Written by Mark Lutz—widely recognized as the world’s leading Python trainer—Python Pocket Reference is an ideal companion to O’Reilly’s classic Python tutorials, Learning Python and Programming Python, also written by Mark.

This fifth edition covers:

• Built-in object types, including numbers, lists, dictionaries, and more
• Statements and syntax for creating and processing objects
• Functions and modules for structuring and reusing code
• Python’s object-oriented programming tools
• Built-in functions, exceptions, and attributes
• Special operator overloading methods
• Widely used standard library modules and extensions
• Command-line options and development tools
• Python idioms and hints
• The Python SQL Database API

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

You'll learn language syntax and programming techniques in a clear and concise manner, with lots of examples that illustrate both correct usage and common idioms. Completely updated for version 3.x, Programming Python also delves into the language as a software development tool, with many code examples scaled specifically for that purpose.

Topics include:

• Quick Python tour: Build a simple demo that includes data representation, object-oriented programming, object persistence, GUIs, and website basics
• System programming: Explore system interface tools and techniques for command-line scripting, processing files and folders, running programs in parallel, and more
• GUI programming: Learn to use Python’s tkinter widget library
• Internet programming: Access client-side network protocols and email tools, use CGI scripts, and learn website implementation techniques
• More ways to apply Python: Implement data structures, parse text-based information, interface with databases, and extend and embed Python

Many experienced programmers try to bend Python to fit patterns they learned from other languages, and never discover Python features outside of their experience. With this book, those Python programmers will thoroughly learn how to become proficient in Python 3.

This book covers:

• Python data model: understand how special methods are the key to the consistent behavior of objects
• Data structures: take full advantage of built-in types, and understand the text vs bytes duality in the Unicode age
• Functions as objects: view Python functions as first-class objects, and understand how this affects popular design patterns
• Object-oriented idioms: build classes by learning about references, mutability, interfaces, operator overloading, and multiple inheritance
• Control flow: leverage context managers, generators, coroutines, and concurrency with the concurrent.futures and asyncio packages
• Metaprogramming: understand how properties, attribute descriptors, class decorators, and metaclasses work

Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It’s ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub.

• Use the IPython shell and Jupyter notebook for exploratory computing
• Learn basic and advanced features in NumPy (Numerical Python)
• Get started with data analysis tools in the pandas library
• Use flexible tools to load, clean, transform, merge, and reshape data
• Create informative visualizations with matplotlib
• Apply the pandas groupby facility to slice, dice, and summarize datasets
• Analyze and manipulate regular and irregular time series data
• Learn how to solve real-world data analysis problems with thorough, detailed examples

Why does this book look so different? Based on the latest research in cognitive science and learning theory, Head First Pythonuses a visually rich format to engage your mind, rather than a text-heavy approach that puts you to sleep. Why waste your time struggling with new concepts? This multi-sensory learning experience is designed for the way your brain really works.

• Leverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualization
• Learn effective strategies and best practices to improve and optimize machine learning systems and algorithms
• Ask – and answer – tough questions of your data with robust statistical models, built for a range of datasets

If you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource.

• Explore how to use different machine learning models to ask different questions of your data
• Learn how to build neural networks using Keras and Theano
• Find out how to write clean and elegant Python code that will optimize the strength of your algorithms
• Discover how to embed your machine learning model in a web application for increased accessibility
• Predict continuous target outcomes using regression analysis
• Uncover hidden patterns and structures in data with clustering
• Organize data using effective pre-processing techniques
• Get to grips with sentiment analysis to delve deeper into textual and social media data

Machine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data – its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success.

Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world's leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization.

Python Machine Learning connects the fundamental theoretical principles behind machine learning to their practical application in a way that focuses you on asking and answering the right questions. It walks you through the key elements of Python and its powerful machine learning libraries, while demonstrating how to get to grips with a range of statistical models.

• Extract information from unstructured text, either to guess the topic or identify "named entities"
• Analyze linguistic structure in text, including parsing and semantic analysis
• Access popular linguistic databases, including WordNet and treebanks
• Integrate techniques drawn from fields as diverse as linguistics and artificial intelligence

Ideal for programmers with some Python experience, and those coming to Python from other programming languages, this book covers a wide range of application areas, including web and network programming, XML handling, database interactions, and high-speed numeric computing. Discover how Python provides a unique mix of elegance, simplicity, practicality, and sheer power.

This edition covers:

• Python syntax, Object-Oriented Python, standard library modules, and third-party Python packages
• Python’s support for file and text operations, persistence and databases, concurrent execution, and numeric computations
• Networking basics, event-driven programming, and client-side network protocol modules
• Python extension modules, and tools for packaging and distributing extensions, modules, and applications

Topics include:

• The pros and cons of braced initialization, noexcept specifications, perfect forwarding, and smart pointer make functions
• The relationships among std::move, std::forward, rvalue references, and universal references
• Techniques for writing clear, correct, effective lambda expressions
• How std::atomic differs from volatile, how each should be used, and how they relate to C++'s concurrency API
• How best practices in "old" C++ programming (i.e., C++98) require revision for software development in modern C++

Effective Modern C++ follows the proven guideline-based, example-driven format of Scott Meyers' earlier books, but covers entirely new material.

"After I learned the C++ basics, I then learned how to use C++ in production code from Meyer's series of Effective C++ books. Effective Modern C++ is the most important how-to book for advice on key guidelines, styles, and idioms to use modern C++ effectively and well. Don't own it yet? Buy this one. Now".

-- Herb Sutter, Chair of ISO C++ Standards Committee and C++ Software Architect at Microsoft

Through exercises in each chapter, you’ll try out programming concepts as you learn them. Think Python is ideal for students at the high school or college level, as well as self-learners, home-schooled students, and professionals who need to learn programming basics. Beginners just getting their feet wet will learn how to start with Python in a browser.

• Start with the basics, including language syntax and semantics
• Get a clear definition of each programming concept
• Learn about values, variables, statements, functions, and data structures in a logical progression
• Discover how to work with files and databases
• Understand objects, methods, and object-oriented programming
• Use debugging techniques to fix syntax, runtime, and semantic errors
• Explore interface design, data structures, and GUI-based programs through case studies

• Become familiar with the most important and advanced parts of the Python code style
• Learn the trickier aspects of Python and put it in a structured context for deeper understanding of the language
• Offers an expert's-eye overview of how these advanced tasks fit together in Python as a whole along with practical examples

Almost anyone can learn to write working script and create high quality code but they might lack a structured understanding of what it means to be 'Pythonic'. If you are a Python programmer who wants to code efficiently by getting the syntax and usage of a few intricate Python techniques exactly right, this book is for you.

• Create a virtualenv and start a new project
• Understand how and when to use the functional programming paradigm
• Get familiar with the different ways the decorators can be written in
• Understand the power of generators and coroutines without digressing into lambda calculus
• Create metaclasses and how it makes working with Python far easier
• Generate HTML documentation out of documents and code using Sphinx
• Learn how to track and optimize application performance, both memory and cpu
• Use the multiprocessing library, not just locally but also across multiple machines
• Get a basic understanding of packaging and creating your own libraries/applications

Python is a dynamic programming language. It is known for its high readability and hence it is often the first language learned by new programmers. Python being multi-paradigm, it can be used to achieve the same thing in different ways and it is compatible across different platforms. Even if you find writing Python code easy, writing code that is efficient, easy to maintain, and reuse is not so straightforward.

This book is an authoritative guide that will help you learn new advanced methods in a clear and contextualised way. It starts off by creating a project-specific environment using venv, introducing you to different Pythonic syntax and common pitfalls before moving on to cover the functional features in Python. It covers how to create different decorators, generators, and metaclasses. It also introduces you to functools.wraps and coroutines and how they work. Later on you will learn to use asyncio module for asynchronous clients and servers. You will also get familiar with different testing systems such as py.test, doctest, and unittest, and debugging tools such as Python debugger and faulthandler. You will learn to optimize application performance so that it works efficiently across multiple machines and Python versions. Finally, it will teach you how to access C functions with a simple Python call. By the end of the book, you will be able to write more advanced scripts and take on bigger challenges.

This book is a comprehensive guide that covers advanced features of the Python language, and communicate them with an authoritative understanding of the underlying rationale for how, when, and why to use them.

This guide, collaboratively written by over a hundred members of the Python community, describes best practices currently used by package and application developers. Unlike other books for this audience, The Hitchhiker’s Guide is light on reusable code and heavier on design philosophy, directing the reader to excellent sources that already exist.

Professional Python goes beyond the basics to teach beginner- and intermediate-level Python programmers the little-known tools and constructs that build concise, maintainable code. Design better architecture and write easy-to-understand code using highly adoptable techniques that result in more robust and efficient applications. Coverage includes Decorators, Context Managers, Magic Methods, Class Factories, Metaclasses, Regular Expressions, and more, including advanced methods for unit testing using asyncio and CLI tools. Each topic includes an explanation of the concept and a discussion on applications, followed by hands-on tutorials based on real-world scenarios. The "Python 3 first" approach covers multiple current versions, while ensuring long-term relevance.

Python offers many tools and techniques for writing better code, but often confusing documentation leaves many programmers in the dark about how to use them. This book shines a light on these incredibly useful methods, giving you clear guidance toward building stronger applications.

• Learn advanced Python functions, classes, and libraries
• Utilize better development and testing tools
• Understand the "what," "when," "why," and "how"

More than just theory or a recipe-style walk-through, this guide helps you learn — and understand — these little-known tools and techniques. You'll streamline your workflow while improving the quality of your output, producing more robust applications with cleaner code and stronger architecture. If you're ready to take your Python skills to the next level, Professional Python is the invaluable guide that will get you there.

With proper training a skilled system designer can take a bad design and rework it into well-designed, robust code. In this book, Martin Fowler shows you where opportunities for refactoring typically can be found, and how to go about reworking a bad design into a good one. Each refactoring step is simple--seemingly too simple to be worth doing. Refactoring may involve moving a field from one class to another, or pulling some code out of a method to turn it into its own method, or even pushing some code up or down a hierarchy. While these individual steps may seem elementary, the cumulative effect of such small changes can radically improve the design. Refactoring is a proven way to prevent software decay.

In addition to discussing the various techniques of refactoring, the author provides a detailed catalog of more than seventy proven refactorings with helpful pointers that teach you when to apply them; step-by-step instructions for applying each refactoring; and an example illustrating how the refactoring works. The illustrative examples are written in Java, but the ideas are applicable to any object-oriented programming language.

This book includes:

• Example programs completely rewritten to illustrate powerful new concepts now available in Python 3: sets, iterators, generators, closures, comprehensions, and much more
• A detailed case study of porting a major library from Python 2 to Python 3
• A comprehensive appendix of all the syntactic and semantic changes in Python 3

This is the perfect resource for you if you need to port applications to Python 3, or if you like to jump into languages fast and get going right away.

This book introduces students with little or no prior programming experience to the art of computational problem solving using Python and various Python libraries, including PyLab. It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of “data science” for using computation to model and interpret data. The book is based on an MIT course (which became the most popular course offered through MIT's OpenCourseWare) and was developed for use not only in a conventional classroom but in a massive open online course (or MOOC) offered by the pioneering MIT-Harvard collaboration edX.

Students are introduced to Python and the basics of programming in the context of such computational concepts and techniques as exhaustive enumeration, bisection search, and efficient approximation algorithms. The book does not require knowledge of mathematics beyond high school algebra, but does assume that readers are comfortable with rigorous thinking and not intimidated by mathematical concepts. Although it covers such traditional topics as computational complexity and simple algorithms, the book focuses on a wide range of topics not found in most introductory texts, including information visualization, simulations to model randomness, computational techniques to understand data, and statistical techniques that inform (and misinform) as well as two related but relatively advanced topics: optimization problems and dynamic programming.

Introduction to Computation and Programming Using Python can serve as a stepping-stone to more advanced computer science courses, or as a basic grounding in computational problem solving for students in other disciplines.

Some of the new topics in this edition include:

• Extensive coverage of the updated SSL support in Python 3

• How to write your own asynchronous I/O loop.

• An overview of the "asyncio" framework that comes with Python 3.4.

• How the Flask web framework connects URLs to your Python code.

• How cross-site scripting and cross-site request forgery can be used to attack your web site, and how to protect against them.

• How a full-stack web framework like Django can automate the round trip from your database to the screen and back.

If you're a Python programmer who needs a deep understanding of how to use Python for network-related tasks and applications, this is the book for you. From web application developers, to systems integrators, to system administrators—this book has everything that you need to know.

Patterns of Enterprise Application Architecture is written in direct response to the stiff challenges that face enterprise application developers. The author, noted object-oriented designer Martin Fowler, noticed that despite changes in technology--from Smalltalk to CORBA to Java to .NET--the same basic design ideas can be adapted and applied to solve common problems. With the help of an expert group of contributors, Martin distills over forty recurring solutions into patterns. The result is an indispensable handbook of solutions that are applicable to any enterprise application platform.

This book is actually two books in one. The first section is a short tutorial on developing enterprise applications, which you can read from start to finish to understand the scope of the book's lessons. The next section, the bulk of the book, is a detailed reference to the patterns themselves. Each pattern provides usage and implementation information, as well as detailed code examples in Java or C#. The entire book is also richly illustrated with UML diagrams to further explain the concepts.

Armed with this book, you will have the knowledge necessary to make important architectural decisions about building an enterprise application and the proven patterns for use when building them.

The topics covered include

· Dividing an enterprise application into layers

· The major approaches to organizing business logic

· An in-depth treatment of mapping between objects and relational databases

· Using Model-View-Controller to organize a Web presentation

· Handling concurrency for data that spans multiple transactions

· Designing distributed object interfaces

By working with a single case study throughout this thoroughly revised book, you’ll learn the entire process of exploratory data analysis—from collecting data and generating statistics to identifying patterns and testing hypotheses. You’ll explore distributions, rules of probability, visualization, and many other tools and concepts.

New chapters on regression, time series analysis, survival analysis, and analytic methods will enrich your discoveries.

• Develop an understanding of probability and statistics by writing and testing code
• Run experiments to test statistical behavior, such as generating samples from several distributions
• Use simulations to understand concepts that are hard to grasp mathematically
• Import data from most sources with Python, rather than rely on data that’s cleaned and formatted for statistics tools
• Use statistical inference to answer questions about real-world data

In the process, you’ll learn the basics of Django, Selenium, Git, jQuery, and Mock, along with current web development techniques. If you’re ready to take your Python skills to the next level, this book—updated for Python 3.6—clearly demonstrates how TDD encourages simple designs and inspires confidence.

• Dive into the TDD workflow, including the unit test/code cycle and refactoring
• Use unit tests for classes and functions, and functional tests for user interactions within the browser
• Learn when and how to use mock objects, and the pros and cons of isolated vs. integrated tests
• Test and automate your deployments with a staging server
• Apply tests to the third-party plugins you integrate into your site
• Run tests automatically by using a Continuous Integration environment
• Use TDD to build a REST API with a front-end Ajax interface

Starting with a walkthrough of today's major networking protocols, with this book you'll learn how to employ Python for network programming, how to request and retrieve web resources, and how to extract data in major formats over the Web. You'll utilize Python for e-mailing using different protocols and you'll interact with remote systems and IP and DNS networking.

As the book progresses, socket programming will be covered, followed by how to design servers and the pros and cons of multithreaded and event-driven architectures. You'll develop practical client-side applications, including web API clients, e-mail clients, SSH, and FTP. These applications will also be implemented through existing web application frameworks.

Bioinformatics Programming Using Python is perfect for anyone involved with bioinformatics -- researchers, support staff, students, and software developers interested in writing bioinformatics applications. You'll find it useful whether you already use Python, write code in another language, or have no programming experience at all. It's an excellent self-instruction tool, as well as a handy reference when facing the challenges of real-life programming tasks.

• Become familiar with Python's fundamentals, including ways to develop simple applications
• Learn how to use Python modules for pattern matching, structured text processing, online data retrieval, and database access
• Discover generalized patterns that cover a large proportion of how Python code is used in bioinformatics
• Learn how to apply the principles and techniques of object-oriented programming
• Benefit from the "tips and traps" section in each chapter

Part I focuses on web scraping mechanics: using Python to request information from a web server, performing basic handling of the server’s response, and interacting with sites in an automated fashion. Part II explores a variety of more specific tools and applications to fit any web scraping scenario you’re likely to encounter.

• Parse complicated HTML pages
• Develop crawlers with the Scrapy framework
• Learn methods to store data you scrape
• Read and extract data from documents
• Clean and normalize badly formatted data
• Read and write natural languages
• Crawl through forms and logins
• Scrape JavaScript and crawl through APIs
• Use and write image-to-text software
• Avoid scraping traps and bot blockers
• Use scrapers to test your website

You’ll learn the framework’s core functionality, as well as how to extend applications with advanced web techniques such as database migration and web service communication. The first part of each chapter provides you with reference and background for the topic in question, while the second part guides you though a hands-on implementation of the topic.

If you have Python experience, this book shows you how to take advantage of the creative freedom Flask provides.

Whether you’re an intermediate-level Python programmer or a student of computational modeling, you’ll delve into examples of complex systems through a series of worked examples, exercises, case studies, and easy-to-understand explanations.

In this updated second edition, you will:

• Work with NumPy arrays and SciPy methods, including basic signal processing and Fast Fourier Transform
• Study abstract models of complex physical systems, including power laws, fractals and pink noise, and Turing machines
• Get Jupyter notebooks filled with starter code and solutions to help you re-implement and extend original experiments in complexity; and models of computation like Turmites, Turing machines, and cellular automata
• Explore the philosophy of science, including the nature of scientific laws, theory choice, and realism and instrumentalism

Ideal as a text for a course on computational modeling in Python, Think Complexity also helps self-learners gain valuable experience with topics and ideas they might not encounter otherwise.

Python in easy steps begins by explaining how to install the free Python interpreter so you can quickly begin to create your own executable programs by copying the book's examples. It demonstrates all the Python language basics before moving on to provide examples of Object Oriented Programming (OOP) and CGI scripting to handle web form data. The book concludes by demonstrating how you can use your acquired knowledge to create and deploy graphical windowed applications.

Python in easy steps makes no assumption you have previous knowledge of any programming language so it's ideal for the newcomer to computer programming. It has an easy-to-follow style that will appeal to programmers moving from another programming language, and to the student who is studying Python programming at school or college, and to those seeking a career in computing who need a fundamental understanding of computer programming.

Python is the language used to program the Raspberry Pi - covered by Raspberry Pi in easy steps. 

Zed Shaw has perfected the world's best system for learning Python. Follow it and you will succeed-just like the hundreds of thousands of beginners Zed has taught to date! You bring the discipline, commitment, and persistence; the author supplies everything else.

In Learn Python the Hard Way, Third Edition, you'll learn Python by working through 52 brilliantly crafted exercises. Read them. Type their code precisely. (No copying and pasting!) Fix your mistakes. Watch the programs run. As you do, you'll learn how software works; what good programs look like; how to read, write, and think about code; and how to find and fix your mistakes using tricks professional programmers use. Most importantly, you'll learn the following, which you need to start writing excellent Python software of your own:

• Installing a complete Python environment
• Organizing and writing code
• Basic mathematics
• Variables
• Strings and text
• Interacting with users
• Working with files
• Looping and logic
• Data structures using lists and dictionaries
• Program design
• Object-oriented programming
• Inheritance and composition
• Modules, classes, and objects
• Python packaging
• Debugging
• Automated testing
• Basic game development
• Basic web development

This tutorial will reward you for every minute you put into it. Soon, you'll know one of the world's most powerful, popular programming languages. You'll be a Python programmer.

Watch Zed, too! The accompanying DVD contains 5+ hours of passionate, powerful teaching: a complete Python video course!

You’ll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Müller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book.

With this book, you’ll learn:

• Fundamental concepts and applications of machine learning
• Advantages and shortcomings of widely used machine learning algorithms
• How to represent data processed by machine learning, including which data aspects to focus on
• Advanced methods for model evaluation and parameter tuning
• The concept of pipelines for chaining models and encapsulating your workflow
• Methods for working with text data, including text-specific processing techniques
• Suggestions for improving your machine learning and data science skills

• New to Python? The definitive guide to Python development for experienced programmers
• Covers core language features thoroughly, including those found in the latest Python releases–learn more than just the syntax!
• Learn advanced topics such as regular expressions, networking, multithreading, GUI, Web/CGI, and Python extensions
• Includes brand-new material on databases, Internet clients, Java/Jython, and Microsoft Office, plus Python 2.6 and 3
• Presents hundreds of code snippets, interactive examples, and practical exercises to strengthen your Python skills

Python is an agile, robust, expressive, fully object-oriented, extensible, and scalable programming language. It combines the power of compiled languages with the simplicity and rapid development of scripting languages. In Core Python Programming, Second Edition , leading Python developer and trainer Wesley Chun helps you learn Python quickly and comprehensively so that you can immediately succeed with any Python project.

Using practical code examples, Chun introduces all the fundamentals of Python programming: syntax, objects and memory management, data types, operators, files and I/O, functions, generators, error handling and exceptions, loops, iterators, functional programming, object-oriented programming and more. After you learn the core fundamentals of Python, he shows you what you can do with your new skills, delving into advanced topics, such as regular expressions, networking programming with sockets, multithreading, GUI development, Web/CGI programming and extending Python in C.

This edition reflects major enhancements in the Python 2.x series, including 2.6 and tips for migrating to 3. It contains new chapters on database and Internet client programming, plus coverage of many new topics, including new-style classes, Java and Jython, Microsoft Office (Win32 COM Client) programming, and much more.

• Learn professional Python style, best practices, and good programming habits
• Gain a deep understanding of Python's objects and memory model as well as its OOP features, including those found in Python's new-style classes
• Build more effective Web, CGI, Internet, and network and other client/server applications
• Learn how to develop your own GUI applications using Tkinter and other toolkits available for Python
• Improve the performance of your Python applications by writing extensions in C and other languages, or enhance I/O-bound applications by using multithreading
• Learn about Python's database API and how to use a variety of database systems with Python, including MySQL, Postgres, and SQLite
• Features appendices on Python 2.6 & 3, including tips on migrating to the next generation!

Python 3 is the best version of the language yet: It is more powerful, convenient, consistent, and expressive than ever before. Now, leading Python programmer Mark Summerfield demonstrates how to write code that takes full advantage of Python 3’s features and idioms. Programming in Python 3, Second Edition, brings together all the knowledge you need to write any program, use any standard or third-party Python 3 library, and create new library modules of your own.

Summerfield draws on his many years of Python experience to share deep insights into Python 3 development you won’t find anywhere else. He begins by illuminating Python’s “beautiful heart”: the eight key elements of Python you need to write robust, high-performance programs. Building on these core elements, he introduces new topics designed to strengthen your practical expertise–one concept and hands-on example at a time. Coverage includes

• Developing in Python using procedural, objectoriented, and functional programming paradigms
• Creating custom packages and modules
• Writing and reading binary, text, and XML files, including optional compression, random access, and text and XML parsing
• Leveraging advanced data types, collections, control structures, and functions
• Spreading program workloads across multiple processes and threads
• Programming SQL databases and key—value DBM files
• Debugging techniques–and using Test Driven Development to avoid bugs in the first place
• Utilizing Python’s regular expression mini-language and module
• Parsing techniques, including how to use the third-party PyParsing and PLY modules
• Building usable, efficient, GUI-based applications
• Advanced programming techniques, including generators, function and class decorators, context managers, descriptors, abstract base classes, metaclasses, coroutines, and more

Programming in Python 3, Second Edition, serves as both tutorial and language reference. It assumes some prior programming experience, and it is accompanied by extensive downloadable example code–all of it tested with Python 3 on Windows, Linux, and Mac OS X.

In this update to the first ever book to cover the popular open source PyGame games development library, you'll stand to gain valuable technical insights and follow along with the creation of a real-world, freely downloadable video game. Written by industry veterans and Python experts Will McGugan and Harrison Kinsley, this is a comprehensive, practical introduction to games development in Python. You can also capitalize upon numerous tips and tricks the authors have accumulated over their careers creating games for some of the world's largest game developers.

Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python.

With this handbook, you’ll learn how to use:

• IPython and Jupyter: provide computational environments for data scientists using Python
• NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python
• Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python
• Matplotlib: includes capabilities for a flexible range of data visualizations in Python
• Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms

—Brandon Rhodes, software engineer at Dropbox and chair of PyCon 2016-2017

It’s easy to start coding with Python, which is why the language is so popular. However, Python’s unique strengths, charms, and expressiveness can be hard to grasp, and there are hidden pitfalls that can easily trip you up.

Effective Python will help you master a truly “Pythonic” approach to programming, harnessing Python’s full power to write exceptionally robust and well-performing code. Using the concise, scenario-driven style pioneered in Scott Meyers’ best-selling Effective C++, Brett Slatkin brings together 59 Python best practices, tips, and shortcuts, and explains them with realistic code examples.

Drawing on years of experience building Python infrastructure at Google, Slatkin uncovers little-known quirks and idioms that powerfully impact code behavior and performance. You’ll learn the best way to accomplish key tasks, so you can write code that’s easier to understand, maintain, and improve.

Key features include

• Actionable guidelines for all major areas of Python 3.x and 2.x development, with detailed explanations and examples
• Best practices for writing functions that clarify intention, promote reuse, and avoid bugs
• Coverage of how to accurately express behaviors with classes and objects
• Guidance on how to avoid pitfalls with metaclasses and dynamic attributes
• More efficient approaches to concurrency and parallelism
• Better techniques and idioms for using Python’s built-in modules
• Tools and best practices for collaborative development
• Solutions for debugging, testing, and optimization in order to improve quality and performance

Designed for the professional programmer, the book is concise, to the point, and highly accessible. It also includes detailed information on the Python library and many advanced subjects that is not available in either the official Python documentation or any other single reference source.

Thoroughly updated to reflect the significant new programming language features and library modules that have been introduced in Python 2.6 and Python 3, the fourth edition of Python Essential Reference is the definitive guide for programmers who need to modernize existing Python code or who are planning an eventual migration to Python 3. Programmers starting a new Python project will find detailed coverage of contemporary Python programming idioms.

This fourth edition of Python Essential Reference features numerous improvements, additions, and updates:

• Coverage of new language features, libraries, and modules
  
• Practical coverage of Python's more advanced features including generators, coroutines, closures, metaclasses, and decorators
• Expanded coverage of library modules related to concurrent programming including threads, subprocesses, and the new multiprocessing module
• Up-to-the-minute coverage of how to use Python 2.6’s forward compatibility mode to evaluate code for Python 3 compatibility
• Improved organization for even faster answers and better usability
• Updates to reflect modern Python programming style and idioms
• Updated and improved example code
• Deep coverage of low-level system and networking library modules — including options not covered in the standard documentation

With Rapid GUI Programming with Python and Qt you'll learn how to build efficient GUI applications that run on all major operating systems, including Windows, Mac OS X, Linux, and many versions of Unix, using the same source code for all of them. Summerfield systematically introduces every core GUI development technique: from dialogs and windows to data handling; from events to printing; and more. Through the book's realistic examples you'll discover a completely new PyQt 4-based programming approach, as well as coverage of many new topics, from PyQt 4's rich text engine to advanced model/view and graphics/view programming. Every key concept is illuminated with realistic, downloadable examples–all tested on Windows, Mac OS X, and Linux with Python 2.5, Qt 4.2, and PyQt 4.2, and on Windows and Linux with Qt 4.3 and PyQt 4.3.

• 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

• 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

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.

• 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

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.

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.

Considered the JavaScript expert by many people in the development community, author Douglas Crockford identifies the abundance of good ideas that make JavaScript an outstanding object-oriented programming language-ideas such as functions, loose typing, dynamic objects, and an expressive object literal notation. Unfortunately, these good ideas are mixed in with bad and downright awful ideas, like a programming model based on global variables.

When Java applets failed, JavaScript became the language of the Web by default, making its popularity almost completely independent of its qualities as a programming language. In JavaScript: The Good Parts, Crockford finally digs through the steaming pile of good intentions and blunders to give you a detailed look at all the genuinely elegant parts of JavaScript, including:

• Syntax
• Objects
• Functions
• Inheritance
• Arrays
• Regular expressions
• Methods
• Style
• Beautiful features

The real beauty? As you move ahead with the subset of JavaScript that this book presents, you'll also sidestep the need to unlearn all the bad parts. Of course, if you want to find out more about the bad parts and how to use them badly, simply consult any other JavaScript book.

With JavaScript: The Good Parts, you'll discover a beautiful, elegant, lightweight and highly expressive language that lets you create effective code, whether you're managing object libraries or just trying to get Ajax to run fast. If you develop sites or applications for the Web, this book is an absolute must.

• Complex data structures
• Parsing
• Templating toolkits
• Working with natural language data
• Unicode
• Interaction with C and other languages