Processing ......
FreeComputerBooks.com
Links to Free Computer, Mathematics, Technical Books all over the World
 
A Practical Introduction to Python Programming
Top Free Data Science Books 🌠 - 100% Free or Open Source!

Book Description

This book is for anyone who wants to understand Python programming. It is degigned as partly a tutorial and partly a reference of Python.

You'll learn to program in a language that's used in millions of smartphones, tablets, and PCs. You'll code along with the book, writing programs to solve real-world problems as you learn the fundamentals of programming using Python 3. You'll learn about design, algorithms, testing, and debugging, and come away with all the tools you need to produce quality code in Python.

Though this book was designed to be used in an introductory programming course, it is also useful for those with prior programming experience looking to learn Python. If you are one of those people, you should be able to breeze through the first several chapters. You should find Part II to be a concise, but not superficial, treatment on GUI programming. Part III contains information on the features of Python that allow you to accomplish big things with surprisingly little code.

About the Authors
  • Brian Heinold is an Associate Professor of Department of Mathematics and Computer Science at Mount Saint Mary's University.
Reviews, Ratings, and Recommendations: Related Book Categories: Read and Download Links: Similar Books:
  • Automate the Boring Stuff with Python (Albert Sweigart)

    Learn how to use Python to write programs that do in minutes what would take you hours to do by hand - no prior programming experience required. You'll create Python programs that effortlessly perform useful and impressive feats of automation.

  • Python for Everybody: Exploring Data in Python 3

    This book 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.

  • Deep Learning with Python, 2nd Edition (Francois Chollet)

    This book introduces the field of deep learning using Python and the powerful Keras library. It offers insights for both novice and experienced machine learning practitioners, and builds your understanding through intuitive explanations and practical examples.

  • Beyond the Basic Stuff with Python: Writing Clean Code

    More than a mere collection of advanced syntax and masterful tips for writing clean code, advance your Python programming skills by using the command line and other professional tools like code formatters, type checkers, linters, and version control.

  • Python Packages (Tomas Beuzen, et al.)

    An open source book that describes modern and efficient workflows for creating Python packages. Covering the entire Python packaging life cycle, this essential guide takes readers from package creation all the way to effective maintenance and updating.

  • Inside The Python Virtual Machine (Obi Ike-Nwosu)

    This book describes how Python code is compiled and run, how the language itself can be modified and will demystify the mysterious bytecodes that run on the Python virtual machine.

  • Architecture Patterns with Python (Harry Percival, et al.)

    Enabling Test-Driven Development, Domain-Driven Design, and Event-Driven Microservices, it introduces proven architectural design patterns to help Python developers manage application complexity, and get the most value out of their test suites.

  • Clean Architectures in Python: Better Software Design

    The clean architecture is the opposite of spaghetti code, where everything is interlaced and there are no single elements that can be easily detached from the rest and replaced without the whole system collapsing.

  • Problem Solving with Algorithms/Data Structures using Python

    This is a textbook about computer science. It is also about Python. However, there is much more. The tools and techniques that you learn here will be applied over and over as you continue your study of computer science.

  • Fundamentals of Python Programming (Richard L. Halterman)

    It focuses on introducing programming techniques and developing good habits. To that end, our approach avoids some of the more esoteric features of Python and concentrates on the programming basics that transfer directly to other imperative programming.

  • O'Reilly® Think Python, 2nd Edition (Allen B. Downey)

    This hands-on guide takes you through the Python programming language a step at a time, beginning with basic programming concepts before moving on to functions, recursion, data structures, and object-oriented design. 2nd edition updated for Python 3.

  • Learn Python the Right Way: How to Think like a Computer Scientist

    The goal of this book is to teach you to think like a computer scientist. This way of thinking combines some of the best features of mathematics, engineering, and natural science.

  • The Big Book of Small Python Projects: 81 Easy Practice Programs

    This book demonstrates how to combine different libraries and frameworks to build amazing things. It picks up where the complete beginner books leave off, expanding on existing concepts and introducing new tools that you'll use every day.

  • Practical Python Projects (Yasoob Khalid)

    This collection of 81 Python projects will have you making digital art, games, animations, counting programs, and more right away. Once you see how the code works, you’ll practice re-creating the programs and experiment by adding your own custom touches.

  • Python Programming Exercises, Gently Explained (Al Sweigart)

    This is the perfect book for beginner and intermediate programmers who want to test their Python skills but aren’t ready to begin professional-level software development. The 42 programming exercises in this book let you practice what you've learned.

  • Functional Programming in Python (David Mertz)

    It describes ways to avoid Python’s imperative-style flow control, the nuances of callable functions, how to work lazily with iterators, and the use of higher-order functions. He also lists several third-party Python libraries useful for functional programming.

  • Python 3 Patterns, Recipes and Idioms (Bruce Eckel, et al)

    This book is aimed at more experienced Python programmers who are looking to deepen their understanding of the language and modern programming idioms. It focuses on some of the more advanced techniques used by libraries, frameworks, and applications.

  • The Recursive Book of Recursion using Python (Al Sweigart)

    Recursion has an intimidating reputation. This book uses Python and JavaScript examples to teach the basics of recursion, exposing the ways that it's often poorly taught and clarifying the fundamental principles of all recursive algorithms.

  • O'Reilly® Python Data Science Handbook: Essential Tools

    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.

  • Modeling and Simulation in Python (Allen B. Downey)

    This book is an introduction to physical modeling using a computational approach with Python. You will learn how to use Python to accomplish many common scientific computing tasks: importing, exporting, and visualizing data; numerical analysis; etc.

  • Introduction to Scientific Programming with Python

    This book offers an initial introduction to programming for scientific and computational applications using the Python programming language. The presentation style is compact and example-based, assuming little or no prior experience in programming.

  • Python for Network Engineers (Natasha Samoylenko)

    Everything in the book is focused on network equipment and interaction with it, using the Python programming language. This immediately makes it possible to use the knowledge gained in the daily work of network engineers.

Book Categories
:
Other Categories
Resources and Links