Learn Axios, Cloudflare and D3

Cloudflare Workers is a serverless application platform that enables you to create and deploy functions to Cloudflare's Edge Network.

Unlike other serverless providers that only have regional data centers, Cloudflare's Edge Network consists of hundreds of servers all over the world.

Cloudflare Workers is a powerful platform, and this course serves as a great introduction for what it can do.

Follow along with Kristian Freeman as you build a localization engine that renders data based on the Edge location nearest to the application's user.

After this course, you'll be ready to start experimenting with your own Cloudflare Workers projects. *Need an idea?* *[Check out the suggested Portfolio Project for this course.](https://egghead.io/projects/introduction-to-cloudflare-workers)*

Cloudflare secures and ensures the reliability of your external-facing resources such as websites, APIs, and applications. It protects your internal resources such as behind-the-firewall applications, teams, and devices. And it is your platform for developing globally-scalable applications.

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Introduction to Cloudflare Workers

In this course we will learn and demonstrate the fundamental concepts and APIs of D3, on our way to building several common chart types. We’ll start with the building blocks upon which all D3 visualizations are built; things like scales, interpolators, and selections. We’ll see how to load data with D3, and how to put its full name, Data Driven Documents, into action. We’ll build column and bar charts, scatter plots, and area charts. Most importantly, we’ll gain an understanding of the conventions and patterns that underlie all D3 projects and examples, enabling you to dissect, understand, and build virtually any D3 visualization on the internet.

D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG and CSS. D3’s emphasis on web standards gives you the full capabilities of modern browsers without tying yourself to a proprietary framework, combining powerful visualization components and a data-driven approach to DOM manipulation.

Build Interactive JavaScript Charts with D3 v4

This course covers D3 v3. If you'd like to learn about v4 of D3 (the latest version) [click here for the course on that](https://egghead.io/courses/build-interactive-javascript-charts-with-d3-v4).

This series will gently guide you through the first steps in getting to know D3. The curve can be steep, but with a few simple tools, you'll be charting your buns off in no time flat.

Use D3 (v3) to Build Interactive Charts with JavaScript

To deploy a Cloudflare Workers serverless function, you'll need to sign up for a free Cloudflare Workers account at [workers.cloudflare.com](http://workers.cloudflare.com/), and select your unique workers.dev subdomain to deploy your functions to.

Create a Cloudflare Workers Account

Using NPM, you can install Cloudflare Workers' CLI (command-line interface), Wrangler, by typing `npm install -g @cloudflare/wrangler` into your command line. Wrangler allows you to generate and publish Cloudflare Workers projects. We'll also use the `wrangler login` command which will give you a link to authorize Wrangler. This will set up an API token specifically for your Wrangler installation that will allow you to publish and read all the Workers and Workers KV information that you need.

Install and Configure the Cloudflare Workers CLI Wrangler

Wranglers generate command, `wrangler generate`, allows you to create new Cloudflare Workers projects. Using the URL parameter, you can also generate new projects based on Cloudflare's starter templates, or open-source projects created by other developers, but for now, you will just use the default. To do this you'll only need to give it a name, for example, `wrangler generate my-worker`,  this will create a new project called my-worker. 

Generate New Cloudflare Workers Projects with Wrangler's generate Command

We'll take a look at the default code in `index.js` in a Workers project. We'll take a second to understand how it works before building the rest of our project. 

First will see what our Worker looks like in an actual browser by running `wrangler preview`. In a terminal, and we'll check out how Serverless functions in Cloudflare Workers listen for HTTPS requests via the "fetch" event and respond to them by creating and returning a new Response.

Write Your First Cloudflare Workers Serverless Function

Using `wrangler whoami` in a terminal we'll grab our account id so we can paste our id into the double quotes of `account_id = ""`  inside of `wrangler.toml` file. Using the `wrangler dev` command we can look at our Workers serverless function and test it before deploying it. Once we're ready to deploy, we can use the `wrangler publish` command to deploy it to our unique workers.dev subdomain.

Preview and Publish Your Cloudflare Workers Project

By updating the response body and setting a corresponding Content-Type header, we can render HTML pages from directly inside of our Cloudflare Workers function.

We will update our Cloudflare Worker to return a call to a template function that we define. That template function returns a string of HTML that we will render in the browser.

Render HTML Pages with Cloudflare Workers

Up until now, we've been rendering plain responses, not based on any information coming in with a request. The request.cf object sent with every incoming HTTP request to a Workers function has a ton of interesting information, including the regionality of the request, and which Cloudflare data center is responding to the request. Using this information, we'll render a dynamic HTML page based on where the user visiting our site is in the world.

Render Cloudflare Region Data for a Request Using request.cf

Deploying to your unique workers.dev subdomain is a great way to test your serverless functions before they're ready to go to production. Once you are ready to deploy to production, you can use Wrangler's environment feature to deploy to your zone, or Cloudflare-managed domain, by providing the "-e" (environment) flag when publishing.

You can check this worker out [here](https://hello-world-worker.signalnerve.com/).

Deploy to a Custom Domain with Cloudflare Wrangler Environments

Most of D3’s native selection APIs also return the selection (or a new selection), to enable multiple method calls to be chained together. Since the code you write isn’t on the selection prototype, chaining your methods would take some extra work. `selection.call()` will call any function reference you give it, providing the selection as the first parameter, and then it returns the selection for you to ensure chaining is supported.

Better Code Organization with selection.call() with D3 v4

Making SVGs responsive is unfortunately not as simple as adding some media queries. This lesson introduces the `viewBox` attribute, which is used to control how SVGs scale. We’ll also examine a reusable function that can be used to make nearly any visualization responsive.

Make D3 v4 Charts Responsive with the viewBox attribute

In D3, the General Update Pattern is the name given to what happens when a data join is followed by operations on the enter, update, and exit selections. When a chart's data changes over time and each update can both create new elements and destroy existing ones, the General Update pattern can help convey meaning to users. This lesson demonstrates the pattern using animated transitions on a column chart.

Animate with the General Update Pattern in D3 v4

Ensuring your charts are responsive is essential if you want them to work regardless of the user's device and screen size. In this lesson we'll learn how the viewBox attribute of SVG elements works, and apply that knowledge to make a future-proof D3 chart.

Responsive D3 charts with the viewBox attribute

Since D3 outputs standard markup, you can use familiar dev tools and inspectors to debug your visualizations. In this lesson we’ll look at how to use Chrome Dev Tools to examine the data associated with your generated markup and experiment with styles to speed up the development process.

Debug D3 v4 with Dev Tools

D3 makes it easy to add meaningful animations to your data visualizations. Whether it’s fading in new items or tweening existing shapes to display new values, adding transitions is easy. This lesson shows you how to add animations while building on your existing knowledge of D3 selections.

Animate Transitions in D3 v4

Create a line chart, then easily convert it to an area chart

Line and Area Charts with D3

Mapping abstract values to visual representations is what data visualization is all about, and that’s exactly what D3 scales do. This is usually done using pretty straightforward algorithms, but nothing is straightforward when you’re working with Date objects in JavaScript. If you’re plotting temporal data, you need to use a time scale.

Convert Dates to Numeric Values with Time Scales in D3 v4

Sometimes data needs to be converted from a continuous range, like test scores, to a discrete set of output values, like letter grades. In this lesson we’ll see how to use `d3.scaleQuantize()` to do exactly that.

Create Labels from Numeric Data with Quantize Scales in D3 v4

AngularJS is an open-source JavaScript framework, maintained by Google, that assists with running single-page applications. Its goal is to augment web-based applications with model–view–controller (MVC) capability, in an effort to make both development and testing easier.

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Integrating D3 with Angular can be very simple. In this lesson, you will learn basic integration as well as how to create D3 charts that can be packaged as AngularJS directives.

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