Version Control With Git

Author: Jon Loeliger
Publisher: "O'Reilly Media, Inc."
ISBN: 1449345042
Size: 38.75 MB
Format: PDF, Kindle
View: 4760
Get up to speed on Git for tracking, branching, merging, and managing code revisions. Through a series of step-by-step tutorials, this practical guide takes you quickly from Git fundamentals to advanced techniques, and provides friendly yet rigorous advice for navigating the many functions of this open source version control system. This thoroughly revised edition also includes tips for manipulating trees, extended coverage of the reflog and stash, and a complete introduction to the GitHub repository. Git lets you manage code development in a virtually endless variety of ways, once you understand how to harness the system’s flexibility. This book shows you how. Learn how to use Git for several real-world development scenarios Gain insight into Git’s common-use cases, initial tasks, and basic functions Use the system for both centralized and distributed version control Learn how to manage merges, conflicts, patches, and diffs Apply advanced techniques such as rebasing, hooks, and ways to handle submodules Interact with Subversion (SVN) repositories—including SVN to Git conversions Navigate, use, and contribute to open source projects though GitHub

Git Mastering Version Control

Author: Ferdinando Santacroce
Publisher: Packt Publishing Ltd
ISBN: 1787122794
Size: 28.22 MB
Format: PDF, Mobi
View: 6540
Learn everything you need to take full control of your workflow with Git with this curated Learning Path – dive in and transform the way you work About This Book Master all the basic concepts of Git to protect your code and make it easier to evolve Filled with practical recipes that will teach you how to use the most advanced features of the Git system Harness the full power of the Git version control system to customize Git behavior, manipulate history, integrate external tools, and explore platform shortcuts Who This Book Is For This learning path is for software developers who want to become proficient at using the Git version control system. A basic understanding of any version control system would be beneficial. What You Will Learn Transport your work to a remote repository in a centralized manner Experiment with your code without affecting functional code files Explore some tools used to migrate to Git from other versioning systems without losing your development history Understand the Git data model and how you can navigate the database with simple commands Debug with Git and use various techniques to find faulty commits Customize Git behavior system-wide, on a per-user, per-repository, and per-file basis Master administering and setting up Git repositories, configuring access, finding and recovering from repository errors, and performing repository maintenance Chose a workflow and configure/set up support for the chosen workflow In Detail Git is one of the most popular types of Distributed Version Control System. Since its inception, it has attracted skilled developers due to its robust, powerful, and reliable features. Like most powerful tools, Git can be hard to approach for the newcomers. However, this learning path will help you overcome this fear and become adept at all the basic and advanced tasks in Git. This course starts with an introduction to version control systems before you delve deeply into the essentials of Git. This serves as a primer for the topics to follow such as branching and merging, creating and managing a GitHub personal repository, and fork and pull requests. You'll also learn how to migrate from SVN using Git tools or TortoiseGit and migrate from other VCSs, concluding with a collection of resources, links, and appendices. As you progress on to the next module, you will learn how you can automate the usual Git processes by utilizing the hook system built into Git. It also covers advanced repository management, including different options to rewrite the history of a Git repository before you discover how you can work offline with Git, how to track what is going on behind the scenes, and how to use the stash for different purposes. Moving forward, you will gain deeper insights into Git's architecture, its underlying concepts, behavior, and best practices. It gives a quick implementation example of using Git for a collaborative development of a sample project to establish the foundation knowledge of Git operational tasks and concepts. By exploring advanced Git practices, you will attain a deeper understanding of Git's behavior, allowing you to customize and extend existing recipes and write your own. This Learning Path is a blend of content, all packaged up keeping your journey in mind. It includes content from the following Packt products: Git Essentials, Ferdinando Santacroce Git Version Control Cookbook, Aske Olsson and Rasmus Voss Mastering Git, Jakub Narebski Style and approach Its step-by-step approach with useful information makes this course the ultimate guide to understanding and mastering Git. This course will show the road to mastery example by example, while also explaining the mental model of Git.

Mastering Git

Author: Jakub Narebski
Publisher: Packt Publishing Ltd
ISBN: 1783553766
Size: 26.36 MB
Format: PDF, Mobi
View: 1421
Attain expert-level proficiency with Git for enhanced productivity and efficient collaboration by mastering advanced distributed version control features About This Book Set up Git for solo and collaborative development Harness the full power of Git version control system to customize Git behavior, manipulate history, integrate external tools and explore platform shortcuts A detailed guide, which explains how to apply advanced Git techniques and workflows and ways to handle submodules Who This Book Is For If you are a Git user with reasonable knowledge of Git and familiarity with basic concepts such as branching, merging, staging, and workflows, this is the book for you. Basic knowledge of installing Git and software configuration management concepts is essential. What You Will Learn Explore project history, find revisions using different criteria, and filter and format how history looks Manage your working directory and staging area for commits and interactively create new revisions and amend them Set up repositories and branches for collaboration Submit your own contributions and integrate contributions from other developers via merging or rebasing Customize Git behavior system-wide, on a per-user, per-repository, and per-file basis Take up the administration and set up of Git repositories, configure access, find and recover from repository errors, and perform repository maintenance Chose a workflow and configure and set up support for the chosen workflow In Detail Git is one of the most popular types of Source Code Management (SCM) and Distributed Version Control System (DVCS). Despite the powerful and versatile nature of the tool enveloping strong support for nonlinear development and the ability to handle large projects efficiently, it is a complex tool and often regarded as “user-unfriendly”. Getting to know the ideas and concepts behind the architecture of Git will help you make full use of its power and understand its behavior. Learning the best practices and recommended workflows should help you to avoid problems and ensure trouble-free development. The book scope is meticulously designed to help you gain deeper insights into Git's architecture, its underlying concepts, behavior, and best practices. Mastering Git starts with a quick implementation example of using Git for a collaborative development of a sample project to establish the foundation knowledge of Git operational tasks and concepts. Furthermore, as you progress through the book, the tutorials provide detailed descriptions of various areas of usage: from archaeology, through managing your own work, to working with other developers. This book also helps augment your understanding to examine and explore project history, create and manage your contributions, set up repositories and branches for collaboration in centralized and distributed version control, integrate work from other developers, customize and extend Git, and recover from repository errors. By exploring advanced Git practices, you will attain a deeper understanding of Git's behavior, allowing you to customize and extend existing recipes and write your own. Style and approach Step-by-step instructions and useful information make this book the ultimate guide to understanding and mastering Git. This book will show road to mastery example by example, while explaining mental model of Git. The Introduction section covers the 'Essentials' just for refreshing the basics. The main highlight is that the concepts are based on HOW the technology/framework works and not just practical 'WHAT to do'.

Programming Skills For Data Science

Author: Michael Freeman
Publisher: Addison-Wesley Professional
ISBN: 0135159083
Size: 66.92 MB
Format: PDF, Kindle
View: 7494
The Foundational Hands-On Skills You Need to Dive into Data Science “Freeman and Ross have created the definitive resource for new and aspiring data scientists to learn foundational programming skills.” –From the foreword by Jared Lander, series editor Using data science techniques, you can transform raw data into actionable insights for domains ranging from urban planning to precision medicine. Programming Skills for Data Science brings together all the foundational skills you need to get started, even if you have no programming or data science experience. Leading instructors Michael Freeman and Joel Ross guide you through installing and configuring the tools you need to solve professional-level data science problems, including the widely used R language and Git version-control system. They explain how to wrangle your data into a form where it can be easily used, analyzed, and visualized so others can see the patterns you’ve uncovered. Step by step, you’ll master powerful R programming techniques and troubleshooting skills for probing data in new ways, and at larger scales. Freeman and Ross teach through practical examples and exercises that can be combined into complete data science projects. Everything’s focused on real-world application, so you can quickly start analyzing your own data and getting answers you can act upon. Learn to Install your complete data science environment, including R and RStudio Manage projects efficiently, from version tracking to documentation Host, manage, and collaborate on data science projects with GitHub Master R language fundamentals: syntax, programming concepts, and data structures Load, format, explore, and restructure data for successful analysis Interact with databases and web APIs Master key principles for visualizing data accurately and intuitively Produce engaging, interactive visualizations with ggplot and other R packages Transform analyses into sharable documents and sites with R Markdown Create interactive web data science applications with Shiny Collaborate smoothly as part of a data science team Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.

Mastering Visual Studio 2019

Author: Kunal Chowdhury
Publisher: Packt Publishing Ltd
ISBN: 178953688X
Size: 20.62 MB
Format: PDF, ePub
View: 547
Explore the new features in Visual Studio 2019 and build apps using WPF, .NET Core, TypeScript, and Azure Key Features Learn how to write better code with the new and improved Visual Studio 2019 toolset Accelerate cloud development with built-in Azure tools Collaborate with a distributed team by integrating Visual Studio with source control repositories Book Description Visual Studio 2019 is the latest IDE from Microsoft for developers targeting Windows and other platforms to build stunning desktop, web and mobile applications. In this book, you’ll learn how to effectively use this IDE to build, debug, and test your applications to enhance productivity by simplifying your most common tasks and allowing more time to focus on other aspects of your project. Starting with an overview of the new features in Visual Studio 2019, you’ll understand what’s improved since its previous edition. This Visual Studio book will help you build applications for Windows using Windows Presentation Foundation (WPF), which provides a unified programming model for developing dynamic, rich, data-driven desktop applications. You’ll then learn about Microsoft's implementation of cloud computing with Azure, followed by building applications using .NET Core and TypeScript. This book will also help you explore NuGet, the package manager for the Microsoft development platform, that enables you to create, publish, and consume packages from a central repository by managing a reference list of packages. Finally, you’ll delve into the debugging and live unit testing techniques that are built into the IDE. By the end of the book, you’ll have become a more efficient Visual Studio 2019 user, and be able to use it for developing, testing, debugging and deploying your applications. What you will learn Increase your productivity with Visual Studio 2019’s new features Understand how the installation wizard works and create an offline installation package Build stunning applications using WPF, .NET Core, and TypeScript Explore NuGet packages in depth Accelerate cloud development with Azure Debug and test your applications efficiently Get to grips with integrating Visual Studio with Git repositories Who this book is for If you’re a Microsoft .NET developer who wants to learn the new features of Visual Studio 2019, or want to delve into cloud computing, .NET Core, TypeScript along with mastering the skills of building, debugging, and unit testing professional apps, you’ll find this book useful. Basic knowledge of Visual Studio, .NET, and C# is assumed.

Proceedings Of The Second Ieee International Symposium On Requirements Engineering March 27 29 1995 York England

Publisher: IEEE Computer Society
ISBN: 9780818670176
Size: 18.21 MB
Format: PDF, ePub
View: 1193
Proceedings of the March 1995 symposium. Papers and panels address topics such as hypermedia enhancements, analyzing human error tolerance requirements, a case driven approach to requirements engineering, consistency checking, user requirements in industrial control system procurement projects, trac

Machine Learning With Spark

Author: Rajdeep Dua
Publisher: Packt Publishing Ltd
ISBN: 1785886428
Size: 10.16 MB
Format: PDF, Docs
View: 2994
Create scalable machine learning applications to power a modern data-driven business using Spark 2.x About This Book Get to the grips with the latest version of Apache Spark Utilize Spark's machine learning library to implement predictive analytics Leverage Spark's powerful tools to load, analyze, clean, and transform your data Who This Book Is For If you have a basic knowledge of machine learning and want to implement various machine-learning concepts in the context of Spark ML, this book is for you. You should be well versed with the Scala and Python languages. What You Will Learn Get hands-on with the latest version of Spark ML Create your first Spark program with Scala and Python Set up and configure a development environment for Spark on your own computer, as well as on Amazon EC2 Access public machine learning datasets and use Spark to load, process, clean, and transform data Use Spark's machine learning library to implement programs by utilizing well-known machine learning models Deal with large-scale text data, including feature extraction and using text data as input to your machine learning models Write Spark functions to evaluate the performance of your machine learning models In Detail This book will teach you about popular machine learning algorithms and their implementation. You will learn how various machine learning concepts are implemented in the context of Spark ML. You will start by installing Spark in a single and multinode cluster. Next you'll see how to execute Scala and Python based programs for Spark ML. Then we will take a few datasets and go deeper into clustering, classification, and regression. Toward the end, we will also cover text processing using Spark ML. Once you have learned the concepts, they can be applied to implement algorithms in either green-field implementations or to migrate existing systems to this new platform. You can migrate from Mahout or Scikit to use Spark ML. By the end of this book, you will acquire the skills to leverage Spark's features to create your own scalable machine learning applications and power a modern data-driven business. Style and approach This practical tutorial with real-world use cases enables you to develop your own machine learning systems with Spark. The examples will help you combine various techniques and models into an intelligent machine learning system.


Author: Sergei Dinkem
ISBN: 9781653201389
Size: 36.28 MB
Format: PDF
View: 5299
Complete Guide to Get Started with DevOpsDevOps is powerful set of collaborative practices that can take your project to the next level faster than you expect, but only if you understand it and properly implement it! Want to master DevOps quickly?There are so many uses for DevOps and so many compelling reasons to implement DevOps in your business or for your own projects. With this guide in your hands, it is easier than ever to maximize your efficiency and productivity in business and in other projects! When you understand how to use DevOps to its maximum potential, you unlock greater efficiency and make better use of your time and your team's time. Easily implement DevOps by following the simple instructions fully explained inside this guide. It doesn't matter if you have never used DevOps before, this book gives you detailed chapters on the principles of DevOps, all of its features, and exactly how to implement them! This step-by-step guide gives you everything you need to know to unlock the power of DevOps and do more in your business and with your team than you ever thought possible!Here is a preview of what you will learn in this guide: What is DevOps? History and Development of Dev Ops Basic Ideas of DevOps Dev Ops Toolchains Stages of Dev Ops Planning Creating Verification Packaging Release Configuration Monitoring Why Use DevOps? Understanding and Implementing the CALMS Framework of Dev Ops Culture Automation Lean Measurement Sharing What Tools Are Used in DevOps? Source Code Repository Git Build Server Jenkins Amazon CodeBuild Configuration Management Puppet Virtual Infrastructure Docker Amazon Web Services Integrating Amazon Cloud Computing into Dev Ops Microsoft Azure Integrating Azure Cloud Computing into Dev Ops Test Automation EC2 Systems Manager Patch Manager Automation Pipeline Orchestration CodePipeline CodeDeploy DevOps services Continuous Delivery Continuous Delivery vs. Continuous Deployment Continuous Delivery Benefits Continuous Integration Why is Continuous Integration Needed? How does Continuous Integration Work? Continuous Integration Benefits Infrastructure as a Service (IaaS) Platform as a Service (PaaS) Software as a Service (SaaS) Dev Ops as a Service (DaaS) Dev Ops as a managed cloud service Monitoring and Logging Amazon CloudWatch Communication and Collaboration And so much more! Even if you have never used DevOps before have no fear! With this guide in your hands that will not be a barrier for you any longer. Learn to master all the best features of DevOps easily when you grab this guide now!

Efficient R Programming

Author: Colin Gillespie
Publisher: "O'Reilly Media, Inc."
ISBN: 1491950757
Size: 20.80 MB
Format: PDF, ePub
View: 3124
There are many excellent R resources for visualization, data science, and package development. Hundreds of scattered vignettes, web pages, and forums explain how to use R in particular domains. But little has been written on how to simply make R work effectively—until now. This hands-on book teaches novices and experienced R users how to write efficient R code. Drawing on years of experience teaching R courses, authors Colin Gillespie and Robin Lovelace provide practical advice on a range of topics—from optimizing the set-up of RStudio to leveraging C++—that make this book a useful addition to any R user’s bookshelf. Academics, business users, and programmers from a wide range of backgrounds stand to benefit from the guidance in Efficient R Programming. Get advice for setting up an R programming environment Explore general programming concepts and R coding techniques Understand the ingredients of an efficient R workflow Learn how to efficiently read and write data in R Dive into data carpentry—the vital skill for cleaning raw data Optimize your code with profiling, standard tricks, and other methods Determine your hardware capabilities for handling R computation Maximize the benefits of collaborative R programming Accelerate your transition from R hacker to R programmer