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YOUR PRACTICAL, HANDS-ON GUIDE TO WRITING APPLICATIONS USING GOGoogle announced the Go programming language to the public in 2009, with the version 1.0 release announced in 2012. Since its announcement to the community, and the compatibility promise of the 1.0 release, the Go language has been used to write scalable and high-impact software programs ranging from command-line applications and critical infrastructure tools to large-scale distributed systems. It's speed, simplicity, and reliability make it a perfect choice for developers working in various domains.In Practical Go - Building Scalable Network + Non-Network Applications, you will learn to use the Go programming language to build robust, production-ready software applications. You will learn just enough to building command line tools and applications communicating over HTTP and gRPC.This practical guide will cover:* Writing command line applications* Writing a HTTP services and clients* Writing RPC services and clients using gRPC* Writing middleware for network clients and servers* Storing data in cloud object stores and SQL databases* Testing your applications using idiomatic techniques* Adding observability to your applications* Managing configuration data from your applicationsYou will learn to implement best practices using hands-on examples written with modern practices in mind. With its focus on using the standard library packages as far as possible, Practical Go will give you a solid foundation for developing large applications using Go leveraging the best of the language's ecosystem.

Doing Math with Python shows you how to use Python to delve into high school-level math topics like statistics, geometry, probability, and calculus. You'll start with simple projects, like a factoring program and a quadratic-equation solver, and then create more complex projects once you've gotten the hang of things. Along the way, you'll discover new ways to explore math and gain valuable programming skills that you'll use throughout your study of math and computer science. Learn how to: -Describe your data with statistics, and visualize it with line graphs, bar charts, and scatter plots -Explore set theory and probability with programs for coin flips, dicing, and other games of chance -Solve algebra problems using Python's symbolic math functions -Draw geometric shapes and explore fractals like the Barnsley fern, the Sierpinski triangle, and the Mandelbrot set -Write programs to find derivatives and integrate functions Creative coding challenges and applied examples help you see how you can put your new math and coding skills into practice. You'll write an inequality solver, plot gravity's effect on how far a bullet will travel, shuffle a deck of cards, estimate the area of a circle by throwing 100,000 "darts" at a board, explore the relationship between the Fibonacci sequence and the golden ratio, and more. Whether you're interested in math but have yet to dip into programming or you're a teacher looking to bring programming into the classroom, you'll find that Python makes programming easy and practical. Let Python handle the grunt work while you focus on the math. Uses Python 3