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MEAP VERSION 3
ABOUT THIS MEAP
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WELCOME
Hi, and thanks so much for purchasing the MEAP of the
Python Workout: 50
Essential Exercises!
Over the last few years, Python has made inroads into many areas, including
system administration, data science, devops, text processing, and Web
development. As such, there are now many courses and books that aim to teach
you Python.
Indeed, I spend just about every day teaching Python at companies around the
world. It's fun and exciting to see so many people learning Python, getting more
done in less time — and enjoying themselves along the way.
For many years, my students would consistently ask one question after taking
my courses: Where can we go to practice the Python we've just learned?
It shouldn't surprise me that they would want such practice. Athletes don't just
hop onto the field and start to play, even if they're good at what they do; they're
constantly improving and sharpening their skills. Even if you understood
everything that the teacher said in your high-school math class, you still needed
to practice, in order to ensure that it sank in. And anyone who has learned a
foreign language knows that there's a world of difference between speaking in
class, and using it in a real-world setting.
And indeed, learning a programming language is much like learning a human
language: You need to understand its underlying structure, its nouns and verbs,
and the ways in which you can and cannot express yourself. Over time, these
rules become natural, and you find yourself able to express more complex ideas
— without having to refer to a translation guide, such as a phrasebook or Stack
Overflow.
My goal in this book is to reinforce the ideas that you learned in your initial
Python course, or when reading your first Python book. As you do each exercise,
you'll probably struggle and feel some frustration. And when you see my
solutions, you might well say, "Oh, of course! Why didn't I think of that?" These
are normal parts of the learning process. Better to experience them in this book,
as you gain fluency, than at work, on a problem that requires your attention.
The book is divided into 10 chapters, each covering a different area of Python.
Overall, the problems get more complex as the book progresses — but that
doesn't mean I'll wait to use functions until the "functions" chapter, or
comprehensions until the "functional programming" chapter. You should use
whatever tool you think is necessary.
Each chapter starts with a reference table, including links, pointing to resources
that might help you to better understand topics that you've forgotten or never
learned. I hope that these will help you to reinforce your Python understanding,
beyond the book itself.
In addition to the exercises and solutions, there are also videos, in which I
demonstrate solving each of the problems, and add to the discussion I present in
the book. The solutions are the same as the ones you can read in the book, but
for many people, the videos make the process come alive a bit more; you'll get
more of the feel of being in one of my live training sessions. In addition, it's
often helpful to see the coding and solving process happen over time, rather than
seeing it all at once on the page. The best way to use the video segments is to
have the book and the video (in Manning's liveVideo platform) open at the same
time. For each exercise, start with the book, complete each exercise, and, if you
like, read the solution and discussion. Then click on the corresponding video
segment to see me demo the solution and offer further insights to the discussion.
If there's one request that I have from you, it's that you not look at the exercise,
think about how to solve it, and look at the solution. The real and deep learning
doesn't happen that way, much as we might like to think otherwise. Only through
actually trying to answer the exercise will you truly learn and improve your
fluency.
When you complete an exercise, don't just read the solution, either. Just as
important as seeing the code is understanding why and how I arrived at that
code. The process I use for finding a solution is a key factor in your learning.

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