Coffee Break Python
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Coffee Break Python

50 Workouts to Kickstart Your Rapid Code Understanding in Python

About the Book

Little time to learn Python?

Python puzzles help you to learn faster, smarter, and better. This book offers 50 educative code puzzles, 10 tips for efficient learning, 5 Python cheat sheets, and 1 accurate way to measure your coding skills. 13,000 Python students have already improved their coding skills on our puzzle-based learning academy Finxter.com.

"I very much enjoy your Finxter.com website because it has some real meat to the problems. Thank you so much for doing this project! I love it!"—David C.

"Your site is awesome."—Victor A.

"I found Finxter.com an excellent tool to brush up on my Python skills."—Jesper R.

As you work through Coffee Break Python, your Python expertise will grow—one coffee at a time. You will train wildly important Python topics such as

- Arithmetic operations: integer & float division, and modular arithmetic;

- Language elements: branching, loops, keywords, and functions;

- Data structures: integer, float, string, list, set, dictionary, and graph;

- Sequence operators: indexing, concatenation, slicing, and built-in functions;

- Function *arguments: default *, arbitrary *, unpacking *, keyword *;

- Set operations: lambda, filter, map, and intersection functions; and

- Algorithms: recursion, Fibonacci, Bsearch, sorting, guess & check, and graph traversal.

As a bonus, you will track your individual Python coding skill level throughout the book.

To get the most out of this book, you should be slightly beyond beginner-level in Python—e.g., you have already experience with another programming language, are a professional engineer, or a student.

So how do you spend your Coffee Break? Python!

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About the Author

Christian Mayer
Christian Mayer

Chris is the founder of the programming education company FINXTER, author of the Coffee Break Python series of self-published books, the popular programming book Python One-Liners (NoStarch 2020), a doctorate computer scientist, and owner of one of the top 10 Python blogs worldwide.

His research interests include graph theory and distributed systems.

You can join the FINXTER email academy and consume a large body of free email courses about various topics in computer science and programming.

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Reader Testimonials

Daniele P.
Daniele P.

Good Job!

As a fellow educator and fellow (former) Ph.D. student, I just wanted to let you know that I'm really impressed with your teaching materials. You're doing a really good job!

Zohaib
Zohaib

I love it!!!

I had a quick look at your book. Simply stated: I loved it!!! It was amaaazing :D It definitely sounds very mature and helpful. I see that I need to learn python properly ;) Also, the puzzles seem very nice.

Yansen
Yansen

Love your book

I love your website and your book.

Melissa
Melissa

Enjoyed and Recommended

I really enjoy the puzzles and the book, and I recommend it to my friends interested in Python :)

Table of Contents

1 Introduction

2 A Case for Puzzle-based Learning

2.1 Overcome the Knowledge Gap

2.2 Embrace the Eureka Moment

2.3 Divide and Conquer

2.4 Improve From Immediate Feedback

2.5 Measure Your Skills

2.6 Individualized Learning

2.7 Small is Beautiful

2.8 Active Beats Passive Learning

2.9 Make Code a First-class Citizen

2.10 What You See is All There is

3 The Elo Rating for Python

3.1 How to Use This Book

3.2 The Ideal Code Puzzle

3.3 How to Exploit the Power of Habits?

3.4 How to Test and Train Your Skills?

3.5 What Can This Book Do For You?

4 A Quick Overview of the Python Language

4.1 Keywords

4.2 Basic Data Types

4.3 Complex Data Types

4.4 Classes

4.5 Functions and Tricks

5 Fifty Code Puzzles

5.1 Hello World

5.2 Variables and Float Division

5.3 Basic Arithmetic Operations

5.4 Comments and Strings

5.5 Index and Concatenate Strings

5.6 List Indexing

5.7 Slicing in Strings

5.8 Integer Division

5.9 String Manipulation Operators

5.10 Implicit String Concatenation

5.11 Sum and Range Functions

5.12 Append Function for Lists

5.13 Overshoot Slicing

5.14 Modulo Operator

5.15 Branching Statements

5.16 Negative Indices

5.17 The For Loop

5.18 Functions and Naming

5.19 Concatenating Slices

5.20 Arbitrary Arguments

5.21 Indirect Recursion

5.22 String Slicing

5.23 Slice Assignment

5.24 Default Arguments

5.25 Slicing and the len() Function

5.26 Nested Lists

5.27 Clearing Sublists

5.28 The Fibonacci Series

5.29 The continue Statement and the Modulo Operator

5.30 Indexing Revisited and The Range Sequence

5.31 Searching in Sorted Matrix

5.32 Maximum Prot Algorithm

5.33 Bubble Sort Algorithm

5.34 Joining Strings

5.35 Arithmetic Calculations

5.36 Binary Search

5.37 Modifying Lists in Loops

5.38 The Lambda Function

5.39 Multi-line Strings and the New-line Character

5.40 Escaping

5.41 Fibonacci Arithmetic

5.42 Quicksort

5.43 Unpacking Keyword Arguments with Dictionaries

5.44 Infinity

5.45 Graph Traversal

5.46 Lexicographical Sorting

5.47 Chaining of Set Operations

5.48 Basic Set Operations

5.49 Simple Unicode Encryption

5.50 The Guess and Check Framework

6 Final Remarks

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