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Python und SMath in der Wärmetechnik: Wärmeübertragung, Sonnenenergie, Gasmischungen u. Verbrennungsrechnung
by Heinz SchmidDieses Buch verbindet Ingenieurstheorie, Thermodynamik und Wärmeübertragung mit Softwareanwendungen wie SMath, MathCAD und Python. Es ist kein klassisches Lehrbuch, behandelt jedoch die grundlegenden Gleichungen und kommentiert Python-Programme. Zudem wird die Entwicklung von Wärmeaustauscher-Programmen mit Python-GUIs thematisiert, unter Nutzung leistungsstarker Bibliotheken. Querverweise zu aktuellen globalen Problemen wie dem Klimawandel und Lösungen, z.B. die Nutzung von grünem Wasserstoff, werden ebenfalls aufgezeigt.
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.
Python Workout: 50 ten-minute exercises
by Reuven M. LernerThe only way to master a skill is to practice. In Python Workout, author Reuven M. Lerner guides you through 50 carefully selected exercises that invite you to flex your programming muscles. As you take on each new challenge, you&’ll build programming skill and confidence.Summary The only way to master a skill is to practice. In Python Workout, author Reuven M. Lerner guides you through 50 carefully selected exercises that invite you to flex your programming muscles. As you take on each new challenge, you&’ll build programming skill and confidence. The thorough explanations help you lock in what you&’ve learned and apply it to your own projects. Along the way, Python Workout provides over four hours of video instruction walking you through the solutions to each exercise and dozens of additional exercises for you to try on your own. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology To become a champion Python programmer you need to work out, building mental muscle with your hands on the keyboard. Each carefully selected exercise in this unique book adds to your Python prowess—one important skill at a time. About the book Python Workout presents 50 exercises that focus on key Python 3 features. In it, expert Python coach Reuven Lerner guides you through a series of small projects, practicing the skills you need to tackle everyday tasks. You&’ll appreciate the clear explanations of each technique, and you can watch Reuven solve each exercise in the accompanying videos. What's inside 50 hands-on exercises and solutions Coverage of all Python data types Dozens more bonus exercises for extra practice About the reader For readers with basic Python knowledge. About the author Reuven M. Lerner teaches Python and data science to companies around the world. Table of Contents 1 Numeric types 2 Strings 3 Lists and tuples 4 Dictionaries and sets 5 Files 6 Functions 7 Functional programming with comprehensions 8 Modules and packages 9 Objects 10 Iterators and generators
The Python Workshop: A Practical, No-Nonsense Introduction to Python Development
by Andrew Bird Graham Lee Dr Lau Han Mario Corchero Jimenez Corey WadeCut through the noise and get real results with a step-by-step approach to learning Python 3.X programming Key Features Experimental projects showcasing the implementation of high-performance deep learning models with Keras. Use-cases across reinforcement learning, natural language processing, GANs and computer vision. Build strong fundamentals of Keras in the area of deep learning and artificial intelligence Book Description You already know you want to learn Python, and a smarter way to learn Python 3 is to learn by doing. The Python Workshop focuses on building up your practical skills so that you can work towards building up your machine learning skills as a data scientist, write scripts that help automate your life and save you time, or even create your own games and desktop applications. You'll learn from real examples that lead to real results. Throughout The Python Workshop, you'll take an engaging step-by-step approach to understanding Python. You won't have to sit through any unnecessary theory. If you're short on time you can jump into a single exercise each day or spend an entire weekend learning about Python scripting. It's your choice. Learning on your terms, you'll build up and reinforce key skills in a way that feels rewarding. Every physical copy of The Python Workshop unlocks access to the interactive edition. With videos detailing all exercises and activities, you'll always have a guided solution. You can also benchmark yourself against assessments, track progress, and receive free content updates. You'll even earn a secure credential that you can share and verify online upon completion. It's a premium learning experience that's included with your printed copy. To redeem, follow the instructions located at the start of your Python book. Fast-paced and direct, The Python Workshop is the ideal companion for Python beginners. You'll build and iterate on your code like a software developer, learning along the way. This process means that you'll find that your new skills stick, embedded as best practice. A solid foundation for the years ahead. What you will learn Learn how to write clean and concise code with Python 3 Understand classes and object-oriented programming Tackle entry-level data science and create engaging visualizations Use Python to create responsive, modern web applications Automate essential day-to-day tasks with Python scripts Get started with predictive Python machine learning Who this book is for This book is designed for professionals, students, and hobbyists who want to learn Python and apply it to solve challenging real-world problems. Although this is a beginner's book, it will help if you already know standard programming topics, such as variables, if-else statements, and functions. Experience with another object-oriented program is beneficial, but not mandatory.
The Python Workshop: Write Python code to solve challenging real-world problems, 2nd Edition
by Corey Wade Mario Corchero Jimenez Andrew Bird Dr. Lau Han Graham LeeGain proficiency, productivity, and power by working on projects and kick-starting your career in Python with this comprehensive, hands-on guide.Key FeaturesUnderstand and utilize Python syntax, objects, methods, and best practicesExplore Python's many features and libraries through real-world problems and big dataUse your newly acquired Python skills in machine learning as well as web and software developmentBook DescriptionPython is among the most popular programming languages in the world. It's ideal for beginners because it's easy to read and write, and for developers, because it's widely available with a strong support community, extensive documentation, and phenomenal libraries – both built-in and user-contributed.This project-based course has been designed by a team of expert authors to get you up and running with Python. You'll work though engaging projects that'll enable you to leverage your newfound Python skills efficiently in technical jobs, personal projects, and job interviews. The book will help you gain an edge in data science, web development, and software development, preparing you to tackle real-world challenges in Python and pursue advanced topics on your own. Throughout the chapters, each component has been explicitly designed to engage and stimulate different parts of the brain so that you can retain and apply what you learn in the practical context with maximum impact.By completing the course from start to finish, you'll walk away feeling capable of tackling any real-world Python development problem.What you will learnWrite efficient and concise functions using core Python methods and librariesBuild classes to address different business needsCreate visual graphs to communicate key data insightsOrganize big data and use machine learning to make regression and classification predictionsDevelop web pages and programs with Python tools and packagesAutomate essential tasks using Python scripts in real-time executionWho this book is forThis book is for professionals, students, and hobbyists who want to learn Python and apply it to solve challenging real-world problems. Although this is a beginner's course, you'll learn more easily if you already have an understanding of standard programming topics like variables, if-else statements, and functions. Experience with another object-oriented program, though not essential, will also be beneficial. If Python is your first attempt at computer programming, this book will help you understand the basics with adequate detail for a motivated student.
Python & XML: XML Processing with Python
by Christopher A. Jones Fred L. Drake JrIf you are a Python programmer who wants to incorporate XML into your skill set, this is the book for you. Python has attracted a wide variety of developers, who use it either as glue to connect critical programming tasks together, or as a complete cross-platform application development language. Yet, because it is object-oriented and has powerful text manipulation abilities, Python is an ideal language for manipulating XML.Python & XML gives you a solid foundation for using these two languages together. Loaded with practical examples, this new volume highlights common application tasks, so that you can learn by doing. The book starts with the basics then quickly progresses to complex topics, like transforming XML with XSLT, querying XML with XPath, and working with XML dialects and validation. It also explores the more advanced issues: using Python with SOAP and distributed web services, and using Python to create scalable streams between distributed applications (like databases and web servers).The book provides effective practical applications, while referencing many of the tools involved in XML processing and Python, and highlights cross-platform issues along with tasks relevant to enterprise computing. You will find ample coverage of XML flow analysis and details on ways in which you can transport XML through your network.Whether you are using Python as an application language, or as an administrative or middleware scripting language, you are sure to benefit from this book. If you want to use Python to manipulate XML, this is your guide.
Python & XML
by Christopher A. Jones Frederick L. Shaw Jr.Python is an ideal language for manipulating XML, and this new volume gives you a solid foundation for using these two languages together. Complete with practical examples that highlight common application tasks, the book starts with the basics then quickly progresses to complex topics, like transforming XML with XSLT and querying XML with XPath. It also explores more advanced subjects, such as SOAP and distributed web services.
A Pythonic Adventure: From Python basics to a working web app
by Pavel AnniTime to take an adventure with friends! Team up with Erik and Simon to learn Python the easy way. This colorful book uses engaging questions and lively conversations to introduce computer programming to young readers one step at a time.In A Pythonic Adventure, you will learn useful Python skills like: Installing Python Working with files Creating text-based dialogs and menus Using if/then, loops, lists, dictionaries, and input/output Building web applications Making your web apps look super professional It&’s fun to learn with friends! In A Pythonic Adventure you&’ll meet Erik and Simon, two brothers who are just beginning their Python journey. Join them as they chat about the language, learn the basics, and build some cool programs. The book&’s dialogue helps young programmers understand complex concepts much more easily. It's the perfect way for young programmers (and their parents) to get started. There&’s no boring lessons or dull exercises in this adventure. You&’ll follow Erik and Simon&’s questions and mistakes, discover how to write programs with a team, and get a chance to create applications you can use in your daily life. By the time they&’re done reading, young learners will not only know how to write code, they&’ll know how to think about problems like professional developers. All code in this book runs on Mac, Windows, Linux, and Raspberry Pi. About the technology Computer programming is an adventure, full of new experiences, challenges, triumphs, and mistakes. In A Pythonic Adventure, you&’ll join brothers Erik and Simon as they learn to create their first Python program. Written especially for young readers, this book is the perfect introduction to a skill that will last a lifetime! About the book A Pythonic Adventure teaches you to code by asking questions, making errors, and trying out different solutions—just like in real life. As you go, you&’ll create a web application for a coffee shop step-by-step, from your first online menu to saving orders in a database. And this unique tutorial goes deeper than other beginner books. You&’ll learn and practice important skills like planning applications, finding bugs, and managing user expectations. What's inside Installing Python Creating text-based dialogs and menus Building web applications Making your web apps look professional About the reader For readers aged 10+. Perfect for adult beginners, too! About the author Pavel Anni is a Principal Customer Engineer at SambaNova Systems, and has also worked for Sun Microsystems, Oracle, and Red Hat. Table of Contents 1 Coffee for friends: First steps 2 Lists: What&’s on the menu? 3 Functions: Don&’t repeat yourself! 4 User errors: Everybody makes mistakes 5 Working with files: Being a shop manager 6 Main menu: Next customer! 7 Creating functions: Get the order and print it 8 Working with JSON: Save the order 9 Complete the menu: A real program 10 Learning Flask: Your first web application 11 Web form for orders: Coffee shop on the web 12 Database: We need good storage 13 Styles: Making it pretty 14 Help from AI: Improving our code 15 Next steps: Plans for the future
Pythonic Programming
by Dmitry ZinovievMake your good Python code even better by following proven and effective pythonic programming tips. Avoid logical errors that usually go undetected by Python linters and code formatters, such as frequent data look-ups in long lists, improper use of local and global variables, and mishandled user input. Discover rare language features, like rational numbers, set comprehensions, counters, and pickling, that may boost your productivity. Discover how to apply general programming patterns, including caching, in your Python code. Become a better-than-average Python programmer, and develop self-documented, maintainable, easy-to-understand programs that are fast to run and hard to break. Python is one of the most popular and rapidly growing modern programming languages. With more than 200 standard libraries and even more third-party libraries, it reaches into the software development areas as diverse as artificial intelligence, bioinformatics, natural language processing, and computer vision. Find out how to improve your understanding of the spirit of the language by using one hundred pythonic tips to make your code safer, faster, and better documented. This programming style manual is a quick reference of helpful hints and a random source of inspiration. Choose the suitable data structures for searching and sorting jobs and become aware of how a wrong choice may cause your application to be completely ineffective. Understand global and local variables, class and instance attributes, and information-hiding techniques. Create functions with flexible interfaces. Manage intermediate computation results by caching them in files and memory to improve performance and reliability. Polish your documentation skills to make your code easy for other programmers to understand. As a bonus, discover Easter eggs cleverly planted in the standard library by its developers. Polish, secure, and speed-up your Python applications, and make them easier to maintain by following pythonic programming tips. What You Need: You will need a Python interpreter (ideally, version 3.4 or above) and the standard Python library that usually comes with the interpreter.
PyTorch 1.0 Reinforcement Learning Cookbook: Over 60 Recipes To Design, Develop, And Deploy Self-learning Ai Models Using Python
by Yuxi (Hayden) LiuMachine learning engineers, data scientists and AI researchers looking for quick solutions to different problems in RL will find the book useful. Prior exposure to machine learning concepts is required, while previous experience with PyTorch will be a bonus.
PyTorch Artificial Intelligence Fundamentals: A recipe-based approach to design, build and deploy your own AI models with PyTorch 1.x
by Jibin MathewUse PyTorch to build end-to-end artificial intelligence systems using Python Key Features Build smart AI systems to handle real-world problems using PyTorch 1.x Become well-versed with concepts such as deep reinforcement learning (DRL) and genetic programming Cover PyTorch functionalities from tensor manipulation through to deploying in production Book Description Artificial Intelligence (AI) continues to grow in popularity and disrupt a wide range of domains, but it is a complex and daunting topic. In this book, you'll get to grips with building deep learning apps, and how you can use PyTorch for research and solving real-world problems. This book uses a recipe-based approach, starting with the basics of tensor manipulation, before covering Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) in PyTorch. Once you are well-versed with these basic networks, you'll build a medical image classifier using deep learning. Next, you'll use TensorBoard for visualizations. You'll also delve into Generative Adversarial Networks (GANs) and Deep Reinforcement Learning (DRL) before finally deploying your models to production at scale. You'll discover solutions to common problems faced in machine learning, deep learning, and reinforcement learning. You'll learn to implement AI tasks and tackle real-world problems in computer vision, natural language processing (NLP), and other real-world domains. By the end of this book, you'll have the foundations of the most important and widely used techniques in AI using the PyTorch framework. What you will learn Perform tensor manipulation using PyTorch Train a fully connected neural network Advance from simple neural networks to convolutional neural networks (CNNs) and recurrent neural networks (RNNs) Implement transfer learning techniques to classify medical images Get to grips with generative adversarial networks (GANs), along with their implementation Build deep reinforcement learning applications and learn how agents interact in the real environment Scale models to production using ONNX Runtime Deploy AI models and perform distributed training on large datasets Who this book is for This PyTorch book is for AI engineers who are just getting started, machine learning engineers, data scientists and deep learning enthusiasts who are looking for a guide to help them solve AI problems effectively. Working knowledge of the Python programming language and a basic understanding of machine learning are expected.
PyTorch Computer Vision Cookbook: Over 70 recipes to master the art of computer vision with deep learning and PyTorch 1.x
by Michael AvendiDiscover powerful ways to use deep learning algorithms and solve real-world computer vision problems using Python Key Features Solve the trickiest of problems in computer vision by combining the power of deep learning and neural networks Leverage PyTorch 1.x capabilities to perform image classification, object detection, and more Train and deploy enterprise-grade, deep learning models for computer vision applications Book Description Computer vision techniques play an integral role in helping developers gain a high-level understanding of digital images and videos. With this book, you'll learn how to solve the trickiest problems in computer vision (CV) using the power of deep learning algorithms, and leverage the latest features of PyTorch 1.x to perform a variety of CV tasks. Starting with a quick overview of the PyTorch library and key deep learning concepts, the book then covers common and not-so-common challenges faced while performing image recognition, image segmentation, object detection, image generation, and other tasks. Next, you'll understand how to implement these tasks using various deep learning architectures such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), long short-term memory (LSTM), and generative adversarial networks (GANs). Using a problem-solution approach, you'll learn how to solve any issue you might face while fine-tuning the performance of a model or integrating it into your application. Later, you'll get to grips with scaling your model to handle larger workloads, and implementing best practices for training models efficiently. By the end of this CV book, you'll be proficient in confidently solving many CV related problems using deep learning and PyTorch. What you will learn Develop, train and deploy deep learning algorithms using PyTorch 1.x Understand how to fine-tune and change hyperparameters to train deep learning algorithms Perform various CV tasks such as classification, detection, and segmentation Implement a neural style transfer network based on CNNs and pre-trained models Generate new images and implement adversarial attacks using GANs Implement video classification models based on RNN, LSTM, and 3D-CNN Discover best practices for training and deploying deep learning algorithms for CV applications Who this book is for Computer vision professionals, data scientists, deep learning engineers, and AI developers looking for quick solutions for various computer vision problems will find this book useful. Intermediate-level knowledge of computer vision concepts, along with Python programming experience is required.
PyTorch Deep Learning Hands-On: Apply modern AI techniques with CNNs, RNNs, GANs, reinforcement learning, and more
by Sherin Thomas Sudhanshu PassiAll the key deep learning methods built step-by-step in PyTorchKey FeaturesUnderstand the internals and principles of PyTorchImplement key deep learning methods in PyTorch: CNNs, GANs, RNNs, reinforcement learning, and moreBuild deep learning workflows and take deep learning models from prototyping to productionBook DescriptionPyTorch is a new, lightweight, and Python-first tool for deep learning. Built by Facebook to offer flexibility and speed, it has quickly become the preferred tool for deep learning experts. PyTorch helps you release deep learning models faster than ever before.PyTorch Deep Learning Hands-On shows how to implement every major deep learning architecture in PyTorch. Starting with simple neural networks, it covers PyTorch for computer vision (CNN), natural language processing (RNN), GANs, and reinforcement learning. You will also build deep learning workflows with the PyTorch framework, migrate models built in Python to highly efficient TorchScript, and deploy to production using the most sophisticated available tools.Each chapter focuses on a different area of deep learning. Chapters start with a refresher on the core principles, before sharing the code you need to implement them in PyTorch.If you want to become a deep learning expert this book is for you.What you will learnUse PyTorch to build:Simple Neural Networks – build neural networks the PyTorch way, with high-level functions, optimizers, and moreConvolutional Neural Networks – create advanced computer vision systemsRecurrent Neural Networks – work with sequential data such as natural language and audioGenerative Adversarial Networks – create new content with models including SimpleGAN and CycleGANReinforcement Learning – develop systems that can solve complex problems such as driving or game playingDeep Learning workflows – move effectively from ideation to production with proper deep learning workflow using PyTorch and its utility packagesProduction-ready models – package your models for high-performance production environmentsWho this book is forMachine learning professionals and enthusiasts who know Python and want to build efficient and powerful deep learning systems in PyTorch.
PyTorch Pocket Reference
by Joe PapaThis concise, easy-to-use reference puts one of the most popular frameworks for deep learning research and development at your fingertips. Author Joe Papa provides instant access to syntax, design patterns, and code examples to accelerate your development and reduce the time you spend searching for answers.Research scientists, machine learning engineers, and software developers will find clear, structured PyTorch code that covers every step of neural network development-from loading data to customizing training loops to model optimization and GPU/TPU acceleration. Quickly learn how to deploy your code to production using AWS, Google Cloud, or Azure and deploy your ML models to mobile and edge devices.Learn basic PyTorch syntax and design patternsCreate custom models and data transformsTrain and deploy models using a GPU and TPUTrain and test a deep learning classifierAccelerate training using optimization and distributed trainingAccess useful PyTorch libraries and the PyTorch ecosystem
PyTorch Recipes: A Problem-Solution Approach
by Pradeepta MishraGet up to speed with the deep learning concepts of Pytorch using a problem-solution approach. Starting with an introduction to PyTorch, you'll get familiarized with tensors, a type of data structure used to calculate arithmetic operations and also learn how they operate. You will then take a look at probability distributions using PyTorch and get acquainted with its concepts. Further you will dive into transformations and graph computations with PyTorch. Along the way you will take a look at common issues faced with neural network implementation and tensor differentiation, and get the best solutions for them. Moving on to algorithms; you will learn how PyTorch works with supervised and unsupervised algorithms. You will see how convolutional neural networks, deep neural networks, and recurrent neural networks work using PyTorch. In conclusion you will get acquainted with natural language processing and text processing using PyTorch.What You Will LearnMaster tensor operations for dynamic graph-based calculations using PyTorchCreate PyTorch transformations and graph computations for neural networksCarry out supervised and unsupervised learning using PyTorch Work with deep learning algorithms such as CNN and RNNBuild LSTM models in PyTorch Use PyTorch for text processing Who This Book Is ForReaders wanting to dive straight into programming PyTorch.