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Python and HDF5: Unlocking Scientific Data
by Andrew ColletteGain hands-on experience with HDF5 for storing scientific data in Python. This practical guide quickly gets you up to speed on the details, best practices, and pitfalls of using HDF5 to archive and share numerical datasets ranging in size from gigabytes to terabytes.Through real-world examples and practical exercises, you’ll explore topics such as scientific datasets, hierarchically organized groups, user-defined metadata, and interoperable files. Examples are applicable for users of both Python 2 and Python 3. If you’re familiar with the basics of Python data analysis, this is an ideal introduction to HDF5.Get set up with HDF5 tools and create your first HDF5 fileWork with datasets by learning the HDF5 Dataset objectUnderstand advanced features like dataset chunking and compressionLearn how to work with HDF5’s hierarchical structure, using groupsCreate self-describing files by adding metadata with HDF5 attributesTake advantage of HDF5’s type system to create interoperable filesExpress relationships among data with references, named types, and dimension scalesDiscover how Python mechanisms for writing parallel code interact with HDF5
Python and R for the Modern Data Scientist
by Rick J. Scavetta Boyan AngelovSuccess in data science depends on the flexible and appropriate use of tools. That includes Python and R, two of the foundational programming languages in the field. This book guides data scientists from the Python and R communities along the path to becoming bilingual. By recognizing the strengths of both languages, you'll discover new ways to accomplish data science tasks and expand your skill set.Authors Rick Scavetta and Boyan Angelov explain the parallel structures of these languages and highlight where each one excels, whether it's their linguistic features or the powers of their open source ecosystems. You'll learn how to use Python and R together in real-world settings and broaden your job opportunities as a bilingual data scientist.Learn Python and R from the perspective of your current languageUnderstand the strengths and weaknesses of each languageIdentify use cases where one language is better suited than the otherUnderstand the modern open source ecosystem available for both, including packages, frameworks, and workflowsLearn how to integrate R and Python in a single workflowFollow a case study that demonstrates ways to use these languages together
Python API Development Fundamentals: Develop a full-stack web application with Python and Flask
by Jack Chan Ray Chung Jack HuangLearn all that's needed to build a fully functional web application from scratch. Key Features Delve deep into the principle behind RESTful API Learn how to build a scalable web application with the RESTful API architecture and Flask framework Know what are the exact tools and methodology to test your applications and how to use them Book Description Python is a flexible language that can be used for much more than just script development. By knowing the Python RESTful APIs work, you can build a powerful backend for web applications and mobile applications using Python. You'll take your first steps by building a simple API and learning how the frontend web interface can communicate with the backend. You'll also learn how to serialize and deserialize objects using the marshmallow library. Then, you'll learn how to authenticate and authorize users using Flask-JWT. You'll also learn how to enhance your APIs by adding useful features, such as email, image upload, searching, and pagination. You'll wrap up the whole book by deploying your APIs to the cloud. By the end of this book, you'll have the confidence and skill to leverage the power of RESTful APIs and Python to build efficient web applications. What you will learn Understand the concept of a RESTful API Build a RESTful API using Flask and the Flask-Restful extension Manipulate a database using Flask-SQLAlchemy and Flask-Migrate Send out plaintext and HTML format emails using the Mailgun API Implement a pagination function using Flask-SQLAlchemy Use caching to improve API performance and efficiently obtain the latest information Deploy an application to Heroku and test it using Postman Who this book is for This book is ideal for aspiring software developers who have a basic-to-intermediate knowledge of Python programming and who want to develop web applications using Python. Knowledge of how web applications work will be beneficial but is not essential.
The Python Apprentice
by Austin Bingham Robert SmallshireLearn the Python skills and culture you need to become a productive member of any Python project. About This Book • Taking a practical approach to studying Python • A clear appreciation of the sequence-oriented parts of Python • Emphasis on the way in which Python code is structured • Learn how to produce bug-free code by using testing tools Who This Book Is For The Python Apprentice is for anyone who wants to start building, creating and contributing towards a Python project. No previous knowledge of Python is required, although at least some familiarity with programming in another language is helpful. What You Will Learn • Learn the language of Python itself • Get a start on the Python standard library • Learn how to integrate 3rd party libraries • Develop libraries on your own • Become familiar with the basics of Python testing In Detail Experienced programmers want to know how to enhance their craft and we want to help them start as apprentices with Python. We know that before mastering Python you need to learn the culture and the tools to become a productive member of any Python project. Our goal with this book is to give you a practical and thorough introduction to Python programming, providing you with the insight and technical craftsmanship you need to be a productive member of any Python project. Python is a big language, and it's not our intention with this book to cover everything there is to know. We just want to make sure that you, as the developer, know the tools, basic idioms and of course the ins and outs of the language, the standard library and other modules to be able to jump into most projects. Style and approach We introduce topics gently and then revisit them on multiple occasions to add the depth required to support your progression as a Python developer. We've worked hard to structure the syllabus to avoid forward references. On only a few occasions do we require you to accept techniques on trust, before explaining them later; where we do, it's to deliberately establish good habits.
Python Architecture Patterns: Master API design, event-driven structures, and package management in Python
by Jaime BueltaMake the best of your test suites by using cutting-edge software architecture patterns in PythonKey FeaturesLearn how to create scalable and maintainable applicationsBuild a web system for micro messaging using concepts in the bookUse profiling to find bottlenecks and improve the speed of the systemBook DescriptionDeveloping large-scale systems that continuously grow in scale and complexity requires a thorough understanding of how software projects should be implemented. Software developers, architects, and technical management teams rely on high-level software design patterns such as microservices architecture, event-driven architecture, and the strategic patterns prescribed by domain-driven design (DDD) to make their work easier. This book covers these proven architecture design patterns with a forward-looking approach to help Python developers manage application complexity—and get the most value out of their test suites. Starting with the initial stages of design, you will learn about the main blocks and mental flow to use at the start of a project. The book covers various architectural patterns like microservices, web services, and event-driven structures and how to choose the one best suited to your project. Establishing a foundation of required concepts, you will progress into development, debugging, and testing to produce high-quality code that is ready for deployment. You will learn about ongoing operations on how to continue the task after the system is deployed to end users, as the software development lifecycle is never finished. By the end of this Python book, you will have developed "architectural thinking": a different way of approaching software design, including making changes to ongoing systems.What you will learnThink like an architect, analyzing software architecture patternsExplore API design, data storage, and data representation methodsInvestigate the nuances of common architectural structuresUtilize and interoperate elements of patterns such as microservicesImplement test-driven development to perform quality code testingRecognize chunks of code that can be restructured as packagesMaintain backward compatibility and deploy iterative changesWho this book is forThis book will help software developers and architects understand the structure of large complex systems and adopt architectural patterns that are scalable. Examples in the book are implemented in Python so a fair grasp of basic Python concepts is expected. Proficiency in any programming languages such as Java or JavaScript is sufficient.
Python Arithmetic: The Informational Nature of Numbers (Studies in Big Data #153)
by Vincenzo MancaThe book is a gentle introduction to Python using arithmetic, and vice versa, with a historical perspective encompassing programming languages within the wider process of development of mathematical notation. The revisitation of typical algorithms that are the core of elementary mathematical knowledge helps to grasp their essence and to clarify some assumptions that are often taken for granted but are very profound and of a very general nature. The first mathematician to define a systematic system for generating numbers was Archimedes of Syracuse in the third century B.C. The Archimedean system, which was defined in a book with the Latin title Arenarius, was not intended to define all numbers, but only very large numbers [13, 22, 23]. However, it can be considered the first system with the three main characteristics of a counting system that have the most important properties for complete arithmetic adequacy: creativity, infinity, and recursion. Creativity means that each numeral is new for numerals that precede it; infinity means that after any numeral there is always another numeral; recursion means that after an initial sequence of numerals coinciding with the digits of the system, digits repeat regularly in all subsequent numerals. Since the numerals are finite expressions of digits, their lengths increase along their generation. In the next chapter, Python is briefly introduced by linking this language to standard mathematical notation, which took its current form throughout a long process that extends from the introduction of decimal numerals to the eighteenth century, particularly within Euler’s notational and conceptual framework. The third chapter is devoted to counting algorithms, showing that something that is usually taken for granted has intriguing aspects that deserve a very subtle analysis: the authors will show that the Python representation of counting algorithms is very informative and demonstrates the informational nature of numbers.
Python Artificial Intelligence Projects: 9 real-world AI projects leveraging machine learning and deep learning with TensorFlow and Keras
by Santanu PattanayakThis book is intended for data scientists, machine learning professionals, and deep learning practitioners who are ready to extend their knowledge and possibilities in AI. If you want to build real-life smart systems to play a crucial role in every complex domain, then this book is what you need. Knowledge of Python programming and deep learning concepts are expected to get the most out of the book.
Python Artificial Intelligence Projects for Beginners: Get up and running with Artificial Intelligence using 8 smart and exciting AI applications
by Joshua EckrothBuild smart applications by implementing real-world artificial intelligence projectsKey FeaturesExplore a variety of AI projects with PythonGet well-versed with different types of neural networks and popular deep learning algorithmsLeverage popular Python deep learning libraries for your AI projectsBook DescriptionArtificial Intelligence (AI) is the newest technology that’s being employed among varied businesses, industries, and sectors. Python Artificial Intelligence Projects for Beginners demonstrates AI projects in Python, covering modern techniques that make up the world of Artificial Intelligence.This book begins with helping you to build your first prediction model using the popular Python library, scikit-learn. You will understand how to build a classifier using an effective machine learning technique, random forest, and decision trees. With exciting projects on predicting bird species, analyzing student performance data, song genre identification, and spam detection, you will learn the fundamentals and various algorithms and techniques that foster the development of these smart applications. In the concluding chapters, you will also understand deep learning and neural network mechanisms through these projects with the help of the Keras library.By the end of this book, you will be confident in building your own AI projects with Python and be ready to take on more advanced projects as you progressWhat you will learnBuild a prediction model using decision trees and random forestUse neural networks, decision trees, and random forests for classificationDetect YouTube comment spam with a bag-of-words and random forestsIdentify handwritten mathematical symbols with convolutional neural networksRevise the bird species identifier to use imagesLearn to detect positive and negative sentiment in user reviewsWho this book is forPython Artificial Intelligence Projects for Beginners is for Python developers who want to take their first step into the world of Artificial Intelligence using easy-to-follow projects. Basic working knowledge of Python programming is expected so that you’re able to play around with code
The Python Audio Cookbook: Recipes for Audio Scripting with Python
by Alexandros DrymonitisThe Python Audio Cookbook offers an introduction to Python for sound and multimedia applications, with chapters that cover writing your first Python programs, controlling Pyo with physical computing, and writing your own GUI, among many other topics. Guiding the reader through a variety of audio synthesis techniques, the book empowers readers to combine their projects with popular platforms, from the Arduino to Twitter, and state-of-the-art practices such as AI. The Python Audio Cookbook balances accessible explanations for theoretical concepts, including Python syntax, audio processing and machine learning, with practical applications. This book is an essential introductory guide to Python for sound and multimedia practitioners, as well as programmers interested in audio applications.
Python Automation Cookbook: 75 Python automation ideas for web scraping, data wrangling, and processing Excel, reports, emails, and more, 2nd Edition
by Jaime BueltaGet a firm grip on the core processes including browser automation, web scraping, Word, Excel, and GUI automation with Python 3.8 and higher Key Features Automate integral business processes such as report generation, email marketing, and lead generation Explore automated code testing and Python's growth in data science and AI automation in three new chapters Understand techniques to extract information and generate appealing graphs, and reports with Matplotlib Book Description In this updated and extended version of Python Automation Cookbook, each chapter now comprises the newest recipes and is revised to align with Python 3.8 and higher. The book includes three new chapters that focus on using Python for test automation, machine learning projects, and for working with messy data. This edition will enable you to develop a sharp understanding of the fundamentals required to automate business processes through real-world tasks, such as developing your first web scraping application, analyzing information to generate spreadsheet reports with graphs, and communicating with automatically generated emails. Once you grasp the basics, you will acquire the practical knowledge to create stunning graphs and charts using Matplotlib, generate rich graphics with relevant information, automate marketing campaigns, build machine learning projects, and execute debugging techniques. By the end of this book, you will be proficient in identifying monotonous tasks and resolving process inefficiencies to produce superior and reliable systems. What you will learn Learn data wrangling with Python and Pandas for your data science and AI projects Automate tasks such as text classification, email filtering, and web scraping with Python Use Matplotlib to generate a variety of stunning graphs, charts, and maps Automate a range of report generation tasks, from sending SMS and email campaigns to creating templates, adding images in Word, and even encrypting PDFs Master web scraping and web crawling of popular file formats and directories with tools like Beautiful Soup Build cool projects such as a Telegram bot for your marketing campaign, a reader from a news RSS feed, and a machine learning model to classify emails to the correct department based on their content Create fire-and-forget automation tasks by writing cron jobs, log files, and regexes with Python scripting Who this book is for Python Automation Cookbook - Second Edition is for developers, data enthusiasts or anyone who wants to automate monotonous manual tasks related to business processes such as finance, sales, and HR, among others. Working knowledge of Python is all you need to get started with this book.
Python Automation Cookbook: Explore the world of automation using Python recipes that will enhance your skills
by Jaime BueltaStep-by-step instructions which take you through each program to automate monotonous tasks with Python 3.7Key FeaturesAutomate integral business processes such as report generation, email marketing, and lead generationBuild your first web application that scrapes data and accesses websites' APIsCreate graphic-rich charts, graphs, and maps using MatplotlibBook DescriptionHave you been doing the same old monotonous office work over and over again? Or have you been trying to find an easy way to make your life better by automating some of your repetitive tasks? Through a tried and tested approach, understand how to automate all the boring stuff using Python. The Python Automation Cookbook helps you develop a clear understanding of how to automate your business processes using Python, including detecting opportunities by scraping the web, analyzing information to generate automatic spreadsheets reports with graphs, and communicating with automatically generated emails. You’ll learn how to get notifications via text messages and run tasks while your mind is focused on other important activities, followed by understanding how to scan documents such as résumés. Once you’ve gotten familiar with the fundamentals, you’ll be introduced to the world of graphs, along with studying how to produce organized charts using Matplotlib. In addition to this, you’ll gain in-depth knowledge of how to generate rich graphics showing relevant information. By the end of this book, you’ll have refined your skills by attaining a sound understanding of how to identify and correct problems to produce superior and reliable systems.What you will learnGet to grips with scraping a website to detect changesSearch and process raw sales files to aggregate information in spreadsheetsExplore techniques to extract information from an Excel spreadsheet and generate exciting reports with graphsDiscover the techniques required to generate random, print-friendly codes to be used as single-use couponsAutomatically generate a marketing campaign, contacting the recipients over different channelsIdentify and implement precise solutionsWho this book is forThe Python Automation Cookbook is for you if you are a developer or anyone who wants to automate monotonous manual tasks related to fields such as finance, sales, and HR, among others.
Python Bibliography
by Developers From DevzoneTwenty years ago, Guido van Rossum was hard at work on the first release of Python. A lot has changed in those twenty years. Many of the programming languages that were contemporaries of Python have started showing their age. Meanwhile, there have been no shortages of new programming languages, yet Python continues to hold up well. Its emphasis on clean syntax, and its melding of object-oriented and functional programming elements, put it years ahead of the other popular languages from the 1990s. The story of Python is not only about it being ahead of its time in terms of syntax and features. It is also about its open development and the community around it. Its value as a scripting language is well known, and it ships with many operating systems. For years Python has been one of the Pâ TMs in the LAMP stack used for numerous web applications. Indeed, Pythonâ TMs popularity with web developers has lead to a multitude of web application frameworks written in Python: Django, TurboGears, Pylons, CherryPy, and so on. Even with technology's fast-moving pace, Python remains on the cutting edge. NoSQL data stores have become increasingly popular, and you can find first class support for using Python with any of these technologies. This is just further evidence of the continued popularity of Python and the vibrant community around it. This bibliography contains a wide selection of books about Python. These range from various introductory to advanced books. Of course, web development is covered, but you might be surprised to see the wide variety of other types of development that are done using Python. Whether you are working on machine learning or just hacking in your spare time, Python has something for you.
Python Business Intelligence Cookbook
by Robert DempseyLeverage 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.
Python Challenges: 100 Proven Programming Tasks Designed to Prepare You for Anything
by Michael IndenAugment your knowledge of Python with this entertaining learning guide, which features 100 exercises and programming puzzles and solutions. Python Challenges will help prepare you for your next exam or a job interview, and covers numerous practical topics such as strings, data structures, recursion, arrays, and more. Each topic is addressed in its own separate chapter, starting with an introduction to the basics and followed by 10 to 15 exercises of various degrees of difficulty, helping you to improve your programming skills effectively. Detailed sample solutions, including the algorithms used for all tasks, are included to maximize your understanding of each area. Author Michael Inden also describes alternative solutions and analyzes possible pitfalls and typical errors. Three appendices round out the book: the first covers the Python command line interpreter, which is often helpful for trying out the code snippets and examples in the book, followed by an overview of Pytest for unit testing and checking the solutions. The last explains the O notation for estimating performance. After reading this book, you'll be prepared to take the next step in your career or tackle your next personal project. All source code is freely available for download via the Apress website. What You Will Learn Improve your Python knowledge by solving enjoyable but challenging programming puzzles Solve mathematical problems, recursions, strings, arrays and more Manage data processing and data structures like lists, sets, maps Handle advanced recursion as well as binary trees, sorting and searching Gamify key fundamentals for fun and easier reinforcement Who this book is for: Programmers, software developers who are either professionals or makers, as well as students and teachers. At least some prior experience with the Python programming is recommended.
Python Concurrency with asyncio
by Matthew FowlerLearn how to speed up slow Python code with concurrent programming and the cutting-edge asyncio library. Use coroutines and tasks alongside async/await syntax to run code concurrently Build web APIs and make concurrency web requests with aiohttp Run thousands of SQL queries concurrently Create a map-reduce job that can process gigabytes of data concurrently Use threading with asyncio to mix blocking code with asyncio code Python is flexible, versatile, and easy to learn. It can also be very slow compared to lower-level languages. Python Concurrency with asyncio teaches you how to boost Python's performance by applying a variety of concurrency techniques. You'll learn how the complex-but-powerful asyncio library can achieve concurrency with just a single thread and use asyncio's APIs to run multiple web requests and database queries simultaneously. The book covers using asyncio with the entire Python concurrency landscape, including multiprocessing and multithreading. About the technology It&’s easy to overload standard Python and watch your programs slow to a crawl. Th e asyncio library was built to solve these problems by making it easy to divide and schedule tasks. It seamlessly handles multiple operations concurrently, leading to apps that are lightning fast and scalable. About the book Python Concurrency with asyncio introduces asynchronous, parallel, and concurrent programming through hands-on Python examples. Hard-to-grok concurrency topics are broken down into simple flowcharts that make it easy to see how your tasks are running. You&’ll learn how to overcome the limitations of Python using asyncio to speed up slow web servers and microservices. You&’ll even combine asyncio with traditional multiprocessing techniques for huge improvements to performance. What's inside Build web APIs and make concurrency web requests with aiohttp Run thousands of SQL queries concurrently Create a map-reduce job that can process gigabytes of data concurrently Use threading with asyncio to mix blocking code with asyncio code About the reader For intermediate Python programmers. No previous experience of concurrency required. About the author Matthew Fowler has over 15 years of software engineering experience in roles from architect to engineering director. Table of Contents 1 Getting to know asyncio 2 asyncio basics 3 A first asyncio application 4 Concurrent web requests 5 Non-blocking database drivers 6 Handling CPU-bound work 7 Handling blocking work with threads 8 Streams 9 Web applications 10 Microservices 11 Synchronization 12 Asynchronous queues 13 Managing subprocesses 14 Advanced asyncio
Python Continuous Integration and Delivery: A Concise Guide with Examples
by Moritz LenzGain the techniques and tools that enable a smooth and efficient software development process in this quick and practical guide on Python continuous integration (CI) and continuous delivery (CD). Based on example applications, this book introduces various kinds of testing and shows you how to set up automated systems that run these tests, and install applications in different environments in controlled ways. Python Continuous Integration and Delivery tackles the technical problems related to software development that are typically glossed over in pure programming texts.After reading this book, you’ll see that in today's fast-moving world, no software project can afford to go through development, then an integration phase of unpredictable length and complexity, and finally be shipped to the customer -- just to find out that the resulting application didn't quite fill their need. Instead, you’ll discover that practicing continuous integration and continuous delivery reduces the risks by keeping changes small and automating otherwise painful processes. What You Will LearnCarry out various kinds of testing, including unit testing and continuous integration testing, of your Python code using JenkinsBuild packages and manage repositoriesIncorporate Ansible and Go for automated packaging and other deploymentsManage more complex and robust deploymentsWho This Book Is ForPython programmers and operating staff that work with Python applications.
Python Cookbook: Recipes for Mastering Python 3
by David Beazley Brian K. JonesIf 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, youâ??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 AlgorithmsStrings and TextNumbers, Dates, and TimesIterators and GeneratorsFiles and I/OData Encoding and ProcessingFunctionsClasses and ObjectsMetaprogrammingModules and PackagesNetwork and Web ProgrammingConcurrencyUtility Scripting and System AdministrationTesting, Debugging, and ExceptionsC Extensions
Python Cookbook
by Alex Martelli David AscherThe Python Cookbook is a collection of problems, solutions, and practical examples for Python programmers, written by Python programmers. It contains over two hundred recipes for text manipulation, object oriented programming, XML processing, system administration, and much more. This book is a treasure trove of useful code for both novices and advanced practitioners, with contributions from such Python luminaries as Guido Van Rossum, Tim Peters, Paul Prescod, and Mark Hammond.
Python Cookbook
by Anna Ravenscroft David Ascher Alex MartelliPortable, 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.
Python Cookbook, 2nd Edition
by Alex Martelli Anna Ravenscroft David AscherPortable, 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 textSearching and sortingWorking with files and the filesystemObject-oriented programmingDealing with threads and processesSystem administrationInteracting with databasesCreating user interfacesNetwork and web programmingProcessing XMLDistributed 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.
Python Crash Course: A Hands-On, Project-Based Introduction to Programming
by Eric MatthesPython Crash Course is a fast-paced, thorough introduction to Python that will have you writing programs, solving problems, and making things that work in no time.In the first half of the book, you’ll learn about basic programming concepts, such as lists, dictionaries, classes, and loops, and practice writing clean and readable code with exercises for each topic. You’ll also learn how to make your programs interactive and how to test your code safely before adding it to a project. In the second half of the book, you’ll put your new knowledge into practice with three substantial projects: a Space Invaders–inspired arcade game, data visualizations with Python’s super-handy libraries, and a simple web app you can deploy online.As you work through Python Crash Course you’ll learn how to:–Use powerful Python libraries and tools, including matplotlib, NumPy, and Pygal–Make 2D games that respond to keypresses and mouse clicks, and that grow more difficult as the game progresses–Work with data to generate interactive visualizations–Create and customize Web apps and deploy them safely online–Deal with mistakes and errors so you can solve your own programming problemsIf you’ve been thinking seriously about digging into programming, Python Crash Course will get you up to speed and have you writing real programs fast. Why wait any longer? Start your engines and code!Uses Python 2 and 3
Python Crash Course, 2nd Edition: A Hands-On, Project-Based Introduction to Programming
by Eric MatthesSecond edition of the best selling Python book in the world. A fast-paced, no-nonsense guide to programming in Python. This book teaches beginners the basics of programming in Python with a focus on real projects.This is the second edition of the best selling Python book in the world. Python Crash Course, 2nd Edition is a straightforward introduction to the core of Python programming. Author Eric Matthes dispenses with the sort of tedious, unnecessary information that can get in the way of learning how to program, choosing instead to provide a foundation in general programming concepts, Python fundamentals, and problem solving. Three real world projects in the second part of the book allow readers to apply their knowledge in useful ways. Readers will learn how to create a simple video game, use data visualization techniques to make graphs and charts, and build and deploy an interactive web application. Python Crash Course, 2nd Edition teaches beginners the essentials of Python quickly so that they can build practical programs and develop powerful programming techniques.
Python Crash Course, 3rd Edition: A Hands-On, Project-Based Introduction to Programming
by Eric MatthesPython Crash Course is the world&’s bestselling programming book, with over 1,500,000 copies sold to date!Python Crash Course is the world&’s best-selling guide to the Python programming language. This fast-paced, thorough introduction will have you writing programs, solving problems, and developing functioning applications in no time.You&’ll start by learning basic programming concepts, such as variables, lists, classes, and loops, and practice writing clean code with exercises for each topic. You&’ll also learn how to make your programs interactive and test your code safely before adding it to a project. You&’ll put your new knowledge into practice by creating a Space Invaders–inspired arcade game, building a set of data visualizations with Python&’s handy libraries, and deploying a simple application online.As you work through the book, you&’ll learn how to:Use powerful Python libraries and tools, including pytest, Pygame, Matplotlib, Plotly, and DjangoMake increasingly complex 2D games that respond to keypresses and mouse clicksGenerate interactive data visualizations using a variety of datasetsBuild apps that allow users to create accounts and manage their own data, and deploy your apps online Troubleshoot coding errors and solve common programming problems New to this edition: This third edition is completely revised to reflect the latest in Python code. New and updated coverage includes VS Code for text editing, the pathlib module for file handling, pytest for testing your code, as well as the latest features of Matplotlib, Plotly, and Django.If you&’ve been thinking about digging into programming, Python Crash Course will provide you with the skills to write real programs fast. Why wait any longer? Start your engines and code!Covers Python 3.x
Python Data Analysis
by Ivan IdrisThis book is for programmers, scientists, and engineers who have knowledge of the Python language and know the basics of data science. It is for those who wish to learn different data analysis methods using Python and its libraries. This book contains all the basic ingredients you need to become an expert data analyst.
Python Data Analysis: Perform data collection, data processing, wrangling, visualization, and model building using Python, 3rd Edition
by Ivan Idris Armando Fandango Avinash NavlaniUnderstand data analysis pipelines using machine learning algorithms and techniques with this practical guideKey FeaturesPrepare and clean your data to use it for exploratory analysis, data manipulation, and data wranglingDiscover supervised, unsupervised, probabilistic, and Bayesian machine learning methodsGet to grips with graph processing and sentiment analysisBook DescriptionData analysis enables you to generate value from small and big data by discovering new patterns and trends, and Python is one of the most popular tools for analyzing a wide variety of data. With this book, you'll get up and running using Python for data analysis by exploring the different phases and methodologies used in data analysis and learning how to use modern libraries from the Python ecosystem to create efficient data pipelines.Starting with the essential statistical and data analysis fundamentals using Python, you'll perform complex data analysis and modeling, data manipulation, data cleaning, and data visualization using easy-to-follow examples. You'll then understand how to conduct time series analysis and signal processing using ARMA models. As you advance, you'll get to grips with smart processing and data analytics using machine learning algorithms such as regression, classification, Principal Component Analysis (PCA), and clustering. In the concluding chapters, you'll work on real-world examples to analyze textual and image data using natural language processing (NLP) and image analytics techniques, respectively. Finally, the book will demonstrate parallel computing using Dask.By the end of this data analysis book, you'll be equipped with the skills you need to prepare data for analysis and create meaningful data visualizations for forecasting values from data.What you will learnExplore data science and its various process modelsPerform data manipulation using NumPy and pandas for aggregating, cleaning, and handling missing valuesCreate interactive visualizations using Matplotlib, Seaborn, and BokehRetrieve, process, and store data in a wide range of formatsUnderstand data preprocessing and feature engineering using pandas and scikit-learnPerform time series analysis and signal processing using sunspot cycle dataAnalyze textual data and image data to perform advanced analysisGet up to speed with parallel computing using DaskWho this book is forThis book is for data analysts, business analysts, statisticians, and data scientists looking to learn how to use Python for data analysis. Students and academic faculties will also find this book useful for learning and teaching Python data analysis using a hands-on approach. A basic understanding of math and working knowledge of the Python programming language will help you get started with this book.