-material, Nuxt and Postgres

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

postgres

We create a PostgreSQL join table for `likes` in the [Supabase](https://supabase.com) dashboard. This has a many-to-many relationship between the `profiles` and `tweets` table, allowing us to store each instance of a like between a user and a tweet.

Additionally, we create Row Level Security (RLS) polices to enable `select`, `insert` and `delete`.

## Code Snippets

**Create likes table**

```sql
create table public.likes (
  id uuid default gen_random_uuid() primary key,
  created_at timestamp with time zone default timezone('utc'::text, now()) not null,
  user_id uuid references public.profiles on delete cascade not null,
  tweet_id uuid references public.tweets on delete cascade not null
);
```

**Enable Row Level Security**

```sql
alter table public.likes enable row level security;
```

**Enable insert action with RLS policy**

```sql
create policy "authenticated users can insert their own likes" ON "public"."likes"
as permissive for select
to authenticated
using (user_id = auth.uid());
```

**Enable delete action with RLS policy**

```sql
create policy "authenticated users can delete their own likes" ON "public"."likes"
as permissive for delete
to authenticated
using (user_id = auth.uid());
```

**Enable select action with RLS policy**

```sql
create policy "authenticated users can select likes" ON "public"."likes"
as permissive for select
to authenticated
using (true);
```

## Resources

- [Managing user data docs](https://supabase.com/docs/guides/auth/managing-user-data)
- [Row Level Security docs](https://supabase.com/docs/guides/auth/row-level-security)

Create a PostgreSQL Join Table in Supabase Studio

[Supabase](https://supabase.com/) has an `auth.users` table that contains information about our user and their session. We want to display the user's name, username and avatar alongside their tweets, but the `auth.users` table cannot be publicly accessible, as it contains sensitive information.

In this lesson, we create a new table called `profiles` and populate it with the data we want to display from the `auth.users` table. Additionally, we set up a PostgreSQL Function and Trigger to create a new profile for any user added to the `auth.users` table.

Lastly, we create an RLS policy for the `profiles` table to enable read access, and re-generate our TypeScript definitions file to contain our new table.

## Code Snippets

**Create profiles table**

```sql
create table public.profiles (
  id uuid not null references auth.users on delete cascade primary key,
  name text not null,
  username text not null,
  avatar_url text not null
);
```

**Enable Row Level Security**

```sql
alter table public.profiles enable row level security;
```

**Enable read access with RLS policy**

```sql
create policy "anyone can select profiles" ON "public"."profiles"
as permissive for select
to public
using (true);
```

**Create PostgreSQL Function to create profile**

```sql
create function public.create_profile_for_user()
returns trigger
language plpgsql
security definer set search_path = public
as $$
begin
  insert into public.profiles (id, name, username, avatar_url)
  values (
    new.id,
    new.raw_user_meta_data->'name',
    new.raw_user_meta_data->'user_name',
    new.raw_user_meta_data->'avatar_url'
  );
  return new;
end;
$$;
```

**Create PostgreSQL Trigger to create profile**

```sql
create trigger on_auth_user_created
  after insert on auth.users
  for each row execute procedure public.create_profile_for_user();
```

## Resources

- [Managing user data docs](https://supabase.com/docs/guides/auth/managing-user-data)
- [Row Level Security docs](https://supabase.com/docs/guides/auth/row-level-security)

Automatically Generate a Profile for Every User with PostgreSQL Function Triggers

[Supabase](https://supabase.com/) uses the `auth.users` table to store information about our users and their sessions. In this lesson, we add a column to the `tweets` table to associate each tweet with one of our users.

Additionally, we set up cascading deletes, so when a user is deleted from the `auth.users` table, their tweets are also deleted.

Lastly, because our database schema has changed, our TypeScript definitions are now incorrect. Therefore, we use the Supabase CLI to introspect our PostgreSQL schema and create a new `database.types.ts` file.

## Code Snippets

**Add foreign key relationship to auth.users**

```sql
alter table public.tweets
add user_id uuid references auth.users on delete cascade not null;
```

**Generate TypeScript definitions**

```bash
npx supabase gen types typescript --project-id your-project-id > lib/database.types.ts
```

## Resources

- [Supabase Auth docs](https://supabase.com/docs/guides/auth)
- [Supabase CLI](https://supabase.com/docs/guides/cli)
- [Generating TypeScript definitions](https://supabase.com/docs/guides/api/rest/generating-types)

Setup a Foreign Key relationship between PostgreSQL tables

Next.js is a minimalistic framework for server-rendered React applications.

Since we're using [Supabase](https://supabase.com/) to authenticate our users, it knows who our user is throughout the rest of the Supabase environment.

In this lesson, we modify our Row Level Security (RLS) policy to only apply to the `authenticated` role to ensure that only authenticated users can select tweets.

Additionally, we use the `useRouter` hook and `router.refresh()` to run our Server Component again and fetch fresh data from Supabase, after the user signs in or out.

## Code Snippets

**Enable authenticated read access with RLS policy**

```sql
create policy "anyone can select tweets" ON "public"."tweets"
as permissive for select
to authenticated
using (true);
```

## Resources

- [Row Level Security docs](https://supabase.com/docs/guides/auth/row-level-security)
- [useRouter hook](https://nextjs.org/docs/app/api-reference/functions/use-router#userouter)

Restrict Access to Authenticated Users with Supabase RLS Policies

[Supabase](https://supabase.com/) is a collection of open source tools that wrap around a PostgreSQL database - Hosting, Auth, Realtime, File Storage, Edge Functions etc. In this lesson, we go to [database.new](https://database.new) to create a free Supabase project.

Additionally, we create a `tweets` table and populate it with some seed data.

## Code Snippets

**Create a `tweets` table**

```sql
create table if not exists tweets (
  id uuid default gen_random_uuid() primary key,
  created_at timestamp with time zone default timezone('utc'::text, now()) not null,
  title text not null
);
```

**Insert tweets**

```sql
insert into tweets(title)
values
  ('first tweet'),
  ('second tweet'),
  ('third tweet');
```

## Resources

- [Supabase docs](https://supabase.com/docs)
- [Supabase SQL Editor](https://app.supabase.com/project/_/sql)

Create a New Supabase Project and Basic PostgreSQL Schema

Hasura allows for the addition of "computed fields" to any table. Computed fields are SQL functions that get added to that tables schema definition. This allows for increased flexibility in querying, and ordering. We will setup a computed field to add a users post count to the user schema, and show how to query and sort by the new computed field.

How to Create a Computed Field in Hasura

Supabase is an open source Firebase alternative. A service to:

- Listen to database changes.
- Query your tables, including filtering, pagination, and deeply nested relationships (like GraphQL).
- Create, update, and delete rows.
- Manage your users and their permissions.
- Interact with your database using a simple UI.

Supabase is not a 1-to-1 mapping of Firebase. Most notably, Supabase uses Postgres rather than a NoSQL store. 

supabase

In this video, you'll learn how to build a full stack app with React, Supabase, and Postgres. We'll start by creating a new Supabase project, initializing a new PostgreSQL "posts" table, and adding rows for the post title and content.

Next, we'll install the Supabase library using NPM or Yarn, and configure a client to connect with the Supabase API. Using the Supabase client, we'll create a basic app that allows users to create and read posts from the Supabase back end.

By the end of this video, you should have a good idea of how to get up and running with building full stack apps using Supabase.

Building a Full Stack App with Supabase and React

We'll store client interaction using Hasura as our primary database. Hasura allows you to build a powerful, secure & flexible GraphQL API that can query data in your databases, HTTP services, serverless functions, as well as third party APIs. 

We'll start by creating a Hasura Cloud account. Proceed to create a Postgres database on Heroku. If you don’t have an account on Heroku, you need to sign up on Heroku. You won’t need a credit card. 

We'll add corgi data to the database using the Unsplash `ID` as our primary key, and `count` as an integer for our count functionality.

Create a Database using Hasura Cloud and a Postgres Instance to Store Data

Vue (pronounced /vjuː/, like view) is a progressive framework for building user interfaces. Unlike other monolithic frameworks, Vue is designed from the ground up to be incrementally adoptable. The core library is focused on the view layer only, and is very easy to pick up and integrate with other libraries or existing projects. On the other hand, Vue is also perfectly capable of powering sophisticated Single-Page Applications when used in combination with modern tooling and supporting libraries.

In this video you'll learn how to use Amplify hosting to deploy a Nuxt site from a Git repository. We'll begin by walking through the steps of creating the deployment and configuring the correct build settings to enable a static build. Once the site is deployed, we'll view the live site hosted on AWS.

Deploying a Nuxt Site to AWS from a Git repository with Amplify hosting

In this video you'll learn how to deploy a static Nuxt site to AWS's global edge CDN in less than two minutes. We'll start from scratch, creating a new Nuxt site using npx and walk through the build configuration to set up the deployment target for Jamstack / static site hosting. From there, we'll initialize a new Amplify project using the Amplify CLI and walk through the settings to configure the proper build command for Amplify hosting. Finally, we'll deploy and view the live site. Once we're finished, we'll delete the project and the hosting service.

Deploying a Nuxt Site to AWS with the Amplify CLI

Thanks for watching the course! In this video I am going to walk you through some info that is good to be aware of before watching the course. 

Introduction to Advanced SQL for Professional Developers

You've got some practice with using SQL to select, update, and join database tables.

But perhaps you've found yourself with a sneaking suspicion that you could be more efficient with your PostgreSQL.

Does your query seem slow?

A lesson on how to profile queries will point you in the direction of a fix.

Are you performing multi-step operations one at a time that are susceptible to errors?

The "all or nothing" transaction is the cure.

These are just a couple of examples of the techniques, tips, and tricks that Tyler Clark has learned in his years of experience working on large scale production applications.

Other topics in this course include working with CSV files, different techniques for aggregating & filtering, and more!

Watch Tyler's course, and continue your journey toward SQL mastery.

Check out the [**Community Notes for this course.**](https://github.com/eggheadio-projects/advanced-sql-for-professional-developers)

Advanced SQL for Professional Developers

Data integrity is critical to scaling and working with large datasets. One additional way to keep this integrity is to define custom types like enums. In this lesson we’ll create and assign data to a custom enum type. 


For more info: 

- https://www.postgresql.org/docs/9.2/sql-createtype.html
- https://docs.oracle.com/cd/A91202_01/901_doc/server.901/a88856/c14ordb.htm#433046
- https://www.c-sharpcorner.com/article/user-defined-table-types-and-table-valued-parameters/

Create a Custom SQL Enum Type 

Working with large datasets is hard. What's even more difficult is trying to read through queries that have many subqueries and joins. In this lesson we will create common table expressions (CTEs for short), which act kind-of like temp tables (but not really) that can help break out complex queries into more readable blocks. 


Common Table Expressions in SQL

Transactions are a fundamental concept within all database systems. When a series of actions need to be done at once or not at all, transactions are how we accomplish this. In this lesson, we'll review how actions are performed, saved, and rollbacked within transactions as well. Some keywords used will be: `start transaction`, `begin`, `commit`, `savepoint`, `rollback`

Perform Multiple Steps in One with SQL Transactions

As we pull data out of our tables there are times when the types don’t match. Or what if we want to compare two values of different types? Casting is a form of changing values from one type to another. There are a couple different ways we can do this in SQL. We'll talk about a common way of casting with `cast` and a shorthand way `::` that is specific to postgres. 

Casting Types in SQL

The where clause does a great job of filtering rows, however when we want to filter out data that is grouped and aggregated, we need to work with the `having` clause. This can be difficult to understand and work with at first, so in this lesson, we will discuss the main differences. 


Filter Grouped and Aggregated Data with SQL Having

Queries can grow in size and become unreadable pretty quickly. Not to mention error-prone if we have to write out the same value multiple times. Just like in almost any other programming language, variables and blocks can be created within SQL. This gives users the ability to write variables at the top of a block and then be referenced through the following transaction.  


Create Variables and Blocks with Do / Declare in SQL

Nulls can be a huge burden if not handled correctly. Conditional logic is tricky and joining tables with null columns requires cognitive recognition. Similar to many popular programming languages, we can conditionally change values within SQL if the returning value is null. 


Create and Safely Handle Nulls in SQL

Most programming languages have some sort of pattern matching and/or regular expressions. SQL is no different! In this lesson we are going to work with `like`, `ilike`, `similar to`, and POSIX to filter out our data. We'll talk about the characters that can be used within our patterns, such as `%`, `_`, `|`, `*`, `+`, `?`, and `()`

Pattern Matching and Regular Expressions in SQL

Imagine instead of filtering all returned rows of data with the WHERE clause (which affects the other selected out columns) you only filtered the data for one aggregate function in the select. The inline filter clause can target only one column, giving you the ability to pull out filtered and unfiltered columns with one select statement. 


Aggregate Inline filters in SQL

I've been using Cursor for a very long time and their "Agent" feature in Composer is fairly new, so I'm still getting used to it. But since Windsurf recently got onto the stage with their Cascade agent, they've slowly been gaining the mind share on the UX for coding agents. I decided to put them to the test by putting Windsurf and Cursor on the exact same screen side by side trying to accomplish the same task and to see which workflow I would prefer. I've been a diehard Cursor user for over a year now, so it's going to take a lot for me to switch to a different IDE. But I just have to say, even from this simple demo, Windsurf is looking pretty nice.

This lesson is just going to walk through creating a CLI using both tools to print out inspirational quotes and to explore how they approach the step-by-step of installing packages and running commands and setting up all the files we need to get this running.

Windsurf Cascade vs. Cursor Composer Agent Side-by-Side Comparison

This TypeScript tutorial explains how to use generics, allowing for different types to be passed as arguments. It discusses the use of shorthand syntax in generics and illustrates with examples. This method is useful for library creation, providing type safety and control to the user.

```typescript
interface PhotoMetadata<T> {
  title: string;
  takenAt: Date;
  customData: T;
}

// Function that processes a photo with custom metadata
function processPhoto<T>(photo: PhotoMetadata<T>): {
  processedTitle: string;
  daysSinceCapture: number;
  customDataSummary: T;
} {
  const today = new Date();
  const daysSinceCapture = Math.floor(
    (today.getTime() - photo.takenAt.getTime()) / (1000 * 60 * 60 * 24)
  );

  return {
    processedTitle: photo.title.toUpperCase(),
    daysSinceCapture,
    customDataSummary: photo.customData
  };
}

// Example usage with different custom data shapes
type CameraSettings = {
  iso: number;
  aperture: string;
  shutterSpeed: string;
}

type LocationData = {
  latitude: number;
  longitude: number;
  locationName: string;
}

// Using with camera settings
const photoWithCamera: PhotoMetadata<CameraSettings> = {
  title: "Sunset at beach",
  takenAt: new Date('2024-01-15'),
  customData: {
    iso: 100,
    aperture: "f/2.8",
    shutterSpeed: "1/1000"
  }
};

// Using with location data
const photoWithLocation: PhotoMetadata<LocationData> = {
  title: "Mountain vista",
  takenAt: new Date('2024-02-01'),
  customData: {
    latitude: 45.5231,
    longitude: -122.6765,
    locationName: "Mount Hood"
  }
};

const processedCameraPhoto = processPhoto(photoWithCamera);
const processedLocationPhoto = processPhoto(photoWithLocation);

processedCameraPhoto.customDataSummary.iso
processedLocationPhoto.customDataSummary.longitude

```

Basic Explanation of Typescript Generics

A very basic explanation of generic function arguments

I've been using Cursor as my primary editor for over a year now, but recently I've heard wonderful things about Windsurf AI Agent features. I decided to record myself building out something I've always wanted to make, but never made the time for.

In this lesson, I demonstrate how to leverage Windsurf's powerful agent process to create a fun word-guessing game inspired by Heads Up. Watch as I build an interactive application featuring category selection and word navigation, complete with data hosting on GitHub Gists and deployment to GitHub Pages - all in under 30 minutes (before editing the lesson down to 12 minutes)!

What makes this project particularly exciting is how Windsurf eliminates the typical friction points of development. While this game was always on my project wishlist, the overhead of setup, configuration, and deployment made it hard to justify the time investment. Windsurf's agent process handles all these pain points seamlessly, from managing URLs to orchestrating deployment.

This lesson perfectly showcases how AI agents can help developers bring their backlog of project ideas to life, transforming what would typically be time-consuming tasks into efficient, enjoyable development experiences.

Build a Word Game with Windsurf's Cascade AI Agent



Discover how to harness the power of Cursor IDE's Composer Agent feature to optimize your code. In this lesson, you'll witness an AI agent doing all the work to generate test suites, implement performance benchmarks, and create optimized function variations - all without writing a single line of code. You'll learn how to validate performance improvements through data-driven benchmarking, ensuring that optimizations are backed by concrete metrics rather than speculation. This hands-on demonstration showcases a groundbreaking approach to automated function development that combines the precision of test-driven development with the efficiency of AI-powered optimization.


Agent-Driven Development in Cursor: Testing, Benchmarking, and Optimizing Functions

This course is aimed for using `zod` effectively in projects based on TypeScript (both browser and node.js). The benefits you gain with this course is not just simply coding, but also understanding when/why/how should you perform runtime validation.

`zod` is the missing piece to TypeScript's capabilities, which can guarantee type-safety only in compile-time.

`zod` can be used whenever the compiler cannot guarantee what happens in runtime. And... it's a very frequent usecase, such as HTTP calls, websockets, etc.

In this course you get quickly up and running by:
1. using `zod` with primitives and objects
2. adapting `zod` quickly to existing projects thanks to automatic generators
3. changing the strategy frm type-first to schema-first
4. using error-throwing `parse` or non-error-throwing `safeParse` basing on your needs
5. applying `zod` to the most common usecase - validating API responses
6. handling errors the most convenient way (out of many!)

Take advantage of runtime validation with `zod`. Take advantage of the detailed lessons in this course 🔥

Effective Runtime Type Checks with Zod


Cursor can now automatically run commands in the terminal and walk step-by-step towards building out your entire project. You give it a goal, then it will suggest the commands you need to run and the files that you need to create and you can work with it to achieve what you're building. This lesson does a quick walkthough of using a Cursor Agent to build a project from scratch and guide it along the way. Cursor Agents definitely feel like a sneak peek at the future of programming!

Cursor Agents Initial Impressions - Allow an AI to Build Your Entire Project

Mock Service Worker is an API mocking library that allows you to write client-agnostic mocks and reuse them across any frameworks, tools, and environments.



Mocking WebSocket APIs with Mock Service Worker


While using anonymous functions might seem convenient, they can create difficulties when trying to identify performance bottlenecks during profiling. This lesson will demonstrate how named functions make it easier to pinpoint and address performance issues, ultimately leading to more efficient and debuggable code. Learning this practice will greatly improve your ability to locate and fix performance issues in complex projects.

Always Name Functions in JavaScript


When attempting to load the same module twice in JavaScript you'll hit a cache and code won't re-run. In scenarios where you actually do want to have state in your modules, you'll have to use a cache-busting technique by passing a query parameter to a dynamic import. This lesson walks through how to add a query parameter, how to add the appropriate types for loading dynamic modules in TypeScript, and when these techniques are valuable.

Import the Same JavaScript Module Multiple Times with Cache Busting



The include keyword in GitHub Actions empowers you to add custom variables to your matrix strategy, providing flexibility beyond standard configurations. In this video, we'll explore how include allows you to define specific combinations of variables, enhancing control over your workflow runs. You'll see how this feature enables you to tailor jobs for unique environments or scenarios not covered by the default matrix options. By leveraging include, you can efficiently manage complex build processes with greater precision. This technique helps you streamline your CI/CD pipeline, making it more adaptable to your project's evolving needs.

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