Learn Bash, Elasticsearch 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

Docker containers wrap a piece of software in a complete filesystem that contains everything needed to run: code, runtime, system tools, system libraries – anything that can be installed on a server. This guarantees that the software will always run the same, regardless of its environment.

docker

This lesson uses some advanced concepts and some bash scripting to build a better Dockerfile. By using the concepts showed here, you will be able to build more future-proof and production-ready containers. If you prefer to focus on the content about containers, feel free to ignore this lesson and come back to it later on if needed.

Currently, we use `sed` to overwrite the hard-coded path to the API. This works well when there is a single value to replace. Now if one of your team members replaced the value of localhost:3000, your build will break.

We'll use `jq` to fix this issue. Jq is a command-line tool that makes it easy to change values in a JSON file. The base image that we used for building the application does not contain this tool, but that is not an issue. To install `jq`, you will need to download the [binary](https://github.com/stedolan/jq/releases/download/jq-${JQ_VERSION}/jq-linux64.), we'll need that to execute `jq` commands in our Dockerfile. This will allow us to update specific properties i

Modify a JSON Configuration File with jq

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

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

Extracting meaningful data from strings is a crucial skill when working with bash, and bash gives us powerful tools to do so: `head`, `tail`, `cut`, `sed`, and `awk`. But these tools can be hard to understand without spending time to learn them, so many developers fall into a rut of blindly copying and pasting commands. No more! With this mini-course, you'll understand the basic ins and outs of these commands in under 15 minutes. 


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

Manipulating strings in bash

In this lesson, we'll use the power of awk to select the columns and rows of data that match our condition. We'll pass a `,` (comma) to the `-F` flag (the F stands for field separator), to tell awk to split on commas. From there, the world is our oyster and we can tell awk to only return rows that match whatever parameters we pass.

Extract Columns of Data from a CSV with awk

`awk` is a specialized tool and programming language for querying and transforming text.   In this lesson, we’ll scratch the surface of the possibilities it provides by leveraging it in one of its most common use cases: extracting data from columns of text. Awk makes it easy to select and print just the columns and rows that we want from commands, like `ps`, that return a table of data.

Extract Data From Columns of Text with awk in Bash

Pandoc is a command-line tool built in Haskell that can convert almost any markup or word processing format interchangeably. You specify the input and the output types and pandoc will do the rest.

In this lesson we will convert a few markdown files to pdf. You will see how to convert a single file and then we'll write a script to loop through a couple files and convert them dynamically.

This lesson requires that you install `pandoc` and have `pdflatex` available.

You can install `pandoc` with brew: `brew install pandoc`
To access `pdflatex`, you can install `basictex` and set the path for `--pdf-engine` to `pdflatex`

Convert a File from Markdown to PDF with pandoc

🚀 In this collection, I will be going over some command line tools I use on a daily basis that make my life a lot easier.

[First up is fzf](https://github.com/junegunn/fzf).

> fzf is a general-purpose command-line fuzzy finder.

Upgrade Your Terminal and Make It a Joy to Work with

`fzf` is a fast cli finder tool. The `fzf` command will launch an interactive find session. You can type a path to a file and see a list of possible results.

Piping the output of commands (such as git branch) to `fzf` makes it easy to find the line you are looking for.

Interactively Find Anything By Piping it to fzf in the terminal

Many people just drop all of their Zsh functions inside of their .zshrc and forget about it. But as your collection of functions begins to grow, you start looking for a better way to organize everything. Since Zsh provides `autoload` for loading in functions dynamically, we can drop all of our functions into individual files, loop through that directory, then autoload each file as a function.

Store Zsh Functions in Individual Files Inside a Directory

SSH provides a secure way for your to [connect to and authenticate with GitHub's servers](https://help.github.com/en/github/authenticating-to-github/about-ssh). While HTTPS connections use usernames and passwords as credentials, SSH instead uses public and private key pairs. These can be generated on your system using a CLI like [`ssh-keygen`](https://help.github.com/en/github/authenticating-to-github/generating-a-new-ssh-key-and-adding-it-to-the-ssh-agent) and then associated with your GitHub account using the public key.

In some cases, you may need to connect to more than one GitHub account from the same system. For example, you may have [separate accounts for personal and professional projects](https://ryanharris.dev/managing-ssh-keys-for-github/), which can be difficult to manage manually. Using `ssh-agent` and a SSH configuration file, you can alleviate this pain point by automatically determining which key to use based on your GitHub repository's `git` URL.

Secure GitHub connections with SSH

When working with multiple GitHub accounts on the same system, you want to ensure that your commits have the proper author information. 

To do this, we'll create a global `git` configuration on our system that uses our personal account's information. Then, in our work-specific repositories, we'll add a local `git` configuration to override our global values.

We will be using the following commands in this lesson:

- `code`
- `git config`

Update gitconfig to Work with Multiple Accounts and SSH Keys

In this lesson, we have two local SSH keys: one associated with our personal GitHub account, the other with our work account. 

To more easily manage them, we will use `ssh-add` to add our keys to our system's key manager `ssh-agent`. Then, we will create a SSH configuration file, which will determine what key to use when connecting to GitHub based upon the URL. 

Once we have set up our configuration file, we can test our connections using `ssh -T` and clone repositories with `git clone`.

Commands we will be using in the lesson:

- `ls`
- `ssh-add`
- `touch`
- `ssh`
- `git clone`

Manage Keys with ssh-agent and Add SSH Configuration

In some cases, you may have multiple GitHub accounts that you need to interact with from the same system. For example, you could have an account for work and another for personal projects, but you don't want to re-authenticate each time you switch between then. By using public SSH keys for each account, you can eliminate this part of the process.

In this lesson, we will create two SSH keys in our terminal using `ssh-keygen` , copy them to our clipboard using `pbcopy` and then add them to our respective GitHub accounts.

Commands we'll be using include:

- `ssh-keygen`
- `ls`
- `pbcopy`

Generate SSH Keys for your GitHub Accounts



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.

Use GitHub Actions Matrix Include for Complex Job Configurations

While running `zod` schema validation agains domain-rich objects, the error message saying that _a string is not a number_ might not be really useful.

Especially, when you need to provide a meaningful feeback to the user, e.g. after they have submitted a form with lots of data.

`zod` allows to customize messages on a very granular level. We can also extract repeatable customization to `zod` error maps.

Finally, in order to process an error message further (e.g. display it to the user), we need to handle the `zod` validation errors effectively. Especially, when a big object validation has failed and we could receive a handful of errors.

That's what we learn in this lesson. 🔥

Customize zod Error Messages and Handle zod Errors Effectively

customize zod validation messages, customize zod schema property messages, reuse error maps across different schemas, navigate through zod error objects

You might want to run `zod` schema checks in different styles.

Sometimes you prefer to conditionally throw the error - that's what `parse` does. But another time you'd prefer to receive a `boolean` property that determines whether the validation was successful or not - and perform further actions accordingly.

Additionally, the error-throwing API of `parse` works extremely well with [TypeScript assertion functions](https://www.typescriptlang.org/docs/handbook/release-notes/typescript-3-7.html#assertion-functions). Their combination is just... perfect! 👌

That's what we learn in this lesson.

Use parse and safeParse Runtime Type-checks with zod

use zod parse function to conditionally throw ZodError, use zod safeParse to get a boolean value and run typescript type guard over success property

In this lesson we learn that TypeScript cannot guarantee correct shapes of responses. That's due to TS performing checks in compile-time, while the response will be availbale in runtime - when TS doesn't exist anymore.

In some situations, such as HTTP requests, runtime type checks such as `zod` are essential for providing quick feedback around data-related errors.

Understand where are the possible mistakes to make while using TypeScript with HTTP calls. Use `fetch` and `axios` along with `zod` schema checks.

Also, note that similar mistakes or mistakes could happen while using web storage (e.g. `localStorage`)

Validate HTTP API Response with zod, fetch and axios

use zod as an HTTP response validation tool along with fetch and axios in order to make sure that the response has expected data structure

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