Learn Chrome-devtools, Natural and Serverless

Starting from a prebuilt frontend, Jason Lengstorf guides you through the creation of a "Corgi Up-boop App" that uses Netlify Functions and Hasura. You can view [the deployed final product on Netlify](https://egghead-serverless-functions.netlify.app/).

You'll set up the Netlify CLI, and configure a local development environment before writing and deploying functions with a few different use cases.

The first example function bypasses CORS restrictions to retrieve corgi data from an example third-party API.

Next, you'll configure environmental variables to securely communicate with the Unsplash API without exposing private keys to the client.

Serverless functions don't persist data by themselves, so we will use  Hasura to create a GraphQL API for tracking the number of "boops" each corgi receives.

This course is an excellent illustration of the speed of Serverless functions, and how fast you can implement functionality in your web applications.

An all-in-one workflow that combines global deployment, continuous integration, and automatic HTTPS.

netlify

Build a Corgi Up-boop Web App with Netlify Serverless Functions and Hasura

Chrome DevTools are incredibly useful for a frontend developer, sometimes we spend more time using them than our text editor of choice.

That's why it's so important to understand this tool better - those quick lessons will teach you things that will help you to become a more effective developer.

You will learn how to:

- **Use (experimental) CSS Overview to learn all about CSS used on a page in a minute**
- **Style console.log messages with CSS** - a _crucial_ skill for any senior developer (j/k)
- **Debug your code (on production and local environment) with logpoints**
- **Run a Lighthouse audit of your site**
- **Choose accessible colors for your website that have an AAA contrast ratio rating**
- **Force a DOM element state in Chrome DevTools**
- **Use Console utilities to make debugging easier**
- **Copy a network request as fetch or cURL with Chrome DevTools**

Have fun!

The Chrome Developer Tools (DevTools for short), are a set of web authoring and debugging tools built into Google Chrome.

chrome-devtools

Chrome DevTools tips & tricks

Miscellaneous one-off lessons on debugging, productivity hacks, and JavaScript tricks.

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

Tips and Tricks

Frontend runtime optimization is heavily impacted by rendering.  Understanding the way the JS engine and the browser work is crucial for optimizing applications and understading how to avoid performance pitfalls.
This collection explains about the Critical Rendering Path, performance bottlenecks and practical solutions.

Critical Rendering Path

Create a serverless application and deploy it in under thirty minutes!

We'll be using Netlify, Vite, TypeScript, and React in our project. This stack synergizes extremely well for rapidly developing professional-quality applications. 

If you haven't heard of Vite, it's the French word for quick! It's also a build tool that consists of a dev-server and an extremely fast bundler. It makes for a rapid development loop.

As for the rest. Netlify makes hosting fast and easy with serverless functions and continuous deployment. React enables you to quickly create reusable components. And TypeScript helps you write cleaner code that is easier to refactor. 

So get started and learn how to use this stack in your own applications!

Deploy a Serverless API React Application with TypeScript

In this course we’ll work through Natural’s API for natural language processing in JavaScript. We’ll look at how to process text: learning how to break up language strings, find the word roots, work with inflectors, find sequences of words, and tag parts of speech. We’ll learn how to find important stats about a body of text: how to compare strings, how to classify text with machine learning, how to use the tf-idf tool to find relevant words. We’ll look at some of the extra tools Natural gives us, including the dictionary/thesaurus of WordNet, a phonetics comparer that lets us see if two words sound the same, and a spellcheck feature. We’ll also look at tries and digraphs, two data structures that help us better analyze bodies of text.

Natural is a general natural language facility for nodejs. Tokenizing, stemming, classification, phonetics, tf-idf, WordNet, string similarity, and some inflections are currently supported.

natural

Natural Language Processing in JavaScript with Natural

In this course we’ll take a deep look at the Elements panel in the chrome devtools. We’ll step through each button and tab on this panel and discuss how to use them to interact with your web application as it runs.

Debug the DOM in Chrome with the Devtools Elements Panel

This course examines the Sources panel in the Chrome DevTools, which allows you to see what files are responsible for the various things on the screen. Bundled into this panel, though, is the single most useful tool for any JavaScript developer - the JavaScript Debugger. We’ll use the Debugger to inspect JavaScript as it runs, allowing you to watch (and even interact with) the state of your application as it runs in ways that’ll blow your mind if you’ve mostly used console.log to debug your applications to this point. 

Debug JavaScript in Chrome with DevTool Sources

This course will examine the Network panel in Chrome DevTools. We’ll step through the request log, examining the various properties exposed. We’ll talk about timing, filtering, throttling and generally using the network panel to better understand the ways in which our applications exist within a connected context.

Debug HTTP with Chrome DevTools Network Panel

If you are developing JavaScript applications you are likely using logging as an integral part of your development process. Did you know that you aren't limited to simple `console.log` statements? Modern browsers give you a lot more logging options to work with!

This course will explore those options and give you some new logging tools for your professional toolbox.

Advanced Logging with the JavaScript Console

Get more mileage from your console output by going beyond mere string logging - log entire introspectable objects, log multiple items in one call, and apply C-Style string substitution to make the console work for you.

Advanced Console Log Arguments

Organize your log output by grouping your logs into collapsable hierarchies using console.group().

Grouping and Nesting Console Log Output

We will learn about “stemming,” the process of finding the root of words, often in order to group words by a common base root. We will look at the Porter and Lancaster Stemmers, briefly touch on Natural’s support for Russian and Spanish stemmers, and introduce the function to stem and tokenize at the same time.

Find the roots of words using stemming in Natural

Inflectors are the modifiers of a word that indicate grammatical categories. While Natural’s coverage of inflectors is not comprehensive, we will show how Natural can pluralize/singularize nouns and count numbers. 

Pluralizing nouns and counting numbers with inflectors in Natural

N-grams are sequences of words, where the 'n' stands for the number of words in the sequence. In this lesson, we will see how to find bigrams (2-grams), trigrams (3-grams), and any other length n-gram in a body of text. 

Find sequences of words (n-grams) using Natural

We will learn how to compare how similar two strings are to each other, examining three algorithms: Jaro-Winkler, Levenshtein, and Dice’s Coefficient.  

You should note that none of these algorithms are inherently better than the others. Instead, it's important to choose the one that best fits your text data. 

Compare similarity of strings through string distance in Natural

In this lesson, we will learn how to train a Naive Bayes classifier or a Logistic Regression classifier - basic machine learning algorithms - in order to classify text into categories.

Classify text into categories with machine learning in Natural

In this lesson, we will learn how to train a Naive Bayes classifier and a Logistic Regression classifier - basic machine learning algorithms - on JSON text data, and classify it into categories.

While this dataset is still considered a small dataset -- only a couple hundred points of data -- we'll start to get better results.

The general rule is that Logistic Regression will work better than Naive Bayes, but only if there is enough data. Since this is still a pretty small dataset, Naive Bayes works better here. Generally, Logistic Regression takes longer to train as well. 

This uses data from Ana Cachopo: http://ana.cachopo.org/datasets-for-single-label-text-categorization

Classify JSON text data with machine learning in Natural

 AJAX allows us to send requests to the server from our javascript applications, rather than allowing the browser to directly request declaratively specified resources. Under the hood, though, AJAX requests are still just HTTP requests - and that means we can use the Network Panel in Chrome’s DevTools to inspect our AJAX operations!


Examine AJAX Requests with Chrome Devtools

Tries are a data structure that provide an efficient way to search for the existence of a word or phrase in a body of text, or to search by prefix. 

Search more efficiently with tries using Natural

To understand the Network DevTool, you have to understand what HTTP is and how it works. Let’s use the Network DevTool to inspect an HTTP request and its corresponding response so that we can understand what the browser is doing.

Search

Search Results