Introduction to Computing Using Python, Ljubomir Perkovic

Introduction to Computing Using Python: An Application Development Focus by Ljubomir Perkovic takes the pedagogical approach of "the right tool for the job at the proper second," and focuses on utility development. The book's approach is fingers-on and problem-oriented, with practice issues and options appearing throughout the text.

The text is imperative-first, however does not draw back from discussing objects early the place appropriate. Discussions of user-outlined courses and Object-Oriented Programming appear later within the text, when students have extra background and the concepts can be motivated. It supplies an imperative-first introduction to Python focusing on computer applications and the method of growing them. The text helps develop computational considering abilities by covering patterns of how issues may be broken down and constructively solved to provide an algorithmic solution.

The book includes a chapter on problem solving and classical algorithms, and ways to apply core skills to application development. The last three chapters introduce a broad array of topics through the context of web crawling and search engines, including recursion, regular expressions, depth-first search, Google's MapReduce framework, GUI widgets, HTML parsers, SQL, and multicore programming.

This book has some good content that helps learning python. I think this is a good book for people learning python.It Emphasizes principles of software development, style, and testing. Topics include procedures and functions, iteration, recursion, arrays and vectors, strings, an operational model of procedure and function calls, algorithms, exceptions, object-oriented programming, and GUIs (graphical user interfaces).

Table of Contents

Chapter 1. Introduction to Computer Science
Chapter 2. Python Data Types
Chapter 3. Imperative Programming
Chapter 4. Text data, Files, and Exceptions
Chapter 5. Execution Control Structures
Chapter 6. Containers and Randomness
Chapter 7. Namespaces
Chapter 8. Object-Oriented Programming
Chapter 9. Graphical User Interfaces
Chapter 10. Recursion
Chapter 11. The Web and Search
Chapter 12. Databases and Data Processing

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Python for Kids: A Playful Introduction to Programming

Python for Kids: A Playful Introduction to Programming by Jason R. Briggs brings Python to life and you (and your parents) into the world of programming. Author gives you through the basics as you experiment with distinctive (and sometimes hilarious) example programs that feature ravenous monsters, secret agents, thieving ravens, and more. New terms are defined; code is colored, dissected, and defined; and quirky, full-color illustrations preserve issues on the lighter side.

Chapters end with programming puzzles designed to stretch your brain and strengthen your understanding. By the end of the book you will have programmed two full games: a clone of the famous Pong and "Mr. Stick Man Races for the Exit"-a platform game with jumps, animation, and more.

As you strike out in your programming journey, you'll learn to use elementary knowledge constructions like lists, tuples, and maps, arrange and reuse your code with functions and modules, use control buildings like loops and conditional statements, draw shapes and patterns with Python's turtle module, create games, animations, and different graphical wonders with tkinter. Why should severe adults have all the enjoyable? This book is your ticket into the superb world of computer programming.

The code on this book runs on nearly anything: Home windows, Mac, Linux, even an OLPC laptop computer or Raspberry Pi! Python is a powerful, expressive programming language that is simple to study and enjoyable to use! However books about studying to program in Python can be form of uninteresting, gray, and boring, and that is no fun for anyone.

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The Practice of Computing Using Python 2nd Edition, Punch

The Practice of Computing Using Python 2nd Edition by William F. Punch and Richard Enbody introduces CS1 college students (majors and non-majors) to computational pondering utilizing Python. With information-manipulation as a theme, readers rapidly see the value in what they’re studying and depart the course with a set of instantly useful computational abilities that can be utilized to problems they encounter in future pursuits.

The book takes “object-use-first” method-writing courses, covered only after students have mastered using objects. This edition is on the market with MyProgrammingLab, an modern online homework and evaluation tool. Via the power of practice and quick personalised feedback, MyProgrammingLab helps college students absolutely grasp the logic, semantics, and syntax of programming.

Three non-obligatory chapters in the book (3, 10, and 13) walk college students via detailed examples of fixing a problem using Python. In addition to design, they present mistakes and how one can recover from them by illustrating the method of creating a solution. The authors also refactor some options as demonstrations of the importance of program design and readability. These chapters can be used in or outdoors of sophistication, or in a lab setting.

College students use Python to kind, apply, graph, and convert data. The authors have incorporated many principally non-numeric examples with a gender-impartial appeal to help this theme: poker fingers, Gettysburg Tackle, EPA mileage information, breast cancer classifier, speech analysis, political debates and S&P 500 analysis.

The authors use objects and methods early while leaving the design and implementation of objects for later in the text--after mastery of the use of objects has been achieved. Functions are covered earlier; break up in two parts. Only the string chapter separates the performance and control chapter. Functions are cut up into two parts due to how Python handles mutable objects resembling lists as parameters-dialogue of those points can solely come after there's an understanding of lists as mutable objects.

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Python Scripting for ArcGIS by Paul A. Zandbergen

Python Scripting for ArcGIS by Paul A. Zandbergen shows easy methods to write Python code that works with spatial data to automate geoprocessing duties in ArcGIS. Readers can thus learn the ability set needed to create customized tools. The book contains 14 chapters, with the corresponding data and workout routines on the accompanying DVD.

The primary viewers for this book consists of experienced ArcGIS customers who want to learn Python however have limited programming or scripting experience. Prior experience with other scripting or programming languages (reminiscent of Perl, VBA, VBScript, Java, or C++) can be helpful but isn't required. More skilled programmers can even profit, however the emphasis is on making Python scripting out there to the massive variety of ArcGIS for Desktop users who want to get extra out of the capabilities of ArcGIS without having to become full-time programmers and learning C++. Readers will, nonetheless, be anticipated to have good general ArcGIS skills and a basic understanding of geoprocessing procedures.

This book can also be supposed for upper-division undergraduate and graduate courses in GIS. A handful of colleges and universities train upper-division courses in GIS programming and/or scripting, and this number is anticipated to increase. It incorporates three main parts. Part 1 covers the basics of geoprocessing in ArcGIS for Desktop as well as the basics of the Python language. Depending on your background and expertise, you could already be familiar with some or all of this material. Part 2 covers methods to write scripts that work with spatial data.

That is really the core of the book and contains chapters on executing tools in Python, describing information, and manipulating and creating information, in addition to a number of extra specialized tasks. Part 3 covers the way to create a tool out of your script and the right way to share your tool with others. By the end of this book, you will be able to create custom tools that use Python scripting to automate basic duties in ArcGIS for Desktop.

Each of the 14 chapters within the book is accompanied by reinforcing the ideas covered in the chapter. All 14 workout routines are included on the Data and Exercises DVD that comes with the book. It's best to first read the chapter and then full the accompanying train before transferring on to the following chapter. Relying in your learning model and familiarity with coding, you may try a number of the code within the chapters if you are reading it, but you can also first read the complete chapter and then start the exercise.

It is best to full the chapters and workouts in order for the reason that ideas introduced in each new chapter construct on the earlier ones. To do the workout routines on this book, you must have ArcGIS 10.1 for Desktop software program installed in your computer, or else download a trial version of the software. You will have the code printed on the inside again cover of this book to access the obtain site.

This book will teach you methods to automate duties in ArcGIS. Maybe by the top of the book, you will turn out to be a Python aficionado or maybe you'll merely be capable to save yourself hours of labor by utilizing one of the scripts from the book. Regardless of the case, past the precise skills of writing Python scripts for ArcGIS, additionally, you will study the basic logic of writing code. This shall be useful beyond the specific task at hand.

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Python for Data Analysis by Wes McKinney

Python for Data Analysis by Wes McKinney deals with the nuts and bolts of manipulating, processing, cleansing, and crunching data in Python. Additionally it is a practical, fashionable introduction to scientific computing in Python, tailored for data-intensive applications. This is a book concerning the parts of the Python language and libraries you’ll successfully resolve a broad set of information analysis problems.

This book will not be an exposition on analytical methods using Python as the implementation language. Written by Wes McKinney, the primary creator of the pandas library, this arms-on book is full of sensible circumstances studies. It’s splendid for analysts new to Python and for Python programmers new to scientific computing.

You should utilize the IPython interactive shell as your major growth setting, be taught basic and advanced NumPy (Numerical Python) features, get began with data analysis tools within the pandas library, use excessive-performance tools to load, clear, remodel, merge, and reshape knowledge, create scatter plots and static or interactive visualizations with mat plot lib and apply the pandas group by facility to slice, cube, and summarize datasets.

You can measure data by points in time, whether it’s specific instances, fixed periods, or intervals. This book shows how to solve problems in web analytics, social sciences, finance, and economics, through detailed examples. Wes McKinney is the main author of pandas, the popular open source Python library for data analysis. Wes is an active speaker and participant in the Python and open source communities. He worked as a quantitative analyst at AQR Capital Management and Python consultant before founding DataPad, a data analytics company.

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Python Programming: An Introduction to Computer Science 2e

Python Programming: An Introduction to Computer Science 2nd Edition by John Zelle is designed to be used as the primary textbook in a school-degree first course in computing. It takes a reasonably traditional approach, emphasizing drawback solving, design, and programming because the core abilities of computer science. However, these concepts are illustrated using a non-traditional language, namely Python.

Python is used because the language, educating Python is just not the principle point of this book. Somewhat, Python is used for example fundamental ideas of design and programming that apply in any language or computing environment. In some places, I have purposely averted sure Python features and idioms that are not generally found in different languages.

There are already many good books about Python in the marketplace; this book is meant as an introduction to computing. This book is extremely clear and well-written. It introduces a novice to the foundational concepts of computer science. There are many great examples and activities that the reader can jump into almost immediately.

Table of Contents Computers and Programs
Writing Simple Programs
Computing with Numbers
Objects and Graphics
Sequences: Strings, Lists, and Files
Defining Functions
Decision Structures
Loop Structures and Booleans
Simulation and Design
Defining Classes
Data Collections
Object-Oriented Design
Algorithm Design and Recursion
Appendix A: Python Quick Reference
Appendix B: Using Python and IDLE
Appendix C: Glossary
Index

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Starting Out with Python 2nd Edition by Tony Gaddis

Starting Out with Python 2nd Edition by Tony Gaddis introduces students to the basics of programming and prepares them to transition into more complicated languages. Python, a simple-to-learn and increasingly common object-oriented language, permits readers to turn into snug with the fundamentals of programming without the troublesome syntax that can be difficult for novices.

Management constructions, features, arrays, and pointers are covered before objects and classes. A clear and scholar-pleasant writing type simplifies programming processes for beginning programmers with two to a few stepped-out explanations following each main concept. Concise real-world examples that students understand relate to foster motivation and retention.

Quite a lot of exercises in every chapter encourage students to place ideas to work as they are learned. Supply code is provided so students can run the packages themselves. Within the Spotlight case research stroll college students through the design of a problem by exhibiting all steps. Idea containers all through the chapter focus students’ attention on key topics.

Notes clarify attention-grabbing or usually misunderstood factors relevant to the subject at hand. Suggestions advise college students on one of the best strategies for explicit actions. Warnings alert students to widespread missteps or issues they might encounter. Checkpoints at key locations in each chapter test students’ understanding of vital lessons.

With the data acquired using Python, college students achieve confidence of their abilities and be taught to recognize the logic behind growing excessive-quality programs. This text discusses control buildings, capabilities, arrays, and pointers before objects and classes. As with all Gaddis texts, clear and easy-to-learn code listings, concise and practical real-world examples, element-oriented explanations, and an abundance of workouts appear in each chapter. This text is meant for a one-semester introductory programming course for college kids with limited programming experience.

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Learning Python 5th Edition by Mark Lutz

Learning Python 5th Edition by Mark Lutz describes complete, in-depth introduction to the core Python language with this hands-on book. This text will enable you rapidly write efficient, excessive-high quality code with Python. It’s an ideal approach to start, whether or not you’re new to programming or knowledgeable developer versed in different 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.

Exploring Python’s major built-in object types such as numbers, lists, and dictionaries, this book shows how to create and process objects with Python statements, 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.

By reading this book, you 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.

This new edition has been brought thoroughly up-to-date with Python 3.3 and 2.7, and expanded substantially to reflect current practice in the Python world. Like its previous editions, this book also applies to all other Python releases in common use today. Whether you're using 3.X, 2.X, or both, you'll find this new edition tailored to your current and future needs.

Among other language extensions, this edition incorporates Python 3.3's namespace packages and Windows launcher, as well as 2.7's adoption of 3.X features such as set and dictionary comprehensions. In addition, this version has grown more 2.X compatible, and has been augmented with enhanced coverage of tools such as super(), descriptors, the MRO, and metaclasses, which have grown more pervasive in today's Python code.

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