Oh Shit Git
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Git
Author: Rheinwerk Publishing, Inc
language: en
Publisher: Packt Publishing Ltd
Release Date: 2025-06-20
Learn Git from scratch to advanced topics, including GitHub integration, branching, error troubleshooting, and using platforms like GitLab for version control in development environments. Key Features Covers Git installation, basic commands, and essential workflows for beginners Detailed exploration of advanced Git features like rebasing, hooks, and submodules Practical troubleshooting guide to address common Git errors and conflicts Book DescriptionThis practical guide is designed to take you from Git beginner to advanced user. Starting with installation and configuration, it covers the essential Git commands you'll need to create and manage repositories, track changes, and work with branches and commits. These fundamental concepts set the stage for more complex workflows and efficient version control management. The book then explores advanced features, such as using platforms like GitHub and GitLab for remote repositories. You'll learn how to collaborate with others through pull requests, set up continuous integration pipelines, and implement automation using hooks. The guide also includes advanced techniques like rebasing and working with submodules, helping you streamline your workflow and manage larger projects effectively. The final sections focus on troubleshooting common Git errors, from merge conflicts to authentication issues. Practical solutions and best practices ensure you can resolve problems quickly and efficiently. The book wraps up with a comprehensive Git command reference, making it a go-to resource for both new users and experienced developers. Whether you're working solo or in teams, this book will help you master version control with confidence.What you will learn Master the fundamentals of Git for version control and workflows Set up and configure Git on various operating systems Work with repositories on GitHub and GitLab platforms Manage branches and handle merge conflicts effectively Implement advanced Git features like hooks and submodules Troubleshoot common Git errors and find solutions Who this book is for This book is ideal for developers, DevOps engineers, and technical teams seeking to improve their Git skills. Beginners can start from scratch with Git’s fundamentals, while experienced users can dive deeper into advanced workflows. A basic understanding of programming concepts is recommended but not mandatory. For those looking to enhance team collaboration and automate workflows, this guide is perfect. It’s also suitable for individuals aiming to master version control in a professional environment or contribute to open-source projects using GitHub, GitLab, and other platforms.
Oh Shit, Git!
"A lot of git commands are confusingly named (why do you create new brnaches with git checkout?) and there are 20 milion different ways to do everything. This zine explains some git fundamentals in plain English, and how to fix a lot of commone git mistakes." --
Scaling Python with Dask
Author: Holden Karau
language: en
Publisher: "O'Reilly Media, Inc."
Release Date: 2023-07-19
Modern systems contain multi-core CPUs and GPUs that have the potential for parallel computing. But many scientific Python tools were not designed to leverage this parallelism. With this short but thorough resource, data scientists and Python programmers will learn how the Dask open source library for parallel computing provides APIs that make it easy to parallelize PyData libraries including NumPy, pandas, and scikit-learn. Authors Holden Karau and Mika Kimmins show you how to use Dask computations in local systems and then scale to the cloud for heavier workloads. This practical book explains why Dask is popular among industry experts and academics and is used by organizations that include Walmart, Capital One, Harvard Medical School, and NASA. With this book, you'll learn: What Dask is, where you can use it, and how it compares with other tools How to use Dask for batch data parallel processing Key distributed system concepts for working with Dask Methods for using Dask with higher-level APIs and building blocks How to work with integrated libraries such as scikit-learn, pandas, and PyTorch How to use Dask with GPUs