- Table View
- List View
Python Requests Essentials
by Bala Subrahmanyam Varanasi Rakesh Vidya ChandraIf you are a Python administrator or developer interested in interacting with web APIs and have a passion for creating your own web applications, this is the book for you. Basic knowledge of Python programming, APIs, and web services will be an advantage.
Python Robotics Projects: Build smart and collaborative robots using Python
by Diwakar VaishLeverage the power of Python to build DIY robotic projectsKey FeaturesDesign, build, and stimulate collaborative robotsBuild high-end robotics projects such as a customized personal JarvisLeverage the power of Python and ROS for DIY robotic projectsBook DescriptionRobotics is a fast-growing industry. Multiple surveys state that investment in the field has increased tenfold in the last 6 years, and is set to become a $100-billion sector by 2020. Robots are prevalent throughout all industries, and they are all set to be a part of our domestic lives. This book starts with the installation and basic steps in configuring a robotic controller. You'll then move on to setting up your environment to use Python with the robotic controller. You'll dive deep into building simple robotic projects, such as a pet-feeding robot, and more complicated projects, such as machine learning enabled home automation system (Jarvis), vision processing based robots and a self-driven robotic vehicle using Python. By the end of this book, you'll know how to build smart robots using Python.What you will learn Get to know the basics of robotics and its functions Walk through interface components with microcontrollers Integrate robotics with the IoT environment Build projects using machine learning Implement path planning and vision processing Interface your robots with BluetoothWho this book is forIf building robots is your dream, then this book is made for you. Prior knowledge of Python would be an added advantage.
Python Scripting For ArcGIS
by Paul A. ZandbergenThis book is a guide for experienced users of ArcGIS® Desktop to get started with Python scripting without needing previous programming experience. Experience with other scripting or programming languages (Perl, VBA, VB script, Java, C++) is helpful but not required. Readers are expected to have good general ArcGIS skills and a basic understanding of geoprocessing procedures.
Python Social Media Analytics
by Michal Krystyanczuk Siddhartha ChatterjeeIf you are a programmer or a data analyst familiar with the Python programming language and want to perform analyses of your social data to acquire valuable business insights, this book is for you. The book does not assume any prior knowledge of any data analysis tool or process.
Python Testing: Beginner's Guide
by Daniel ArbuckleThe book begins with the very foundations of automated testing, and expands on them until the best-practice tools and techniques are fully covered. New concepts are illustrated with step-by-step hands-on exercises. Testing will be easier and more enjoyable with this beginner's guide. If you are a Python developer and want to write tests for your applications, this book will get you started and show you the easiest way to learn testing. You need to have sound Python programming knowledge to follow along. An awareness of software testing would be good, but no formal knowledge of testing is expected nor do you need to have any knowledge of the libraries discussed in the book.
Python Testing Cookbook
by Greg L. TurnquistThis cookbook is written as a collection of code recipes containing step-by-step directions on how to install or build different types of Python test tools to solve different problems. Each recipe contains explanations of how it works along with answers to common questions and cross references to other relevant recipes. The easy-to-understand recipe names make this a handy test reference book. Python developers and programmers with a basic understanding of Python and Python testing will find this cookbook beneficial. It will build on that basic knowledge equipping you with the intermediate and advanced skills required to fully utilize the Python testing tools. Broken up into lots of small code recipes, you can read this book at your own pace, whatever your experience. No prior experience of automated testing is required.
Python Testing Cookbook: Easy solutions to test your Python projects using test-driven development and Selenium, 2nd Edition
by Greg L. Turnquist Bhaskar N. DasFix everyday testing problems in Python with the help of this solution-based guideKey FeaturesUse powerful tools such as doctest and unittest to make testing convenientApply automation testing to an existing legacy system that isn't test orientedA practical guide to ease testing in Python using real-world examplesBook DescriptionAutomated testing is the best way to increase efficiency while reducing the defects of software testing. It helps find bugs in code easily and at an early stage so that they can be tackled efficiently. This book delves into essential testing concepts used in Python to help you build robust and maintainable code.Python Testing Cookbook begins with a brief introduction to Python's unit testing framework to help you write automated test cases. You will learn how to write suitable test sets for your software and run automated test suites with Nose. You will then work with the unittest.mock library, which allows you to replace the parts of your system that are being tested with mock objects and make assertions about how they have been used. You will also see how to apply Test-driven Development (TDD) and Behavior-driven Development (BDD) and how to eliminate issues caused by TDD. The book explains how to integrate automated tests using Continuous Integration and perform smoke/load testing. It also covers best practices and will help you solve persistent testing issues in Python. The book concludes by helping you understand how doctest works and how Selenium can be used to test code efficiently. What you will learnRun test cases from the command line with increased verbosityWrite a Nose extension to pick tests based on regular expressionsCreate testable documentation using doctestUse Selenium to test the Web User InterfaceWrite a testable story with Voidspace Mock and NoseConfigure TeamCity to run Python tests on commitUpdate project-level scripts to provide coverage reportsWho this book is forIf you’re a Python developer who wants to take testing to the next level and would like to expand your testing skills, this book is for you. It is assumed that you have some Python programming knowledge.
Python Testing with pytest: Simple, Rapid, Effective, and Scalable
by Brian OkkenDo 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.
Python Testing with pytest
by Brian OkkenTest applications, packages, and libraries large and small with pytest, Python's most powerful testing framework. pytest helps you write tests quickly and keep them readable and maintainable. In this fully revised edition, explore pytest's superpowers - simple asserts, fixtures, parametrization, markers, and plugins - while creating simple tests and test suites against a small database application. 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. This book shows you how. pytest is undeniably the best choice for testing Python projects. It's a full-featured, flexible, and extensible testing framework. pytest's fixture model allows you to share test data and setup procedures across multiple layers of tests. The pytest framework gives you powerful features such as assert rewriting, parametrization, markers, plugins, parallel test execution, and clear test failure reporting - 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 yet powerful tool. Write short, maintainable tests that elegantly express what you're testing. Speed up test times by distributing tests across multiple processors and running tests in parallel. Use Python's builtin assert statements instead of awkward assert helper functions to make your tests more readable. Move setup code out of tests and into fixtures to separate setup failures from 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, and even existing unittest tests. Write simple, maintainable tests quickly with pytest. What You Need: The examples in this book were written using Python 3.10 and pytest 7. pytest 7 supports Python 3.5 and above.
Python Testing with Selenium: Learn to Implement Different Testing Techniques Using the Selenium WebDriver
by Sujay RaghavendraImplement different testing techniques using Selenium WebDriver with the Python programming language. This quick reference provides simple functional test cases with a syntax-based approach for Selenium WebDriver. You’ll begin by reviewing the basics of Selenium WebDriver and its architectural design history and then move on to the configuration and installation of Selenium library for different web browsers, including the basic commands needed to start test scripts in various browsers. You’ll review action commands of keyboard and mouse for testing user interactions in a web page and see how hyperlinks are tested. The book also examines various web elements using eight different locators provided by Selenium to help you choose the one best suited to your needs. All Python scripts are ready to test real examples, all of which are explained thoroughly with problem statements. You’ll use different Python design patterns to automate test scripts that can be incorporated with Selenium. In the end, Python Testing with Selenium will provide you with the expertise to write your own test cases in future. What You’ll Learn Install and configure Selenium WebDriver with Python for different web-browsers Review basic commands of Selenium Locate web elements Work with UI based web elements Assert web elements and handle exceptions Write test scripts in Page Object Model Write test cases with Unittest framework Who This Book Is For Python developers/testers who want to test their web applications
Python Text Processing with NLTK 2.0 Cookbook
by Jacob PerkinsThe learn-by-doing approach of this book will enable you to dive right into the heart of text processing from the very first page. Each recipe is carefully designed to fulfill your appetite for Natural Language Processing. Packed with numerous illustrative examples and code samples, it will make the task of using the NLTK for Natural Language Processing easy and straightforward. This book is for Python programmers who want to quickly get to grips with using the NLTK for Natural Language Processing. Familiarity with basic text processing concepts is required. Programmers experienced in the NLTK will also find it useful. Students of linguistics will find it invaluable.
Python Text Processing with NLTK 2.0 Cookbook: LITE
by Jacob PerkinsThe learn-by-doing approach of this book will enable you to dive right into the heart of text processing from the very first page. Each recipe is carefully designed to fulfill your appetite for Natural Language Processing. Packed with numerous illustrative examples and code samples, it will make the task of using the NLTK for Natural Language Processing easy and straightforward. This book is for Python programmers who want to quickly get to grips with using the NLTK for Natural Language Processing. Familiarity with basic text processing concepts is required. Programmers experienced in the NLTK will also find it useful. Students of linguistics will find it invaluable.
Python Tools for Scientists: An Introduction to Using Anaconda, JupyterLab, and Python's Scientific Libraries
by Lee VaughanAn introduction to the Python programming language and its most popular tools for scientists, engineers, students, and anyone who wants to use Python for research, simulations, and collaboration.Python Tools for Scientists will introduce you to Python tools you can use in your scientific research, including Anaconda, Spyder, Jupyter Notebooks, JupyterLab, and numerous Python libraries. You&’ll learn to use Python for tasks such as creating visualizations, representing geospatial information, simulating natural events, and manipulating numerical data.Once you&’ve built an optimal programming environment with Anaconda, you&’ll learn how to organize your projects and use interpreters, text editors, notebooks, and development environments to work with your code. Following the book&’s fast-paced Python primer, you&’ll tour a range of scientific tools and libraries like scikit-learn and seaborn that you can use to manipulate and visualize your data, or analyze it with machine learning algorithms.You&’ll also learn how to:Create isolated projects in virtual environments, build interactive notebooks, test code in the Qt console, and use Spyder&’s interactive development featuresUse Python&’s built-in data types, write custom functions and classes, and document your codeRepresent data with the essential NumPy, Matplotlib, and pandas librariesUse Python plotting libraries like Plotly, HoloViews, and Datashader to handle large datasets and create 3D visualizationsRegardless of your scientific field, Python Tools for Scientists will show you how to choose the best tools to meet your research and computational analysis needs.
Python Tools for Visual Studio
by Martino Sabia Cathy WangThis is a hands-on guide that provides exemplary coverage of all the features and concepts related to PTVS. The book is intended for developers who are aiming to enhance their productivity in Python projects with automation tools that Visual Studio provides for the .Net community. Some basic knowledge of Python programming is essential.
Python Unit Test Automation
by Ashwin PajankarQuickly learn how to automate unit testing of Python 3 code with Python 3 automation libraries, such as doctest, unittest, nose, nose2, and pytest. This book explores the important concepts in software testing and their implementation in Python 3 and shows you how to automate, organize, and execute unit tests for this language. This knowledge is often acquired by reading source code, manuals, and posting questions on community forums, which tends to be a slow and painful process. Python Unit Test Automation will allow you to quickly ramp up your understanding of unit test libraries for Python 3 through the practical use of code examples and exercises. All of which makes this book a great resource for software developers and testers who want to get started with unit test automation in Python 3 and compare the differences with Python 2. This short work is your must-have quick start guide to mastering the essential concepts of software testing in Python. What You'll Learn: Essential concepts in software testing Various test automation libraries for Python, such as doctest, unittest, nose, nose2, and pytest Test-driven development and best practices for test automation in Python Code examples and exercises Who This Book Is For: Python developers, software testers, open source enthusiasts, and contributors to the Python community
Python Unit Test Automation: Automate, Organize, and Execute Unit Tests in Python
by Ashwin PajankarLearn how to automate unit tests of Python 3 with automation libraries, such as doctest, unittest, nose, nose2, pytest, and selenium. This book explores important concepts in software test automation and demonstrates how to automate, organize, and execute unit tests with Python. It also introduces readers to the concepts of web browser automation and logging.This new edition starts with an introduction to Python 3. Next, it covers doctest and pydoc. This is followed by a discussion on unittest, a framework that comes packaged with Python 3 itself. There is a dedicated section on creating test suites, followed by an explanation of how nose2 provides automatic test module discovery. Moving forward, you will learn about pytest, the most popular third-party library and testrunner for Python. You will see how to write and execute tests with pytest. You’ll also learn to discover tests automatically with pytest.This edition features two brand new chapters, the first of which focuses on the basics of web browser automation with Selenium. You’ll learn how to use Selenium with unittest to write test cases for browser automation and use the Selenium IDE with web browsers such as Chrome and Firefox. You’ll then explore logging frameworks such as Python’s built-in logger and the third-party framework loguru.The book concludes with an exploration of test-driven development with pytest, during which you will execute a small project using TDD methodology.What You Will LearnStart testing with doctest and unittestUnderstand the idea of unit testingGet started with nose 2 and pytestLearn how to use logger and loguruWork with Selenium and test driven development Who This Book Is ForPython developers, software testers, open source enthusiasts, and contributors to the Python community.
Python Unlocked
by Arun TigeraniyaBecome more fluent in Python--learn strategies and techniques for smart and high-performance Python programming About This Book * Write smarter, bug-free, high performance code with minimal effort * Uncover the best tools and options available to Python developers today * Deploy decorators, design patters, and various optimization techniques to use Python 3.5 effectively Who This Book Is For If you are a Python developer and you think that you don't know everything about the language yet, then this is the book for you. We will unlock the mysteries and re-introduce you to the hidden features of Python to write efficient programs, making optimal use of the language. What You Will Learn * Manipulate object creation processes for instances, classes, and functions * Use the best possible language constructs to write data structures with super speed and maintainability * Make efficient use of design patterns to decrease development time and make your code more maintainable * Write better test cases with an improved understanding of the testing framework of Python and unittests, and discover how to develop new functionalities in it * Write fully-optimized code with the Python language by profiling, compiling C modules, and more * Unlock asynchronous programming to build efficient and scalable applications In Detail Python is a versatile programming language that can be used for a wide range of technical tasks--computation, statistics, data analysis, game development, and more. Though Python is easy to learn, it's range of features means there are many aspects of it that even experienced Python developers don't know about. Even if you're confident with the basics, its logic and syntax, by digging deeper you can work much more effectively with Python - and get more from the language. Python Unlocked walks you through the most effective techniques and best practices for high performance Python programming - showing you how to make the most of the Python language. You'll get to know objects and functions inside and out, and will learn how to use them to your advantage in your programming projects. You will also find out how to work with a range of design patterns including abstract factory, singleton, strategy pattern, all of which will help make programming with Python much more efficient. Finally, as the process of writing a program is never complete without testing it, you will learn to test threaded applications and run parallel tests. If you want the edge when it comes to Python, use this book to unlock the secrets of smarter Python programming. Style and approach This is book had been created to help you to "unlock" the best ways to tackle the challenges and performance bottlenecks that many Python developers face today. The keys are supported with program examples to help you understand the concepts better and see them in action.
Python Web Development with Sanic: An in-depth guide for Python web developers to improve the speed and scalability of web applications
by Adam HopkinsBuild a performant and scalable web application using Sanic, along with maintaining clean code to fit your unique challenges and business requirementsKey FeaturesExpand your knowledge of web application architecture for building scalable web appsLearn the core philosophies of performance and scalability from one of the creators of SanicCreate a complete Python web app from scratch and learn to translate the knowledge you gain across various use casesBook DescriptionToday's developers need something more powerful and customizable when it comes to web app development. They require effective tools to build something unique to meet their specific needs, and not simply glue a bunch of things together built by others. This is where Sanic comes into the picture. Built to be unopinionated and scalable, Sanic is a next-generation Python framework and server tuned for high performance.This Sanic guide starts by helping you understand Sanic's purpose, significance, and use cases. You'll learn how to spot different issues when building web applications, and how to choose, create, and adapt the right solution to meet your requirements. As you progress, you'll understand how to use listeners, middleware, and background tasks to customize your application. The book will also take you through real-world examples, so you will walk away with practical knowledge and not just code snippets.By the end of this web development book, you'll have gained the knowledge you need to design, build, and deploy high-performance, scalable, and maintainable web applications with the Sanic framework.What you will learnUnderstand the difference between WSGI, Async, and ASGI serversDiscover how Sanic organizes incoming data, why it does it, and how to make the most of itImplement best practices for building reliable, performant, and secure web appsExplore useful techniques for successfully testing and deploying a Sanic web appCreate effective solutions for the modern web, including task management, bot integration, and GraphQLIdentify security concerns and understand how to deal with them in your Sanic appsWho this book is forThis book is for Python web developers who have basic to intermediate-level knowledge of how web technologies work and are looking to take their applications to the next level using the power of the Sanic framework. Working knowledge of Python web development along with frameworks such as Django and/or Flask will be helpful but is not required. A basic to intermediate-level understanding of Python 3, HTTP, RESTful API patterns, and modern development practices and tools, such as type annotations, pytest, and virtual environments will also be beneficial.
Python Web Penetration Testing Cookbook
by Cameron Buchanan Terry IpThis book is for testers looking for quick access to powerful, modern tools and customizable scripts to kick-start the creation of their own Python web penetration testing toolbox.
Python Web Scraping Cookbook: Over 90 Proven Recipes To Get You Scraping With Python, Micro Services, Docker And Aws
by Michael HeydtPython Web Scraping Cookbook is a solution-focused book that will teach you techniques to develop high-performance Scrapers, and deal with cookies, hidden form fields, Ajax-based sites, proxies, and more. By the end of this book, you will be able to scrape websites more efficiently with more accurate data, and how to package, deploy and operate scrapers in the cloud.
Python Web Scraping Cookbook: Over 90 proven recipes to get you scraping with Python, microservices, Docker, and AWS
by Michael Heydt Jay ZengUntangle your web scraping complexities and access web data with ease using Python scripts Key Features Hands-on recipes for advancing your web scraping skills to expert level. One-Stop Solution Guide to address complex and challenging web scraping tasks using Python. Understand the web page structure and collect meaningful data from the website with ease Book Description Python Web Scraping Cookbook is a solution-focused book that will teach you techniques to develop high-performance scrapers and deal with crawlers, sitemaps, forms automation, Ajax-based sites, caches, and more.You'll explore a number of real-world scenarios where every part of the development/product life cycle will be fully covered. You will not only develop the skills to design and develop reliable, performance data flows, but also deploy your codebase to an AWS. If you are involved in software engineering, product development, or data mining (or are interested in building data-driven products), you will find this book useful as each recipe has a clear purpose and objective. Right from extracting data from the websites to writing a sophisticated web crawler, the book's independent recipes will be a godsend on the job. This book covers Python libraries, requests, and BeautifulSoup. You will learn about crawling, web spidering, working with AJAX websites, paginated items, and more. You will also learn to tackle problems such as 403 errors, working with proxy, scraping images, LXML, and more. By the end of this book, you will be able to scrape websites more efficiently and to be able to deploy and operate your scraper in the cloud. What you will learn Use a wide variety of tools to scrape any website and data—including BeautifulSoup, Scrapy, Selenium, and many more Master expression languages such as XPath, CSS, and regular expressions to extract web data Deal with scraping traps such as hidden form fields, throttling, pagination, and different status codes Build robust scraping pipelines with SQS and RabbitMQ Scrape assets such as images media and know what to do when Scraper fails to run Explore ETL techniques of build a customized crawler, parser, and convert structured and unstructured data from websites Deploy and run your scraper-as-aservice in AWS Elastic Container Service Who this book is for This book is ideal for Python programmers, web administrators, security professionals or someone who wants to perform web analytics would find this book relevant and useful. Familiarity with Python and basic understanding of web scraping would be useful to take full advantage of this book.
Python Web Scraping, Second Edition
by Katharine Jarmul Richard LawsonSuccessfully scrape data from any website with the power of Python 3.xAbout This Book* A hands-on guide to web scraping using Python with solutions to real-world problems* Create a number of different web scrapers in Python to extract information* This book includes practical examples on using the popular and well-maintained libraries in Python for your web scraping needsWho This Book Is ForThis book is aimed at developers who want to use web scraping for legitimate purposes. Prior programming experience with Python would be useful but not essential. Anyone with general knowledge of programming languages should be able to pick up the book and understand the principals involved.What You Will Learn* Extract data from web pages with simple Python programming* Build a concurrent crawler to process web pages in parallel* Follow links to crawl a website* Extract features from the HTML* Cache downloaded HTML for reuse* Compare concurrent models to determine the fastest crawler* Find out how to parse JavaScript-dependent websites* Interact with forms and sessionsIn DetailThe Internet contains the most useful set of data ever assembled, most of which is publicly accessible for free. However, this data is not easily usable. It is embedded within the structure and style of websites and needs to be carefully extracted. Web scraping is becoming increasingly useful as a means to gather and make sense of the wealth of information available online.This book is the ultimate guide to using the latest features of Python 3.x to scrape data from websites. In the early chapters, you'll see how to extract data from static web pages. You'll learn to use caching with databases and files to save time and manage the load on servers. After covering the basics, you'll get hands-on practice building a more sophisticated crawler using browsers, crawlers, and concurrent scrapers.You'll determine when and how to scrape data from a JavaScript-dependent website using PyQt and Selenium. You'll get a better understanding of how to submit forms on complex websites protected by CAPTCHA. You'll find out how to automate these actions with Python packages such as mechanize. You'll also learn how to create class-based scrapers with Scrapy libraries and implement your learning on real websites.By the end of the book, you will have explored testing websites with scrapers, remote scraping, best practices, working with images, and many other relevant topics.Style and approachThis hands-on guide is full of real-life examples and solutions starting simple and then progressively becoming more complex. Each chapter in this book introduces a problem and then provides one or more possible solutions.
Python Web Scraping - Second Edition
by Katharine Jarmul Richard LawsonSuccessfully scrape data from any website with the power of Python 3.x About This Book • A hands-on guide to web scraping using Python with solutions to real-world problems • Create a number of different web scrapers in Python to extract information • This book includes practical examples on using the popular and well-maintained libraries in Python for your web scraping needs Who This Book Is For This book is aimed at developers who want to use web scraping for legitimate purposes. Prior programming experience with Python would be useful but not essential. Anyone with general knowledge of programming languages should be able to pick up the book and understand the principals involved. What You Will Learn • Extract data from web pages with simple Python programming • Build a concurrent crawler to process web pages in parallel • Follow links to crawl a website • Extract features from the HTML • Cache downloaded HTML for reuse • Compare concurrent models to determine the fastest crawler • Find out how to parse JavaScript-dependent websites • Interact with forms and sessions In Detail The Internet contains the most useful set of data ever assembled, most of which is publicly accessible for free. However, this data is not easily usable. It is embedded within the structure and style of websites and needs to be carefully extracted. Web scraping is becoming increasingly useful as a means to gather and make sense of the wealth of information available online. This book is the ultimate guide to using the latest features of Python 3.x to scrape data from websites. In the early chapters, you'll see how to extract data from static web pages. You'll learn to use caching with databases and files to save time and manage the load on servers. After covering the basics, you'll get hands-on practice building a more sophisticated crawler using browsers, crawlers, and concurrent scrapers. You'll determine when and how to scrape data from a JavaScript-dependent website using PyQt and Selenium. You'll get a better understanding of how to submit forms on complex websites protected by CAPTCHA. You'll find out how to automate these actions with Python packages such as mechanize. You'll also learn how to create class-based scrapers with Scrapy libraries and implement your learning on real websites. By the end of the book, you will have explored testing websites with scrapers, remote scraping, best practices, working with images, and many other relevant topics. Style and approach This hands-on guide is full of real-life examples and solutions starting simple and then progressively becoming more complex. Each chapter in this book introduces a problem and then provides one or more possible solutions.
The Python Workbook: A Brief Introduction with Exercises and Solutions
by Ben StephensonWhile other textbooks devote their pages to explaining introductory programming concepts, The Python Workbook focuses exclusively on exercises, following the philosophy that computer programming is a skill best learned through experience and practice. Designed to support and encourage hands-on learning about programming, this student-friendly work contains 174 exercises, spanning a variety of academic disciplines and everyday situations. Solutions to selected exercises are also provided, supported by brief annotations that explain the technique used to solve the problem, or highlight specific points of Python syntax. No background knowledge is required to solve the exercises, beyond the material covered in a typical introductory Python programming course. Undergraduate students undergoing their first programming course and wishing to enhance their programming abilities will find the exercises and solutions provided in this book to be ideal for their needs.
The Python Workbook: A Brief Introduction with Exercises and Solutions (Texts in Computer Science)
by Ben StephensonThis student-friendly textbook encourages the development of programming skills through active practice by focusing on exercises that support hands-on learning. The Python Workbook provides a compendium of 186 exercises, spanning a variety of academic disciplines and everyday situations. Solutions to selected exercises are also provided, supported by brief annotations that explain the technique used to solve the problem, or highlight a specific point of Python syntax.This enhanced new edition has been thoroughly updated and expanded with additional exercises, along with concise introductions that outline the core concepts needed to solve them. The exercises and solutions require no prior background knowledge, beyond the material covered in a typical introductory Python programming course.Features: uses an accessible writing style and easy-to-follow structure; includes a mixture of classic exercises from the fields of computer science and mathematics, along with exercises that connect to other academic disciplines; presents the solutions to approximately half of the exercises; provides annotations alongside the solutions, which explain the approach taken to solve the problem and relevant aspects of Python syntax; offers a variety of exercises of different lengths and difficulties; contains exercises that encourage the development of programming skills using if statements, loops, basic functions, lists, dictionaries, files, and recursive functions.Undergraduate students enrolled in their first programming course and wishing to enhance their programming abilities will find the exercises and solutions provided in this book to be ideal for their needs.