The Art of Doing: Code 40 Challenging Python Programs Today!

The Art of Doing: Code 40 Challenging Python Programs Today!, Computer Science Through Python Application. Learn by doing.

Hello, my name is Michael Eramo.  I am an experienced educator, life long learner, and a self-taught programmer.  I hold official Bachelor’s Degrees in Music Industry, Education, and Physics, a Master’s Degree in Mathematical Science, and a certificate in Software Development from Microsoft.  While I owe my extensive knowledge base in Music, Physics, Mathematics, and Education to the many great educators I have worked with, my understanding of Computer Science is all my own.

I have never taken an “official” computer science course; I am completely self-taught.  However, do not let that deter you from taking this course!  Instead, let it motivate you that you too can learn anything you want to.  Not only have I done it, but I’ve come to realize what works best for the self-taught programmer, and I have perfected the process!

See, I had this deep fear right after my son was born that I was done growing as an individual; that the person I was at 30 was going to be the same person I was at 55.  I felt that there was literally ZERO time in the day to do anything other than go to work and be a dad.  That is, until I bought a book on Computer Science, and a sense of wonder was woken.  I’ve read countless books, watched hundreds of videos, and put in thousands of hours exploring and writing code.  I would routinely wake up at 3:00 AM to learn for a few hours before I had to go to my full time job, teaching high school, before I went to my part time job of teaching college.  Days were long, but getting up at 3:00 AM to read, to learn, or to code benefited me more than a few extra hours of sleep.  It helped me realize that I was never done learning; never done growing.  To me, that is what defines a life long learner.

I have years of classroom experience as a high school Physics teacher, Computer Science teacher, and college Mathematics professor.  I am part of the New York State Master Teacher Program; a network of more than 800 outstanding public school teachers throughout the state who share a passion for their own STEM learning and for collaborating with colleagues to inspire the next generation of STEM leaders.  Most importantly, I know what motivates people to learn on their own; to find a way to create time to learn, when there is no time to be had.  I understand that time is valuable and that all learning should be engaging, meaningful, and have purpose.

Combining my expertise as an educator and my own personal interest in self-taught computer science led me to a telling realization;  most educational material for the self-taught programmer is NOT EDUCATIONAL AT ALL.  Instead, it falls into one of two categories:

• Writing small “snippets” of programs that taken out of context, seem to serve no purpose at all and frankly, are beneath the user.  Prime examples include using a for loop to print out all even numbers from 1 to 100 or using if statements to respond to generic user input.  Here, users are bored and aren’t challenge to create anything with meaning.  There is little purpose other than gaining what is essentially factual level knowledge.  It is a waste of your time.
• Watching others code whole “applications” without a true understanding of what is going on.  These are programs whose scope is beyond the user in which there is no clear guide to walk the user through the thought process without just giving them the answers.  Here, without proper support and guidance, the user just defaults to letting someone else unfold the solution for them.  There is little engagement in watching someone else work and rarely a thought generated on one’s own.  It is a waste of time.

Yes, I will admit that some learning does take place in doing simple tasks or watching others complete complicated tasks.  In fact, much of how I learned was done this way.  However, I’m telling you it pales in comparison to the learning that takes place by DOING meaningful and appropriately challenging work.  This is the art of doing.

The art of doing is the art form of transforming oneself from a passive learner who watches, to one who sees the process of learning for what it truly is; a mechanism to better oneself.  In “The Art of Doing”, I have worked very hard to put together 40 meaningful, engaging, and purposeful “Challenge Problems” for you to solve.

Each challenge problem is differentiated for 3 levels of learning.

• First, you are given a description of the program you are to create and example output.  This allows users an opportunity to solve well defined problems that are meaningful and appropriate in scope.  Here, all of the solution is user generated. It is engaged learning.

• Second, you are given a comprehensive guide that will assist you in thought process needed to successfully code your program.  This allows users appropriate assistance that tests their knowledge and forces them to generate the thoughts needed to solve the given problem.  It is meaningful learning.

• Third, you are given completed code, with comments, to highlight how to accomplish the end goal.  This allows users to reference a working version of the program if they are stuck and cannot solve a portion of the problem without assistance.  Rather than grow frustrated, the user can quickly reference this code to gain intellectual footing, and work back to solving the problem on their own.  It is purposeful learning.

Engaging, meaningful, and with purpose.  These challenge problems are vehicles that not only teach computer science, but teach you the art of doing.  I guarantee that after completing them all you will consider yourself a life long learner and be proud to call yourself a self-taught programmer.

Throughout the scope of this book and its 40 challenge problems, you will get exposed to numerous ideas, theories, and fundamental computer science concepts. By working through all 40 challenge problems, you will gain a mastery level understanding of the following topics:

Data Types:

• Strings: A series of characters
• Integers: Whole numbers
• Floats: Decimal numbers
• Lists: A mutable collection
• Tuples: An immutable collection
• Ranges: A sequence of integers
• Booleans: A True or False value
• Dictionaries: A collection of associated key-value pairs

Control Flow:

• For Loops
• If Statements
• If/Else Statements
• If/Elif/Else Statements
• Break
• Pass
• Continue
• While Loops
• Def
• Return

Assignment, Algebraic, Logical, Members, and Comparison Operators

• = Assignment
• += Compound Assignment
• -= Compound Assignment
• + Concatenation (strings)
• + Addition (ints and floats)
• – Subtraction
• * Multiplication
• / Division
• ** Exponentiation
• % Modulo Division
• And
• Or
• Not
• In
• Not in
• == Equal to
• != Not Equal to
• < Less than
• > Greater Than
• <= Less Than or Equal
• >= Greater Than or Equal

Over 20 Built In Python Functions:

• print()
• type()
• str()
• int()
• float()
• input()
• round()
• sorted()
• len()
• range()
• list()
• min()
• max()
• sum()
• zip()
• bin()
• hex()
• set()
• bool()
• super()

String Methods:

• .upper()
• .lower()
• .title()
• .strip()
• .count()
• .join()
• .startswith()
• .replace()
• .split()

Lists Methods:

• .append()
• .insert()
• .pop()
• .remove()
• .sort()
• .reverse()
• .copy()
• .index()

Dictionary Methods:

• .items()
• .keys()
• .values()
• .most_common()

And External Libraries:

• math
• datetime
• cmath
• random
• collections
• time
• matplotlib
• tkinter