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Python Cookbook
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Download or read book Python Cookbook written by David Beazley and published by "O'Reilly Media, Inc.". This book was released on 2013-05-10 with total page 706 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you need help writing programs in Python 3, or want to update older Python 2 code, this book is just the ticket. Packed with practical recipes written and tested with Python 3.3, this unique cookbook is for experienced Python programmers who want to focus on modern tools and idioms. Inside, you’ll find complete recipes for more than a dozen topics, covering the core Python language as well as tasks common to a wide variety of application domains. Each recipe contains code samples you can use in your projects right away, along with a discussion about how and why the solution works. Topics include: Data Structures and Algorithms Strings and Text Numbers, Dates, and Times Iterators and Generators Files and I/O Data Encoding and Processing Functions Classes and Objects Metaprogramming Modules and Packages Network and Web Programming Concurrency Utility Scripting and System Administration Testing, Debugging, and Exceptions C Extensions
Download or read book Python Cookbook written by Alex Martelli and published by "O'Reilly Media, Inc.". This book was released on 2005-03-18 with total page 847 pages. Available in PDF, EPUB and Kindle. Book excerpt: Portable, powerful, and a breeze to use, Python is the popular open source object-oriented programming language used for both standalone programs and scripting applications. It is now being used by an increasing number of major organizations, including NASA and Google.Updated for Python 2.4, The Python Cookbook, 2nd Edition offers a wealth of useful code for all Python programmers, not just advanced practitioners. Like its predecessor, the new edition provides solutions to problems that Python programmers face everyday.It now includes over 200 recipes that range from simple tasks, such as working with dictionaries and list comprehensions, to complex tasks, such as monitoring a network and building a templating system. This revised version also includes new chapters on topics such as time, money, and metaprogramming.Here's a list of additional topics covered: Manipulating text Searching and sorting Working with files and the filesystem Object-oriented programming Dealing with threads and processes System administration Interacting with databases Creating user interfaces Network and web programming Processing XML Distributed programming Debugging and testing Another advantage of The Python Cookbook, 2nd Edition is its trio of authors--three well-known Python programming experts, who are highly visible on email lists and in newsgroups, and speak often at Python conferences.With scores of practical examples and pertinent background information, The Python Cookbook, 2nd Edition is the one source you need if you're looking to build efficient, flexible, scalable, and well-integrated systems.
Book Synopsis Machine Learning with Python Cookbook by : Chris Albon
Download or read book Machine Learning with Python Cookbook written by Chris Albon and published by "O'Reilly Media, Inc.". This book was released on 2018-03-09 with total page 305 pages. Available in PDF, EPUB and Kindle. Book excerpt: This practical guide provides nearly 200 self-contained recipes to help you solve machine learning challenges you may encounter in your daily work. If you’re comfortable with Python and its libraries, including pandas and scikit-learn, you’ll be able to address specific problems such as loading data, handling text or numerical data, model selection, and dimensionality reduction and many other topics. Each recipe includes code that you can copy and paste into a toy dataset to ensure that it actually works. From there, you can insert, combine, or adapt the code to help construct your application. Recipes also include a discussion that explains the solution and provides meaningful context. This cookbook takes you beyond theory and concepts by providing the nuts and bolts you need to construct working machine learning applications. You’ll find recipes for: Vectors, matrices, and arrays Handling numerical and categorical data, text, images, and dates and times Dimensionality reduction using feature extraction or feature selection Model evaluation and selection Linear and logical regression, trees and forests, and k-nearest neighbors Support vector machines (SVM), naïve Bayes, clustering, and neural networks Saving and loading trained models
Download or read book Violent Python written by TJ O'Connor and published by Newnes. This book was released on 2012-12-28 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: Violent Python shows you how to move from a theoretical understanding of offensive computing concepts to a practical implementation. Instead of relying on another attacker’s tools, this book will teach you to forge your own weapons using the Python programming language. This book demonstrates how to write Python scripts to automate large-scale network attacks, extract metadata, and investigate forensic artifacts. It also shows how to write code to intercept and analyze network traffic using Python, craft and spoof wireless frames to attack wireless and Bluetooth devices, and how to data-mine popular social media websites and evade modern anti-virus. Demonstrates how to write Python scripts to automate large-scale network attacks, extract metadata, and investigate forensic artifacts Write code to intercept and analyze network traffic using Python. Craft and spoof wireless frames to attack wireless and Bluetooth devices Data-mine popular social media websites and evade modern anti-virus
Book Synopsis Beyond the Basic Stuff with Python by : Al Sweigart
Download or read book Beyond the Basic Stuff with Python written by Al Sweigart and published by No Starch Press. This book was released on 2020-12-16 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: BRIDGE THE GAP BETWEEN NOVICE AND PROFESSIONAL You've completed a basic Python programming tutorial or finished Al Sweigart's bestseller, Automate the Boring Stuff with Python. What's the next step toward becoming a capable, confident software developer? Welcome to Beyond the Basic Stuff with Python. More than a mere collection of advanced syntax and masterful tips for writing clean code, you'll learn how to advance your Python programming skills by using the command line and other professional tools like code formatters, type checkers, linters, and version control. Sweigart takes you through best practices for setting up your development environment, naming variables, and improving readability, then tackles documentation, organization and performance measurement, as well as object-oriented design and the Big-O algorithm analysis commonly used in coding interviews. The skills you learn will boost your ability to program--not just in Python but in any language. You'll learn: Coding style, and how to use Python's Black auto-formatting tool for cleaner code Common sources of bugs, and how to detect them with static analyzers How to structure the files in your code projects with the Cookiecutter template tool Functional programming techniques like lambda and higher-order functions How to profile the speed of your code with Python's built-in timeit and cProfile modules The computer science behind Big-O algorithm analysis How to make your comments and docstrings informative, and how often to write them How to create classes in object-oriented programming, and why they're used to organize code Toward the end of the book you'll read a detailed source-code breakdown of two classic command-line games, the Tower of Hanoi (a logic puzzle) and Four-in-a-Row (a two-player tile-dropping game), and a breakdown of how their code follows the book's best practices. You'll test your skills by implementing the program yourself. Of course, no single book can make you a professional software developer. But Beyond the Basic Stuff with Python will get you further down that path and make you a better programmer, as you learn to write readable code that's easy to debug and perfectly Pythonic Requirements: Covers Python 3.6 and higher
Book Synopsis Python and AWS Cookbook by : Mitch Garnaat
Download or read book Python and AWS Cookbook written by Mitch Garnaat and published by "O'Reilly Media, Inc.". This book was released on 2011-10-31 with total page 75 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on Elastic Compute Cloud (EC2) and Simple Storage Service (S3) for developers writing in Python.
Book Synopsis Python for Finance Cookbook by : Eryk Lewinson
Download or read book Python for Finance Cookbook written by Eryk Lewinson and published by Packt Publishing Ltd. This book was released on 2020-01-31 with total page 426 pages. Available in PDF, EPUB and Kindle. Book excerpt: Solve common and not-so-common financial problems using Python libraries such as NumPy, SciPy, and pandas Key FeaturesUse powerful Python libraries such as pandas, NumPy, and SciPy to analyze your financial dataExplore unique recipes for financial data analysis and processing with PythonEstimate popular financial models such as CAPM and GARCH using a problem-solution approachBook Description Python is one of the most popular programming languages used in the financial industry, with a huge set of accompanying libraries. In this book, you'll cover different ways of downloading financial data and preparing it for modeling. You'll calculate popular indicators used in technical analysis, such as Bollinger Bands, MACD, RSI, and backtest automatic trading strategies. Next, you'll cover time series analysis and models, such as exponential smoothing, ARIMA, and GARCH (including multivariate specifications), before exploring the popular CAPM and the Fama-French three-factor model. You'll then discover how to optimize asset allocation and use Monte Carlo simulations for tasks such as calculating the price of American options and estimating the Value at Risk (VaR). In later chapters, you'll work through an entire data science project in the financial domain. You'll also learn how to solve the credit card fraud and default problems using advanced classifiers such as random forest, XGBoost, LightGBM, and stacked models. You'll then be able to tune the hyperparameters of the models and handle class imbalance. Finally, you'll focus on learning how to use deep learning (PyTorch) for approaching financial tasks. By the end of this book, you’ll have learned how to effectively analyze financial data using a recipe-based approach. What you will learnDownload and preprocess financial data from different sourcesBacktest the performance of automatic trading strategies in a real-world settingEstimate financial econometrics models in Python and interpret their resultsUse Monte Carlo simulations for a variety of tasks such as derivatives valuation and risk assessmentImprove the performance of financial models with the latest Python librariesApply machine learning and deep learning techniques to solve different financial problemsUnderstand the different approaches used to model financial time series dataWho this book is for This book is for financial analysts, data analysts, and Python developers who want to learn how to implement a broad range of tasks in the finance domain. Data scientists looking to devise intelligent financial strategies to perform efficient financial analysis will also find this book useful. Working knowledge of the Python programming language is mandatory to grasp the concepts covered in the book effectively.
Book Synopsis Python Business Intelligence Cookbook by : Robert Dempsey
Download or read book Python Business Intelligence Cookbook written by Robert Dempsey and published by Packt Publishing Ltd. This book was released on 2015-12-22 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leverage the computational power of Python with more than 60 recipes that arm you with the required skills to make informed business decisions About This Book Want to minimize risk and optimize profits of your business? Learn to create efficient analytical reports with ease using this highly practical, easy-to-follow guide Learn to apply Python for business intelligence tasks—preparing, exploring, analyzing, visualizing and reporting—in order to make more informed business decisions using data at hand Learn to explore and analyze business data, and build business intelligence dashboards with the help of various insightful recipes Who This Book Is For This book is intended for data analysts, managers, and executives with a basic knowledge of Python, who now want to use Python for their BI tasks. If you have a good knowledge and understanding of BI applications and have a “working” system in place, this book will enhance your toolbox. What You Will Learn Install Anaconda, MongoDB, and everything you need to get started with your data analysis Prepare data for analysis by querying cleaning and standardizing data Explore your data by creating a Pandas data frame from MongoDB Gain powerful insights, both statistical and predictive, to make informed business decisions Visualize your data by building dashboards and generating reports Create a complete data processing and business intelligence system In Detail The amount of data produced by businesses and devices is going nowhere but up. In this scenario, the major advantage of Python is that it's a general-purpose language and gives you a lot of flexibility in data structures. Python is an excellent tool for more specialized analysis tasks, and is powered with related libraries to process data streams, to visualize datasets, and to carry out scientific calculations. Using Python for business intelligence (BI) can help you solve tricky problems in one go. Rather than spending day after day scouring Internet forums for “how-to” information, here you'll find more than 60 recipes that take you through the entire process of creating actionable intelligence from your raw data, no matter what shape or form it's in. Within the first 30 minutes of opening this book, you'll learn how to use the latest in Python and NoSQL databases to glean insights from data just waiting to be exploited. We'll begin with a quick-fire introduction to Python for BI and show you what problems Python solves. From there, we move on to working with a predefined data set to extract data as per business requirements, using the Pandas library and MongoDB as our storage engine. Next, we will analyze data and perform transformations for BI with Python. Through this, you will gather insightful data that will help you make informed decisions for your business. The final part of the book will show you the most important task of BI—visualizing data by building stunning dashboards using Matplotlib, PyTables, and iPython Notebook. Style and approach This is a step-by-step guide to help you prepare, explore, analyze and report data, written in a conversational tone to make it easy to grasp. Whether you're new to BI or are looking for a better way to work, you'll find the knowledge and skills here to get your job done efficiently.
Book Synopsis Modern Python Cookbook by : Steven F. Lott
Download or read book Modern Python Cookbook written by Steven F. Lott and published by Packt Publishing Ltd. This book was released on 2020-07-31 with total page 823 pages. Available in PDF, EPUB and Kindle. Book excerpt: Python is a great language that can power your applications with great speed, safety, and scalability. We cover 133 Python recipes. This book simplifies Python for everybody, right from beginners to experts. All recipes take a problem-solution approach to resolve issues commonly faced by Python programmers across the globe.
Book Synopsis Modern Python Cookbook by : Steven F. Lott
Download or read book Modern Python Cookbook written by Steven F. Lott and published by Packt Publishing Ltd. This book was released on 2016-11-30 with total page 686 pages. Available in PDF, EPUB and Kindle. Book excerpt: The latest in modern Python recipes for the busy modern programmer About This Book Develop succinct, expressive programs in Python Learn the best practices and common idioms through carefully explained and structured recipes Discover new ways to apply Python for the new age of development Who This Book Is For The book is for web developers, programmers, enterprise programmers, engineers, big data scientist, and so on. If you are a beginner, Python Cookbook will get you started. If you are experienced, it will expand your knowledge base. A basic knowledge of programming would help. What You Will Learn See the intricate details of the Python syntax and how to use it to your advantage Improve your code readability through functions in Python Manipulate data effectively using built-in data structures Get acquainted with advanced programming techniques in Python Equip yourself with functional and statistical programming features Write proper tests to be sure a program works as advertised Integrate application software using Python In Detail Python is the preferred choice of developers, engineers, data scientists, and hobbyists everywhere. It is a great scripting language that can power your applications and provide great speed, safety, and scalability. By exposing Python as a series of simple recipes, you can gain insight into specific language features in a particular context. Having a tangible context helps make the language or standard library feature easier to understand. This book comes with over 100 recipes on the latest version of Python. The recipes will benefit everyone ranging from beginner to an expert. The book is broken down into 13 chapters that build from simple language concepts to more complex applications of the language. The recipes will touch upon all the necessary Python concepts related to data structures, OOP, functional programming, as well as statistical programming. You will get acquainted with the nuances of Python syntax and how to effectively use the advantages that it offers. You will end the book equipped with the knowledge of testing, web services, and configuration and application integration tips and tricks. The recipes take a problem-solution approach to resolve issues commonly faced by Python programmers across the globe. You will be armed with the knowledge of creating applications with flexible logging, powerful configuration, and command-line options, automated unit tests, and good documentation. Style and approach This book takes a recipe-based approach, where each recipe addresses specific problems and issues. The recipes provide discussions and insights and an explanation of the problems.
Book Synopsis Artificial Intelligence with Python Cookbook by : Ben Auffarth
Download or read book Artificial Intelligence with Python Cookbook written by Ben Auffarth and published by Packt Publishing Ltd. This book was released on 2020-10-30 with total page 459 pages. Available in PDF, EPUB and Kindle. Book excerpt: Work through practical recipes to learn how to solve complex machine learning and deep learning problems using Python Key FeaturesGet up and running with artificial intelligence in no time using hands-on problem-solving recipesExplore popular Python libraries and tools to build AI solutions for images, text, sounds, and imagesImplement NLP, reinforcement learning, deep learning, GANs, Monte-Carlo tree search, and much moreBook Description Artificial intelligence (AI) plays an integral role in automating problem-solving. This involves predicting and classifying data and training agents to execute tasks successfully. This book will teach you how to solve complex problems with the help of independent and insightful recipes ranging from the essentials to advanced methods that have just come out of research. Artificial Intelligence with Python Cookbook starts by showing you how to set up your Python environment and taking you through the fundamentals of data exploration. Moving ahead, you’ll be able to implement heuristic search techniques and genetic algorithms. In addition to this, you'll apply probabilistic models, constraint optimization, and reinforcement learning. As you advance through the book, you'll build deep learning models for text, images, video, and audio, and then delve into algorithmic bias, style transfer, music generation, and AI use cases in the healthcare and insurance industries. Throughout the book, you’ll learn about a variety of tools for problem-solving and gain the knowledge needed to effectively approach complex problems. By the end of this book on AI, you will have the skills you need to write AI and machine learning algorithms, test them, and deploy them for production. What you will learnImplement data preprocessing steps and optimize model hyperparametersDelve into representational learning with adversarial autoencodersUse active learning, recommenders, knowledge embedding, and SAT solversGet to grips with probabilistic modeling with TensorFlow probabilityRun object detection, text-to-speech conversion, and text and music generationApply swarm algorithms, multi-agent systems, and graph networksGo from proof of concept to production by deploying models as microservicesUnderstand how to use modern AI in practiceWho this book is for This AI machine learning book is for Python developers, data scientists, machine learning engineers, and deep learning practitioners who want to learn how to build artificial intelligence solutions with easy-to-follow recipes. You’ll also find this book useful if you’re looking for state-of-the-art solutions to perform different machine learning tasks in various use cases. Basic working knowledge of the Python programming language and machine learning concepts will help you to work with code effectively in this book.
Book Synopsis Python Feature Engineering Cookbook by : Soledad Galli
Download or read book Python Feature Engineering Cookbook written by Soledad Galli and published by Packt Publishing Ltd. This book was released on 2020-01-22 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: Extract accurate information from data to train and improve machine learning models using NumPy, SciPy, pandas, and scikit-learn libraries Key FeaturesDiscover solutions for feature generation, feature extraction, and feature selectionUncover the end-to-end feature engineering process across continuous, discrete, and unstructured datasetsImplement modern feature extraction techniques using Python's pandas, scikit-learn, SciPy and NumPy librariesBook Description Feature engineering is invaluable for developing and enriching your machine learning models. In this cookbook, you will work with the best tools to streamline your feature engineering pipelines and techniques and simplify and improve the quality of your code. Using Python libraries such as pandas, scikit-learn, Featuretools, and Feature-engine, you’ll learn how to work with both continuous and discrete datasets and be able to transform features from unstructured datasets. You will develop the skills necessary to select the best features as well as the most suitable extraction techniques. This book will cover Python recipes that will help you automate feature engineering to simplify complex processes. You’ll also get to grips with different feature engineering strategies, such as the box-cox transform, power transform, and log transform across machine learning, reinforcement learning, and natural language processing (NLP) domains. By the end of this book, you’ll have discovered tips and practical solutions to all of your feature engineering problems. What you will learnSimplify your feature engineering pipelines with powerful Python packagesGet to grips with imputing missing valuesEncode categorical variables with a wide set of techniquesExtract insights from text quickly and effortlesslyDevelop features from transactional data and time series dataDerive new features by combining existing variablesUnderstand how to transform, discretize, and scale your variablesCreate informative variables from date and timeWho this book is for This book is for machine learning professionals, AI engineers, data scientists, and NLP and reinforcement learning engineers who want to optimize and enrich their machine learning models with the best features. Knowledge of machine learning and Python coding will assist you with understanding the concepts covered in this book.
Book Synopsis Modern Python Standard Library Cookbook by : Alessandro Molina
Download or read book Modern Python Standard Library Cookbook written by Alessandro Molina and published by Packt Publishing Ltd. This book was released on 2018-08-31 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build optimized applications in Python by smartly implementing the standard library Key Features Strategic recipes for effective application development in Python Techniques to create GUIs and implement security through cryptography Best practices for developing readily scalable, production-ready applications Book Description The Python 3 Standard Library is a vast array of modules that you can use for developing various kinds of applications. It contains an exhaustive list of libraries, and this book will help you choose the best one to address specific programming problems in Python. The Modern Python Standard Library Cookbook begins with recipes on containers and data structures and guides you in performing effective text management in Python. You will find Python recipes for command-line operations, networking, filesystems and directories, and concurrent execution. You will learn about Python security essentials in Python and get to grips with various development tools for debugging, benchmarking, inspection, error reporting, and tracing. The book includes recipes to help you create graphical user interfaces for your application. You will learn to work with multimedia components and perform mathematical operations on date and time. The recipes will also show you how to deploy different searching and sorting algorithms on your data. By the end of the book, you will have acquired the skills needed to write clean code in Python and develop applications that meet your needs. What you will learn Store multiple values per key in associative containers Create interactive character-based user interfaces Work with native time and display data for your time zone Read/write SGML family languages, both as a SAX and DOM parser to meet file sizes and other requirements Group equivalent items using itertools and sorted features together Use partials to create unary functions out of multi-argument functions Implement hashing algorithms to store passwords in a safe way Who this book is for If you are a developer who wants to write highly responsive, manageable, scalable, and resilient code in Python, this book is for you. Prior programming knowledge in Python will help you make the most out of the book.
Book Synopsis Python Parallel Programming Cookbook by : Giancarlo Zaccone
Download or read book Python Parallel Programming Cookbook written by Giancarlo Zaccone and published by Packt Publishing Ltd. This book was released on 2015-08-26 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master efficient parallel programming to build powerful applications using Python About This Book Design and implement efficient parallel software Master new programming techniques to address and solve complex programming problems Explore the world of parallel programming with this book, which is a go-to resource for different kinds of parallel computing tasks in Python, using examples and topics covered in great depth Who This Book Is For Python Parallel Programming Cookbook is intended for software developers who are well versed with Python and want to use parallel programming techniques to write powerful and efficient code. This book will help you master the basics and the advanced of parallel computing. What You Will Learn Synchronize multiple threads and processes to manage parallel tasks Implement message passing communication between processes to build parallel applications Program your own GPU cards to address complex problems Manage computing entities to execute distributed computational tasks Write efficient programs by adopting the event-driven programming model Explore the cloud technology with DJango and Google App Engine Apply parallel programming techniques that can lead to performance improvements In Detail Parallel programming techniques are required for a developer to get the best use of all the computational resources available today and to build efficient software systems. From multi-core to GPU systems up to the distributed architectures, the high computation of programs throughout requires the use of programming tools and software libraries. Because of this, it is becoming increasingly important to know what the parallel programming techniques are. Python is commonly used as even non-experts can easily deal with its concepts. This book will teach you parallel programming techniques using examples in Python and will help you explore the many ways in which you can write code that allows more than one process to happen at once. Starting with introducing you to the world of parallel computing, it moves on to cover the fundamentals in Python. This is followed by exploring the thread-based parallelism model using the Python threading module by synchronizing threads and using locks, mutex, semaphores queues, GIL, and the thread pool. Next you will be taught about process-based parallelism where you will synchronize processes using message passing along with learning about the performance of MPI Python Modules. You will then go on to learn the asynchronous parallel programming model using the Python asyncio module along with handling exceptions. Moving on, you will discover distributed computing with Python, and learn how to install a broker, use Celery Python Module, and create a worker. You will also understand the StarCluster framework, Pycsp, Scoop, and Disco modules in Python. Further on, you will learn GPU programming with Python using the PyCUDA module along with evaluating performance limitations. Next you will get acquainted with the cloud computing concepts in Python, using Google App Engine (GAE), and building your first application with GAE. Lastly, you will learn about grid computing concepts in Python and using PyGlobus toolkit, GFTP and GASS COPY to transfer files, and service monitoring in PyGlobus. Style and approach A step-by-step guide to parallel programming using Python, with recipes accompanied by one or more programming examples. It is a practically oriented book and has all the necessary underlying parallel computing concepts.
Book Synopsis Maya Programming with Python Cookbook by : Adrian Herbez
Download or read book Maya Programming with Python Cookbook written by Adrian Herbez and published by Packt Publishing Ltd. This book was released on 2016-07-29 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master complex workflows and conquer the world with Python and Maya About This Book Improve your modelling skills and reduce your scripting problems using Python in Maya Learn to communicate with web applications using Python for easier team development A quick and practical answer to every problem you can have whilst scripting in Maya with Python Who This Book Is For This book is for Python developers who have just started scripting with Maya. What You Will Learn Find out how to use Python scripting to automate tedious tasks Create functional user interfaces to make scripts easy to share with others Add new functionality to Maya via the power of scripting Import and export arbitrary data into and out of Maya Improve your workflow, and that of your team Create custom create custom controls to make rigs that are easy to work with Implement a system to render 3D assets for isometric games Use script jobs to trigger actions automatically in response to user interaction Open a command port to allow other applications to communicate with Maya In Detail Maya is a 3D graphics and animation software, used to develop interactive 3D applications and games with stupendous visual effects. The Maya Programming with Python Cookbook is all about creating fast, powerful automation systems with minimum coding using Maya Python. With the help of insightful and essential recipes, this book will help you improve your modelling skills. Expand your development options and overcome scripting problems encountered whilst developing code in Maya. Right from the beginning, get solutions to complex development concerns faced when implementing as parts of build. Style and approach This book is comprised of a set of practical recipes, grouped under specific topics, which can be referred to independently or in sequence. These recipes provide quick solutions to common problems, and cover most of the real-world scenarios that developers are likely to face when working with Maya.
Book Synopsis An Object-Oriented Python Cookbook in Quantum Information Theory and Quantum Computing by : M.S. Ramkarthik
Download or read book An Object-Oriented Python Cookbook in Quantum Information Theory and Quantum Computing written by M.S. Ramkarthik and published by CRC Press. This book was released on 2022-09-30 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: This first-of-a-kind textbook provides computational tools in state-of-the-art OOPs Python that are fundamental to quantum information, quantum computing, linear algebra and one-dimensional spin half condensed matter systems. Over 104 subroutines are included, and the codes are aided by mathematical comments to enhance clarity. Suitable for beginner and advanced readers alike, students and researchers will find this textbook to be a helpful guide and a compendium which they can readily use. Features Includes over 104 codes in OOPs Python, all of which can be used either as a standalone program or integrated with any other main program without any issues. Every parameter in the input, output and execution has been provided while keeping both beginner and advanced users in mind. The output of every program is explained thoroughly with detailed examples. Detailed mathematical commenting is done alongside the code which enhances clarity about the flow and working of the code.
Book Synopsis Python GUI Programming Cookbook by : Burkhard A. Meier
Download or read book Python GUI Programming Cookbook written by Burkhard A. Meier and published by Packt Publishing Ltd. This book was released on 2015-12-01 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over 80 object-oriented recipes to help you create mind-blowing GUIs in Python About This Book Use object-oriented programming to develop amazing GUIs in Python Create a working GUI project as a central resource for developing your Python GUIs Packed with easy-to-follow recipes to help you develop code using the latest released version of Python Who This Book Is For If you are a Python programmer with intermediate level knowledge of GUI programming and want to learn how to create beautiful, effective, and responsive GUIs using the freely available Python GUI frameworks, this book is for you. What You Will Learn Create amazing GUIs with Python's built-in Tkinter module Customize the GUIs by using layout managers to arrange the GUI widgets Advance to an object-oriented programming style using Python Develop beautiful charts using the free Matplotlib Python module Use threading in a networked environment to make the GUIs responsive Discover ways to connect the GUIs to a database Understand how unit tests can be created and internationalize the GUI Extend the GUIs with free Python frameworks using best practices In Detail Python is a multi-domain, interpreted programming language. It is a widely used general-purpose, high-level programming language. It is often used as a scripting language because of its forgiving syntax and compatibility with a wide variety of different eco-systems. Its flexible syntax enables developers to write short scripts while at the same time, they can use object-oriented concepts to develop very large projects. Python GUI Programming Cookbook follows a task-based approach to help you create beautiful and very effective GUIs with the least amount of code necessary. This book uses the simplest programming style, using the fewest lines of code to create a GUI in Python, and then advances to using object-oriented programming in later chapters. If you are new to object-oriented programming (OOP), this book will teach you how to take advantage of the OOP coding style in the context of creating GUIs written in Python. Throughout the book, you will develop an entire GUI application, building recipe upon recipe, connecting the GUI to a database. In the later chapters, you will explore additional Python GUI frameworks, using best practices. You will also learn how to use threading to ensure your GUI doesn't go unresponsive. By the end of the book, you will be an expert in Python GUI programming to develop a common set of GUI applications. Style and approach Every recipe in this programming cookbook solves a problem you might encounter in your programming career. At the same time, most of the recipes build on each other to create an entire, real-life GUI application.
