Python 3 – Deep Dive (Part 1 – Functional)
Original price was: $199.99.$42.00Current price is: $42.00.
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.
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Description
Python 3 – Deep Dive (Part 1 – Functional)
What you’ll learn
An in-depth look at variables, memory, namespaces and scopes
A deep dive into Python’s memory management and optimizations
In-depth understanding and advanced usage of Python’s numerical data types (Booleans, Integers, Floats, Decimals, Fractions, Complex Numbers)
Advanced Boolean expressions and operators
Advanced usage of callables including functions, lambdas and closures
Functional programming techniques such as map, reduce, filter, and partials
Create advanced decorators, including parametrized decorators, class decorators, and decorator classes
Advanced decorator applications such as memoization and single dispatch generic functions
Use and understand Python’s complex Module and Package system
Idiomatic Python and best practices
Understand Python’s compile-time and run-time and how this affects your code
Avoid common pitfalls
Description
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!)
Who this course is for:
Anyone with a basic understanding of Python that wants to take it to the next level and get a really deep understanding of the Python language and its data structures.
Anyone preparing for an in-depth Python technical interview.
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