Learn Android, Puppeteer and Python

OpenGraph images are the images you see when you paste a link into a social platform and it "unfurls" into an image, title, and description. This happens on Twitter, Discord, Slack, and many other platforms. This collection goes over everything from designing OpenGraph images in Figma, to implementing them in CodeSandbox, to returning headless browser screenshots from Netlify Functions, and finally using Cloudinary as a write-through cache. 

You will come away from this collection with the ability to ship an API that you can use on any of your sites, and also on-demand, that can generate images for not only OpenGraph unfurls, but also for Instagram, GitHub, and more. Using headless browsers with playwright to generate our images means we get full access to all the responsive power of CSS and all the logical power of JS to handle layout, importing assets like pngs, choosing different fonts, and more.

The image below is generated via the project you'll build and deploy in this course

![An example opengraph image](https://relaxed-payne-d1bfbe.netlify.com/opengraph?title=Building%20an%20OpenGraph%20image%20generation%20API%20with%20Cloudinary%20Netlify%20Functions%20and%20React&tags=figma,netlify%20functions,playwright&author=chrisbiscardi)

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

Building an OpenGraph image generation API with Cloudinary, Netlify Functions, and React

Neural networks, with Keras, bring powerful machine learning to Python applications. They can answer questions like “How much traffic will hit my website tonight?” or answer classification questions like “Will this customer buy our product?” or “Will the stock price go up or down tomorrow?”

In this course, we’ll build a fully connected neural network with Keras. This is the most basic type of neural network you can create, but it’s powerful in application and can jumpstart your exploration of other frameworks. 

We’ll start the course by creating the primary network. Then we’ll:

- build and configure the network, then evaluate and test the accuracy of each
- save the model and learn how to load it and use it to make predictions in the future
- expose the model as part of a tiny web application that can be used to make predictions

You don’t need to know a lot of Python for this course, but some basic Python knowledge will be helpful. Enjoy!

Python is a widely used dynamically typed programming language. It allows for many different programming paradigms including object-oriented, imperative, functional programming, and procedural styles.

python

Fully Connected Neural Networks with Keras

End-to-end testing assures you of a few things: that all the integrated pieces of an application properly function, all those pieces work together as expected, and your tests include and simulate real-user scenarios — something unit and integration tests just don't do.

This course introduces you to two great tools for E2E testing: 

* Puppeteer opens and runs applications in a Chromium browser and performs the actions it's given.
* Jest asserts that the integrated pieces work as expected and that add-on libraries like Faker and pixelmatch take our tests to the next level.

Over 9 lessons, we will create common application features and use Puppeteer and Jest to run different types of tests against them. You'll get practice using these tools to render content, mimic user activity, automate tests, and measure the overall performance of your application.

jest

End to End Testing with Google's Puppeteer and Jest

In Introduction to Python, we will start at the beginning: Installing python 3 and using virtual environments. With a working environment, we will learn how to manipulate strings and numbers, and gain working knowledge of data structures and flow control. We will build on that by introducing modules and classes and learn how to interact with our python applications using command line switches, console input and files.

At the end of this course, you’ll have a great working knowledge of Python, fully capable of creating your own Python projects from scratch or jumping into an existing application with the capability to read, understand, and contribute to the application.

Check out these [**community notes for this course on Github**](https://github.com/eggheadio-projects/introduction-to-the-python-3-programming-language-notes).

Introduction to the Python 3 Programming Language

A lot of the time, web apps are built primarily with the desktop layout in consideration, and the mobile layout suffers as a result. In this course we are going to discuss using features of user interface which are optimised for mobile devices.

We are going to discuss CSS features that make a big difference and build entire components that work great on mobile devices and browsers. We are going to take into account browser support to ensure our users are getting the experience we want them to.

More and more of our users depend on their mobile device to use our web apps. With this in mind, we are going to look at how to optimise the components we build for smaller viewports, and how to ensure our customer gets an optimised version of our web app for their device.

We are going to discuss different ways we can view, test, and debug our web app in a mobile setting so that we know what we are seeing is what our user is seeing, because sometimes a desktop browser emulating a mobile device just isn’t enough.


HTML 5 is the structure of our web pages. It is the markup that represents the DOM (document object model).

html

Optimize User Experience for Mobile Devices and Browsers

Artificial intelligence. Machine learning. Bots. Computers learning and communicating with us to do our bidding. But, where do you start? How do you get a machine to even begin to understand what you speak or type at it? There are several common machine learning algorithms that will help us begin to answer these questions.

In this course we’ll learn about common machine learning algorithms that don’t require implementing a neural network. We will not be going too much into the math behind them, but instead learn what each algorithm is good for, and how to train them. We'll also learn about a few metrics for evaluating models.

We’ll implement these in Python using `scikit-learn` using `scikit-learn`’s built-in data sets. The focus of this course is on implementation and a high-level understanding of these algorithms. 

We'll look at a few ways to evaluate our models, for both classification and regression models. We'll touch on mean squared error and coefficient of determination (for regression), and accuracy score, logarithmic loss, confusion matrices, and classification reports (for classification). 

Python 2.7 is used in the lesson videos but the code provided has Python 3 available. The only breaking change is the `print` statement API.

For additional information on installation, vocabulary, and common errors visit the `README.md` to the course code attached to each lesson.

Simple and efficient tools for data mining and data analysis

scikit-learn

Introductory Machine Learning Algorithms in Python with scikit-learn

AWS Amplify allows developers to create, configure, and deploy Serverless APIs and functions directly from their front-end environment.In this collection, you'll learn how to deploy various types of APIs and functions using the Amplify CLI. You'll also learn how to share code among various functions using Lambda layers and schedule functions to run at an interval to implement Serverless cron jobs.

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

Up and Running with AWS Amplify Functions

Learn how to create tuples in Python. The videos in this collection will also cover more advanced features of tuples

The Ins and Outs of Python Tuples

Open source framework for building truly native mobile apps with Angular, TypeScript or JavaScript.

nativescript

We will learn how to add an Android library to our project and translate it’s Java api to NativeScript. For this lesson, we will look at [Filestack’s Android SDK](https://github.com/filestack/filepicker-android) built with Gradle. Specifically, we will cover how to immediately start working with the library even when a [NativeScript](/q/nativescript) plugin does not exist for it.

Use an Android library in NativeScript for Angular using Java apis

Flutter allows you to build beautiful native apps on iOS and Android from a single codebase.

flutter

In this lesson we’ll learn how to style Text & Container widgets & also get a general understanding of how styling works in Flutter applications

Style a Flutter Text and Container Widget

Progressive Web Apps can speed up app loading times, and even allow you to run your web app offline, and install it on a mobile device!  However, setting up a PWA correctly can be tricky.

In this course, we'll create a PWA from start to finish, using create-react-app.  We'll create a custom service worker, and use different caching strategies for different types of assets.

Finally, we'll look at how to install the app on both iOS and Android devices, and how to customize the app name, icon, and splash screen.

Course Introduction: Progressive Web Apps in React with create-react-app

In this lesson we’ll learn how to use themes in order to share colors and font styles throughout our application.

Using Themes in Flutter to Share Colors and Font Styles

In this lesson we’ll learn how to render both local & network images in a Flutter application using the Image class.


Load an Image in a Flutter App with the Image Class

In this lesson we’ll learn about the main layout widgets you'll need when building your user interface in Flutter. We’ll take a look at Container, Center, Row, Column, Stack, & GridView widgets learn how they work.

Building Layouts in Flutter with Layout Widgets

In this lesson we’ll learn how Navigation in Flutter works by navigating to a new page when clicking on a button using the push & pop methods. We'll also look at how to pass properties to a new screen dynamically.

Getting Started with Navigation in Flutter

In this lesson, we'll learn how to specify a configuration object containing all of the routes for our application & navigate between them in a Flutter application.

Navigation with Named Routes in Flutter

ListView is the most commonly used scrolling widget in a Flutter application. In this video, we'll learn how to create dynamic lists using Flutter's ListView widget to render both lists of Strings & lists of Maps

Building Dynamic Lists in Flutter with ListViews

In this lesson we’ll learn how to fetch & then display data from an API over the network in a Flutter application using the http package.

Fetching & Displaying Data from an API in Flutter using the http Package

Sometimes you get strings instead of objects and you have to parse them out. Here's an example where the raw data I got from a Twitch chatbot message wasn't useful to me until I parsed it into a dictionary.

Turning a key/value string into a dictionary in Python

Puppeteer is a Node library which provides a high-level API to control headless Chrome or Chromium over the DevTools Protocol. It can also be configured to use full (non-headless) Chrome or Chromium.

puppeteer

When taking screenshots, it's important that the browser is big enough to show all of the content in the DOM that we want to screenshot. We can do this by setting the viewport.

Setting the viewport on a Playwright headless browser

In this lesson, you'll learn how to deploy a serverless function using the Python runtime, connect it to an API endpoint, and interact with it from a React application.

Topics

Instructors

Content Type