Python 3: Deep Dive (Part 4 - OOP)

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Python 3: Deep Dive (Part 4 - OOP) provided by Udemy is a comprehensive online course, which lasts for 37 hours worth of material. Python 3: Deep Dive (Part 4 - OOP) is taught by Fred Baptiste. Upon completion of the course, you can receive an e-certificate from Udemy. The course is taught in Englishand is Paid Course. Visit the course page at Udemy for detailed price information.

Overview
  • Python Object Oriented Programming (OOP)

    What you'll learn:

    • Python Object Oriented Concepts
    • Classes
    • Methods and Binding
    • Instance, Class and Static Methods
    • Properties
    • Property Decorators
    • Single Inheritance
    • Slots
    • Descriptors
    • Enumerations
    • Exceptions
    • Metaprogramming

    This Python3: Deep Dive Part 4 course takes a closer look at object oriented programming (OOP) in Python.

    MAIN COURSE TOPICS

    • what are classes and instances

    • class data and function attributes

    • properties

    • instance, class and static methods

    • polymorphism and the role special functions play in this

    • single inheritance

    • slots

    • the descriptor protocol and its relationship to properties and functions

    • enumerations

    • exceptions

    • metaprogramming (including metaclasses)


    COURSE PREREQUISITES

    Please note this is NOT a beginner level course. You must have a strong working knowledge of functional Python programming as well as some practical experience developing Python applications in order to fully benefit from this course.

    • In-depth functional Python programming

    • functions, closures, scopes, decorators (using and writing them)

    • zip, sorted, any, all, and the itertools module in general

    • sequences, iterables, iterators and generators (what they are and how to implement the corresponding protocols)

    • generators, yield, and context managers

    • mapping types, hashing and relation to object equality

    • some prior knowledge of basic OOP concepts

    • know how to work with Python virtual environments and pip install

    • available Jupyter Notebook (freely available) to follow along with the course notebooks

    • how to use git

    [Please note that this is not a cookbook style course - I don't show you how to solve specific problems, but rather a broad and in-depth look at how OOP works in the context of Python, that will allow you to apply these concepts and techniques to your own problems.]