Learn Bash, Flow and Recoil

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

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

Recoil offers several hooks to use for consuming state in React, and this lesson looks at how to choose which hook to use, and what happens when you don't use the right hook (hint: **extra renders**).

The three basic RecoilJS hooks are:

1. `useRecoilState`, which is great for reading and writing state,
2. `useRecoilValue`, ideal for reading state, and
3. `useSetRecoilState`, the primary candidate when you just need to write state.

Choose the Right Hook for Your Recoil State

When consuming asynchronous selectors in Recoil, you're going to need to tell React what to render while the API is fetching its data. 

One way to solve this issue is by setting a fallback value using React `Suspense`. But there's another option that gives you fine-grained control, and that's by preventing the selectors from returning a promise in the first place.

In this lesson we're going to have our selectors return Recoil's `Loadable` object, which always contains the current selector value (`contents`) and what state the selector is in (`state`). By consuming this with the `useRecoilValueLoadable` hook rather than the regular `useRecoilValue` hook, we can manually define whatever we want React to render in each of the 3 states: `hasError`, `hasValue`, and `loading`.

Handle Recoil Asynchronous Selectors using Loadables in React

Selectors are great for automatically triggering API calls with Recoil because they are automatically run as soon as any dependencies are updated, and because selectors are shared across your application.

Be aware that Recoil will cache your selector values, so asynchronous selectors are best utilized when the data is not meant to change throughout the life-cycle of an application. Fetching a user's avatar would be a good use case.

When writing asynchronous selectors, one thing to keep in mind is that React must always know what to render - even while your data is being fetched. One solution for this is to use Suspense, a React component that allows you to supply a fallback value to render until your data returns. In this lesson, we'll look at how to call APIs inside selectors and handle situations where selectors return promises.

Use Recoil Selectors to Make API Calls in React

In this lesson, we're going to learn how to create Recoil selectors that accept arguments. These are made possible using the `selectorFamily` utility function.

We'll start with an existing application that uses a regular `selector` to display a sorted array of Todo items, and then we'll refactor it so that we're able to supply the sort type (`ascending` or `descending`) in the React component itself.

For more information on `selectorFamily`, have a look at the official RecoilJS docs: https://recoiljs.org/docs/api-reference/utils/selectorFamily


Use selectorFamily to take arguments in your Recoil selectors

Learn how to set state in Recoil using the `useRecoilState` hook. 

Sound familiar? It should, because it works very similarly to React's built-in `useState` hook (the functional component equivalent of `setState`).

In this lesson, we'll practice removing and adding items from an array that we keep in state using a Recoil atom. We'll create new immutable functions, and then call our setter functions in order to update the state.

Update Recoil State in React using useRecoilState

In this lesson, we're going to show how RecoilJS selectors are used to display computed data in React. While atoms are the go-to state objects in Recoil, selectors are the ideal choice when data can be computed based on existing state - like displaying the price of a restaurant order. And your selector output always remains up to date - just subscribe to it using one of the RecoilJS hooks.

Display Computed Data Using Recoil Selectors in React

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

Parsing arguments in zsh functions can be a bit difficult to manage if you try and customize it for each new function. Luckily, that's where zparseopts comes in. zparseopts is a utility function which can parse out each of the arguments you define and store them inside of an associative array for easy access. This makes accessing arguments as easy as looking them up by name.

Pass Arguments to zsh Functions with zparseopts

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

It can be difficult to work on multiple projects that use different versions of Node.

`nvm` ([Node Version Manger](https://github.com/nvm-sh/nvm)) make this easier by allowing you to download multiple versions and switch between them. You can also add a NVM configuration file (i.e. `.nvmrc`) to specify which version you want to use for each project.

In this lesson, we'll cover the following commands:

- `nvm install`
- `nvm ls`
- `nvm ls-remote`
- `nvm use`

Install and Manage Node.js Versions with nvm

Git is a free and open source distributed version control system designed to handle everything from small to very large projects with speed and efficiency.

Using the [GitHub CLI](https://github.com/cli/cli) and a shell script, we will automate the process of monitoring pull requests in repositories we maintain. Specifically, open PRs we have created and those awaiting our review.

Monitor Pull Requests with the GitHub CLI

AI is amazing for generating code, but often leaves us staring at functions and libraries we've never seen before. This creates a huge problem: When things break (and they will break), we're lost. We don't understand the individual pieces, let alone how they interact. Knowing one part isn't enough; we need to see how unfamiliar components work together.

The solution? Real-world examples.

This lesson introduces ghx, a tool I built to do exactly that. ghx searches GitHub, finding actual code examples that use the specific combinations of functions and libraries that are tripping you up. Instead of generic documentation, you get concrete implementations. You can find the ghx repository at https://github.com/johnlindquist/ghx.

Here's the workflow we cover:

Identify the Unknown: Pinpoint the AI-generated code you don't understand – specific functions, libraries, or their interactions.

Search with ghx: Use ghx to search GitHub for examples using those terms together. ghx finds repos where those elements co-exist.

Consolidate Examples: ghx combines the relevant code snippets from those examples into a single, digestible file.

Ask the AI (Again, but Better!): Feed this consolidated code to an AI (like a coding-focused model in an AI studio). Now, instead of asking general questions, you can ask targeted questions based on real-world usage:

"Explain how these functions are used together in these examples."

"What are some common use cases for this combination of libraries?"

"Show me alternative code snippets that achieve the same result."

"Can you identify potential problems or areas for improvement, based on these examples?"

Iterate. Use your improved understanding to make changes, and then repeat the process to debug.

By leveraging ghx and targeted AI prompting, we transform from being lost in a sea of unfamiliar code to actively learning from how others have solved similar problems. We gain a deeper understanding of our AI-generated codebase, making debugging, modification, and future development far more manageable. This gives you the tools to understand, debug and improve your own code.

John Lindquist

How to Work with AI-Generated Code You Don't Understand with ghx and Gemini

In this less we create a custom Zod schema using `z.custom`.

The example case covers room numbers validation: it must start with an uppercase letter followed by three digits. `z.custom` allows the creation of a brand new custom schema with a callback function that returns a boolean indicating validity.

We highlight a challenge with type inference in Zod's custom schemas: callback parameter types don't get aligned automatically - type-safety must be explicitly defined using type parameters.

We run tests against various room numbers and demonstrate how to effectively validate inputs and manage error messages.


Tomasz Ducin

Create Custom Zod Schemas and Validate project-specific data

Create custom validation logic in Zod using z.custom, for primitive values, ensuring type safety and proper error messages for room numbers.


Excessive properties refer to any additional attributes that are not explicitly listed in an object schema. When creating an object based on a schema, it is important to ensure that only the defined properties are included.

In TypeScript, if an object is created with an extra property that isn't defined in the schema, TypeScript will not raise an error unless the type is explicitly annotated. When the type is annotated, TypeScript will issue an error indicating that the extra property is not allowed.

Zod provides a strict utility to enforce similar checks. This feature ensures that only specified properties are allowed in an object schema. When unnecessary properties are added at both the top level and within nested schemas, Zod will throw errors indicating unrecognized keys.

Adding an unrecognized property to a Zod schema results in an error message that specifies which keys are not recognized. Applying strict checks on nested schemas ensures that all levels of the data structure are validated correctly.


Make Excessive Object Properties Fail on Zod Validation

Prevent excessive properties in TypeScript and Zod schemas using strict checks for better data validation

In this lesson we discuss how Zod works with TypeScript to handle special types like `undefined`, `null`, `any`, `unknown`, `never` and `void`.

We modify our room booking schema to demonstrate the use of `optional` and `nullable` Zod utilities.

By using `.optional`, we allow a property to be either its _original type_ or `undefined`. With `.nullable`, we allow it to be either its _original type_ or `null`. Finally, `.nullish` allows a value to be either its _original type_, `null`, or `undefined`.

For all cases, we run tests to show how these schemas work in practice, as well as how TypeScript infers types.


Declare Lack of Value in zod (optional, nullable and nullish)

use Zod for TypeScript schemas, including handling undefined, null, and special types like optional and nullable values, as well as any, unknown never and void

In this lesson we make use of partial validation of large and nested schemas in Zod.

Instead of creating many small schemas, which can complicate maintenance, Zod allows for the extraction of specific parts of a schema using the concept of ".shape". It "unwraps" the object schema, enabling access to sub-schemas within specific properties.

Additionally, we can use the `.unwrap` to get into element schemas of altered schemas such as `.optional` or `.array`.

Simplify working with complex schemas without the need to break them into hundreds of small schemas.

Use Zod Schemas partially using shape and unwrap

Manage large and nested Zod Schemas by extracting partial validations using shape and unwrap utilities

In this lesson we cover implementing sets and maps in Zod.

Using `z.set`, a schema for string-based amenities is created. We demonstrate how validation works by intentionally introducing errors and customizing error messages for better clarity.

Next, a map is created for existing guestDetails schema using `z.map`, with string keys and an existing `z.object`-based schema. The validation process is shown again by deliberately breaking the schema, such as omitting the age property, which triggers appropriate error messages.


Validate maps and sets using Zod schemas

Use sets and maps in Zod for schema validation, ensuring type safety for both keys and values.

In this lesson we'll use a few predefined schemas which will serve as constituents to create union and intersection schemas.

Three room booking schemas are defined: _single_, _double_, and _suite_. Each schema has slight differences in the structure.

The `z.union` utility is used to create a union of these schemas, allowing for validation against any of them. Type inference (using `z.infer`) for the room booking schema produces a union of object literals, exactly like in TypeScript.

We also create an intersection using `z.intersection`, combining room booking details with discount information.

These techniques enhance data validation and allow to make `zod` aligned even more with `TypeScript`.


Define Unions and Intersections with Zod

implement unions and intersections in Zod schemas for example domain related objects, enhancing TypeScript validation with clear examples

This lesson demonstrates how to provide runtime type-safety for arrays in TypeScript applications.

First we need to understand the challenges behind ensuring array type-safety in TypeScript. We explain how TypeScript infers arrays with an undefined length, making it difficult to guarantee that array accesses are safe.

Zod schemas provide the `z.array` to define arrays of various element types. 

We compare how utilities such as `.min`, `.max` and `.nonempty` get reflected in inferred TypeScript types, and how zod processes the validation.


Declare Precise Array Types within Zod Schemas

Provide array type safety in TypeScript using Zod schemas, including handling non-empty arrays for better validation

In this lesson we make string-based schemas more specific using Zod in TypeScript. We focus on defining allowed values for a room type, showing how to use literals and enums effectively.

Zod's `z.literal` method allows us to specify a single allowed value for a string schema. For example, if we want to define a room type as `"premium"` and make it backward-type-safe in TypeScript, we can use `z.literal("premium")` to ensure that only this value is valid.

`z.enum` lets us define a set of allowed string values. This is useful when we have multiple options for room types, like `"standard",` `"premium"` or `"childrenFriendly"`. 

`z.enum` creates a union of TypeScript-compatible string literals, making it easy to validate against multiple values. Zod enums can be used to extract or exclude specific values from the enum.

Finally, zod's `z.nativeEnum` a native enum creates an equivalent of TypeScript's native `enum` ("real enums", we could say).

We can validate against all these values just like we do with literals and enums.


Work with Zod Literals and Enums Effectively

Use Zod for string schemas in TypeScript, including literals, enums, and native enums for room type validation

In this lesson, we dive into the Zod's `refine` utility, allowing defining more complex schema validation **on top of existing schemas and utilities**.

Sometimes, we need special validation rules for our applications to work correctly. The `refine` utility lets developers create their own validation rules. This method's uses a callback to check if the input is valid. We also create meaningful messages when something doesn’t meet the validation rules.

We use a practical example involving a room booking schemawith `dueDate` and `price` property refinement.


Apply Schema Custom Refinement with Zod

Enhance your TypeScript validation skills with Zod's refine utility for custom room booking schemas, focusing on date and price validation.


Search

Search Results