Python 3: Deep Dive (Part 1) - Udemy

Hello!

This is Part 1 of a series of courses intended to dive into the inner mechanics and more complicated aspects of Python 3.

This is not a beginner course - if you've been coding Python for a week or a couple of months, you probably should keep writing Python for a bit more before tackling this series.

On the other hand, if you're now starting to ask yourself questions like:

• I wonder how this works?

• is there another way of doing this?

• what's a closure? is that the same as a lambda?

• I know how to use a decorator someone else wrote, but how does it work? Can I write my own?

• why isn't this boolean expression returning a boolean value?

• what does an import actually do, and why am I getting side effects?

• and similar types of question...

then this course is for you.

Please make sure you review the pre-requisites for this course - although I give a brief refresh of basic concepts at the beginning of the course, those are concepts you should already be very comfortable with as you being this course.

In this course series, I will give you a much more fundamental and deeper understanding of the Python language and the standard library.

Python is called a "batteries-included" language for good reason - there is a ton of functionality in base Python that remains to be explored and studied.

So this course is not about explaining my favorite 3rd party libraries - it's about Python, as a language, and the standard library.

In particular this course is based on the canonical CPython. You will also need Jupyter Notebooks to view the downloadable fully-annotated Python notebooks.

It's about helping you explore Python and answer questions you are asking yourself as you develop more and more with the language.

In Python 3: Deep Dive (Part 1) we will take a much closer look at:

• Variables - in particular that they are just symbols pointing to objects in memory

• Namespaces and scope

• Python's numeric types

• Python boolean type - there's more to a simple or statement than you might think!

• Run-time vs compile-time and how that affects function defaults, decorators, importing modules, etc

• Functions in general (including lambdas)

• Functional programming techniques (such as map, reduce, filter, zip, etc)

• Closures

• Decorators

• Imports, modules and packages

• Tuples as data structures

• Named tuples

To get the most out of this course, you should be prepared to pause the coding videos, and attempt to write code before I do! Sit back during the concept videos, but lean in for the code videos!

And after you have seen a code video, pause the course, and try things out yourself - explore, experiment, play with code, and see how things work (or don't work! - that's also a great way to learn!)