Learn to Code by Solving Problems - A Python Programming Primer

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.
 

Inhalt:

Acknowledgements
Introduction
Chapter 1: Getting Started
Chapter 2: Making Decisions
Chapter 3: Repeating Code: Definite Loops
Chapter 4: Repeating Code: Indefinite Loops
Chapter 5: Organizing Values Using Lists
Chapter 6: Designing Programs with Functions
Chapter 7: Reading and Writing Files
Chapter 8: Organizing Values Using Sets and Dictionaries
Chapter 9: Designing Algorithms with Complete Search
Chapter 10: Big O and Program Efficiency
Afterword