Learn Docker, Lodash and Reactfire

While "It works on my computer" might give you an excuse to close a bug ticket in the backlog, it doesn't really work when you're working on a team.

You need to ensure that your application can run regardless of what hardware your teammates are running or libraries they have installed.

Docker solves this problem by collecting everything your application needs to run into a container.

Containers aren't just for source code. They can hold configuration, scripts, and even their own filesystem. It's similar to a Virtual Machine, without having to bring a full operating system along for the ride.

Because containers run in isolation, there is some configuration involved to allow for files to be saved and containers to communicate with one another.

One of the most useful ways to get your head around Docker is to see it in action.

Follow along with Joel Lord as he works through the process of preparing an application to run in separate containers for the frontend and backend of an application that searches for gifs and re-encodes them with a caption supplied by the user.

You'll see how to configure the separate containers to communicate with one another, work with environment variables, and persist data to your local machine. Along the way, you'll pick up some tips on useful commands and bash scripting. Finally, you'll learn how to use Docker Compose to make it easy to run multiple containers simultaneously.


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

Containerize Full-Stack JavaScript Applications with Docker

In this course we will take a simple Node.js app that connects to a MongoDB database and uses an Express web server, and learn how to setup a full software development deployment process as well as how to properly “Dockerize” the app. 

We’ll step through setting up proper version control techniques, managing configuring within the environment, setting up proper build/deploy/run processes, and all with abiding by Docker best practices. We’ll also make sure our deployment is setup for scale, and have consistent development practices in place for reliable app deployments.

Build a Twelve-Factor Node.js App with Docker

Zeit’s mission statement is to ‘Make Cloud computing as easy and accessible as Mobile computing.’ To that end, they’ve released some pretty amazing and powerful tools. In this course we’re going to take a look at `now`, their deployment tool, to see why it’s hands-down the simplest way to launch node applications, docker containers and even static files to the cloud.


We’ll also dig into some of now’s more advanced capabilities, including host aliasing, environment variables and integration with hosted databases.

Deploy Web Apps with Zeit Now

[Lodash](https://lodash.com/docs/) is a collection of utilities that have become a staple of modern web development. This collection will show you how to re-create its most common methods using simple JavaScript techniques available in any modern web browser. In addition to re-building tools like `_.merge`, `_.get` and `_.debounce` from scratch you will also learn how to replace them completely in some cases with modern syntax such as [optional chaining](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Operators/Optional_chaining), [nullish coalescing](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Operators/Nullish_coalescing_operator) and [Object.fromEntries](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Object/fromEntries).

This collection should interest the following groups:
- Those who want to better understand common JavaScript patterns
- Engineers who want to reduce their dependence on Lodash (for performance or other reasons)
- Candidates preparing for a technical job interview (where it is common to be asked how to implement some of these methods).

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

Recreating Popular JavaScript Utility Methods from Lodash

Kubernetes is an API to a computer. Multiple computers actually. Here we'll talk about what K8s is, how you can choose between the plethora of K8s related hosting options, and what the process looks like for getting some containers running.

WTF is Kubernetes (K8s)

Use [Hasura](https://hasura.io/), an open source GraphQL engine to setup a backend.

You need to have Docker installed. You can [install](https://docs.docker.com/install/) from the Docker website.

Set up a GraphQL Backend with Hasura and Docker

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

postgres

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

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

Running YugabyteDB Cluster Locally using docker-compose

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

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

Set up Hasura GraphQL engine with YugabyteDB distributed SQL

When we need to spin up a database instance for our new project, installing the database management system directly on our local machine is almost always a bad idea. Luckily, Docker is here to help us practically reduce the complexity of dealing with "missing dependencies" and weird error messages down to zero.

In this lesson, we will learn how to get a PostgreSQL instance running locally with Docker Compose, so we can work on the database integration of our project and test things out with ease. To follow this lesson, you will need to have Docker pre-installed.

Set up and run a PostgreSQL instance locally with Docker Compose

This lesson will demonstrate how to recreate a simplified version of the popular [lodash.merge](https://lodash.com/docs/4.17.15#merge) method from scratch.

First we'll create a test file with two objects that we want to merge together and demonstrate the output after running them through lodash.merge , then we'll go about creating our own version of the function.

Our initial version will support only one `source` object to merge in, and will support only the subset of JavaScript syntax supported by the JSON spec, including the following types:
- `boolean`, `number`, `string`
- object literal
- array

After getting basic types to merge we'll show off two methods for merging arrays, either using [concat](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Array/concat) or recursively going through the children and merging them.

Finally we'll build our own `isObject` function to check for object literals and recursively apply our `mergeJSON` function to any object literals in our `source` object.

And last we'll add support for multiple `source` objects to be merged in using a `for...of` loop.


**Note**

The `mergeJSON` method we create approximates the `lodash.merge` functionality but does not seek to replace it. It may be useful for some use cases, but primarily it's meant to be a tool for understanding how to merge objects with recursion.

Build lodash.merge from Scratch

This lesson will demonstrate how to replace common uses of [lodash.get](https://lodash.com/docs/4.17.15#get) with [optional chaining](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Operators/Optional_chaining) syntax.

`_.get` is by far my favorite lodash method. I've been on so many projects where the results of a network call was a large and often unreliable blob of data. After countless attempts to reign in errors caused by trying to access non-existent properties I've come to rely on _.get as a simple & safe way to retrieve data from those objects. However, as is always the case in web development, times are changing and the tools we need to safely access properties of complex objects are now being built into the platform. [Optional chaining syntax](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Operators/Optional_chaining) gives us the power of _.get without several of the tradeoffs. It doesn't require an extra library to use, it plays nicely with TypeScript and it can be used when calling methods as well as when accessing properties.

This lesson covers 4 common use cases of `lodash.get` and converts them to using optional chaining syntax.

1. Nested Object and Array Access
2. String and Variable Property Access
3. Calling a Method on an Object that may Not Exist
4. Providing a Default Value when a Property does Not Exist 

---

 ### Resources

- [Nullish coalescing operator](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Operators/Nullish_coalescing_operator)

Replace lodash.get with Optional Chaining Syntax

This lesson will demonstrate how to recreate a simplified version of the popular [lodash.get](https://lodash.com/docs/4.17.15#get) method from scratch.

Our function takes 3 parameters `obj`, `string` and `defaultValue`.

The primary technique we discuss is splitting the `string` on any kind of separator we might see such as `[`, `]`, or `.` and then filtering out any empty strings we get in our array. Once we have that array of path parts, we can loop through each part with a `for..of` loop then keep reaching into object until we either a) run out of parts to try 🎉 or b) hit a dead end (`null` or `undefined`). The entire function is very simple to write, but can be incredibly powerful when you're safely trying to access large and complex blobs of data that might be coming from a database or server response. 

Build lodash.get from Scratch

This lesson will demonstrate how to recreate a simplified version of the popular [lodash.debounce](https://lodash.com/docs/4.17.15#debounce) method from scratch. **I literally failed a job interview by messing up this question, so watch carefully!**

Debounce is an incredible tool most commonly used to prevent responding too quickly to user input that is in motion. For example, preventing excessive AJAX requests made while a user types into an autocomplete field or quickly responding to window resize events without bringing your browser to a halt.

Our approach is to build the simplest `debounce` method possible using a [setTimeout](https://developer.mozilla.org/en-US/docs/Web/API/WindowOrWorkerGlobalScope/setTimeout) which gets cleared each time the supplied function is called thereby delaying the execution of our function until input stops for a given amount of time.

The [Lodash implementation of debounce](https://lodash.com/docs/4.17.15#debounce) includes support for a number of options including `leading`, `maxWait`, and `trailing` which we have not covered in this video, but may in future lessons.

### Variations

Modern implementations of `setTimeout` include support for additional arguments which get passed into your function so an alternative to the approach used in this lesson would be `setTimeout(fn, wait, ...args)`

### ES5 Compatbility

If you are in an es5 environment skip the rest/spread syntax and use:

```
var args = Array.prototype.slice.call(arguments)
```

And later, in your setTimeout function:

```
fn.apply(null, args)
```

----

There are some really great resources out there to learn more about debounce, here are my two favorites:

- https://css-tricks.com/debouncing-throttling-explained-examples/
- http://benalman.com/projects/jquery-throttle-debounce-plugin/


Build lodash.debounce from Scratch

This lessons builds on [Build lodash.debounce from scratch](https://egghead.io/lessons/javascript-build-lodash-debounce-from-scratch) to add support for one of its more interesting options: `maxWait`. The `maxWait` option ensures that a debounced method is deferred no longer than the time specified. This is helpful if we need to respond to a long running interaction while it's still in progress. 

In this lesson we'll demonstrate how continuously typing into a debounced input field prevents us from logging any input at all. We'll add a `maxWait` option as a third parameter to our `debounce` function and set it up using an additional `setTimeout` call.

Essentially `maxWait` works by adding a second timer which will fire in the case that the normal debounce timer does not get called. We avoid unnecessarily triggering our debounced function by calling `clearTimeout` in both of our `setTimeout` functions to clear out whichever timer didn't just fire. We also need to set the `maxTimer` variable to `null` to tell our function it's safe to start a new maxWait timer each time either timer fires.


**Notes**

- `setTimeout` returns a timer ID not the actual timer object itself, which is why we have to `null` it out *after* we already call `clearTimeout`
- If you don't `null` out `maxTimer` in your original timer, the maxWait timer will stop triggering after the debounce timer is called the first time. I learned that one the hard way when I first recorded this video.


Extending debounce with a maxWait Option

`_.pick` and its sibling `_.omit` are popular utilities which apply filter-like functionality to objects. This lesson will demonstrate two different techniques for building the functionality found in [_.pick](https://lodash.com/docs/4.17.15#pick).

1. Using `for...of` to loop through the `keys` array
2. Using `for..in` to loop through the target object

This lesson will also cover how to emulate `_.pick`'s support for either an array or multiple arguments for the picked keys using [Rest params](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Functions/rest_parameters) and [Array.prototype.flat()](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Array/flat).


Build lodash.pick from Scratch

`_.omitBy` and its sibling `_.pickBy` are popular utilities which apply filter-like functionality to objects. Both of them accept a function to determine if a given entry in the object should be included in the output object. This lesson will demonstrate an approach to build both of these utilities from a single function using the combo of `Object.entries` and `Object.fromEntries`.

`Object.entries` converts an object into an array of key, value pairs. We couple that with the native Array filter method, to create a generate `filter()` method that works on objects. Once we've filtered our object we use `Object.fromEntries` to convert the array back into an object. This works great for both `omitBy` and `pickBy`.

**Note**

`Object.fromEntries` is part of the ES2019 spec and may need [a polyfill](https://github.com/ungap/from-entries) to work depending on your environment.

---

- [MDN Guide: Object.entries](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Object/entries)
- [MDN Guide: Object.fromEntries](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Object/fromEntries)



Build lodash.omitBy and lodash.pickBy with Object.fromEntries

First, we'll get a tour of the application and what it does then we will start configuring a fresh project. 

The application UI is simple. It asks for a keyword and will search and display a random GIF from Giphy. Once you are satisfied with the image, you will be able to add a caption to it. The server will deconstruct the GIF frames, add the caption and re-create the GIF for you. Everything is then saved to a database so that all the users can benefit from your creations.

The tech involved to do this is a Vue frontend, Node.js backend, and MySQL database. I'll walk you through cloning, installing dependencies, configuring the giphy API key that we use, and starting the application. You'll notice at the end we'll need to configure the database. We'll get an error but this is expected!

Configure and Run a Node.js API Powered by a Vue Application

In this lesson, you will learn how to start basic containers and how to use them in your day to day developer life. You will also learn how to start a database container that can be used with the demo application for this course.

Running Your First Container

You will learn how to create your own images that will include all the source code of your application, along with a specific version of Node.js and all the dependencies that are needed. Once you are done, you will be able to share this image with other people and this will ensure that everyone is running the same environment. It will event let people that don’t have Node.js run this server. This will also have the added benefit of cleaning up everything once you close the application.

You'll notice that we will run into the same error stating we can't connect to the database. This is expected and we'll fix this in [Allow Container to Communicate through Docker Networks](https://egghead.io/lessons/docker-allow-container-to-communicate-through-docker-networks)

Create a Custom Image with a Dockerfile running Node.js

In the last lesson [Create a Custom Image with a Dockerfile running Node.js](https://egghead.io/lessons/docker-create-a-custom-image-with-a-dockerfile-running-node-js?pl=introduction-to-docker-afaf), our backend stopped working again because it couldn’t find the database.

One of the advantages of running containers is that they run in isolation. As far as the container is concerned, nothing exists outside of it. It behaves as if it was its own operating system. This is why the backend can’t find the database on "localhost". The two containers are running on the same host but as far as the backend is concerned, there is no database. The same goes for the database. It can’t see anything outside of what is running in its container therefore it can’t see the backend application running.

When you need a way for multiple containers to talk to each other, Docker has a tool called networks to help you. We'll use a network to allow our backend to successfully connect to the database.

Allow Containers to Communicate through Docker Networks

For your front end, a VueJs application has been created from the CLI. VueJS, just like React and Angular applications have a development mode as well as a production mode.

Once you are ready to deploy this application, you won’t want to use the same code as you do when you develop. In fact, you will need to run another script to build a production application. This script will take all of your JavaScript files and merge everything into a single minified JavaScript file. It will do the same for your CSS. By doing so, you will end up with a minimal set of files that can be served over any static file webserver. In this case, you will be using an Nginx server to serve those files. Nginx is an open-source, high-performance HTTP server that will be able to handle many requests to your front end.

We'll do this with a multi-step build in a Dockerfile that will discard the first container that we use to build the source code and run it in a container that's built on top of the nginx image.

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