Best learning Scroll for Python KEY FEATURES ● 16 chapters covering basic (loops) to advanced (NumPy) topics in Python. ● Focus on one topic per chapter to help learners understand topics in depth. ● Key points from Theory highlighted in each chapter for better retention. ● More than 1000 questions that give ample opportunity for practice. ● 7 Model test papers for learners to test their progress. DESCRIPTION This book contains to-the-point theory followed by questions about programming skills in Python. It provides an active and structured way of learning Python. The readers can test their learning by attempting MCQs, True/False questions, and questions about finding the output in a code, identifying the error and much more. The explanations of the answers provide detailed information about the concepts tested. All topics in Python are divided into 16 chapters in this book. These includes Syntax, Input-output, Data types, Strings, Operators and Expressions, Decision Control Statements, Loops, Functions, Lists, Dictionaries, Sets, Tuples, Classes, Files, Graphics, Arrays and Databases. More than 1000 questions are included for all the topics. WHAT YOU WILL LEARN ● Syntax of writing Python programs. ● All possible errors encountered while programming in Python. ● Execution of different constructs in detail. ● Handling graphics and databases in Python. ● Using Arrays in Python. ● Handling programs and files in Python. WHO THIS BOOK IS FOR This book is meant for the students of Undergraduate, postgraduate level and for the beginners in Python. TABLE OF CONTENTS 1. Syntax and Input–Output 2. Data types 3. Strings 4. Operators and Expressions 5. Decision Control statements 6. Loops 7. User- Defined Functions 8. Lists 9. Dictionaries 10. Sets 11. Tuples 12. Classes 13. Files 14. Graphics 15. Arrays (NumPy) 16. Databases Appendix A: Python keywords and their use Appendix B: Operators in Python and their precedence Appendix C: Libraries in Python and common functions Bibliography Model Test Paper 1 (Solved) Model Test Paper 2 (Solved) Model Test Paper 3 (Solved) Model Test Paper 4 (Solved) Model Test Paper 5 (Solved) Model Test Paper 6 (Solved) Model Test Paper 7 (Unsolved)

Description:This book gives you an opportunity to check your proficiency in Python by answering the questions in this book. The Programs / commands presented in this book are executed using Python version 3.5.2. The questions are categorized based on various facts of programming in python. The aim is to cover the topics in depth. Detailed explanation of each question helps even a novice learner.Salient features -More than 400 questions for testing skills in Python -Topics covered in sequence for novice readers -Getting started section gives a good start and overview -Questions are represented topic-wise so that a Python programmer can directly go for t--Testing a particular topic -Multiple choice questions with True/False options also -Questions based on output help to learn the programming skills and various in-built functions in Python-Better understanding through detailed explanation -Solved Model test papers help to learn theory questionsTable of Contents:Chapter 1 : Input -OutputChapter 2 : Operators and ExpressionsChapter 3 : Decision Control statementsChapter 4 : FunctionsChapter 5 : LoopsChapter 6 : ListsChapter 7 : StringsChapter 8 : Sets and DictionariesChapter 9 : TuplesChapter 10 : ClassesChapter 11 : FilesChapter 12 : GraphicsChapter 13 : In-built functionsChapter 14 : MiscellaneousAppendix A: Python keywords and their useAppendix B: Operators in Python and their precedence Appendix C: Libraries in Python and common functionsBibliographyModel Test Paper 1 (Solved)Model Test Paper 2 (Solved)Model Test Paper 3 (Unsolved)Model Test Paper 4 (Unsolved)

Do less work when testing your Python code, but be just as expressive, just as elegant, and just as readable. The pytest testing framework helps you write tests quickly and keep them readable and maintainable - with no boilerplate code. Using a robust yet simple fixture model, it's just as easy to write small tests with pytest as it is to scale up to complex functional testing for applications, packages, and libraries. This book shows you how. For Python-based projects, pytest is the undeniable choice to test your code if you're looking for a full-featured, API-independent, flexible, and extensible testing framework. With a full-bodied fixture model that is unmatched in any other tool, the pytest framework gives you powerful features such as assert rewriting and plug-in capability - with no boilerplate code. With simple step-by-step instructions and sample code, this book gets you up to speed quickly on this easy-to-learn and robust tool. Write short, maintainable tests that elegantly express what you're testing. Add powerful testing features and still speed up test times by distributing tests across multiple processors and running tests in parallel. Use the built-in assert statements to reduce false test failures by separating setup and test failures. Test error conditions and corner cases with expected exception testing, and use one test to run many test cases with parameterized testing. Extend pytest with plugins, connect it to continuous integration systems, and use it in tandem with tox, mock, coverage, unittest, and doctest. Write simple, maintainable tests that elegantly express what you're testing and why. What You Need: The examples in this book are written using Python 3.6 and pytest 3.0. However, pytest 3.0 supports Python 2.6, 2.7, and Python 3.3-3.6.

Portable, powerful, and a breeze to use, Python is the popular open source object-oriented programming language used for both standalone programs and scripting applications. Python is considered easy to learn, but there's no quicker way to mastery of the language than learning from an expert teacher. This edition of Learning Python puts you in the hands of two expert teachers, Mark Lutz and David Ascher, whose friendly, well-structured prose has guided many a programmer to proficiency with the language. Learning Python, Second Edition, offers programmers a comprehensive learning tool for Python and object-oriented programming. Thoroughly updated for the numerous language and class presentation changes that have taken place since the release of the first edition in 1999, this guide introduces the basic elements of the latest release of Python 2.3 and covers new features, such as list comprehensions, nested scopes, and iterators/generators. Beyond language features, this edition of Learning Python also includes new context for less-experienced programmers, including fresh overviews of object-oriented programming and dynamic typing, new discussions of program launch and configuration options, new coverage of documentation sources, and more. There are also new use cases throughout to make the application of language features more concrete. The first part of Learning Python gives programmers all the information they'll need to understand and construct programs in the Python language, including types, operators, statements, classes, functions, modules and exceptions. The authors then present more advanced material, showing how Python performs common tasks by offering real applications and the libraries available for those applications. Each chapter ends with a series of exercises that will test your Python skills and measure your understanding. Learning Python, Second Edition is a self-paced book that allows readers to focus on the core Python language in depth. As you work through the book, you'll gain a deep and complete understanding of the Python language that will help you to understand the larger application-level examples that you'll encounter on your own. If you're interested in learning Python--and want to do so quickly and efficiently--then Learning Python, Second Edition is your best choice.

See how an AI assistant can bring your ideas to life immediately! Once, to be a programmer you had to write every line of code yourself. Now tools like GitHub Copilot can instantly generate working programs based on your description in plain English. An instant bestseller, Learn AI-Assisted Python Programming has taught thousands of aspiring programmers how to write Python the easy way--with the help of AI. It's perfect for beginners, or anyone who's struggled with the steep learning curve of traditional programming. In Learn AI-Assisted Python Programming, Second Edition you'll learn how to: - Write fun and useful Python applications--no programming experience required! - Use the GitHub Copilot AI coding assistant to create Python programs - Write prompts that tell Copilot exactly what to do - Read Python code and understand what it does - Test your programs to make sure they work the way you want them to - Fix code with prompt engineering or human tweaks - Apply Python creatively to help out on the job AI moves fast, and so the new edition of Learn AI-Assisted Python Programming, Second Edition is fully updated to take advantage of the latest models and AI coding tools. Written by two esteemed computer science university professors, it teaches you everything you need to start programming Python in an AI-first world. You'll learn skills you can use to create working apps for data analysis, automating tedious tasks, and even video games. Plus, in this new edition, you'll find groundbreaking techniques for breaking down big software projects into smaller tasks AI can easily achieve. Purchase of the print book includes a free eBook in PDF and ePub formats from Manning Publications. About the technology AI has changed the way we write computer programs forever. You describe in plain English what you want your program to do, and AI coding assistants like Github Copilot can generate the code for you instantly! If you can use a web browser and move files around on your computer, you can create useful software. This book shows you how. About the book Learn AI-Assisted Python Programming, Second Edition teaches you how to create your own games, tools, and other simple applications using Copilot and the user-friendly Python language. You'll be amazed how quickly you can go from an idea to a working program! Authors Leo Porter and Dan Zingaro guide you step by step as you go from creating simple functions, like a small program that tells you if a password is strong enough, to writing games and tools that help you automate tedious tasks. As you go, you'll learn just enough Python to understand and improve what Copilot creates. About the reader No experience required! About the author Dr. Leo Porter is a Teaching Professor at UC San Diego. Dr. Daniel Zingaro is an Associate Teaching Professor at the University of Toronto. The technical editor on this book was Peter Morgan.

Learn Azure in a Month of Lunches, Second Edition, is a tutorial on writing, deploying, and running applications in Azure. In it, you’ll work through 21 short lessons that give you real-world experience. Each lesson includes a hands-on lab so you can try out and lock in your new skills. Summary You can be incredibly productive with Azure without mastering every feature, function, and service. Learn Azure in a Month of Lunches, Second Edition gets you up and running quickly, teaching you the most important concepts and tasks in 21 practical bite-sized lessons. As you explore the examples, exercises, and labs, you'll pick up valuable skills immediately and take your first steps to Azure mastery! This fully revised new edition covers core changes to the Azure UI, new Azure features, Azure containers, and the upgraded Azure Kubernetes Service. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Microsoft Azure is vast and powerful, offering virtual servers, application templates, and prebuilt services for everything from data storage to AI. To navigate it all, you need a trustworthy guide. In this book, Microsoft engineer and Azure trainer Iain Foulds focuses on core skills for creating cloud-based applications. About the book Learn Azure in a Month of Lunches, Second Edition, is a tutorial on writing, deploying, and running applications in Azure. In it, you’ll work through 21 short lessons that give you real-world experience. Each lesson includes a hands-on lab so you can try out and lock in your new skills. What's inside Understanding Azure beyond point-and-click Securing applications and data Automating your environment Azure services for machine learning, containers, and more About the reader This book is for readers who can write and deploy simple web or client/server applications. About the author Iain Foulds is an engineer and senior content developer with Microsoft. Table of Contents PART 1 - AZURE CORE SERVICES 1 Before you begin 2 Creating a virtual machine 3 Azure Web Apps 4 Introduction to Azure Storage 5 Azure Networking basics PART 2 - HIGH AVAILABILITY AND SCALE 6 Azure Resource Manager 7 High availability and redundancy 8 Load-balancing applications 9 Applications that scale 10 Global databases with Cosmos DB 11 Managing network traffic and routing 12 Monitoring and troubleshooting PART 3 - SECURE BY DEFAULT 13 Backup, recovery, and replication 14 Data encryption 15 Securing information with Azure Key Vault 16 Azure Security Center and updates PART 4 - THE COOL STUFF 17 Machine learning and artificial intelligence 18 Azure Automation 19 Azure containers 20 Azure and the Internet of Things 21 Serverless computing

Ingest, transform, manipulate, and visualize your data beyond Power BI's capabilities. Purchase of the print or Kindle book includes a free eBook in PDF format. Key Features Discover best practices for using Python and R in Power BI by implementing non-trivial code Enrich your Power BI dashboards using external APIs and machine learning models Create any visualization, as complex as you want, using Python and R scripts Book DescriptionThe latest edition of this book delves deep into advanced analytics, focusing on enhancing Python and R proficiency within Power BI. New chapters cover optimizing Python and R settings, utilizing Intel's Math Kernel Library (MKL) for performance boosts, and addressing integration challenges. Techniques for managing large datasets beyond available RAM, employing the Parquet data format, and advanced fuzzy matching algorithms are explored. Additionally, it discusses leveraging SQL Server Language Extensions to overcome traditional Python and R limitations in Power BI. It also helps in crafting sophisticated visualizations using the Grammar of Graphics in both R and Python. This Power BI book will help you master data validation with regular expressions, import data from diverse sources, and apply advanced algorithms for transformation. You'll learn how to safeguard personal data in Power BI with techniques like pseudonymization, anonymization, and data masking. You'll also get to grips with the key statistical features of datasets by plotting multiple visual graphs in the process of building a machine learning model. The book will guide you on utilizing external APIs for enrichment, enhancing I/O performance, and leveraging Python and R for analysis. You'll reinforce your learning with questions at the end of each chapter.What you will learn Configure optimal integration of Python and R with Power BI Perform complex data manipulations not possible by default in Power BI Boost Power BI logging and loading large datasets Extract insights from your data using algorithms like linear optimization Calculate string distances and learn how to use them for probabilistic fuzzy matching Handle outliers and missing values for multivariate and time-series data Apply Exploratory Data Analysis in Power BI with R Learn to use Grammar of Graphics in Python Who this book is for This book is for business analysts, business intelligence professionals, and data scientists who already use Microsoft Power BI and want to add more value to their analysis using Python and R. Working knowledge of Power BI is required to make the most of this book. Basic knowledge of Python and R will also be helpful.

Identify vulnerabilities across applications, network and systems using simplified cybersecurity scripting KEY FEATURES ● Exciting coverage on red teaming methodologies and penetration testing techniques. ● Explore the exploitation development environment and process of creating exploit scripts. ● Includes powerful Python libraries to analyze the web and helps identifying critical vulnerabilities. ● Conduct wireless attacks and identify potential threats using Python. DESCRIPTION This book starts with an understanding of penetration testing and red teaming methodologies and teaches Python 3.x from scratch for those who are not familiar with programming. The book gives the skills of how to create scripts for cracking, and brute force attacks. The second part of this book focuses on the network and wireless level. The book teaches you the skills of how to create an offensive tool using Python 3.x to identify different services and ports using different Python network modules and conducting network attacks. In the network monitoring section, you will be able to monitor layers 3 and 4. And finally, you will be able to conduct different attacks on wireless. The last part of this book focuses on web applications and exploitation developments. It focuses on how to create scripts to extract web information such as links, images, documents, etc. It also focuses on how to create scripts to identify and exploit web vulnerabilities and how to bypass WAF. The last chapter of this book focuses on exploitation development starting with how to play with the stack and then moving on to how to use Python in fuzzing and creating exploitation scripts. WHAT YOU WILL LEARN ● Learn to code Python scripts from scratch to identify web vulnerabilities. ● Conduct network attacks, create offensive tools, and identify vulnerable services and ports. ● Perform deep monitoring of network up to layers 3 and 4. ● Execute web scraping scripts to extract images, documents, and links. WHO THIS BOOK IS FOR This book is for Penetration Testers, Security Researchers, Red Teams, Security Auditors and IT Administrators who want to start with an action plan in protecting their IT systems. All you need is some basic understanding of programming concepts and working of IT systems. Hands-on experience with python will be more beneficial but not required. TABLE OF CONTENTS 1. Start with Penetration Testing and Basic Python 2. Cracking with Python 3. Service and Applications Brute Forcing with Python 4. Python Services Identifications - Ports and Banner 5. Python Network Modules and Nmap 6. Network Monitoring with Python 7. Attacking Wireless with Python 8. Analyze Web Applications with Python 9. Attack Web Application with Python 10. Exploitation Development with Python

By taking you through the development of a real web application from beginning to end, the second edition of this hands-on guide demonstrates the practical advantages of test-driven development (TDD) with Python. You’ll learn how to write and run tests before building each part of your app, and then develop the minimum amount of code required to pass those tests. The result? Clean code that works. In the process, you’ll learn the basics of Django, Selenium, Git, jQuery, and Mock, along with current web development techniques. If you’re ready to take your Python skills to the next level, this book—updated for Python 3.6—clearly demonstrates how TDD encourages simple designs and inspires confidence. Dive into the TDD workflow, including the unit test/code cycle and refactoring Use unit tests for classes and functions, and functional tests for user interactions within the browser Learn when and how to use mock objects, and the pros and cons of isolated vs. integrated tests Test and automate your deployments with a staging server Apply tests to the third-party plugins you integrate into your site Run tests automatically by using a Continuous Integration environment Use TDD to build a REST API with a front-end Ajax interface

Learn to use IPython and Jupyter Notebook for your data analysis and visualization work. Key Features Leverage the Jupyter Notebook for interactive data science and visualization Become an expert in high-performance computing and visualization for data analysis and scientific modeling A comprehensive coverage of scientific computing through many hands-on, example-driven recipes with detailed, step-by-step explanations Book Description Python is one of the leading open source platforms for data science and numerical computing. IPython and the associated Jupyter Notebook offer efficient interfaces to Python for data analysis and interactive visualization, and they constitute an ideal gateway to the platform. IPython Interactive Computing and Visualization Cookbook, Second Edition contains many ready-to-use, focused recipes for high-performance scientific computing and data analysis, from the latest IPython/Jupyter features to the most advanced tricks, to help you write better and faster code. You will apply these state-of-the-art methods to various real-world examples, illustrating topics in applied mathematics, scientific modeling, and machine learning. The first part of the book covers programming techniques: code quality and reproducibility, code optimization, high-performance computing through just-in-time compilation, parallel computing, and graphics card programming. The second part tackles data science, statistics, machine learning, signal and image processing, dynamical systems, and pure and applied mathematics. What you will learn Master all features of the Jupyter Notebook Code better: write high-quality, readable, and well-tested programs; profile and optimize your code; and conduct reproducible interactive computing experiments Visualize data and create interactive plots in the Jupyter Notebook Write blazingly fast Python programs with NumPy, ctypes, Numba, Cython, OpenMP, GPU programming (CUDA), parallel IPython, Dask, and more Analyze data with Bayesian or frequentist statistics (Pandas, PyMC, and R), and learn from actual data through machine learning (scikit-learn) Gain valuable insights into signals, images, and sounds with SciPy, scikit-image, and OpenCV Simulate deterministic and stochastic dynamical systems in Python Familiarize yourself with math in Python using SymPy and Sage: algebra, analysis, logic, graphs, geometry, and probability theory Who this book is for This book is intended for anyone interested in numerical computing and data science: students, researchers, teachers, engineers, analysts, and hobbyists. A basic knowledge of Python/NumPy is recommended. Some skills in mathematics will help you understand the theory behind the computational methods.