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| python reference guide: Python Essential Reference David M. Beazley, 2009 Python Essential Reference is the definitive reference guide to the Python programming language--the one authoritative handbook that reliably untangles and explains both the core Python library. Designed for the practicing 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 complete guide for programmers who need to modernize existing Python code or who are planning an eventual migration to Python 3. |
| python reference guide: 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 reference guide: 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 reference guide: Text Processing in Python David Mertz, 2003 bull; Demonstrates how Python is the perfect language for text-processing functions. bull; Provides practical pointers and tips that emphasize efficient, flexible, and maintainable approaches to text-processing challenges. bull; Helps programmers develop solutions for dealing with the increasing amounts of data with which we are all inundated. |
| python reference guide: 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 reference guide: Python Martin C. Brown, 2001 Includes complete module guide and details on using Python for RAD--cover. |
| python reference guide: Python Standard Library Berajah Jayne, 2020-05 An extremely handy programmer's standard library reference that is as durable as it is portable. This 6 page laminated guide includes essential script modules used by developers of all skill levels to simplify the process of programming in Python. This guide is all script and is organized to find needed script quickly. As with QuickStudy reference on any subject, with continued reference, the format lends itself to memorization. Beginning students or seasoned programmers will find this tool a perfect go-to for the at-a-glance script answer and memory jog you might need. At this price and for the bank of script included it's an easy add to your programmer's toolbox. 6 page laminated guide includes: General Functionality Date/Time Processing System and Computer Controls OS Module Classes of the OS Module Pathlib Module Threading Module Debugging Functionality PDB Module Debugging for the PDB Module Mathematic and Numeric Operations Math Module Random Module Iterable and Iterator Operations Collections Module Classes of the Collections Module Itertools Module Web and Data Transfer Operations HTML Parser Module HTML Module Audio Manipulation |
| python reference guide: Python Programming Language Berajah Jayne, 2019-05 Created for developers of all skill levels to find the essentials of common operations combined with the fastest reference guide for writing code. This handy 6 page laminated guide is a concise desktop reference to key concepts behind Python logic, syntax, and operation. Expertly written to concisely cover the planning of a program written in Python, assigning your first variables, importing other libraries, formatting output strings, and creating classes. Beginning students or seasoned programmers will find this tool a perfect go-to for reference to those core concepts. This unbeatable value makes it easy to add this reference to your programmer's toolbox. 6 page laminated guide includes: Working with Python Using Python Code Importing Modules Scope (Indentation) Naming Conventions Reserved Keywords Comments Writing Code Basics Making Variables Types Console Error Handling Saving & Loading Files Coding Structures Math Operators (int, float & complex) List Operations (list, tuple & dict) Strings Statements Functions Dictionaries Using Structures String Formatting String Methods Escape Sequences Bool Characters Writing Boolean Statements Recursion & Iteration Classes Coding Concepts Inheritance Generators Polymorphism Lambda Expressions |
| python reference guide: Python in a Nutshell Alex Martelli, 2006-07-14 This volume offers Python programmers a straightforward guide to the important tools and modules of this open source language. It deals with the most frequently used parts of the standard library as well as the most popular and important third party extensions. |
| python reference guide: Basic Core Python Programming Meenu Kohli, 2021-04-21 Learn the most popular software programming language in easy steps Ê KEY FEATURESÊÊ _ Extensive coverage on fundamentals and core concepts of Python programming. _ A complete reference guide to crack Python Interviews and exams. _ Includes ample MCQs and solved examples to prepare you for theory and practical exams. _ Easy-to-understand text with explanatory illustrations. DESCRIPTIONÊ Basic Core Python Programming is an absolute beginners book. It focuses on the fundamentals of Python programming and simplifies coding concepts. This book makes it easy to learn the concepts of Python variables, Expressions, Decision structures, and Iteration. Equipped with a lot of exercises and Q&As, you donÕt just practice the programming but also gain an in-depth understanding of the basic concepts of Python. You will start your journey right from how to go about Python installation and start using its interactive development environment and go on to learn how to build logic and implement it with coding. You will explore different types of data, operators, and in-built functions. This book covers numerous coding examples that will help you understand the importance of each data type, how to work with each one of them, and when to use them. You can learn some more practical useful concepts like how to implement control structures and use them for decision making and controlling the program flow. WHAT YOU WILL LEARN _ Stronghold on Python variables, expressions, decision structures, and iterations. _ Practical knowledge on how to work with various data types, operators, and in-built functions. _ Learn to implement strings, lists, arrays, and control structures. _ Learn how to control the program flow and how to use it for decision-making. _ A great reference book on Python basics for software programmers. WHO THIS BOOK IS FORÊÊ This book is highly appealing to all tech-savvy students, programming enthusiasts, IT undergraduates, and computer science students. You do not need any prior knowledge Êof programming to begin with this book as long as you have the interest to learn to program. TABLE OF CONTENTS 1. Introduction 2. Python Basics 3. Numbers, Operators, and In-built Functions 4. Strings 5. Lists and Arrays 6. Tuples and Dictionaries 7. Sets and Frozen Sets 8. Program Flow Control in Python |
| python reference guide: 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 reference guide: Python Toby Donaldson, 2008-12-04 Python is a remarkably powerful dynamic programming language that is used in a wide variety of application domains such as Web, database access, desktop GUIs, game and software development, and network programming. Fans of Python use the phrase batteries included to describe the standard library, which covers everything from asynchronous processing to zip files. The language itself is a flexible powerhouse that can handle practically any application domain. This task-based tutorial is for students with no programming experience as well as those programmers who have some experience with the programming language and now want to take their skills to the next level. The book walks a reader through all the fundamentals and then moves on to more advanced topics. It's a complete end-to-end tutorial and reference. |
| python reference guide: 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 reference guide: Machine Learning Pocket Reference Matthew Harrison, 2019 With detailed notes, tables, and examples, this handy reference will help you navigate the basics of structured machine learning. Author Matt Harrison delivers a valuable guide that you can use for additional support during training and as a convenient resource when you dive into your next machine learning project. Ideal for programmers, data scientists, and AI engineers, this book includes an overview of the machine learning process and walks you through classification with structured data. You'll also learn methods for clustering, predicting a continuous value (regression), and reducing dimensionality, among other topics. This pocket reference includes sections that cover: Classification, using the Titanic dataset Cleaning data and dealing with missing data Exploratory data analysis Common preprocessing steps using sample data Selecting features useful to the model Model selection Metrics and classification evaluation Regression examples using k-nearest neighbor, decision trees, boosting, and more Metrics for regression evaluation Clustering Dimensionality reduction Scikit-learn pipelines. |
| python reference guide: Python Tutorial 3.11.3 Guido Van Rossum, Python Development Team, 2023-05-12 |
| python reference guide: Python Pocket Reference Mark Lutz, 1998 This handy reference guide summarizes Python statements, built-in functions, escape and formatting codes, and other prominent Python language features. |
| python reference guide: 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 reference guide: 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 reference guide: Python for Data Mining Quick Syntax Reference Valentina Porcu, 2018-12-19 Learn how to use Python and its structures, how to install Python, and which tools are best suited for data analyst work. This book provides you with a handy reference and tutorial on topics ranging from basic Python concepts through to data mining, manipulating and importing datasets, and data analysis. Python for Data Mining Quick Syntax Reference covers each concept concisely, with many illustrative examples. You'll be introduced to several data mining packages, with examples of how to use each of them. The first part covers core Python including objects, lists, functions, modules, and error handling. The second part covers Python's most important data mining packages: NumPy and SciPy for mathematical functions and random data generation, pandas for dataframe management and data import, Matplotlib for drawing charts, and scikitlearn for machine learning. What You'll Learn Install Python and choose a development environment Understand the basic concepts of object-oriented programming Import, open, and edit files Review the differences between Python 2.x and 3.x Who This Book Is For Programmers new to Python's data mining packages or with experience in other languages, who want a quick guide to Pythonic tools and techniques. |
| python reference guide: The Python Quick Syntax Reference Gregory Walters, 2014-02-28 The Python Quick Syntax Reference is the go to book that contains an easy to read and use guide to Python programming and development. This condensed code and syntax reference presents the Python language in a well-organized format designed to be used time and again. You won't find jargon, bloated samples, case studies, or history of Hello World and computer theory in this handy reference. This Python syntax reference is packed with useful information and is a must-have for any Python developer. |
| python reference guide: 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 reference guide: The Quick Python Book Vernon L. Ceder, Naomi R. Ceder, 2010 Introduces the programming language's syntax, control flow, and basic data structures and covers its interaction with applications and mangement of large collections of code. |
| python reference guide: Python by Example Nichola Lacey, 2019-06-06 A refreshingly different and engaging way of learning how to program using Python. This book includes example code and brief user-friendly explanations, along with 150 progressively trickier challenges. As readers are actively involved in their learning, they quickly master the new skills and gain confidence in creating their own programs. |
| python reference guide: Beginning Python Magnus Lie Hetland, 2006-11-07 Beginning Python: From Novice to Professional is the most comprehensive book on the Python ever written. Based on Practical Python, this newly-revised book is both an introduction and practical reference for a swath of Python-related programming topics, including addressing language internals, database integration, network programming, and web services. Advanced topics, such as extending Python and packaging/distributing Python applications, are also covered. Ten different projects illustrate the concepts introduced in the book. You will learn how to create a P2P file-sharing application and a web-based bulletin board, and how to remotely edit web-based documents and create games. Author Magnus Lie Hetland is an authority on Python and previously authored Practical Python. He also authored the popular online guide, Instant Python Hacking, on which both books are based. |
| python reference guide: Python Object-Oriented Programming Steven F. Lott, Dusty Phillips, 2021-07-02 A comprehensive guide to exploring modern Python through data structures, design patterns, and effective object-oriented techniques Key Features Build an intuitive understanding of object-oriented design, from introductory to mature programs Learn the ins and outs of Python syntax, libraries, and best practices Examine a machine-learning case study at the end of each chapter Book Description Object-oriented programming (OOP) is a popular design paradigm in which data and behaviors are encapsulated in such a way that they can be manipulated together. Python Object-Oriented Programming, Fourth Edition dives deep into the various aspects of OOP, Python as an OOP language, common and advanced design patterns, and hands-on data manipulation and testing of more complex OOP systems. These concepts are consolidated by open-ended exercises, as well as a real-world case study at the end of every chapter, newly written for this edition. All example code is now compatible with Python 3.9+ syntax and has been updated with type hints for ease of learning. Steven and Dusty provide a comprehensive, illustrative tour of important OOP concepts, such as inheritance, composition, and polymorphism, and explain how they work together with Python's classes and data structures to facilitate good design. In addition, the book also features an in-depth look at Python's exception handling and how functional programming intersects with OOP. Two very powerful automated testing systems, unittest and pytest, are introduced. The final chapter provides a detailed discussion of Python's concurrent programming ecosystem. By the end of the book, you will have a thorough understanding of how to think about and apply object-oriented principles using Python syntax and be able to confidently create robust and reliable programs. What you will learn Implement objects in Python by creating classes and defining methods Extend class functionality using inheritance Use exceptions to handle unusual situations cleanly Understand when to use object-oriented features, and more importantly, when not to use them Discover several widely used design patterns and how they are implemented in Python Uncover the simplicity of unit and integration testing and understand why they are so important Learn to statically type check your dynamic code Understand concurrency with asyncio and how it speeds up programs Who this book is for If you are new to object-oriented programming techniques, or if you have basic Python skills and wish to learn how and when to correctly apply OOP principles in Python, this is the book for you. Moreover, if you are an object-oriented programmer coming from other languages or seeking a leg up in the new world of Python, you will find this book a useful introduction to Python. Minimal previous experience with Python is necessary. |
| python reference guide: 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 reference guide: 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 reference guide: 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 reference guide: Introduction to Computation and Programming Using Python, second edition John V. Guttag, 2016-08-08 The new edition of an introductory text that teaches students the art of computational problem solving, covering topics ranging from simple algorithms to information visualization. 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 in a massive open online course (MOOC). This new edition has been updated for Python 3, reorganized to make it easier to use for courses that cover only a subset of the material, and offers additional material including five new chapters. 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. 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. This edition offers expanded material on statistics and machine learning and new chapters on Frequentist and Bayesian statistics. |
| python reference guide: 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 reference guide: 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 reference guide: Python GUI Programming - a Complete Reference Guide Alan D. Moore, B. M. Harwani, 2019-06-24 Explore Python's GUI frameworks and create visually stunning and feature-rich applications Key Features Integrate stunning data visualizations using Tkinter Canvas and Matplotlib Understand the basics of 2D and 3D animation in GUI applications Explore PyQt's powerful features to easily design and customize your GUI applications Book Description A responsive graphical user interface (GUI) helps you interact with your application, improves user experience, and enhances the efficiency of your applications. With Python, you'll have access to elaborate GUI frameworks that you can use to build interactive GUIs that stand apart from the rest. This Learning Path begins by introducing you to Tkinter and PyQt, before guiding you through the application development process. As you expand your GUI by adding more widgets, you'll work with networks, databases, and graphical libraries that enhance its functionality. You'll also learn how to connect to external databases and network resources, test your code, and maximize performance using asynchronous programming. In later chapters, you'll understand how to use the cross-platform features of Tkinter and Qt5 to maintain compatibility across platforms. You'll be able to mimic the platform-native look and feel, and build executables for deployment across popular computing platforms. By the end of this Learning Path, you'll have the skills and confidence to design and build high-end GUI applications that can solve real-world problems. This Learning Path includes content from the following Packt products: Python GUI Programming with Tkinter by Alan D. Moore Qt5 Python GUI Programming Cookbook by B. M. Harwani What you will learn Visualize graphs in real time with Tkinter's animation capabilities Use PostgreSQL authentication to ensure data security for your application Write unit tests to avoid regression when updating code Handle different signals generated on mouse clicks using QSpinBox and sliders Employ network concepts, internet browsing, and Google Maps in UI Use graphics rendering to implement animations in your GUI Who this book is for If you're an intermediate Python programmer looking to enhance your coding skills by writing powerful GUIs in Python using PyQT and Tkinter, this is an ideal Learning Path for you. A strong understanding of the Python language is a must to grasp the concepts explained in this book. |
| python reference guide: Python All-in-One For Dummies John C. Shovic, Alan Simpson, 2019-04-18 Your one-stop resource on all things Python Thanks to its flexibility, Python has grown to become one of the most popular programming languages in the world. Developers use Python in app development, web development, data science, machine learning, and even in coding education classes. There's almost no type of project that Python can't make better. From creating apps to building complex websites to sorting big data, Python provides a way to get the work done. Python All-in-One For Dummies offers a starting point for those new to coding by explaining the basics of Python and demonstrating how it’s used in a variety of applications. Covers the basics of the language Explains its syntax through application in high-profile industries Shows how Python can be applied to projects in enterprise Delves into major undertakings including artificial intelligence, physical computing, machine learning, robotics and data analysis This book is perfect for anyone new to coding as well as experienced coders interested in adding Python to their toolbox. |
| python reference guide: Powerful Python Aaron Maxwell, 2024-11-08 Once you've mastered the basics of Python, how do you skill up to the top 1%? How do you focus your learning time on topics that yield the most benefit for production engineering and data teams—without getting distracted by info of little real-world use? This book answers these questions and more. Based on author Aaron Maxwell's software engineering career in Silicon Valley, this unique book focuses on the Python first principles that act to accelerate everything else: the 5% of programming knowledge that makes the remaining 95% fall like dominos. It's also this knowledge that helps you become an exceptional Python programmer, fast. Learn how to think like a Pythonista: explore advanced Pythonic thinking Create lists, dicts, and other data structures using a high-level, readable, and maintainable syntax Explore higher-order function abstractions that form the basis of Python libraries Examine Python's metaprogramming tool for priceless patterns of code reuse Master Python's error model and learn how to leverage it in your own code Learn the more potent and advanced tools of Python's object system Take a deep dive into Python's automated testing and TDD Learn how Python logging helps you troubleshoot and debug more quickly |
| python reference guide: Beyond the Basic Stuff with Python Al Sweigart, 2020-12-16 BRIDGE THE GAP BETWEEN NOVICE AND PROFESSIONAL You've completed a basic Python programming tutorial or finished Al Sweigart's bestseller, Automate the Boring Stuff with Python. What's the next step toward becoming a capable, confident software developer? Welcome to Beyond the Basic Stuff with Python. More than a mere collection of advanced syntax and masterful tips for writing clean code, you'll learn how to advance your Python programming skills by using the command line and other professional tools like code formatters, type checkers, linters, and version control. Sweigart takes you through best practices for setting up your development environment, naming variables, and improving readability, then tackles documentation, organization and performance measurement, as well as object-oriented design and the Big-O algorithm analysis commonly used in coding interviews. The skills you learn will boost your ability to program--not just in Python but in any language. You'll learn: Coding style, and how to use Python's Black auto-formatting tool for cleaner code Common sources of bugs, and how to detect them with static analyzers How to structure the files in your code projects with the Cookiecutter template tool Functional programming techniques like lambda and higher-order functions How to profile the speed of your code with Python's built-in timeit and cProfile modules The computer science behind Big-O algorithm analysis How to make your comments and docstrings informative, and how often to write them How to create classes in object-oriented programming, and why they're used to organize code Toward the end of the book you'll read a detailed source-code breakdown of two classic command-line games, the Tower of Hanoi (a logic puzzle) and Four-in-a-Row (a two-player tile-dropping game), and a breakdown of how their code follows the book's best practices. You'll test your skills by implementing the program yourself. Of course, no single book can make you a professional software developer. But Beyond the Basic Stuff with Python will get you further down that path and make you a better programmer, as you learn to write readable code that's easy to debug and perfectly Pythonic Requirements: Covers Python 3.6 and higher |
| python reference guide: Introducing Python Bill Lubanovic, 2019-11-06 Easy to understand and fun to read, this updated edition of Introducing Python is ideal for beginning programmers as well as those new to the language. Author Bill Lubanovic takes you from the basics to more involved and varied topics, mixing tutorials with cookbook-style code recipes to explain concepts in Python 3. End-of-chapter exercises help you practice what you’ve learned. You’ll gain a strong foundation in the language, including best practices for testing, debugging, code reuse, and other development tips. This book also shows you how to use Python for applications in business, science, and the arts, using various Python tools and open source packages. |
| python reference guide: Learning Python Mark Lutz, 2007-10-22 Portable, powerful, and a breeze to use, Python is ideal for both standalone programs and scripting applications. With this hands-on book, you can master the fundamentals of the core Python language quickly and efficiently, whether you're new to programming or just new to Python. Once you finish, you will know enough about the language to use it in any application domain you choose. Learning Python is based on material from author Mark Lutz's popular training courses, which he's taught over the past decade. Each chapter is a self-contained lesson that helps you thoroughly understand a key component of Python before you continue. Along with plenty of annotated examples, illustrations, and chapter summaries, every chapter also contains Brain Builder, a unique section with practical exercises and review quizzes that let you practice new skills and test your understanding as you go. This book covers: Types and Operations -- Python's major built-in object types in depth: numbers, lists, dictionaries, and more Statements and Syntax -- the code you type to create and process objects in Python, along with Python's general syntax model Functions -- Python's basic procedural tool for structuring and reusing code Modules -- packages of statements, functions, and other tools organized into larger components Classes and OOP -- Python's optional object-oriented programming tool for structuring code for customization and reuse Exceptions and Tools -- exception handling model and statements, plus a look at development tools for writing larger programs Learning Python gives you a deep and complete understanding of the language that will help you comprehend any application-level examples of Python that you later encounter. If you're ready to discover what Google and YouTube see in Python, this book is the best way to get started. |
| python reference guide: 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 reference guide: Python Phrasebook Brad Dayley, 2006 A pocket guide jam-packed with immediately useful and essential code phrases for the Python developer's everyday use! |
| python reference guide: Murachs Python Programming Joel Murach, Michael Urban, 2016 This book is for anyone who wants to learn Python. If Python is your first programming language, it helps you master all the skills and concepts you need to program in any modern language, as you learn Python itself. If you're an experienced programmer who wants to add Python to your resume, it will help you learn Python faster and better. |
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 …
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 …
