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| python 2.7 manual: The Hitchhiker's Guide to Python Kenneth Reitz, Tanya Schlusser, 2016-08-30 The Hitchhiker's Guide to Python takes the journeyman Pythonista to true expertise. More than any other language, Python was created with the philosophy of simplicity and parsimony. Now 25 years old, Python has become the primary or secondary language (after SQL) for many business users. With popularity comes diversityâ??and possibly dilution. 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 Hitchhikerâ??s Guide is light on reusable code and heavier on design philosophy, directing the reader to excellent sources that already exist. |
| python 2.7 manual: Think Python Allen B. Downey, 2015-12-02 If you want to learn how to program, working with Python is an excellent way to start. This hands-on guide takes you through the language a step at a time, beginning with basic programming concepts before moving on to functions, recursion, data structures, and object-oriented design. This second edition and its supporting code have been updated for Python 3. Through exercises in each chapter, youâ??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 |
| python 2.7 manual: Python Language Reference Manual Guido Van Rossum, Fred L. Drake, 2003 Describes the syntax and datatypes of Python, an object-oriented interpreted programming language. |
| python 2.7 manual: Python Data Science Handbook Jake VanderPlas, 2016-11-21 For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. 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 |
| python 2.7 manual: Python Tutorial 3.11.3 Guido Van Rossum, Python Development Team, 2023-05-12 |
| python 2.7 manual: Python for Software Design Allen Downey, 2009-03-09 Python for Software Design is a concise introduction to software design using the Python programming language. The focus is on the programming process, with special emphasis on debugging. The book includes a wide range of exercises, from short examples to substantial projects, so that students have ample opportunity to practice each new concept. |
| python 2.7 manual: Learn Python 3 the Hard Way Zed A. Shaw, 2017-06-26 You Will Learn Python 3! Zed Shaw has perfected the world’s best system for learning Python 3. Follow it and you will succeed—just like the millions of beginners Zed has taught to date! You bring the discipline, commitment, and persistence; the author supplies everything else. In Learn Python 3 the Hard Way, 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 a computer works; what good programs look like; and how to read, write, and think about code. Zed then teaches you even more in 5+ hours of video where he shows you how to break, fix, and debug your code—live, as he’s doing the exercises. Install a complete Python environment Organize and write code Fix and break code Basic mathematics Variables Strings and text Interact with users Work 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 Automated testing Basic game development Basic web development It’ll be hard at first. But soon, you’ll just get it—and that will feel great! This course 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. This Book Is Perfect For Total beginners with zero programming experience Junior developers who know one or two languages Returning professionals who haven’t written code in years Seasoned professionals looking for a fast, simple, crash course in Python 3 |
| python 2.7 manual: The Definitive Guide to Jython Josh Juneau, Jim Baker, Frank Wierzbicki, Leo Soto Muoz, Victor Ng, Alex Ng, Donna L. Baker, 2010-12-28 Jython is an open source implementation of the high-level, dynamic, object-oriented scripting language Python seamlessly integrated with the Java platform. The predecessor to Jython, JPython, is certified as 100% Pure Java. Jython is freely available for both commercial and noncommercial use and is distributed with source code. Jython is complementary to Java. The Definitive Guide to Jython, written by the official Jython team leads, covers Jython 2.5 (or 2.5.x)—from the basics to more advanced features. This book begins with a brief introduction to the language and then journeys through Jython’s different features and uses. The Definitive Guide to Jython is organized for beginners as well as advanced users of the language. The book provides a general overview of the Jython language itself, but it also includes intermediate and advanced topics regarding database, web, and graphical user interface (GUI) applications; Web services/SOA; and integration, concurrency, and parallelism, to name a few. |
| python 2.7 manual: Natural Language Processing with Python Steven Bird, Ewan Klein, Edward Loper, 2009-06-12 This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and translation. With it, you'll learn how to write Python programs that work with large collections of unstructured text. You'll access richly annotated datasets using a comprehensive range of linguistic data structures, and you'll understand the main algorithms for analyzing the content and structure of written communication. Packed with examples and exercises, Natural Language Processing with Python will help you: 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 This book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library. If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages -- or if you're simply curious to have a programmer's perspective on how human language works -- you'll find Natural Language Processing with Python both fascinating and immensely useful. |
| python 2.7 manual: How To Code in Python 3 Lisa Tagliaferri, 2018-02-01 This educational book introduces emerging developers to computer programming through the Python software development language, and serves as a reference book for experienced developers looking to learn a new language or re-familiarize themselves with computational logic and syntax. |
| python 2.7 manual: Programming with C++20 Andreas Fertig, 2021-11-26 Programming with C++20 teaches programmers with C++ experience the new features of C++20 and how to apply them. It does so by assuming C++11 knowledge. Elements of the standards between C++11 and C++20 will be briefly introduced, if necessary. However, the focus is on teaching the features of C++20. You will start with learning about the so-called big four Concepts, Coroutines, std::ranges, and modules. The big four a followed by smaller yet not less important features. You will learn about std::format, the new way to format a string in C++. In chapter 6, you will learn about a new operator, the so-called spaceship operator, which makes you write less code. You then will look at various improvements of the language, ensuring more consistency and reducing surprises. You will learn how lambdas improved in C++20 and what new elements you can now pass as non-type template parameters. Your next stop is the improvements to the STL. Of course, you will not end this book without learning about what happened in the constexpr-world. |
| python 2.7 manual: Python Packages Tomas Beuzen, Tiffany Timbers, 2022-04-20 Python Packages introduces Python packaging at an introductory and practical level that’s suitable for those with no previous packaging experience. Despite this, the text builds up to advanced topics such as automated testing, creating documentation, versioning and updating a package, and implementing continuous integration and deployment. Covering the entire Python packaging life cycle, this essential guide takes readers from package creation all the way to effective maintenance and updating. Python Packages focuses on the use of current and best-practice packaging tools and services like poetry, cookiecutter, pytest, sphinx, GitHub, and GitHub Actions. Features: The book’s source code is available online as a GitHub repository where it is collaborated on, automatically tested, and built in real time as changes are made; demonstrating the use of good reproducible and clear project workflows. Covers not just the process of creating a package, but also how to document it, test it, publish it to the Python Package Index (PyPI), and how to properly version and update it. All concepts in the book are demonstrated using examples. Readers can follow along, creating their own Python packages using the reproducible code provided in the text. Focuses on a modern approach to Python packaging with emphasis on automating and streamlining the packaging process using new and emerging tools such as poetry and GitHub Actions. |
| python 2.7 manual: Fluent Python Luciano Ramalho, 2015-07-30 Python’s simplicity lets you become productive quickly, but this often means you aren’t using everything it has to offer. With this hands-on guide, you’ll learn how to write effective, idiomatic Python code by leveraging its best—and possibly most neglected—features. Author Luciano Ramalho takes you through Python’s core language features and libraries, and shows you how to make your code shorter, faster, and more readable at the same time. 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 |
| python 2.7 manual: The Ball Python Manual Philippe de Vosjoli, 2004-11-01 Written by a team of internationally respected herpetologists led by Philippe de Vosjoli, The Ball Python Manual is an authoritative introduction to this popular snake. The ball python is admired around the world for its distinctly African appearance and its relative medium size and tameability. This colorful manual offers up-to-date and reliable information on selection, acclimating, handling, housing and maintaining ball pythons, all of which will be extremely valuable to newcomers to this remarkable python. Dr. Roger Klingenberg's chapter on health care is indispensable for all snake keepers with excellent advice for troubleshooting health issues for each of the snake's anatomical regions. The breeding chapter by David and Tracy Barker discusses sexing, sexual maturity, and all aspects of captive reproduction and hatching. The volume concludes with resources and a complete index. |
| python 2.7 manual: A Hands-On Introduction to Using Python in the Atmospheric and Oceanic Sciences Johnny Wei-Bing Lin, 2012 This book is a mini-course for researchers in the atmospheric and oceanic sciences. We assume readers will already know the basics of programming... in some other language. - Back cover. |
| python 2.7 manual: pytest Quick Start Guide Bruno Oliveira, 2018-08-29 Python's built-in unittest module is showing it's age; hard to extend, debug and track what's going on. The pytest framework overcomes these problems and simplifies testing your Python software. Many users love to use pytest and the improvement in their testing shows! This book is the ideal introduction to pytest, teaching you how to write ... |
| python 2.7 manual: Learning Python Mark Lutz, 2013-06-12 Get a comprehensive, in-depth introduction to the core Python language with this hands-on book. Based on author Mark Lutz’s popular training course, this updated fifth edition will help you quickly write efficient, high-quality code with Python. It’s an ideal way to begin, whether you’re new to programming or a professional developer versed in other languages. Complete with quizzes, exercises, and helpful illustrations, this easy-to-follow, self-paced tutorial gets you started with both Python 2.7 and 3.3— the latest releases in the 3.X and 2.X lines—plus all other releases in common use today. You’ll also learn some advanced language features that recently have become more common in Python code. Explore Python’s major built-in object types such as numbers, lists, and dictionaries Create and process objects with Python statements, and learn Python’s general syntax model Use functions to avoid code redundancy and package code for reuse Organize statements, functions, and other tools into larger components with modules Dive into classes: Python’s object-oriented programming tool for structuring code Write large programs with Python’s exception-handling model and development tools Learn advanced Python tools, including decorators, descriptors, metaclasses, and Unicode processing |
| python 2.7 manual: Learning Python Mark Lutz, 2013-06-12 Based on author Mark Lutz's popular training course, this updated fifth edition will help you quickly write efficient, high-quality code with Python. It's an ideal way to begin, whether you're new to programming or a professional developer versed in other languages.--Provided by publisher. |
| python 2.7 manual: Introduction to Python for Science and Engineering David J. Pine, 2024-09-23 Introduction to Python for Science and Engineering offers a quick and incisive introduction to the Python programming language for use in any science or engineering discipline. The approach is pedagogical and “bottom up,” which means starting with examples and extracting more general principles from that experience. No prior programming experience is assumed. Readers will learn the basics of Python syntax, data structures, input and output, conditionals and loops, user-defined functions, plotting, animation, and visualization. They will also learn how to use Python for numerical analysis, including curve fitting, random numbers, linear algebra, solutions to nonlinear equations, numerical integration, solutions to differential equations, and fast Fourier transforms. Readers learn how to interact and program with Python using JupyterLab and Spyder, two simple and widely used integrated development environments. All the major Python libraries for science and engineering are covered, including NumPy, SciPy, Matplotlib, and Pandas. Other packages are also introduced, including Numba, which can render Python numerical calculations as fast as compiled computer languages such as C but without their complex overhead. |
| python 2.7 manual: The Hitchhiker's Guide to Python Kenneth Reitz, Tanya Schlusser, 2016-08-30 The Hitchhiker's Guide to Python takes the journeyman Pythonista to true expertise. More than any other language, Python was created with the philosophy of simplicity and parsimony. Now 25 years old, Python has become the primary or secondary language (after SQL) for many business users. With popularity comes diversityâ??and possibly dilution. 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 Hitchhikerâ??s Guide is light on reusable code and heavier on design philosophy, directing the reader to excellent sources that already exist. |
| python 2.7 manual: Python for Scientists John M. Stewart, 2017-07-20 Scientific Python is taught from scratch in this book via copious, downloadable, useful and adaptable code snippets. Everything the working scientist needs to know is covered, quickly providing researchers and research students with the skills to start using Python effectively. |
| python 2.7 manual: Python Pocket Reference Mark Lutz, 2014-01-22 Updated for both Python 3.4 and 2.7, this convenient pocket guide is the perfect on-the-job quick reference. Youâ??ll find concise, need-to-know information on Python types and statements, special method names, built-in functions and exceptions, commonly used standard library modules, and other prominent Python tools. The handy index lets you pinpoint exactly what you need. Written by Mark Lutzâ??widely recognized as the worldâ??s leading Python trainerâ??Python Pocket Reference is an ideal companion to Oâ??Reillyâ??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 Pythonâ??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 |
| python 2.7 manual: Python 101 Michael Driscoll, 2014-06-03 Learn how to program with Python from beginning to end. This book is for beginners who want to get up to speed quickly and become intermediate programmers fast! |
| python 2.7 manual: Rapid GUI Programming with Python and Qt Mark Summerfield, 2007-10-18 Whether you're building GUI prototypes or full-fledged cross-platform GUI applications with native look-and-feel, PyQt 4 is your fastest, easiest, most powerful solution. Qt expert Mark Summerfield has written the definitive best-practice guide to PyQt 4 development. 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. |
| python 2.7 manual: The Python Library Reference Guido van Rossum, Python Development Team, 2018-02-03 This book is the first half of The Python Library Reference for Release 3.6.4, and covers chapters 1-18. The second book may be found with ISBN 9781680921090. The original Python Library Reference book is 1920 pages long. This book contains the original page numbers and index, along with the back sections fully intact. While reference-index describes the exact syntax and semantics of the Python language, this library reference manual describes the standard library that is distributed with Python. It also describes some of the optional components that are commonly included in Python distributions. Python's standard library is very extensive, offering a wide range of facilities as indicated by the long table of contents listed below. The library contains built-in modules (written in C) that provide access to system functionality such as file I/O that would otherwise be inaccessible to Python programmers, as well as modules written in Python that provide standardized solutions for many problems that occur in everyday programming. Some of these modules are explicitly designed to encourage and enhance the portability of Python programs by abstracting away platform-specifics into platform-neutral APIs. This book is available for free as a PDF at python.org. |
| python 2.7 manual: Python for Everybody : Exploring Data Using Python 3 , 2009 |
| python 2.7 manual: Dive Into Python Mark Pilgrim, 2013-11-09 Whether you're an experienced programmer looking to get into Python or grizzled Python veteran who remembers the days when you had to import the string module, Dive Into Python is your 'desert island' Python book. — Joey deVilla, Slashdot contributor As a complete newbie to the language...I constantly had those little thoughts like, 'this is the way a programming language should be taught.' — Lasse Koskela , JavaRanch Apress has been profuse in both its quantity and quality of releasesand (this book is) surely worth adding to your technical reading budget for skills development. — Blane Warrene, Technology Notes I am reading this ... because the language seems like a good way to accomplish programming tasks that don't require the low-level bit handling power of C. — Richard Bejtlich, TaoSecurity Python is a new and innovative scripting language. It is set to replace Perl as the programming language of choice for shell scripters, and for serious application developers who want a feature-rich, yet simple language to deploy their products. Dive Into Python is ahands-on guide to the Python language. Each chapter starts with a real, complete code sample, proceeds to pick it apart and explain the pieces, and then puts it all back together in a summary at the end. This is the perfect resource for you if you like to jump into languages fast and get going right away. If you're just starting to learn Python, first pick up a copy of Magnus Lie Hetland's Practical Python. |
| python 2.7 manual: Publishing Python Packages Dane Hillard, 2023-02-28 Create masterful, maintainable Python packages! This book includes pro tips for design, automation, testing, deployment, and even release as an open source project! In Publishing Python Packages you will learn how to: Build extensions and console script commands Use tox to automate packaging, installing, and testing Build a continuous integration pipeline using GitHub Actions Improve code quality and reduce manual review using black, mypy, and flake8 Create published documentation for your packages Keep packages up to date with pyupgrade and Dependabot Foster an open source community using GitHub features Publishing Python Packages teaches you how to easily share your Python code with your team and the outside world. Learn a repeatable and highly automated process for package maintenance that’s based on the best practices, tools, and standards of Python packaging. This book walks you through creating a complete package, including a C extension, and guides you all the way to publishing on the Python Package Index. Whether you’re entirely new to Python packaging or looking for optimal ways to maintain and scale your packages, this fast-paced and engaging guide is for you. Foreword by David Beazley. About the technology Successful Python packages install easily, run flawlessly, and stay reliably up to date. Publishing perfect Python packages requires a rigorous process that supports systematic testing and review, along with excellent documentation. Fortunately, the Python ecosystem includes tools and techniques to automate package creation and publishing. About the book Publishing Python Packages presents a practical process for sharing Python code in an automated and scalable way. Get hands-on experience with the latest packaging tools, and learn the ins and outs of package testing and continuous integration. You’ll even get pro tips for setting up a maintainable open source project, including licensing, documentation, and nurturing a community of contributors. What's inside Build extensions and console script commands Improve code quality with automated review and testing Create excellent documentation Keep packages up to date with pyupgrade and Dependabot About the reader For intermediate Python programmers. About the author Dane Hillard has spent the majority of his development career using Python to build web applications. Table of Contents PART 1 FOUNDATIONS 1 The what and why of Python packages 2 Preparing for package development 3 The anatomy of a minimal Python package PART 2 CREATING A VIABLE PACKAGE 4 Handling package dependencies, entry points, and extensions 5 Building and maintaining a test suite 6 Automating code quality tooling PART 3 GOING PUBLIC 7 Automating work through continuous integration 8 Authoring and maintaining documentation 9 Making a package evergreen 10 Scaling and solidifying your practices 11 Building a community |
| python 2.7 manual: Data Mining for Business Analytics Galit Shmueli, Peter C. Bruce, Peter Gedeck, Nitin R. Patel, 2019-10-14 Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python presents an applied approach to data mining concepts and methods, using Python software for illustration Readers will learn how to implement a variety of popular data mining algorithms in Python (a free and open-source software) to tackle business problems and opportunities. This is the sixth version of this successful text, and the first using Python. It covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, recommender systems, clustering, text mining and network analysis. It also includes: A new co-author, Peter Gedeck, who brings both experience teaching business analytics courses using Python, and expertise in the application of machine learning methods to the drug-discovery process A new section on ethical issues in data mining Updates and new material based on feedback from instructors teaching MBA, undergraduate, diploma and executive courses, and from their students More than a dozen case studies demonstrating applications for the data mining techniques described End-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presented A companion website with more than two dozen data sets, and instructor materials including exercise solutions, PowerPoint slides, and case solutions Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python is an ideal textbook for graduate and upper-undergraduate level courses in data mining, predictive analytics, and business analytics. This new edition is also an excellent reference for analysts, researchers, and practitioners working with quantitative methods in the fields of business, finance, marketing, computer science, and information technology. “This book has by far the most comprehensive review of business analytics methods that I have ever seen, covering everything from classical approaches such as linear and logistic regression, through to modern methods like neural networks, bagging and boosting, and even much more business specific procedures such as social network analysis and text mining. If not the bible, it is at the least a definitive manual on the subject.” —Gareth M. James, University of Southern California and co-author (with Witten, Hastie and Tibshirani) of the best-selling book An Introduction to Statistical Learning, with Applications in R |
| python 2.7 manual: Programming Visual Illusions for Everyone Marco Bertamini, 2017-08-08 If you find visual illusions fascinating Programming Visual Illusions for Everyone is a book for you. It has some background, some history and some theories about visual illusions, and it describes in some detail twelve illusions. Some are about surfaces, some are about apparent size of objects, some are about colour and some involve movement. This is only one aspect of the book. The other is to show you how you can create these effects on any computer. The book includes a brief introduction to a powerful programming language called Python. No previous experience with programming is necessary. There is also an introduction to a package called PsychoPy that makes it easy to draw on a computer screen. It is perfectly ok if you have never heard the names Python or PsychoPy before. Python is a modern and easy-to-read language, and PsychoPy takes care of all the graphical aspects of drawing on a screen and also interacting with a computer. By the way, both Python and PsychoPy are absolutely free. Is this a book about illusions or about programming? It is both! |
| python 2.7 manual: Binary Analysis Cookbook Michael Born, 2019-09-20 Explore open-source Linux tools and advanced binary analysis techniques to analyze malware, identify vulnerabilities in code, and mitigate information security risks Key FeaturesAdopt a methodological approach to binary ELF analysis on LinuxLearn how to disassemble binaries and understand disassembled codeDiscover how and when to patch a malicious binary during analysisBook Description Binary analysis is the process of examining a binary program to determine information security actions. It is a complex, constantly evolving, and challenging topic that crosses over into several domains of information technology and security. This binary analysis book is designed to help you get started with the basics, before gradually advancing to challenging topics. Using a recipe-based approach, this book guides you through building a lab of virtual machines and installing tools to analyze binaries effectively. You'll begin by learning about the IA32 and ELF32 as well as IA64 and ELF64 specifications. The book will then guide you in developing a methodology and exploring a variety of tools for Linux binary analysis. As you advance, you'll learn how to analyze malicious 32-bit and 64-bit binaries and identify vulnerabilities. You'll even examine obfuscation and anti-analysis techniques, analyze polymorphed malicious binaries, and get a high-level overview of dynamic taint analysis and binary instrumentation concepts. By the end of the book, you'll have gained comprehensive insights into binary analysis concepts and have developed the foundational skills to confidently delve into the realm of binary analysis. What you will learnTraverse the IA32, IA64, and ELF specificationsExplore Linux tools to disassemble ELF binariesIdentify vulnerabilities in 32-bit and 64-bit binariesDiscover actionable solutions to overcome the limitations in analyzing ELF binariesInterpret the output of Linux tools to identify security risks in binariesUnderstand how dynamic taint analysis worksWho this book is for This book is for anyone looking to learn how to dissect ELF binaries using open-source tools available in Linux. If you’re a Linux system administrator or information security professional, you’ll find this guide useful. Basic knowledge of Linux, familiarity with virtualization technologies and the working of network sockets, and experience in basic Python or Bash scripting will assist you with understanding the concepts in this book |
| python 2.7 manual: An Introduction to Statistical Learning Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani, Jonathan Taylor, 2023-06-30 An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R (ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users. |
| python 2.7 manual: Error Handling in Python Ms A. Deepika, 2025-06-02 Written by Ms A. Deepika |
| python 2.7 manual: Python Cookbook David Beazley, Brian K. Jones, 2013-05-10 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, 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 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 |
| python 2.7 manual: Geospatial Computational Methods John N. Hatzopoulos, Nikolaos J. Hatzopoulos, 2024-05-01 This book is for students and professionals involved in Geospatial Computations and related areas such as Geomatics, Surveying Engineering, Geoinformatics, Geospatial Information Science and Technology (GIS&T), Geography, Geology, Agriculture, and Geointelligence. More emphasis is given to using scientific methods and tools materialized in algorithms and software to produce practical results. Specifically, algorithms such as error analysis of measurements and the least squares adjustment method to obtain ground coordinates of points with their reliability to construct the geometric framework of the geographical space necessary for various geospatial applications such as a Geographic Information System (GIS) are discussed. Other algorithms involve interpolation methods for DEM and spatial data analysis. Furthermore, such algorithms in the geospatial area are basic surveying methods using a total station, photogrammetry, digital terrain modeling, GNSS, augmented reality, coordinate transformations, map projections, and interpolation. Most algorithms are implemented into 27 educational computer programs and necessary data to understand GIS&T operations from the inside with a didactics approach targeting to become more intelligent than machines. The educational programs include general photogrammetric operations with aerial photography and drones, 3-D surveying network adjustment, GNSS navigation solutions, and many others. This approach helps to obtain high-quality scientific and technological bases, which in turn enhance the ability to exploit and use most tools and functions of existing GIS&T systems and, therefore, to be highly competitive as a professional in the market. This book has ten chapters such as Measurements and Errors Estimation and Accuracy Standards, Specialized Numerical Methods, Error Propagation & Least Squares Adjustment, Condition Method and Generalized Least Squares, Applications to Map Projections and Transformation of Coordinates, Applications to Surveying Networks, Applications of Computational Methods in Photogrammetry, Digital Elevation Models (DEM), Computer Programming – Scripting & AI. |
| python 2.7 manual: Python for Biologists Martin Jones, 2013 Python for biologists is a complete programming course for beginners that will give you the skills you need to tackle common biological and bioinformatics problems. |
| python 2.7 manual: The Rust Programming Language (Covers Rust 2018) Steve Klabnik, Carol Nichols, 2019-08-12 The official book on the Rust programming language, written by the Rust development team at the Mozilla Foundation, fully updated for Rust 2018. The Rust Programming Language is the official book on Rust: an open source systems programming language that helps you write faster, more reliable software. Rust offers control over low-level details (such as memory usage) in combination with high-level ergonomics, eliminating the hassle traditionally associated with low-level languages. The authors of The Rust Programming Language, members of the Rust Core Team, share their knowledge and experience to show you how to take full advantage of Rust's features--from installation to creating robust and scalable programs. You'll begin with basics like creating functions, choosing data types, and binding variables and then move on to more advanced concepts, such as: Ownership and borrowing, lifetimes, and traits Using Rust's memory safety guarantees to build fast, safe programs Testing, error handling, and effective refactoring Generics, smart pointers, multithreading, trait objects, and advanced pattern matching Using Cargo, Rust's built-in package manager, to build, test, and document your code and manage dependencies How best to use Rust's advanced compiler with compiler-led programming techniques You'll find plenty of code examples throughout the book, as well as three chapters dedicated to building complete projects to test your learning: a number guessing game, a Rust implementation of a command line tool, and a multithreaded server. New to this edition: An extended section on Rust macros, an expanded chapter on modules, and appendixes on Rust development tools and editions. |
| python 2.7 manual: Elements of Programming Interviews Adnan Aziz, Tsung-Hsien Lee, Amit Prakash, 2012 The core of EPI is a collection of over 300 problems with detailed solutions, including 100 figures, 250 tested programs, and 150 variants. The problems are representative of questions asked at the leading software companies. The book begins with a summary of the nontechnical aspects of interviewing, such as common mistakes, strategies for a great interview, perspectives from the other side of the table, tips on negotiating the best offer, and a guide to the best ways to use EPI. The technical core of EPI is a sequence of chapters on basic and advanced data structures, searching, sorting, broad algorithmic principles, concurrency, and system design. Each chapter consists of a brief review, followed by a broad and thought-provoking series of problems. We include a summary of data structure, algorithm, and problem solving patterns. |
| python 2.7 manual: The Definitive Guide to Pylons James Gardner, 2008-12-17 In this book, cofounder and lead developer James Gardner brings you a comprehensive introduction to Pylons, the web framework that uses the best of Ruby, Python, and Perl and the emerging WSGI standard to provide structure and flexibility. You’ll learn how to create your own Pylons-driven web site and attain the mastery of advanced Pylons features. You’ll also learn how to stretch Pylons to its fullest ability, as well as share Gardner’s unique insight and extensive experience in developing and deploying Pylons for a wide variety of situations. |
| python 2.7 manual: Discovering Computer Science Jessen Havill, 2016-07-06 Discovering Computer Science: Interdisciplinary Problems, Principles, and Python Programming introduces computational problem solving as a vehicle of discovery in a wide variety of disciplines. With a principles-oriented introduction to computational thinking, the text provides a broader and deeper introduction to computer science than typical introductory programming books. Organized around interdisciplinary problem domains, rather than programming language features, each chapter guides students through increasingly sophisticated algorithmic and programming techniques. The author uses a spiral approach to introduce Python language features in increasingly complex contexts as the book progresses. The text places programming in the context of fundamental computer science principles, such as abstraction, efficiency, and algorithmic techniques, and offers overviews of fundamental topics that are traditionally put off until later courses. The book includes thirty well-developed independent projects that encourage students to explore questions across disciplinary boundaries. Each is motivated by a problem that students can investigate by developing algorithms and implementing them as Python programs. The book's accompanying website — http://discoverCS.denison.edu — includes sample code and data files, pointers for further exploration, errata, and links to Python language references. Containing over 600 homework exercises and over 300 integrated reflection questions, this textbook is appropriate for a first computer science course for computer science majors, an introductory scientific computing course or, at a slower pace, any introductory computer science course. |
Is there a "not equal" operator in Python…
Jun 16, 2012 · Python is dynamically, but strongly typed, and other statically typed languages would …
What does colon equal (:=) in Python …
In Python this is simply =. To translate this pseudocode into Python you would need to know …
What is Python's equivalent of && (lo…
Sep 13, 2023 · There is no bitwise negation in Python (just the bitwise inverse operator ~ - but that is …
What does the "at" (@) symbol do in Py…
Jun 17, 2011 · Functions, in Python, are first class objects - which means you can pass a function as …
python - What is the purpose of the -m s…
You must run python my_script.py from the directory where the file is located. Alternatively - …
Is there a "not equal" operator in Python? - Stack Overflow
Jun 16, 2012 · Python is dynamically, but strongly typed, and other statically typed languages would complain about comparing different types. There's also the else clause: # This will …
What does colon equal (:=) in Python mean? - Stack Overflow
In Python this is simply =. To translate this pseudocode into Python you would need to know the data structures being referenced, and a bit more of the algorithm implementation. Some notes …
What is Python's equivalent of && (logical-and) in an if-statement?
Sep 13, 2023 · There is no bitwise negation in Python (just the bitwise inverse operator ~ - but that is not equivalent to not). See also 6.6. Unary arithmetic and bitwise/binary operations and …
What does the "at" (@) symbol do in Python? - Stack Overflow
Jun 17, 2011 · Functions, in Python, are first class objects - which means you can pass a function as an argument to another function, and return functions. Decorators do both of these things. If …
python - What is the purpose of the -m switch? - Stack Overflow
You must run python my_script.py from the directory where the file is located. Alternatively - python path/to/my_script.py. However, you can run python -m my_script (ie refer to the script …
What does [:-1] mean/do in python? - Stack Overflow
Mar 20, 2013 · Working on a python assignment and was curious as to what [:-1] means in the context of the following code: instructions = f.readline()[:-1] Have searched on here on S.O. …
python - Errno 13 Permission denied - Stack Overflow
Jul 16, 2020 · The problem here is your user doesn't have proper rights/permissions to open the file this means that you'd need to grant some administrative privileges to your python ide …
python - Iterating over dictionaries using 'for' loops - Stack Overflow
Jul 21, 2010 · In Python 3.x, iteritems() was replaced with simply items(), which returns a set-like view backed by the dict, like iteritems() but even better. This is also available in 2.7 as …
python - What exactly do "u" and "r" string prefixes do, and what …
There are two types of string in Python 2: the traditional str type and the newer unicode type. If you type a string literal without the u in front you get the old str type which stores 8-bit …
python - How do I execute a program or call a system command?
Note on Python version: If you are still using Python 2, subprocess.call works in a similar way. ProTip: shlex.split can help you to parse the command for run, call, and other subprocess …
