Python Made Easy

Python has become one of the most versatile and widely used programming languages, known for its simplicity and efficiency. Python Made Easy is designed to help beginner developers easily learn the fundamentals and intermediate concepts of Python. This book provides a structured approach to learning Python, covering essential topics from basic syntax to complex data structures and numerical computing.

The book starts with an introduction to Python, explaining its advantages, drawbacks, and the importance of style guides. It then delves into key programming concepts, including variables, lists, strings, dictionaries, tuples, and rare data structures, helping readers build a strong foundation. Readers will also explore loops, conditional statements, Boolean logic, essential mathematical operations, and NumPy's use for numerical computations. Complex topics such as object-oriented programming, inheritance, file handling, unit testing, and data visualization using Matplotlib are covered in depth. Additionally, the book introduces practical applications in numerical mathematics, including Monte Carlo integration and differential equations.

By the end, readers will have an understanding of Python's core principles and practical applications, empowering them to write efficient, scalable, and well-structured code. This book is particularly helpful if you already know some other programming language and you want to kick start your Python knowledge.

What you will learn:

• Understand Python fundamentals, including variables, loops, and data structures.
• What is object-oriented programming, inheritance, and file handling.
• Explore numerical computing with NumPy and data visualization using Matplotlib.

• Gain hands-on experience with unit testing, Monte Carlo integration, and real-world applications.

  Who this book is for:

  Beginners and aspiring programmers, software professionals transitioning to Python and students

  Explains data structures, OOP, file handling, and unit testing with practical examples Explores NumPy, Matplotlib, and numerical computing for real-world applications Covers writing efficient, scalable, and well-structured Python code with best practices

  Autorentext

Marco Gähler began his career studying physics at ETH Zurich before transitioning to software engineering. In 2018, he joined Zurich Instruments, where he developed electronic devices used in quantum computing. At the time of writing, he is founding a company EasyCare, which organizes home treatment of elderly people.

Throughout his career, Marco has observed the pitfalls in code written by self-taught developers, for example PhD students, and recognized the need for clear, practical guidance on simple programming practices.

Inhalt

Chapter 1: About Python.- Chapter 2: Naming.- Chapter 3: Components of Code.- Chapter 4: Loops and if Statements.- Chapter 5: Basic Mathematics.- Chapter 6: Functions and Methods.- Chapter 7: Classes.- Chapter 8: Util.- Chapter 9: Unit Tests.- Chapter 10: Matplotlib.- Chapter 11: Numerical mathematics.- Chapter 12. More Examples.