Learn Npm, Python and Svelte

npm is the package manager for JavaScript. Find, share, and reuse packages of code from hundreds of thousands of developers — and assemble them in powerful new ways.

Introduction to Monorepos with NPM Workspaces

JavaScript community has been shaken recently by a release of Svelte 3 and for a good reason - it's a completely different approach than React or Vue. To quote the docs:

"[Svelte](https://svelte.dev/) is a radical new approach to building user interfaces. Whereas traditional frameworks like React and Vue do the bulk of their work in the browser, Svelte shifts that work into a compile step that happens when you build your app."

**The best part?** If you have 26 spare minutes you can learn the basics of Svelte 3 and start building your own apps with it!

Enjoy!



The magical disappearing UI framework

 - The web's JavaScript bloat crisis, solved. Svelte turns your templates into tiny, framework-less vanilla JavaScript.
 - Simple and familiar. Build apps out of composable, easy-to-write blocks using languages you already know.
 - Super fast, rock solid. Compile-time static analysis ensures the browser does no more work than it needs to.

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Up and running with Svelte 3

You can’t be everywhere at once. Neither can node packages. But with a utility called npx — included in npm v5.2 and later — you can interact and run with node modules even if they’re not downloaded locally. The same is true for gists and remote branches of GitHub. As long as npm installed, your work can be wherever you are.

This course from Elijah Manor unlocks the power of the npx utility. Over 17 minutes, we will examine the npx package runner and look through various scenarios where the tool is helpful when running node packages from the command line. You’ll learn to use npm to:

- test out various versions of a package
- run packages without globally installing
- run code directly from GitHub
- make working with packages much easier

Execute npm Package Binaries with the npx Package Runner

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.

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Fully Connected Neural Networks with Keras

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

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

npm is like a giant library of code building blocks. There are tons of these “blocks”, aka “packages” that we can compose together to build cool things. We can use packages by other developers, but we can also write and publish our own. 

In this course we will learn how to create, publish, and update our own packages. We will create a JavaScript utility module to filter out sensitive words from a string, including tests and development file watching. We will then cover publishing and updating our package. This same approach can be used to create and publish other types of packages too like components (React, Angular, Web Components etc.) and command line interfaces.

Publish JavaScript packages on npm

In this course we will introduce the topic of using npm scripts as a build tool. We will start simple and then continue to build a small website as we introduce new topics. By the end of the course, you'll know how to get started and what tools and techniques are needed for you to create your own set of build scripts.

How to Use npm Scripts as Your Build Tool

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.

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Up and Running with AWS Amplify Functions

Creating forms is one of the simplest and most complicated things at the same time. A basic form consists of many different things happening, we have to retain the value, we have to keep watch of validation and we have to show error messages when something is invalid, this is on both the fields and on the entire form itself if we send a request off to the backend service.

So we're going to create a form using just the normal svelte features. Then we'll look into creating a form using the svelte forms lib. 

Create forms in Svelte with Svelte Forms Lib

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

Misunderstanding scope can cause problems in your application. Watch this lesson to learn how Python scope works and the hidden implications it presents. Local scope, nonlocal scope, and global scope variables are demonstrated and explained.

Understand Scope in Python

A module is a function extracted to a file. This allows you to import the function and use it in any other code you may write. You’ll learn how to create modules, import them, and make them stand-alone as you learn what `if __name__ == “__main__”` means in Python.

Reuse Code in Multiple Projects with Python Modules

Why should you have to write all the code? Why can’t you leverage code written by others? I’ve got great news: you can. You’ll learn how to search pip, Python’s package installer, to find and install packages to add new features and functionality to your application.

Manage packages with pip in Python

Object oriented classes work much like classes in other languages. Learn how to create them and use them, learn the difference between class variables and instance variables, creating class methods, and learn how to create classes that inherit from other classes.

Use Python Classes

A lot of the power behind npm scripts is creating custom scripts that are outside the basic set that npm natively understands. In this lesson we will install the ESLint node package, create a new eslint npm script, briefly discuss about environment variables and how npm knows where to find your binary, and then execute our custom script from the command line.

Create a custom npm script

Often times you’ll have variations that you’ll want to make to your npm scripts and repeating yourself is inefficient and verbose. Instead you can create a base script and pass arguments into it from another script.

Pass arguments to npm scripts

In this lesson we will look at pulling out complex npm script logic into an external JavaScript file. Instead of writing bash scripts you can leverage your JavaScript abilities to automate your build process. We’ll use some helper node modules such as shelljs, opn-cli, and babel-cli. 

Create a node script to replace a complex npm script

In addition to package.json level variables (such as name and version), you can have custom conf settings that can be used in your npm scripts. These config values can be overridden outside of the package.json by using the npm config set command if necessary.

Use custom config settings in your npm scripts

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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The React team has an official Command Line Interface (CLI) for building React projects called "Create React App"; in this lesson, we show how to use this tool to quickly set up new projects using the `create-react-app {project-name}` command. We then use the npm scripts that are provided: `npm start` to develop, `npm run build` to ship, and `npm run eject` to opt out of the abstracted tooling.

The benefits of this tool are:
- It's officially maintained by the React team; this means best practices out of the box
- Zero config, one dependency
- Config is abstracted so React team can make improvements under the hood and you get the new goodness for free
- Clean command line output for errors
- You can "eject" at any time if needed

Set up React apps with zero configuration in two minutes

Getting input from the user via a console command can be done with `input` in Python. Learn how to implement it and validate user input in this lesson.