Learn Postgres, Python and Realm

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

Python is a widely used dynamically typed programming language. It allows for many different programming paradigms including object-oriented, imperative, functional programming, and procedural styles.

python

To take the user input in Python you use a built-in method input(). The data type of the user input is string. Later based on the use case the data type of the user input can be changed to a different data type based on the requirement.

 Example:

1. 
```
>> a = input("Enter your birthday date ")
>> 31
>> a
>> '31' 
```

2. 
```
>> b = input("Enter List of numbers: ")
>> [1, 2, 3, 4]
>> b
>>  '[1, 2, 3, 4]'
```

NOTE: While creating the example Python interpreter is used which is why the program waits for the user to input. And, once the user enters the input then prompts the user to enter the next line of code.


Use built-in method input() to take User Input in Python

Use the equality operator to compare the values of the objects. Identity operator is used to verifying that objects are equal but are not referring to the same object in memory. 

Use cases where identity operator is used are:
- to test if the object is None
- to test if the object is of a particular type or not

There may be use cases where the output returned by both the operators is the same. But, in your program, you have used the identity operator instead of the equality operator. 

To avoid such mistakes it is important to understand the difference between identity and equality operator.


Difference between Equality Operator and Identity Operator in Python

The identity operator is used for checking whether the object is of the mentioned type.

Example:

```
>> a = "Hello World!"
>> type(a) is str
>> True
```
The result returned in the above case is true because the type of object is str. 

Identity operator is also used to compare the object with None. 

Example:

```
>> a = None
>> a is None
>> print(a)
>> True
```

Internally, the identity operator compares the memory address of the objects. Built-in `id()` method returns a unique number i.e address of the object in memory. If the address of both the objects in memory is the same identity operator returns the result as True.

Example:

```
>> a = 10
>> b = 10
>> a is b
>> True
>> id(a)
>> 916744
>> id(b)
>> 916744
```

The above code snippet tells us that value of both the objects is the same and variables `a` and `b` are referring to the same object in memory. 



Identity Operator in Python

Variable names in Python can be of any length. Variables names can have alphabets [A-Z][a-z], digits [0-9] and underscores. A variable name starting with a digit is an invalid variable name. 

Variable Names in Python

Built-in id() method determines the memory address of the object in Python. Knowing this concept will help you in understanding what happens under the hood when you use identity operator (is and not is). 

Use Built-in id() Method to Determine the Memory Address of the Object

While solving real-life use cases through programming and also while testing your code you will come across scenarios where you have to compare the value of different objects. And, then to solve the problem you can use the equality operator.

Use Equality Operator to Compare the Value of Objects in Python

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

Tuples are immutable so there is no way to add or replace items in tuples. There is a way to get around this by adding two tuples into one. 

Understand Immutability with Python Tuples

AWS Amplify allows developers to create, configure, and deploy Serverless APIs and functions directly from their front-end environment.In this collection, you'll learn how to deploy various types of APIs and functions using the Amplify CLI. You'll also learn how to share code among various functions using Lambda layers and schedule functions to run at an interval to implement Serverless cron jobs.

JavaScript® (often shortened to JS) is a lightweight, interpreted, object-oriented language with first-class functions, most known as the scripting language for Web pages, but used in many non-browser environments as well such as node.js or Apache CouchDB. It is a prototype-based, multi-paradigm scripting language that is dynamic, and supports object-oriented, imperative, and functional programming styles.

javascript

Up and Running with AWS Amplify Functions

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

Learn to create a one item tuple. When creating a one item tuple, a comma has to be included after the item. Otherwise, your tuple will not return tuple as its data type. 

Create a One Item Tuple in Python

Learn how to create a tuple in Python. A tuple is an immutable data type that contains several items similar to a list. Items in a tuple can be of any data type.

Create a Tuple in Python

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 

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.

In React 19, managing script tags efficiently within components can lead to performance enhancements and simpler code structures.

Originally, using script tags directly in a React component involved complex setups, like using `useEffect` to dynamically add JavaScript code. For instance, a component might dynamically inject script tags to load external widgets. This approach, while functional, resulted in multiple script tags and duplicate iframe elements. This duplication not only cluttered the output but also negatively impacted performance by loading scripts multiple times.

The workaround for this would be to manually hoist any common scripts and maybe load them when they weren't needed by any components.

With React 19 we now have a more effective method. This involves directly placing the script tag within the React component's return statement. This approach ensures that React handles the script loading, avoiding the duplication of script tags.

By implementing the script tags this way, the loading initiator becomes React DOM, which efficiently manages script loading and deduplication. This setup prevents multiple requests for the same script when the component is rendered multiple times, enhancing the overall application performance.

Furthermore, directly embedding the script tag simplifies the code, making the component cleaner and more maintainable.

Efficiently Render Script Tags in React 19 Components

Learn how to efficiently render script tags in React 19 components to improve performance by avoiding duplicate script loads and simplifying your code.

Let's learn how to dynamically manage title tags in React 19 applications. Rendering `<title>` dynamically is simple enough, however, a challenge arises when multiple title tags are present in the document, which can lead to issues with screen readers and search engine optimization (SEO). The solution presented involves ensuring that only one title tag is rendered at a time by using conditional rendering.

Also we need to make sure to have a single string within the title tag using a template literal, ensuring our HTML remains valid and optimized.


Deduplicate Title tags with React 19

Learn to manage multiple title tags in React 19 dynamically. Ensure accessibility and SEO by preventing duplicate title tags with clear examples.

In React 19, we can easily add a title tag like "Starship Deets" which then appears in the head section of the HTML even when we render it inside our components. This method also applies to meta tags such as character set and viewport settings, which are also lifted to the head section automatically.

This is an awesome feature because it maintains the same composition style we are familiar with in React components. It simplifies the handling of HTML head elements without needing extra setups like `useEffect` for accessing the head section. Even in situations where our components are rendering within a body element, like within a div, we can manage our head content directly within our components. React takes care of hoisting these elements where they need to go.


Hoist Title and Meta tags in React 19

Hoisting title and meta tags directly in React 19 components allows for simpler composition, similar to other React elements. Manage meta and title tags.

<PodcastLinks />

Dax Raad, known for his strong opinions on Twitter, sat down for a chat about web dev, career moves, and building cool stuff. He's not afraid to throw some heat at popular tools like [Next.js](https://nextjs.org/), though he still helps people use it. Dax is particularly excited about local-first development, which he thinks isn't getting enough attention. He argues that sometimes the best web dev move is to step away from web dev entirely and explore other areas of programming.

When it comes to career growth, Dax encourages developers to think beyond the "web dev" label and see themselves as programmers capable of tackling any challenge. He advocates for trying out weird stuff and learning unusual languages, as these experiences can lead to unexpected opportunities. Taking smart risks in your career can open doors to awesome possibilities.

In the business world, Dax is a fan of making "asymmetric bets" - moves with low downside but huge potential upside. He applies this philosophy to his work on [SST](https://sst.dev/), reasoning that even if it fails, he'll walk away with valuable experience. He also emphasizes the importance of resisting quick payouts in favor of potentially bigger wins down the road.

Looking to the future of tech, Dax is betting on local-first development. He sees potential in getting in early on emerging technologies like [Solid.js](https://www.solidjs.com/). Building in public and making connections in new tech communities can pay off in unexpected ways.

Dax also challenges the notion of constant hyper-productivity in tech. He suggests balancing focused work with time for exploration and learning. Sometimes, he points out, what seems like a "dumb" choice (like learning a niche language) can turn out to be a smart career move in the long run.

## Good Stuff Mentioned

- [Next.js](https://nextjs.org/)
- [Vercel](https://vercel.com/)
- [SST](https://sst.dev/)
- [Elixir](https://elixir-lang.org/)
- [Solid.js](https://www.solidjs.com/)
- [RepliCache](https://replicache.dev/)
- [Linear](https://linear.app/)
- [Remix](https://remix.run/)
- [Shopify](https://www.shopify.com/)
- [React](https://react.dev/)

Developer Career Growth and Asymmetric Bets with Dax Raad

<PodcastLinks />

Dev and Joel discuss React Miami conference, praising its fun atmosphere and location. They chat about React Server Components, with Dev sharing his experience building a mini framework. They talk about Vinxi, Nitro, and the unjs ecosystem as tools for creating custom frameworks. The conversation touches on Vue's popularity outside web dev circles and non-web dev conferences. They discuss the benefits of TypeScript and strongly-typed APIs. Dev mentions his upcoming talk on durable objects at [a conference in Dallas](https://x.com/DThompsonDev/status/1829674506237194456). They end by discussing WebSockets, PartyKit, and platform-specific frameworks.

## What's Good?

- [React Miami Conference](https://www.reactmiami.com/) 
- [Brenley Dueck's blog post on Simple RSC with Vinxi:](https://www.brenelz.com/posts/simple-rsc-with-vinxi/)
- [Vinxi](https://github.com/nksaraf/vinxi)
- [Nitro](https://nitro.unjs.io/guide/configuration)
- [unjs ecosystem](https://unjs.io/)
- [Solid Start](https://start.solidjs.com/)
- [TanStack Router](https://tanstack.com/router/latest) 
- [PartyKit](https://github.com/partykit/partykit) 
- [Durable Objects (Cloudflare)](https://developers.cloudflare.com/durable-objects/)
- [Flightcontrol](https://www.flightcontrol.dev/) 
- [SST](https://sst.dev/)
- [OpenNext](https://open-next.js.org/)

Nitro, Vinxi, and RSCs - What's Good with Dev Agrawal

**Note:** This course is being actively developed and more lessons will be added in the future.

Cursor is an AI-enhnaced code editor that allows you to call upon the robots to refactor or stub out functions for you with natural language. 

In this course, John will show you workflows that will save you time and effort by utilizing the features such as its mult-line editing and context.

In particular, by giving Cursor's AI the proper context, whether that's lines of code or multiple files, you'll get better output when trying to extend or refactor logic that's present.


Bite-size video tutorials for badass web developers.

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