The Python Workshop: Write Python code to solve challenging real-world problems, 2nd Edition

600 Pages·2022·69.869 MB·English

by  Corey Wade, Mario Corchero Jimenez, Andrew Bird, Dr. Lau Cher Han, Graham Lee

The Python Workshop
Write Python code to solve challenging real-world problems
Corey Wade
Mario Corchero Jiménez
Andrew Bird
Dr. Lau Cher Han
Graham Lee
BIRMINGHAM—MUMBAI
The Python Workshop
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First published: November 2019
Second edition: October 2022
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Contributors
About the authors
Corey Wade, MS Mathematics, MFA Writing & Consciousness, is the director and founder of
Berkeley Coding Academy where he teaches Python and data science to teenagers from around the
world. A regular contributor to Towards Data Science, Corey has also authored Hands-On Gradient
Boosting with XGBoost and scikit-learn. Corey has taught math and programming for 18 years at
the Independent Study program of Berkeley High School. When not teaching or building machine
learning models in Python, Corey reads poetry and studies the stars. You can visit his website at
berkeleycodingacademy.com.
Mario Corchero Jiménez is a senior software developer at Bloomberg. He leads the Python infrastructure
team, enabling the company to work effectively with Python and building company-wide libraries
and tools. His professional experience is mainly in C++ and Python and he has contributed patches to
multiple Python open source projects. He is a PSF fellow, having received the PSF Q3 2018 Community
Award, and the vice president of Python España (Spain’s Python association). He has also served as
the chairperson of PyLondinium, PyConES17, and PyCon Charlas at PyCon 2018. Mario is passionate
about the Python community, open source and inner source.
Andrew Bird is the data and analytics manager at Vesparum Capital. He leads the software and data
science teams at Vesparum, overseeing full-stack web development in Django and React. He is an
Australian actuary (FIAA, CERA) who has previously worked with Deloitte Consulting in financial
services. Andrew also currently works as a full-stack developer for Draftable Pvt. Ltd. He voluntarily
manages the ongoing development of the donation portal for the Effective Altruism Australia website.
Dr. Lau Cher Han is a chief data scientist and is currently the CEO of LEAD, an institution that provides
programs on data science, full-stack web development, and digital marketing. Well-versed in programming
languages such as JavaScript, Python, C#, and so on, he is experienced in MEAN Stack, ASP.NET, and
Python Django web frameworks. He is multilingual and speaks English, Chinese, and Bahasa fluently.
His knowledge of Chinese even includes its dialects of Hokkien, Teochew, and Cantonese.
Graham Lee is an experienced programmer and writer. He has written several books, including
Professional Cocoa Application Security, Test-Driven iOS Development, APPropriate Behaviour, and
APPosite Concerns. He is a developer who’s been programming for long enough to want to start telling
other people about the mistakes he’s made in the hope that they’ll avoid repeating them. In his case,
this means having worked for about 12 years as a professional. His first programming experience can
hardly be called professional at all, as it was in BASIC on a Dragon 32 microcomputer.
About the reviewer
Jeyapriya Udayanakumar is currently an associate professor at Stella Maris College, Chennai, India,
and she has been pursuing her passion for teaching for more than 20 years. She has an interest in
computer programming and believes that programming should be taught to students as an art. She
has guided many student projects and been a part of some of them in real time. She has headed the
department of computer science for 7 years and has been the dean of academic affairs for 3 years.
She is known for her teaching skills and competency, has a penchant for clarity in terms of gauging
goals and learning outcomes, and can connect with learners and assess their needs with ease. She has
completed a master’s degree in computer applications.

Table of Contents
Preface xix
1
Python Fundamentals – Math, Strings, Conditionals, and Loops 1
Overview 1 Docstrings 17
Introduction 1 Activity 2 – finding the area of a triangle 17
Technical requirements 2 Strings – concatenation,
Opening a Jupyter Notebook 3 methods, and input() 18
String syntax 18
Python as a calculator 4
Exercise 7 – string error syntax 19
Standard math operations 4
Escape characters 20
Basic math operations 5
Multiline strings 21
Order of operations 7
The print() function 21
Exercise 1 – getting to know
Exercise 8 – displaying strings 21
the order of operations 7
String operations and concatenation 23
Python concept – spacing 8
Exercise 9 – string concatenation 23
Number types – integers and floats 8
Exercise 2 – integer and float types 9 String interpolation 24
Complex number types 10 Comma separators 24
Errors in Python 10 f-strings 24
Variable assignment 11 The len() function 25
Exercise 3 – assigning variables 11 String methods 25
Casting – changing types 12 Exercise 10 – implementing string methods 26
Activity 1 – assigning values to variables 13 Casting 27
Variable names 13 Exercise 11 – types and casting 27
Exercise 4 – naming variables 14 The input() function 28
Multiple variables 15 Exercise 12 – using the input() function 29
Exercise 5 – assigning multiple variables 15 Activity 3 – using the input()
Comments 16 function to rate your day 30
Exercise 6 – comments in Python 16
viii Table of Contents
String indexing and slicing 30 if else 41
Indexing 30 Exercise 17 – using the if-else syntax 41
The elif statement 42
Slicing 32
Loops 43
Strings and their methods 33
while loops 43
Booleans and conditionals 34
The break keyword 45
Booleans 34
Activity 4 – finding the least common
Exercise 13 – Boolean variables 34
multiple (LCM) 46
Logical operators 35
Programs 46
Comparison operators 36
Exercise 18 – calculating perfect squares 47
Exercise 14 – comparison operators 37
Exercise 19 – real estate offer 48
Comparing strings 39
for loops 50
Exercise 15 – practicing comparing strings 39
Exercise 20 – using for loops 50
Conditionals 39
The continue keyword 53
The if syntax 39
Activity 5 – building conversational
Indentation 40 bots using Python 55
Exercise 16 – using the if syntax 40
Summary 56
2
Python Data Structures 57
Overview 57 Activity 6 – using a nested list to store
employee data 67
Introduction 57
Technical requirements 59 Matrix operations 68
The power of lists 59 Exercise 27 – implementing matrix
operations (addition and subtraction) 69
Exercise 21 – working with Python lists 60
Matrix multiplication operations 70
List methods 61
Exercise 28 – implementing matrix
Exercise 22 – basic list operations 61 operations (multiplication) 71
Accessing an item from a list 62
Dictionary keys and values 72
Exercise 23 – accessing an item from
Exercise 29 – using a dictionary to store
shopping list data 62
a movie record 73
Adding an item to a list 63
Activity 7 – storing company employee
Exercise 24 – adding items to our shopping list 64
table data using a list and a dictionary 75
Exercise 25 – looping through a list 65
Dictionary methods 76
Matrices as nested lists 65
Exercise 26 – using a nested list to store Exercise 30 – accessing a dictionary
data from a matrix 66 using dictionary methods 76
Table of Contents ix
Tuples 77 A survey of sets 80
Exercise 31 – exploring tuple properties Exercise 33 – using sets in Python 81
in a dance genre list 78 Set operations 82
Zipping and unzipping dictionaries Exercise 34 – implementing set operations 83
and lists using zip() 79
Choosing types 85
Exercise 32 – using the zip() method to
manipulate dictionaries 79 Summary 87
3
Executing Python – Programs, Algorithms, and Functions 89
Overview 89 Exercise 43 – defining and calling
a function in the shell 107
Introduction 89
Exercise 44 – defining and calling
Technical requirements 90
a function in a Python script 108
Python scripts and modules 90
Exercise 45 – importing and calling
Exercise 35 – writing and executing the function from the shell 109
our first script 91 Positional arguments 109
Python function example 92 Keyword arguments 110
Exercise 36 – writing and importing Exercise 46 – defining a function
our first module 92 with keyword arguments 110
Shebangs in Ubuntu 93 Exercise 47 – defining a function
Docstrings 94 with positional and keyword arguments 110
Exercise 37 – adding a docstring to Exercise 48 – using **kwargs 111
my_module.py 94 Activity 9 – formatting customer names 112
Importing libraries 95
Iterative functions 113
Exercise 38 – finding the system date 96
Exercise 49 – a simple function
The if __name__ == ‘__main__’ statement 97
with a for loop 114
Activity 8 – what’s the time? 98
Exiting early 114
Python algorithms 98 Exercise 50 – exiting the function during
Exercise 39 – finding the maximum number 99 the for loop 114
Time complexity 100 Activity 10 – the Fibonacci function
with an iteration 115
Sorting algorithms 101
Exercise 40 – using bubble sort in Python 103 Recursive functions 116
Searching algorithms 104
A terminating case 117
Exercise 41 – linear search in Python 104
Exercise 51 – recursive countdown 118
Exercise 42 – binary search in Python 106
Exercise 52 – factorials with iteration
Basic functions 107 and recursion 118
Activity 11 – the Fibonacci function