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3.7 Code Practice Python: Mastering the Fundamentals and Beyond
Author: Dr. Anya Sharma, PhD in Computer Science, Associate Professor at the University of California, Berkeley, specializing in Python programming and software engineering education.
Keywords: 3.7 code practice python, Python 3.7 practice, Python 3.7 exercises, Python coding practice, learn Python 3.7, Python 3.7 tutorial, Python programming practice, Python 3.7 code examples, improve Python skills, Python 3.7 challenges.
Publisher: TechVerse Publications, a leading publisher of technical and academic books and online resources known for its rigorous editorial process and commitment to accuracy and clarity.
Editor: Mr. David Chen, Senior Editor at TechVerse Publications, with 15 years of experience editing technical documentation and programming tutorials.
Summary: This comprehensive guide dives deep into "3.7 code practice Python," providing a structured approach to mastering Python programming using the features and functionalities of Python 3.7. It explores the significance of practical exercises in solidifying theoretical knowledge, detailing various practice methods, resources, and strategies to enhance coding skills. We will cover fundamental concepts like data types, control structures, functions, and object-oriented programming, all within the context of Python 3.7, highlighting specific features available in this version. The article will also address advanced topics, offering challenges and projects to push learners beyond the basics. The aim is to equip readers with the practical experience necessary to confidently develop Python programs and solve real-world problems.
1. The Importance of 3.7 Code Practice Python
The significance of hands-on practice in mastering any programming language, especially Python, cannot be overstated. While understanding the theoretical concepts of Python 3.7 is essential, translating that knowledge into functional code through consistent 3.7 code practice Python is crucial for developing proficiency. Python 3.7, a stable and widely-used version, offers a rich set of features, and practicing with it solidifies your understanding of these features and builds your coding intuition. This practice strengthens problem-solving skills, allowing you to approach challenges methodically and efficiently. Furthermore, consistent 3.7 code practice Python enhances your ability to debug code, identify errors, and implement solutions effectively, a vital skill for any programmer.
2. Fundamental Concepts in 3.7 Code Practice Python
This section outlines the core areas of Python 3.7 that require dedicated practice:
Data Types: Mastering data types like integers, floats, strings, booleans, lists, tuples, dictionaries, and sets is foundational. 3.7 code practice Python should include numerous exercises involving data manipulation, type conversions, and utilizing the built-in functions for each data type.
Control Structures: Practicing with `if`, `elif`, `else` statements, `for` and `while` loops is crucial for controlling the flow of execution in your programs. 3.7 code practice Python examples should include scenarios demanding iterative processes and conditional logic. Implementing nested loops and conditional statements effectively will solidify understanding.
Functions: Functions are vital for modularity and reusability. Practice defining and calling functions, using arguments and return values, and understanding function scope. 3.7 code practice Python exercises should cover various function types, including recursive functions and lambda functions.
Object-Oriented Programming (OOP): Python supports OOP concepts like classes, objects, inheritance, polymorphism, and encapsulation. Building classes, creating instances, and utilizing OOP principles in your programs is crucial. 3.7 code practice Python should include examples of designing classes representing real-world entities and implementing inheritance and polymorphism.
Modules and Packages: Learning how to import and use external modules and packages is essential for expanding your programming capabilities. Practice working with popular libraries like `math`, `random`, `datetime`, and `os`. 3.7 code practice Python exercises should involve solving problems using functionalities provided by these libraries.
File Handling: Practicing file input/output operations is crucial for working with external data. Learn to read from and write to files using different modes. 3.7 code practice Python should include examples of reading data from CSV files, writing data to text files, and handling file exceptions.
Error Handling: Mastering exception handling with `try`, `except`, `finally` blocks is vital for robust programming. 3.7 code practice Python should involve coding scenarios prone to errors (e.g., file not found, division by zero) and implementing proper error handling techniques.
3. Strategies for Effective 3.7 Code Practice Python
Start with the basics: Begin with fundamental concepts and gradually move towards more complex topics.
Break down problems: Decompose complex problems into smaller, manageable parts.
Use online resources: Leverage online tutorials, documentation, and code examples to aid your learning.
Solve coding challenges: Participate in online coding challenges on platforms like HackerRank, LeetCode, and Codewars.
Build small projects: Create small, self-contained projects to apply your knowledge and build your portfolio.
Collaborate with others: Discuss coding challenges and share solutions with fellow learners.
Review and refactor: Regularly review your code and refactor it to improve efficiency and readability.
4. Resources for 3.7 Code Practice Python
Numerous resources are available to support your 3.7 code practice Python journey:
Online tutorials: Websites like Codecademy, Udemy, Coursera, and freeCodeCamp offer interactive Python tutorials and courses.
Python documentation: The official Python documentation is a comprehensive resource for learning the language's features and functionalities.
Online coding platforms: HackerRank, LeetCode, and Codewars provide coding challenges and exercises of varying difficulty.
Books: Numerous books are available on Python programming, ranging from beginner to advanced levels.
5. Advanced 3.7 Code Practice Python: Tackling Complex Challenges
Once you’ve mastered the fundamentals, you should transition to more advanced topics and challenges. These might include:
Working with databases: Practice connecting to databases (e.g., SQLite, MySQL, PostgreSQL) and performing database operations.
Web development: Learn web frameworks like Django or Flask to build web applications.
Data analysis and visualization: Explore libraries like NumPy, Pandas, and Matplotlib for data analysis and visualization.
Machine learning: Delve into machine learning libraries like scikit-learn to build predictive models.
6. Debugging and Troubleshooting in 3.7 Code Practice Python
Effective debugging is a critical skill. Learn to use debugging tools, interpret error messages, and use print statements to trace program execution. Practice identifying common errors like syntax errors, runtime errors, and logic errors.
7. Maintaining and Refactoring Code
As your projects grow in complexity, maintainability becomes crucial. Learn to write clean, well-documented code. Regularly refactor your code to improve efficiency and readability. Use version control systems like Git to track changes and collaborate effectively.
8. Building a Python Portfolio
As you progress with 3.7 code practice Python, start building a portfolio of your projects. This demonstrates your skills to potential employers or clients. Choose projects that showcase your abilities and highlight your problem-solving skills.
Conclusion
Consistent 3.7 code practice Python is paramount for success in programming. By focusing on the fundamentals, utilizing diverse resources, and tackling progressively challenging projects, you can significantly improve your Python skills and build a strong foundation for a rewarding career in software development or related fields. Remember to be patient, persistent, and enjoy the learning process!
FAQs
1. What are the key differences between Python 3.7 and earlier versions? Python 3.7 introduced several enhancements, including improved data classes, asyncio enhancements, and breakpoint() for easier debugging.
2. Is it necessary to learn Python 3.7 specifically, or can I use a later version? While newer versions build upon 3.7, understanding the fundamentals in 3.7 provides a solid base for learning subsequent versions.
3. Where can I find Python 3.7 documentation? The official Python documentation is readily available online and provides comprehensive information.
4. What are some good resources for beginners learning Python 3.7? Codecademy, freeCodeCamp, and various YouTube channels offer excellent beginner tutorials.
5. How much time should I dedicate daily to 3.7 code practice Python? A consistent 30 minutes to an hour of daily practice can yield significant results.
6. What are some common mistakes beginners make when learning Python 3.7? Common mistakes include indentation errors, incorrect variable assignments, and misunderstanding scope.
7. How can I overcome the frustration of debugging? Break down problems into smaller parts, use debugging tools effectively, and don't hesitate to seek help from online communities.
8. Is it important to learn a specific IDE for Python 3.7? While not mandatory, using an IDE like VS Code or PyCharm can enhance your coding experience with features like autocompletion and debugging tools.
9. What kind of projects can I work on to improve my Python 3.7 skills? Start with small projects like simple calculators, text-based games, or basic data analysis tasks.
Related Articles
1. "Mastering Data Structures in Python 3.7": This article focuses on in-depth exploration of various data structures and their efficient implementation in Python 3.7, including advanced techniques.
2. "Python 3.7 for Data Science: A Practical Guide": This guide provides a hands-on introduction to data analysis and manipulation using Python 3.7 and popular libraries like NumPy and Pandas.
3. "Building Web Applications with Python 3.7 and Flask": This tutorial will guide you through building simple to complex web applications using the Flask framework and Python 3.7.
4. "Introduction to Object-Oriented Programming with Python 3.7": This article teaches the core principles of object-oriented programming and demonstrates how to implement them effectively within Python 3.7.
5. "Advanced Python 3.7: Working with Databases and APIs": Explores database interactions (SQLAlchemy, etc.) and API integration in Python 3.7.
6. "Debugging Techniques for Python 3.7": This article will focus on advanced debugging strategies and tools for resolving complex issues in Python 3.7 programs.
7. "Best Practices for Python 3.7 Code Style and Readability": This guide will cover code style guidelines, documentation techniques, and best practices for writing clean, maintainable Python 3.7 code.
8. "Python 3.7 for Beginners: A Step-by-Step Tutorial": This tutorial provides a gentle introduction to Python 3.7, perfect for absolute beginners.
9. "Python 3.7 Projects for Beginners: Build Your Portfolio": This article suggests several beginner-friendly projects to build your Python 3.7 skills and create a portfolio.
| 37 code practice python: Python for Everybody Charles R. Severance, 2016-04-09 Python for Everybody is designed to introduce students to programming and software development through the lens of exploring data. You can think of the Python programming language as your tool to solve data problems that are beyond the capability of a spreadsheet.Python is an easy to use and easy to learn programming language that is freely available on Macintosh, Windows, or Linux computers. So once you learn Python you can use it for the rest of your career without needing to purchase any software.This book uses the Python 3 language. The earlier Python 2 version of this book is titled Python for Informatics: Exploring Information.There are free downloadable electronic copies of this book in various formats and supporting materials for the book at www.pythonlearn.com. The course materials are available to you under a Creative Commons License so you can adapt them to teach your own Python course. |
| 37 code practice python: Coding for Kids: Python Adrienne B. Tacke, 2019-03-19 Games and activities that teach kids ages 10+ to code with Python Learning to code isn't as hard as it sounds—you just have to get started! Coding for Kids: Python starts kids off right with 50 fun, interactive activities that teach them the basics of the Python programming language. From learning the essential building blocks of programming to creating their very own games, kids will progress through unique lessons packed with helpful examples—and a little silliness! Kids will follow along by starting to code (and debug their code) step by step, seeing the results of their coding in real time. Activities at the end of each chapter help test their new knowledge by combining multiple concepts. For young programmers who really want to show off their creativity, there are extra tricky challenges to tackle after each chapter. All kids need to get started is a computer and this book. This beginner's guide to Python for kids includes: 50 Innovative exercises—Coding concepts come to life with game-based exercises for creating code blocks, drawing pictures using a prewritten module, and more. Easy-to-follow guidance—New coders will be supported by thorough instructions, sample code, and explanations of new programming terms. Engaging visual lessons—Colorful illustrations and screenshots for reference help capture kids' interest and keep lessons clear and simple. Encourage kids to think independently and have fun learning an amazing new skill with this coding book for kids. |
| 37 code practice python: Python in Practice Mark Summerfield, 2013 Winner of the 2014 Jolt Award for Best Book Whether you are an experienced programmer or are starting your career, Python in Practice is full of valuable advice and example to help you improve your craft by thinking about problems from different perspectives, introducing tools, and detailing techniques to create more effective solutions. --Doug Hellmann, Senior Developer, DreamHost If you're an experienced Python programmer, Python in Practice will help you improve the quality, reliability, speed, maintainability, and usability of all your Python programs. Mark Summerfield focuses on four key themes: design patterns for coding elegance, faster processing through concurrency and compiled Python (Cython), high-level networking, and graphics. He identifies well-proven design patterns that are useful in Python, illuminates them with expert-quality code, and explains why some object-oriented design patterns are irrelevant to Python. He also explodes several counterproductive myths about Python programming--showing, for example, how Python can take full advantage of multicore hardware. All examples, including three complete case studies, have been tested with Python 3.3 (and, where possible, Python 3.2 and 3.1) and crafted to maintain compatibility with future Python 3.x versions. All code has been tested on Linux, and most code has also been tested on OS X and Windows. All code may be downloaded at www.qtrac.eu/pipbook.html. Coverage includes Leveraging Python's most effective creational, structural, and behavioral design patterns Supporting concurrency with Python's multiprocessing, threading, and concurrent.futures modules Avoiding concurrency problems using thread-safe queues and futures rather than fragile locks Simplifying networking with high-level modules, including xmlrpclib and RPyC Accelerating Python code with Cython, C-based Python modules, profiling, and other techniques Creating modern-looking GUI applications with Tkinter Leveraging today's powerful graphics hardware via the OpenGL API using pyglet and PyOpenGL |
| 37 code practice python: Python Programming in Context Bradley N. Miller, David L. Ranum, Julie Anderson, 2019-10-01 Python Programming in Context, Third Edition provides a comprehensive and accessible introduction to Python fundamentals. Updated with the latest version of Python, the new Third Edition offers a thorough overview of multiple applied areas, including image processing, cryptography, astronomy, the Internet, and bioinformatics. Taking an active learning approach, each chapter starts with a comprehensive real-world project that teaches core design techniques and Python programming while engaging students. An ideal first language for learners entering the rapidly expanding field of computer science, Python gives students a solid platform of key problem-solving skills that translate easily across programming languages. |
| 37 code practice python: 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! |
| 37 code practice python: 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 |
| 37 code practice python: Python Tutorial 3.11.3 Guido Van Rossum, Python Development Team, 2023-05-12 |
| 37 code practice python: 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 |
| 37 code practice python: Learn Python the Hard Way Zed Shaw, 2014 Master Python and become a programmer - even if you never thought you could. This breakthrough book and CD can help practically anyone get started in programming. Zed A. Shaw teaches the Python programming language through a series of 52 brilliantly-crafted exercises. |
| 37 code practice python: Python Basics Dan Bader, Joanna Jablonski, Fletcher Heisler, 2021-03-16 Make the Leap From Beginner to Intermediate in Python... Python Basics: A Practical Introduction to Python 3 Your Complete Python Curriculum-With Exercises, Interactive Quizzes, and Sample Projects What should you learn about Python in the beginning to get a strong foundation? With Python Basics, you'll not only cover the core concepts you really need to know, but you'll also learn them in the most efficient order with the help of practical exercises and interactive quizzes. You'll know enough to be dangerous with Python, fast! Who Should Read This Book If you're new to Python, you'll get a practical, step-by-step roadmap on developing your foundational skills. You'll be introduced to each concept and language feature in a logical order. Every step in this curriculum is explained and illustrated with short, clear code samples. Our goal with this book is to educate, not to impress or intimidate. If you're familiar with some basic programming concepts, you'll get a clear and well-tested introduction to Python. This is a practical introduction to Python that jumps right into the meat and potatoes without sacrificing substance. If you have prior experience with languages like VBA, PowerShell, R, Perl, C, C++, C#, Java, or Swift the numerous exercises within each chapter will fast-track your progress. If you're a seasoned developer, you'll get a Python 3 crash course that brings you up to speed with modern Python programming. Mix and match the chapters that interest you the most and use the interactive quizzes and review exercises to check your learning progress as you go along. If you're a self-starter completely new to coding, you'll get practical and motivating examples. You'll begin by installing Python and setting up a coding environment on your computer from scratch, and then continue from there. We'll get you coding right away so that you become competent and knowledgeable enough to solve real-world problems, fast. Develop a passion for programming by solving interesting problems with Python every day! If you're looking to break into a coding or data-science career, you'll pick up the practical foundations with this book. We won't just dump a boat load of theoretical information on you so you can sink or swim-instead you'll learn from hands-on, practical examples one step at a time. Each concept is broken down for you so you'll always know what you can do with it in practical terms. If you're interested in teaching others how to Python, this will be your guidebook. If you're looking to stoke the coding flame in your coworkers, kids, or relatives-use our material to teach them. All the sequencing has been done for you so you'll always know what to cover next and how to explain it. What Python Developers Say About The Book: Go forth and learn this amazing language using this great book. - Michael Kennedy, Talk Python The wording is casual, easy to understand, and makes the information flow well. - Thomas Wong, Pythonista I floundered for a long time trying to teach myself. I slogged through dozens of incomplete online tutorials. I snoozed through hours of boring screencasts. I gave up on countless crufty books from big-time publishers. And then I found Real Python. The easy-to-follow, step-by-step instructions break the big concepts down into bite-sized chunks written in plain English. The authors never forget their audience and are consistently thorough and detailed in their explanations. I'm up and running now, but I constantly refer to the material for guidance. - Jared Nielsen, Pythonista |
| 37 code practice python: Python Programming Fundamentals Kent D. Lee, 2010-10-26 Computer programming is a skill that can bring great enjoyment from the creativity involved in designing and implementing a solution to a problem. This classroom-tested and easy-to-follow textbook teaches the reader how to program using Python, an accessible language which can be learned incrementally. Through an extensive use of examples and practical exercises, students will learn to recognize and apply abstract patterns in programming, as well as how to inspect the state of a program using a debugger tool. Features: contains numerous examples and solved practice exercises designed for an interactive classroom environment; highlights several patterns which commonly appear in programs, and presents exercises that reinforce recognition and application of these patterns; introduces the use of a debugger, and includes supporting material that reveals how programs work; presents the Tkinter framework for building graphical user interface applications and event-driven programs; provides helpful additional resources for instructors at the associated website: http://cs.luther.edu/~leekent/CS1. This hands-on textbook for active learning in the classroom will enable undergraduates in computer science to develop the necessary skills to begin developing their own programs. It employs Python as the introductory language due to the wealth of support available for programmers. |
| 37 code practice python: Ultimate Python Programming Deepali Srivastava, 2024-05-16 Dive deep into the core concepts of Python KEY FEATURES ● The concepts in this book are illustrated through numerous short code snippets and more than 650 programming examples. ● The book contains a comprehensive collection of over 900 end-of-chapter exercises, including both MCQs and programming exercises. The solutions to all the exercises are also available. ● The book includes coding conventions and best practices for writing efficient, readable, and maintainable code. DESCRIPTION This book provides a comprehensive and thorough introduction to Python, a popular programming language used by various top companies across various domains. Whether you are a novice starting your programming journey or an experienced programmer looking to expand your skill set, this book is designed to assist you in mastering core Python concepts. Starting with the basics, this book guides you through the setup, basic commands, and key language rules. The book covers important ideas like different types of data, variables, and how to control the flow of your programs. You will also learn about collections for organizing data, functions for reusable code, modules for organizing bigger projects, and object-oriented programming for modeling real-world things. Advanced topics include customizing object behavior, efficient data processing, modifying function behavior, and handling errors gracefully. The book includes many figures and coding examples to give you a visual and hands-on experience. There are numerous exercises that provide opportunities to further reinforce your knowledge. By the end of this book, readers will develop a strong foundation in core Python and will gain the confidence to excel in their studies and professional work. WHAT YOU WILL LEARN ● Develop programs using procedural, object-oriented, and functional paradigms. ● Understand complex topics like iterators, generators, and decorators. ● Learn how to create and use modules and packages. ● Master the advanced concepts of object-oriented programming. ● Learn how to handle errors in Python and interact with files. ● Automate resource management patterns using context managers. WHO THIS BOOK IS FOR This book can be used by anyone who wants to learn Python from scratch. It can be a valuable resource for engineering students and students from other streams who have Python as part of their curriculum. This book facilitates a swift introduction to the language for individuals aiming to transition into data science, AI, or ML. TABLE OF CONTENTS 1. Introduction to Python 2. Getting Started 3. Strings 4. Lists and Tuples 5. Dictionaries and Sets 6. Conditional Execution 7. Loops 8. Looping Techniques 9. Comprehensions 10. Functions 11. Modules and Packages 12. Namespaces and Scope 13. Files 14. Object Oriented Programming 15. Magic Methods 16. Inheritance and Polymorphism 17. Iterators and Generators 18. Decorators 19. Lambda Expressions and Functional Programming 20. Exception Handling 21. Context Managers Solutions |
| 37 code practice python: Head First Python Paul Barry, 2016-11-21 Want to learn the Python language without slogging your way through how-to manuals? With Head First Python, you’ll quickly grasp Python’s fundamentals, working with the built-in data structures and functions. Then you’ll move on to building your very own webapp, exploring database management, exception handling, and data wrangling. If you’re intrigued by what you can do with context managers, decorators, comprehensions, and generators, it’s all here. This second edition is a complete learning experience that will help you become a bonafide Python programmer in no time. Why does this book look so different? Based on the latest research in cognitive science and learning theory, Head First Pythonuses a visually rich format to engage your mind, rather than a text-heavy approach that puts you to sleep. Why waste your time struggling with new concepts? This multi-sensory learning experience is designed for the way your brain really works. |
| 37 code practice python: 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. |
| 37 code practice python: Python Programming in Context Julie Anderson, Jon Anderson, 2024-04-29 Python Programming in Context provides a comprehensive and accessible introduction to Python fundamentals. Taking an active learning approach, each chapter starts with a comprehensive real-world project that teaches core design techniques and Python programming to immediately engage students. An ideal first language for learners entering the rapidly expanding fields of computer science, data science, and scientific programming, this comprehensive textbook gives students a solid platform of key problem-solving skills that translate easily across programming languages-- |
| 37 code practice python: Python Institute PCAP Practice Exam Anthony Daccache, Certified Associate in Python Programming certification focuses on the Object-Oriented Programming approach to Python, and shows that the individual is familiar with the more advanced aspects of programming, including the essentials of OOP, the essentials of modules and packages, the exception handling mechanism in OOP, advanced operations on strings, list comprehensions, lambdas, generators, closures, and file processing. PCAP certification gives its holders confidence in their programming skills, helps them stand out in the job market, and gives them a head start on preparing for and advancing to the professional level. Certified Associate in Python Programming certification is a professional, high-stakes credential that measures the candidate's ability to perform intermediate-level coding tasks in the Python language, including the ability to design, develop, debug, execute, and refactor multi-module Python programs, as well as measures their skills and knowledge related to analyzing and modeling real-life problems in OOP categories with the use of the fundamental notions and techniques available in the object-oriented approach. The PCAP certification shows that the individual is familiar with the following concepts: modules, packages, and PIP, character encoding, strings and string processing, generators, iterators, closures, files, file streams, and file processing, exception hierarchies, and exception classes and objects, working with selected Standard Library modules, and the fundamentals of the Object-Oriented Programming (OOP) approach. PCAP: Exam Information Exam Duration: 65 minutes, NDA/Tutorial: 10 minutes Number of Questions : 40 Format : single- and multiple-select questions Python 3.x Passing score: 70% Language: English |
| 37 code practice python: A Primer on Scientific Programming with Python Hans Petter Langtangen, 2016-07-28 The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example and problem-oriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology and finance. The book teaches Matlab-style and procedural programming as well as object-oriented programming. High school mathematics is a required background and it is advantageous to study classical and numerical one-variable calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in various branches of science and engineering, with the aid of numerical methods and programming. By blending programming, mathematics and scientific applications, the book lays a solid foundation for practicing computational science. From the reviews: Langtangen ... does an excellent job of introducing programming as a set of skills in problem solving. He guides the reader into thinking properly about producing program logic and data structures for modeling real-world problems using objects and functions and embracing the object-oriented paradigm. ... Summing Up: Highly recommended. F. H. Wild III, Choice, Vol. 47 (8), April 2010 Those of us who have learned scientific programming in Python ‘on the streets’ could be a little jealous of students who have the opportunity to take a course out of Langtangen’s Primer.” John D. Cook, The Mathematical Association of America, September 2011 This book goes through Python in particular, and programming in general, via tasks that scientists will likely perform. It contains valuable information for students new to scientific computing and would be the perfect bridge between an introduction to programming and an advanced course on numerical methods or computational science. Alex Small, IEEE, CiSE Vol. 14 (2), March /April 2012 “This fourth edition is a wonderful, inclusive textbook that covers pretty much everything one needs to know to go from zero to fairly sophisticated scientific programming in Python...” Joan Horvath, Computing Reviews, March 2015 |
| 37 code practice python: Python in Practice Mark Summerfield, 2013-08-20 Winner of the 2014 Jolt Award for Best Book “Whether you are an experienced programmer or are starting your career, Python in Practice is full of valuable advice and example to help you improve your craft by thinking about problems from different perspectives, introducing tools, and detailing techniques to create more effective solutions.” —Doug Hellmann, Senior Developer, DreamHost If you’re an experienced Python programmer, Python in Practice will help you improve the quality, reliability, speed, maintainability, and usability of all your Python programs. Mark Summerfield focuses on four key themes: design patterns for coding elegance, faster processing through concurrency and compiled Python (Cython), high-level networking, and graphics. He identifies well-proven design patterns that are useful in Python, illuminates them with expert-quality code, and explains why some object-oriented design patterns are irrelevant to Python. He also explodes several counterproductive myths about Python programming—showing, for example, how Python can take full advantage of multicore hardware. All examples, including three complete case studies, have been tested with Python 3.3 (and, where possible, Python 3.2 and 3.1) and crafted to maintain compatibility with future Python 3.x versions. All code has been tested on Linux, and most code has also been tested on OS X and Windows. All code may be downloaded at www.qtrac.eu/pipbook.html. Coverage includes Leveraging Python’s most effective creational, structural, and behavioral design patterns Supporting concurrency with Python’s multiprocessing, threading, and concurrent.futures modules Avoiding concurrency problems using thread-safe queues and futures rather than fragile locks Simplifying networking with high-level modules, including xmlrpclib and RPyC Accelerating Python code with Cython, C-based Python modules, profiling, and other techniques Creating modern-looking GUI applications with Tkinter Leveraging today’s powerful graphics hardware via the OpenGL API using pyglet and PyOpenGL |
| 37 code practice python: Taming PYTHON By Programming Jeeva Jose, This is a great book for Python Beginner and Advanced Learner which covers Basics to Advanced Python Programming where each topic is explained with the help of Illustrations and Examples. More than 450 solved programs of this book are tested in Python 3.4.3 for windows. The range of Python Topics covered makes this book unique which can be used as a self study material or for instructor assisted teaching. This books covers Python Syllabus of all major national and international universities. Also it includes frequently asked questions for interviews and examination which are provided at the end of each chapter. |
| 37 code practice python: Programming in Python 3 Mark Summerfield, 2008-12-16 Python 3 is the best version of the language yet: It is more powerful, convenient, consistent, and expressive than ever before. Now, leading Python programmer Mark Summerfield demonstrates how to write code that takes full advantage of Python 3’s features and idioms. The first book written from a completely “Python 3” viewpoint, Programming in Python 3 brings together all the knowledge you need to write any program, use any standard or third-party Python 3 library, and create new library modules of your own. Summerfield draws on his many years of Python experience to share deep insights into Python 3 development you won’t find anywhere else. He begins by illuminating Python’s “beautiful heart”: the eight key elements of Python you need to write robust, high-performance programs. Building on these core elements, he introduces new topics designed to strengthen your practical expertise—one concept and hands-on example at a time. This book’s coverage includes Developing in Python using procedural, object-oriented, and functional programming paradigms Creating custom packages and modules Writing and reading binary, text, and XML files, including optional compression, random access, and text and XML parsing Leveraging advanced data types, collections, control structures, and functions Spreading program workloads across multiple processes and threads Programming SQL databases and key-value DBM files Utilizing Python’s regular expression mini-language and module Building usable, efficient, GUI-based applications Advanced programming techniques, including generators, function and class decorators, context managers, descriptors, abstract base classes, metaclasses, and more Programming in Python 3 serves as both tutorial and language reference, and it is accompanied by extensive downloadable example code—all of it tested with the final version of Python 3 on Windows, Linux, and Mac OS X. |
| 37 code practice python: Learn to Code by Solving Problems Daniel Zingaro, 2021-06-29 Learn to Code by Solving Problems is a practical introduction to programming using Python. It uses coding-competition challenges to teach you the mechanics of coding and how to think like a savvy programmer. Computers are capable of solving almost any problem when given the right instructions. That’s where programming comes in. This beginner’s book will have you writing Python programs right away. You’ll solve interesting problems drawn from real coding competitions and build your programming skills as you go. Every chapter presents problems from coding challenge websites, where online judges test your solutions and provide targeted feedback. As you practice using core Python features, functions, and techniques, you’ll develop a clear understanding of data structures, algorithms, and other programming basics. Bonus exercises invite you to explore new concepts on your own, and multiple-choice questions encourage you to think about how each piece of code works. You’ll learn how to: Run Python code, work with strings, and use variables Write programs that make decisions Make code more efficient with while and for loops Use Python sets, lists, and dictionaries to organize, sort, and search data Design programs using functions and top-down design Create complete-search algorithms and use Big O notation to design more efficient code By the end of the book, you’ll not only be proficient in Python, but you’ll also understand how to think through problems and tackle them with code. Programming languages come and go, but this book gives you the lasting foundation you need to start thinking like a programmer. |
| 37 code practice python: Masterminds of Programming Federico Biancuzzi, Chromatic, 2009-03-21 Masterminds of Programming features exclusive interviews with the creators of several historic and highly influential programming languages. In this unique collection, you'll learn about the processes that led to specific design decisions, including the goals they had in mind, the trade-offs they had to make, and how their experiences have left an impact on programming today. Masterminds of Programming includes individual interviews with: Adin D. Falkoff: APL Thomas E. Kurtz: BASIC Charles H. Moore: FORTH Robin Milner: ML Donald D. Chamberlin: SQL Alfred Aho, Peter Weinberger, and Brian Kernighan: AWK Charles Geschke and John Warnock: PostScript Bjarne Stroustrup: C++ Bertrand Meyer: Eiffel Brad Cox and Tom Love: Objective-C Larry Wall: Perl Simon Peyton Jones, Paul Hudak, Philip Wadler, and John Hughes: Haskell Guido van Rossum: Python Luiz Henrique de Figueiredo and Roberto Ierusalimschy: Lua James Gosling: Java Grady Booch, Ivar Jacobson, and James Rumbaugh: UML Anders Hejlsberg: Delphi inventor and lead developer of C# If you're interested in the people whose vision and hard work helped shape the computer industry, you'll find Masterminds of Programming fascinating. |
| 37 code practice python: Get Programming Ana Bell, 2018-03-27 Get Programming: Learn to code with Python teaches you the basics of computer programming using the Python language. In this exercise-driven book, you'll be doing something on nearly every page as you work through 38 compact lessons and 7 engaging capstone projects. By exploring the crystal-clear illustrations, exercises that check your understanding as you go, and tips for what to try next, you'll start thinking like a programmer in no time. This book works perfectly alongside our video course Get Programming with Python in Motion, available exclusively at Manning.com: www.manning.com/livevideo/get-programming-with-python-in-motion Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. What's Inside Programming skills you can use in any language Learn to code—no experience required Learn Python, the language for beginners Dozens of exercises and examples help you learn by doing About the Reader No prior programming experience needed. Table of Contents LEARNING HOW TO PROGRAM Lesson 1 - Why should you learn how to program? Lesson 2 - Basic principles of learning a programming language UNIT 1 - VARIABLES, TYPES, EXPRESSIONS, AND STATEMENTS Lesson 3 - Introducing Python: a programming language Lesson 4 - Variables and expressions: giving names and values to things Lesson 5 - Object types and statements of code 46 Lesson 6 - Capstone project: your first Python program-convert hours to minutes UNIT 2 - STRINGS, TUPLES, AND INTERACTING WITH THE USER Lesson 7 - Introducing string objects: sequences of characters Lesson 8 - Advanced string operations Lesson 9 - Simple error messages Lesson 10 - Tuple objects: sequences of any kind of object Lesson 11 - Interacting with the user Lesson 12 - Capstone project: name mashup UNIT 3 - MAKING DECISIONS IN YOUR PROGRAMS Lesson 13 - Introducing decisions in programs Lesson 14 - Making more-complicated decisions Lesson 15 - Capstone project: choose your own adventure UNIT 4 - REPEATING TASKS Lesson 16 - Repeating tasks with loops Lesson 17 - Customizing loops Lesson 18 - Repeating tasks while conditions hold Lesson 19 - Capstone project: Scrabble, Art Edition UNIT 5 - ORGANIZING YOUR CODE INTO REUSABLE BLOCKS Lesson 20 - Building programs to last Lesson 21 - Achieving modularity and abstraction with functions Lesson 22 - Advanced operations with functions Lesson 23 - Capstone project: analyze your friends UNIT 6 - WORKING WITH MUTABLE DATA TYPES Lesson 24 - Mutable and immutable objects Lesson 25 - Working with lists Lesson 26 - Advanced operations with lists Lesson 27 - Dictionaries as maps between objects Lesson 28 - Aliasing and copying lists and dictionaries Lesson 29 - Capstone project: document similarity UNIT 7 - MAKING YOUR OWN OBJECT TYPES BY USING OBJECT-ORIENTED PROGRAMMING Lesson 30 - Making your own object types Lesson 31 - Creating a class for an object type Lesson 32 - Working with your own object types Lesson 33 - Customizing classes Lesson 34 - Capstone project: card game UNIT 8 - USING LIBRARIES TO ENHANCE YOUR PROGRAMS Lesson 35 - Useful libraries Lesson 36 - Testing and debugging your programs Lesson 37 - A library for graphical user interfaces Lesson 38 - Capstone project: game of tag Appendix A - Answers to lesson exercises Appendix B - Python cheat sheet Appendix C - Interesting Python libraries |
| 37 code practice python: The Practice of Reproducible Research Justin Kitzes, Daniel Turek, Fatma Deniz, 2018 The Practice of Reproducible Research presents concrete examples of how researchers in the data-intensive sciences are working to improve the reproducibility of their research projects. In each of the thirty-one case studies in this volume, the author or team describes the workflow that they used to complete a real-world research project. Authors highlight how they utilized particular tools, ideas, and practices to support reproducibility, emphasizing the very practical how, rather than the why or what, of conducting reproducible research. Part 1 provides an accessible introduction to reproducible research, a basic reproducible research project template, and a synthesis of lessons learned from across the thirty-one case studies. Parts 2 and 3 focus on the case studies themselves. The Practice of Reproducible Research is an invaluable resource for students and researchers who wish to better understand the practice of data-intensive sciences and learn how to make their own research more reproducible. |
| 37 code practice python: BBC Micro:bit in Practice Ashwin Pajankar, Abhishek Sharma, Sandeep Saini, 2022-12-09 Develop real-world interactive physical computing applications using the Micro:bit with more than 100 MicroPython examples with circuit diagrams Key FeaturesExplore hardware programming and leverage the power of the BBC Micro:bit and MicroPythonBuild real-life creative projects step by step with each chapter increasing in complexity and interactivityLearn the features of the Micro:bit and how to interface it with electronic components through circuits and code examplesBook Description This book is a one-stop guide for learning BBC Micro:bit with MicroPython, exploring many hardware components and programming techniques to provide detailed insights into developing practical applications with the Micro:bit. It will also show you how hardware components can be manipulated using a combination of Micro:bit and MicroPython for developing practical projects. BBC Micro:bit in Practice will help you gain a holistic understanding of the BBC Micro:bit platform and MicroPython programming, guiding you through mini projects aimed at developing practical knowledge of circuit design and writing programs. You'll learn how to write programs for working with built-in LEDs and buttons, interfacing external LEDs, buttons, motors, buzzers, and much more. You'll also work with built-in radio, speakers, accelerometer, and a compass. You'll dive into concepts related to the Micro:bit filesystem, interfacing external displays, and working with libraries in detail before exploring sewable circuits and wearable technology. After reading this Micro:bit book, you'll understand how to apply principles in electronics and MicroPython to create interesting real-life projects from scratch. What you will learnExplore the essentials of the BBC Micro:bit, its hardware specifications, and versionsProgram built-in and external LEDs and buttonsProgram external LED-based displays, buzzers, and stepper motorsUse analog input and pulse width modulation to drive a servo motorDetect gestures with internal sensors such as accelerometer, compass, and magnetometerWork on projects with built-in features such as music, speech, radio, and filesystemExplore the advanced features of the Micro:bitWho this book is for This book is for anyone who wants to use the combination of MicroPython and the BBC Micro:bit for building exciting real-life projects. Engineers, researchers, hobbyists, and technology instructors working in areas such as embedded systems, electronics, software development, IoT, robotics, teaching, and training will find this book useful for building projects. Prior experience with building basic electronic circuits and any programming language, not necessarily MicroPython, will be helpful. |
| 37 code practice python: Exploring the Infinite Jennifer Brooks, 2016-11-30 Exploring the Infinite addresses the trend toward a combined transition course and introduction to analysis course. It guides the reader through the processes of abstraction and log- ical argumentation, to make the transition from student of mathematics to practitioner of mathematics. This requires more than knowledge of the definitions of mathematical structures, elementary logic, and standard proof techniques. The student focused on only these will develop little more than the ability to identify a number of proof templates and to apply them in predictable ways to standard problems. This book aims to do something more; it aims to help readers learn to explore mathematical situations, to make conjectures, and only then to apply methods of proof. Practitioners of mathematics must do all of these things. The chapters of this text are divided into two parts. Part I serves as an introduction to proof and abstract mathematics and aims to prepare the reader for advanced course work in all areas of mathematics. It thus includes all the standard material from a transition to proof course. Part II constitutes an introduction to the basic concepts of analysis, including limits of sequences of real numbers and of functions, infinite series, the structure of the real line, and continuous functions. Features Two part text for the combined transition and analysis course New approach focuses on exploration and creative thought Emphasizes the limit and sequences Introduces programming skills to explore concepts in analysis Emphasis in on developing mathematical thought Exploration problems expand more traditional exercise sets |
| 37 code practice python: Exercises for Programmers Brian P. Hogan, 2015-09-04 When you write software, you need to be at the top of your game. Great programmers practice to keep their skills sharp. Get sharp and stay sharp with more than fifty practice exercises rooted in real-world scenarios. If you're a new programmer, these challenges will help you learn what you need to break into the field, and if you're a seasoned pro, you can use these exercises to learn that hot new language for your next gig. One of the best ways to learn a programming language is to use it to solve problems. That's what this book is all about. Instead of questions rooted in theory, this book presents problems you'll encounter in everyday software development. These problems are designed for people learning their first programming language, and they also provide a learning path for experienced developers to learn a new language quickly. Start with simple input and output programs. Do some currency conversion and figure out how many months it takes to pay off a credit card. Calculate blood alcohol content and determine if it's safe to drive. Replace words in files and filter records, and use web services to display the weather, store data, and show how many people are in space right now. At the end you'll tackle a few larger programs that will help you bring everything together. Each problem includes constraints and challenges to push you further, but it's up to you to come up with the solutions. And next year, when you want to learn a new programming language or style of programming (perhaps OOP vs. functional), you can work through this book again, using new approaches to solve familiar problems. What You Need: You need access to a computer, a programming language reference, and the programming language you want to use. |
| 37 code practice python: 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 |
| 37 code practice python: 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. |
| 37 code practice python: 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. |
| 37 code practice python: Teach Your Kids to Code Bryson Payne, 2015-04-01 Teach Your Kids to Code is a parent's and teacher's guide to teaching kids basic programming and problem solving using Python, the powerful language used in college courses and by tech companies like Google and IBM. Step-by-step explanations will have kids learning computational thinking right away, while visual and game-oriented examples hold their attention. Friendly introductions to fundamental programming concepts such as variables, loops, and functions will help even the youngest programmers build the skills they need to make their own cool games and applications. Whether you've been coding for years or have never programmed anything at all, Teach Your Kids to Code will help you show your young programmer how to: –Explore geometry by drawing colorful shapes with Turtle graphics –Write programs to encode and decode messages, play Rock-Paper-Scissors, and calculate how tall someone is in Ping-Pong balls –Create fun, playable games like War, Yahtzee, and Pong –Add interactivity, animation, and sound to their apps Teach Your Kids to Code is the perfect companion to any introductory programming class or after-school meet-up, or simply your educational efforts at home. Spend some fun, productive afternoons at the computer with your kids—you can all learn something! |
| 37 code practice python: Visual Studio Code for Python Programmers April Speight, 2021-06-04 Become proficient and efficient with Visual Studio Code and learn how to integrate all your external tools! Visual Studio Code for Python Programmers helps Python developers become not just familiar, but productive in Visual Studio Code. To start, you’ll find the steps for installing Visual Studio Code on Windows, Mac and Linux platforms, along with an introduction to the editing features of the workspace. Coverage of more advanced functionality includes managing source code, debugging, unit testing, and Jupyter Notebook support. The book finishes with a walk-through of real-world projects which utilize Visual Studio Code features introduced in the book. For developers, the choice of an editor is a very personal one. You have idiosyncratic needs and wants that are unique to you as a developer. This book will help you learn how to customize Visual Studio Code to meet your needs and Python development workflow. Introduces you to the features of the Visual Studio Code workspace and how those features can be customized Demonstrates how Visual Studio Code allows you to choose your structure according to your needs Covers editing code in Python, including syntax highlighting, code completion, object definition, refactoring, and code navigation Describes Git integration and how to perform common Git functions (commits, checkouts, branches, and merges) from within Visual Studio Code Highlights debugging features for Python developers A final section on Real World Applications will step you through several examples (and features integration with Django, Flask, Jupyter Notebook, Docker, and Azure), so you can hit the ground running with Visual Studio Code. |
| 37 code practice python: Study Material Python YCT Expert Team Youth Competition Times , 2023-24 O Level M3-R5 Study Material Python |
| 37 code practice python: Electronics All-in-One For Dummies Doug Lowe, 2017-01-18 A comprehensive collection of 8 books in 1 offering electronics guidance that can't be found anywhere else! If you know a breadboard from a breadbox but want to take your hobby electronics skills to the next level, this is the only reference you need. Electronics All-in-One For Dummies has done the legwork for you — offering everything you need to enhance your experience as an electronics enthusiast in one convenient place. Written by electronics guru and veteran For Dummies author Doug Lowe, this down-to-earth guide makes it easy to grasp such important topics as circuits, schematics, voltage, and safety concerns. Plus, it helps you have tons of fun getting your hands dirty working with the Raspberry Pi, creating special effects, making your own entertainment electronics, repairing existing electronics, learning to solder safely, and so much more. Create your own schematics and breadboards Become a circuit-building expert Tackle analog, digital, and car electronics Debunk and grasp confusing electronics concepts If you're obsessed with all things electronics, look no further! This comprehensive guide is packed with all the electronics goodies you need to add that extra spark to your game! |
| 37 code practice python: Programming for Computations - Python Svein Linge, Hans Petter Langtangen, 2016-07-25 This book presents computer programming as a key method for solving mathematical problems. There are two versions of the book, one for MATLAB and one for Python. The book was inspired by the Springer book TCSE 6: A Primer on Scientific Programming with Python (by Langtangen), but the style is more accessible and concise, in keeping with the needs of engineering students. The book outlines the shortest possible path from no previous experience with programming to a set of skills that allows the students to write simple programs for solving common mathematical problems with numerical methods in engineering and science courses. The emphasis is on generic algorithms, clean design of programs, use of functions, and automatic tests for verification. |
| 37 code practice python: Practice of Computing Using Python, The: Pearson New International Edition William F. Punch, Richard Enbody, 2013-08-29 For CS1 courses in Python Programming (including majors and non-majors). A problem-solving approach to programming with Python. The Practice of Computing Using Python introduces CS1 students (majors and non-majors) to computational thinking using Python.With data-manipulation as a theme, students quickly see the value in what they’re learning and leave the course with a set of immediately useful computational skills that can be applied to problems they encounter in future pursuits. The book takes an “object-use-first” approach–writing classes is covered only after students have mastered using objects. This edition is available with MyProgrammingLab, an innovative online homework and assessment tool. Through the power of practice and immediate personalized feedback, MyProgrammingLab helps students fully grasp the logic, semantics, and syntax of programming. Note: If you are purchasing the standalone text or electronic version, MyProgrammingLab does not come automatically packaged with the text. To purchase MyProgrammingLab, please visit: myprogramminglab.com or you can purchase a package of the physical text + MyProgrammingLab by searching for ISBN 10: 0132992833 / ISBN 13: 9780132992831.MyProgrammingLab is not a self-paced technology and should only be purchased when required by an instructor |
| 37 code practice python: 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 |
| 37 code practice python: Python Programming John M. Zelle, 2004 This book is suitable for use in a university-level first course in computing (CS1), as well as the increasingly popular course known as CS0. It is difficult for many students to master basic concepts in computer science and programming. A large portion of the confusion can be blamed on the complexity of the tools and materials that are traditionally used to teach CS1 and CS2. This textbook was written with a single overarching goal: to present the core concepts of computer science as simply as possible without being simplistic. |
| 37 code practice python: 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. |
| 37 code practice python: Foundations and Practice of Security Jean Luc Danger, Mourad Debbabi, Jean-Yves Marion, Joaquin Garcia-Alfaro, Nur Zincir Heywood, 2014-03-20 This book constitutes the carefully refereed post-proceedings of the 6th Symposium on Foundations and Practice of Security, FPS 2013, held in La Rochelle, France, in October 2013. The 25 revised full papers presented together with a keynote address were carefully reviewed and selected from 65 submissions. The papers are organized in topical sections on security protocols, formal methods, physical security, attack classification and assessment, access control, cipher attacks, ad-hoc and sensor networks, resilience and intrusion detection. |
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