Learn Algolia, Cloudflare and D3

Cloudflare Workers let you write JavaScript Service Workers that run directly in Cloudflare's 200+ edge locations around the world.

With a Cloudflare Worker, you can modify your site's HTTP requests and responses, make parallel requests, and even reply directly from the edge.

Cloudflare Workers are written against a similar API to the W3C Service Workers standard. However, while Service Workers run inside the end user's browser, Cloudflare Workers run on Cloudflare's servers. This means that Cloudflare Workers can implement trusted code (which the client cannot tamper with), and will work no matter what browser the user is running.

In this course, Kristian Freeman will teach you how to build and deploy a Serverless API with Cloudflare Workers. By learning how to build your own serverless JSON APIs, you can effectively manage a highly-available backend for your projects, without needing to learn DevOps or manage services.

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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Build a Serverless API with Cloudflare Workers

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)*

Introduction to Cloudflare Workers

Today’s users expect great things from their search experiences — speed, relevance, and usability, to name a few. Algolia provides developers with out-of-the-box and customizable search experiences that are a joy to build.

This introductory course on the Algolia search solution focuses on the user-facing part of search. Using the Algolia InstantSearch.js front-end library, we’ll see how to build an engaging search experience in no time. (28 minutes, to be exact.) 

**Prerequisites:** 
You don’t need previous experience with search to follow this course — we’ll use an example index with an e-commerce data set preconfigured. We will work mainly in JavaScript, so basic JS knowledge is expected.

If you want to play with your own index settings and data set, you can [create a free Algolia account here](https://www.algolia.com/users/sign_up/hacker/?utm_medium=link&utm_source=egghead&utm_campaign=education), but this is not required to follow along with this first course. 

Algolia's full suite APIs enable teams to develop unique search and discovery experiences for their customers across all platforms and devices. Type a query. Click a link. Open an app. Everything your customers do sends a signal about what they want. Algolia decodes that intent to deliver the right content - instantly.

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Getting Started with Algolia InstantSearch.js

The “Edge” is where you write and store your code where your data is being produced. This allows for a quick and efficient data transfer, eliminating or severely reducing lag. 

Supabase is a suite of open-source tools wrapping a PostgreSQL database. It provides the building blocks of an app - database hosting, auth, file storage, real-time, and edge functions - so we can focus on what makes our app unique.

Cloudflare Workers are serverless functions that run at the Edge! In this course, we will use the Wrangler CLI tool for interfacing with your Cloudflare account and creating or publishing your Workers.

KV Storage is a cache that Cloudflare makes available to our Workers. It replicates across multiple CDN nodes, making it super performant to cache data.

Combined, these three things give you the benefits of that reduced lag in a smooth and streamlined process. 

Throughout this course, Jon will teach you how to create a small blog that hits the key points of how to:

- Query Supabase from Cloudflare Workers
- Read and write KV Storage cache from Cloudflare Worker
- Cache Supabase response at the Edge with KV storage

And more! 

Cache Supabase data at the Edge with Cloudflare Workers and KV Storage

D3, or Data Driven Documents, is the defacto standard for data visualization on the web. It's an incredibly powerful library that gives you all the tools you need to build just about visualization you can dream of.

D3 is not a collection of predefined charts. Instead, it's a robust set of utilities you can use to ingest and transform data, to map that data to screen values, and ultimately to manipulate the DOM to render your visuals.

When working with React, D3's desire to manipulate the DOM is at odds with React's goal of rendering the UI as a function of state. So how do we handle this? Simply put, we use D3 for everything up to the point where we want to render our output, and then we hand all that data to React for rendering.

In this course, we'll start from scratch and build out an SVG bar chart for some sample data. We'll lean on D3 for its tools and then hand that data off to React for rendering.

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.

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Create A Bar Chart with React and D3

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

The Edge is one of the most exciting new topics in web development. At the front of the pack is Cloudflare, whose network boasts servers located in hundreds of cities all over the world instead of in regions like "East" or "West".

More servers in more locations mean a faster experience for your users.

But what about the data part of the equation?

If the application you're working on skews more toward "reading" rather than "writing" data, Cloudflare Workers KV is a perfect fit.

Once you create a KV namespace— the "KV" stands for "key-value"— Cloudflare keeps track of your application data. The most commonly accessed data will be propagated around the world to the various Edge servers, while less popular data will be stored in more central locations.

Kristian Freeman has produced courses that introduce how to build and deploy sites and JSON APIs powered by Cloudflare Workers.

Today, he will show you how Workers KV can be integrated into a Cloudflare Workers project through building a Todo App.

## The Project

![todo-app-screenshot](https://res.cloudinary.com/dg3gyk0gu/image/upload/v1639014074/course-resources/Build-data-driven-applications-on-the-edge-with-Workers-and-Workers-KV/CleanShot_2021-12-08_at_16.46.39_2x.png)

Before you groan about a bland Todo App, think about it this way: 

The Todo App is the perfect example of the CRUD operations. Cloudflare KV has its own nuances for reading and writing data through a concept called Binding that is easier to grok when you understand the larger example as a whole.

As the course progresses, Kristian shares examples of how you can store more complex key-values, along with data operations like editing and filtering.

One of the coolest features that Cloudflare KV allows for is user-specific data that is tied to the IP address the request originates from. In other words, you'll be able to share your deployed Todo app with anyone around the world, and they will only see their personal items.

## **Gain these Skills**

- Manipulating data using Cloudflare Workers KV
- Make data unique to each user without logging in
- Effectively store lightweight data in Cloudflare Workers KV
- Setting up a key-value store and connected projects
- Reading and writing to a serverless key-value store
- Storing complex values in a Cloudflare KV store

## **Prerequisites**

You'll need to have a basic understanding of what Cloudflare Workers is recommended but not necessary. This course is relatively beginner-friendly into the world of Workers KV that you can get by with no knowledge on Cloudflare Workers. 

But if you want to get the most out of this course, we would recommend taking [Introduction to Cloudflare Workers](https://egghead.io/courses/introduction-to-cloudflare-workers-5aa3) to get a better understanding of how Workers KV comes into play. 

## **What's Next? (You might also like these resources:)**

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. → [Introduction to Cloudflare Workers](https://egghead.io/courses/introduction-to-cloudflare-workers-5aa3) 

Learn how to build your own serverless APIs so you can manage a highly available backend for your projects. No Learning DevOps or managing services necessary. →  [Build a Serverless API with Cloudflare Workers](https://egghead.io/courses/build-a-serverless-api-with-cloudflare-workers-d67ca551)

Using Cloudflare Pages and Cloudflare Workers, it's easy to create dynamic front ends that you can deploy in just seconds from GitHub. → [Deploy Dynamic Frontend Applications with Cloudflare Pages](https://egghead.io/courses/deploy-dynamic-frontend-applications-with-cloudflare-pages-6aaa00a1)

Build Data-Driven Applications on the Edge with Workers and Workers KV

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

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.

angularjs

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.

Create a D3 Chart as an Angular Directive

As of version 4, D3 is a completely modular tool, composed of many small libraries. You can use them independently or as a whole, and even create custom builds that include only the parts you need. This lesson will review the options available for installing and using D3, and will set up a local environment for rapid experimentation.

Install and Configure D3 v4

When your data contains discrete, non-numeric property values that you need to format or convert before displaying, `d3.scaleOrdinal()` is the API you need. Maybe you need to convert a “pass”/”fail” field to “green”/”red” for coloring your bubble chart? This lesson shows you exactly what to do.

Create Labels from Non-numeric Data with Ordinal Scales in D3 v4

Mapping abstract values to visual representations is what data visualization is all about, and that’s exactly what D3 scales do. Turning a test score into a column height, or a percentage into an opacity requires translating from one set of possible values to another, and linear scales perform a direct, proportional conversion of inputs to outputs. In this lesson we’ll learn the basic API of D3 scales and how to use them.

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