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See below for a selection of the latest books from Programming & scripting languages: general category. Presented with a red border are the Programming & scripting languages: general books that have been lovingly read and reviewed by the experts at Lovereading. With expert reading recommendations made by people with a passion for books and some unique features Lovereading will help you find great Programming & scripting languages: general books and those from many more genres to read that will keep you inspired and entertained. And it's all free!
Python Workout presents 50 exercises designed to deepen the reader's skill with Python. Readers will not only tackle exercises using built-in data structures, but also more advanced techniques, such as functional programming, object-oriented programming, iterators, and generators. With each engaging challenge, readers will practice a new skill and learn how to apply it to everyday coding tasks. Key Features 50 hands-on exercises and solutions Basic Python sequence types Python dictionaries and sets Functional programming in Python Creating your own classes Working with Python objects Generator functions Intended for readers with basic Python skills. About the technology Python is a versatile, elegant, general purpose programming language. Essential for data analysis, web development, artificial intelligence, games, desktop apps, and more, Python skills are a hot commodity. Reuven M. Lerner, an independent consultant for more than two decades, teaches Python, data science, and Git to companies around the world. His Better developers newsletter and blog are read by thousands of Python developers each week. Reuven has written a monthly column, At the Forge, for Linux Journal since 1996 and is a panellist on the weekly Freelancers Show podcast. Reuven lives with his wife and three children in Modi'in, Israel, and can be reached at https://lerner.co.il/ or on Twitter at @reuvenmlerner.
This book builds on basic Python tutorials to explain various Python language features that aren't routinely covered: from reusable console scripts that play double duty as micro-services by leveraging entry points, to using asyncio efficiently to collate data from a large number of sources. Along the way, it covers type-hint based linting, low-overhead testing and other automated quality checking to demonstrate a robust real-world development process. Some powerful aspects of Python are often documented with contrived examples that explain the feature as a standalone example only. By following the design and build of a real-world application example from prototype to production quality you'll see not only how the various pieces of functionality work but how they integrate as part of the larger system design process. In addition, you'll benefit from the kind of useful asides and library recommendations that are a staple of conference Q&A sessions at Python conferences as well as discussions of modern Python best practice and techniques to better produce clear code that is easily maintainable. Advanced Python Development is intended for developers who can already write simple programs in Python and want to understand when it's appropriate to use new and advanced language features and to do so in a confident manner. It is especially of use to developers looking to progress to a more senior level and to very experienced developers who have thus far used older versions of Python. What You'll Learn Understand asynchronous programming Examine developing plugin architectures Work with type annotations Review testing techniques Explore packaging and dependency management Who This Book Is For Developers at the mid to senior level who already have Python experience.
This easy-to-use, classroom-tested textbook covers the C programming language for computer science and IT students. Designed for a compulsory fundamental course, it presents the theory and principles of C. More than 500 exercises and examples of progressive difficulty aid students in understanding all the aspects and peculiarities of the C language. The exercises test students on various levels of programming and the examples enhance their concrete understanding of programming know-how. Instructor's manual and PowerPoint slides are available upon qualifying course adoption
Develop standalone Django apps to serve as the reusable building blocks for larger Django projects. This book explores best practices for publishing these apps, with special considerations for testing Django apps, and strategies for extracting existing functionality into a separate package. This jumpstart reference is divided into four distinct and sequential sections, all containing short, engaging chapters that can be read in a modular fashion, depending on your level of experience. The first section covers the structure and scope of standalone Django apps. The second section digs into questions about pulling code out of existing projects and into new standalone apps for reuse. The third section details additional, advanced technical best practices toward making standalone apps as broadly useful as possible. The fourth and final section covers strategies for managing a published Django app. Django Standalone Apps is the perfect resource for developers who have at least some prior experience working with Django web applications and want to simplify their deployments and share their knowledge as open source packages. What You'll Learn Scope a standalone Django app project for optimum usefulness Extract code from existing projects to reuse Test a standalone app outside of your Django project Reuse your own code for increased delivery cadence and code quality Review best practices for maintaining a Django app package Who This Book Is For Professional developers who work with Django. Deep expertise is not required or expected, but readers should have working familiarity with Django.
The job of the constraint programmer is to use mathematical constraints to model real world constraints and objects. In this book, Kim Marriott and Peter Stuckey provide the first comprehensive introduction to the discipline of constraint programming and, in particular, constraint logic programming. The book covers the necessary background material from artificial intelligence, logic programming, operations research, and mathematical programming. Topics discussed range from constraint-solving techniques to programming methodologies for constraint programming languages. Because there is not yet a universally used syntax for constraint logic programming languages, the authors present the programs in a way that is independent of any existing programming language. Practical exercises cover how to use the book with a number of existing constraint languages.
Learn GUI application development from the ground up, taking a practical approach by building simple projects that teach the fundamentals of using PyQt. Each chapter gradually moves on to teach more advanced and diverse concepts to aid you in designing interesting applications using the latest version of PyQt. You'll start by reviewing the beginning steps of GUI development from, using different projects in every chapter to teach new widgets or concepts that will help you to build better UIs. As you follow along, you will construct more elaborate GUIs, covering topics that include storing data using the clipboard, graphics and animation, support for SQL databases, and multithreading applications. Using this knowledge, you'll be able to build a photo editor, games, a text editor, a working web browser and an assortment of other GUIs. Beginning PyQt will guide you through the process of creating UIs to help you bring your own ideas to life. Learn what is necessary to begin making your own applications and more with PyQt! What You'll Learn Create your own cross-platform GUIs with PyQt and Python Use PyQt's many widgets and apply them to building real applications Build larger applications and break the steps into smaller parts for deeper understanding Work with complex applications in PyQt, from animation to databases and more Who This Book Is For Individuals who already have a fundamental understanding of the Python programming language and are looking to either expand their skills in Python or have a project where they need to create a UI, but may have no prior experience or no idea how to begin.
Master the practical aspects of implementing deep learning solutions with PyTorch, using a hands-on approach to understanding both theory and practice. This new edition will prepare you for applying deep learning to real world problems with a sound theoretical foundation and practical know-how with PyTorch, a platform developed by Facebook's Artificial Intelligence Research Group. You'll start with a perspective on how and why deep learning with PyTorch has emerged as an path-breaking framework with a set of tools and techniques to solve real-world problems. Next, the book will ground you with the mathematical fundamentals of linear algebra, vector calculus, probability and optimization. Having established this foundation, you'll move on to key components and functionality of PyTorch including layers, loss functions and optimization algorithms. You'll also gain an understanding of Graphical Processing Unit (GPU) based computation, which is essential for training deep learning models. All the key architectures in deep learning are covered, including feedforward networks, convolution neural networks, recurrent neural networks, long short-term memory networks, autoencoders and generative adversarial networks. Backed by a number of tricks of the trade for training and optimizing deep learning models, this edition of Deep Learning with Python explains the best practices in taking these models to production with PyTorch. What You'll Learn Review machine learning fundamentals such as overfitting, underfitting, and regularization. Understand deep learning fundamentals such as feed-forward networks, convolution neural networks, recurrent neural networks, automatic differentiation, and stochastic gradient descent. Apply in-depth linear algebra with PyTorch Explore PyTorch fundamentals and its building blocks Work with tuning and optimizing models Who This Book Is For Beginners with a working knowledge of Python who want to understand Deep Learning in a practical, hands-on manner.
William Bo Rothwell's Advanced Perl Programming continues where his previous book left off, more or less, as it guides you through advanced techniques of the Perl programming language starting with command-line options, references, and arrays and hashes from advanced data types. Next, you'll learn about typeglobs for symbolic entries. Additionally, you'll see advanced subroutine handling, then packages and namespaces. Furthermore, you'll build advanced modules and install CPAN modules. Unlike Java and C++, modules have been around in Perl for a long time now. Along the way, you'll learn and use POD mark up language for Perl documentation. Moreover, you'll get a survey of the many advanced features and data structures of the current Perl programming language. You'll also get a survey of the new features of the latest Perl 5.x release. After reading and using this book, you'll have the tools, techniques, and source code to be an expert Perl programmer. What You Will Learn Carry out command-line parsing and extract scripts Create references; return values from a reference; work with the ref Function and strict refs Work with advanced Perl data types using arrays, hashes, and hash of hashes Use Typeglobs for symbol table entries Build modules and install CPAN modules Write documentation for Perl using POD Work with the newest features in Perl, including the smartmatch operator, yada yada, automated regex modifiers, the CORE namespace and more Who This Book Is For Those with experience with Perl or who have read Rothwell's prior books, Beginning Perl Programming and Pro Perl Programming.
Cover classical algorithms commonly used as artificial intelligence techniques and program agile artificial intelligence applications using Pharo. This book takes a practical approach by presenting the implementation details to illustrate the numerous concepts it explains. Along the way, you'll learn neural net fundamentals to set you up for practical examples such as the traveling salesman problem and cover genetic algorithms including a fun zoomorphic creature example. Furthermore, Practical Agile AI with Pharo finishes with a data classification application and two game applications including a Pong-like game and a Flappy Bird-like game. This book is informative and fun, giving you source code to play along with. You'll be able to take this source code and apply it to your own projects. What You Will Learn Use neurons, neural networks, learning theory, and more Work with genetic algorithms Incorporate neural network principles when working towards neuroevolution Include neural network fundamentals when building three Pharo-based applications Who This Book Is For Coders and data scientists who are experienced programmers and have at least some prior experience with AI or deep learning. They may be new to Pharo programming, but some prior experience with it would be helpful.
Understand and implement big data analysis solutions in pandas with an emphasis on performance. This book strengthens your intuition for working with pandas, the Python data analysis library, by exploring its underlying implementation and data structures. Thinking in Pandas introduces the topic of big data and demonstrates concepts by looking at exciting and impactful projects that pandas helped to solve. From there, you will learn to assess your own projects by size and type to see if pandas is the appropriate library for your needs. Author Hannah Stepanek explains how to load and normalize data in pandas efficiently, and reviews some of the most commonly used loaders and several of their most powerful options. You will then learn how to access and transform data efficiently, what methods to avoid, and when to employ more advanced performance techniques. You will also go over basic data access and munging in pandas and the intuitive dictionary syntax. Choosing the right DataFrame format, working with multi-level DataFrames, and how pandas might be improved upon in the future are also covered. By the end of the book, you will have a solid understanding of how the pandas library works under the hood. Get ready to make confident decisions in your own projects by utilizing pandas-the right way. What You Will Learn Understand the underlying data structure of pandas and why it performs the way it does under certain circumstances Discover how to use pandas to extract, transform, and load data correctly with an emphasis on performance Choose the right DataFrame so that the data analysis is simple and efficient. Improve performance of pandas operations with other Python libraries Who This Book Is ForSoftware engineers with basic programming skills in Python keen on using pandas for a big data analysis project. Python software developers interested in big data.