Design Patterns in Python

Design Patterns in Python, available at $54.99, has an average rating of 4, with 78 lectures, 1 quizzes, based on 216 reviews, and has 1778 subscribers.

You will learn about Design Patterns in Python Learn All 23 GoF Design Patterns Creational Patterns : Factory, Abstract Factory, Builder, Prototype, Singleton Structural Patterns : Decorator, Adapter, Facade, Bridge, Composite, Flyweight, Proxy Behavioral Patterns : Command, Chain of Responsibility, Observer, Interpreter, Iterator, Mediator, Memento, State, Strategy, Template, Visitor Learn Many Python Concepts : ABCMeta, Exception Handling, Lists, Dictionaries, Tuples, Sets, id, Dunder Attributes and Methods, Time, Decimal, *Args and more. Learn Quality Software Design Standards using Pep8, Pylint and MyPy UML Diagramming : Inherits, Implements, Composition, Aggregates, Association Learn Each Pattern from Conceptual and Use Case Points of View Develop Your Software Engineering Vocabulary This course is ideal for individuals who are Python Developers or Software Architects or Software Engineers It is particularly useful for Python Developers or Software Architects or Software Engineers.

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Summary

Title: Design Patterns in Python

Price: $54.99

Average Rating: 4

Number of Lectures: 78

Number of Quizzes: 1

Number of Published Lectures: 78

Number of Curriculum Items: 79

Number of Published Curriculum Objects: 78

Original Price: $89.99

Quality Status: approved

Status: Live

What You Will Learn

Design Patterns in Python
Learn All 23 GoF Design Patterns
Creational Patterns : Factory, Abstract Factory, Builder, Prototype, Singleton
Structural Patterns : Decorator, Adapter, Facade, Bridge, Composite, Flyweight, Proxy
Behavioral Patterns : Command, Chain of Responsibility, Observer, Interpreter, Iterator, Mediator, Memento, State, Strategy, Template, Visitor
Learn Many Python Concepts : ABCMeta, Exception Handling, Lists, Dictionaries, Tuples, Sets, id, Dunder Attributes and Methods, Time, Decimal, *Args and more.
Learn Quality Software Design Standards using Pep8, Pylint and MyPy
UML Diagramming : Inherits, Implements, Composition, Aggregates, Association
Learn Each Pattern from Conceptual and Use Case Points of View
Develop Your Software Engineering Vocabulary

Who Should Attend

Python Developers
Software Architects
Software Engineers

Target Audiences

Python Developers
Software Architects
Software Engineers

Learn All of the 23 GoF (Gang of Four) Design Patterns and Implemented them in Python.

Design Patterns are descriptions or templates that can be repeatedly applied to commonly recurring problems during in software design.

A familiarity of Design Patterns is very useful when planning, discussing, managing and documenting your applications from now and into the future.

Also, throughout the course, as each design pattern is discussed and demonstrated using example code, I introduce new Python coding concepts along with each new design pattern. So that as you progress through the course and try out the examples, you will also get experience and familiarity with some of the finer details of the Python programming language.

In this course, you will learn about these 23 Design Patterns,

Creational
- Factory
- Abstract Factory
- Builder
- Prototype
- Singleton
Structural
- Decorator
- Adapter
- Facade
- Bridge
- Composite
- Flyweight
- Proxy
Behavioral
- Command
- Chain of Responsibility
- Observer Pattern
- Interpreter
- Iterator
- Mediator
- Memento
- State
- Strategy
- Template
- Visitor

In the list of patterns above, there are Creational, Structural and Behavioral patterns.

Creational: Abstracts the instantiation process so that there is a logical separation between how objects are composed and finally represented.
Structural: Focuses more on how classes and objects are composed using the different structural techniques, and to form structures with more or altered flexibility.
Behavioral : Are concerned with the inner algorithms, process flow, the assignment of responsibilities and the intercommunication between objects.

Design patterns will give you a useful and common vocabulary for when designing, documenting, analyzing, restructuring new and existing software development projects from now and into the future.

I look forward to having you take part in my course.

Sean Bradley

Course Curriculum

Chapter 1: Introduction

Lecture 1: Environment Setup

Lecture 2: Coding Conventions

Lecture 3: UML Diagrams

Chapter 2: Creational Design Patterns

Lecture 1: Factory

Lecture 2: Factory Pattern Use Case

Lecture 3: ABCMeta

Lecture 4: Abstract Factory

Lecture 5: Abstract Factory Use Case

Lecture 6: Exception Handling

Lecture 7: Builder

Lecture 8: Builder Pattern Use Case

Lecture 9: Python List

Lecture 10: Prototype

Lecture 11: Prototype Pattern Use Case

Lecture 12: Python id() Function

Lecture 13: Singleton

Lecture 14: Singleton Use Case

Lecture 15: Python Dictionary

Chapter 3: Structural Design Patterns

Lecture 1: Decorator

Lecture 2: Decorator Use Case

Lecture 3: __str__ Dunder Method

Lecture 4: getattr() Method

Lecture 5: Adapter

Lecture 6: Adapter Use Case

Lecture 7: Python isinstance() Function

Lecture 8: Python time Module

Lecture 9: Facade

Lecture 10: Facade Use Case

Lecture 11: Python Decimal

Lecture 12: Python Type Hints

Lecture 13: Bridge Pattern

Lecture 14: Bridge Use Case

Lecture 15: Python Tuple

Lecture 16: Python *args

Lecture 17: Composite Pattern

Lecture 18: Composite Use Case

Lecture 19: Conditional Expressions (Ternary Operators)

Lecture 20: Flyweight Pattern

Lecture 21: Flyweight Use Case

Lecture 22: Python String Justification

Lecture 23: Proxy Pattern

Lecture 24: Proxy Use Case

Lecture 25: Python __class__ Attribute

Lecture 26: Avoiding Circular Imports

Chapter 4: Behavioural Design Patterns

Lecture 1: Command

Lecture 2: Command Use Case

Lecture 3: Single Leading Underscore

Lecture 4: Chain of Responsibility Pattern

Lecture 5: Chain of Responsibility Use Case

Lecture 6: Python Floor Division

Lecture 7: Accepting User Input

Lecture 8: Observer Pattern

Lecture 9: Observer Use Case

Lecture 10: Python Set

Lecture 11: Interpreter Pattern

Lecture 12: Interpreter Use Case

Lecture 13: String Slicing

Lecture 14: Python __repr__ Dunder Method

Lecture 15: Iterator Pattern

Lecture 16: Iterator Use Case

Lecture 17: Python iter() Function

Lecture 18: Mediator Pattern

Lecture 19: Mediator Use Case

Lecture 20: Memento Pattern

Lecture 21: Memento Use Case

Lecture 22: Python Getters/Setters

Lecture 23: State Pattern

Lecture 24: State Use Case

Lecture 25: Dunder __call__ Attribute

Lecture 26: Strategy Pattern

Lecture 27: Strategy Use Case

Lecture 28: Template Method Pattern

Lecture 29: Template Method Use Case

Lecture 30: Visitor Pattern

Lecture 31: Visitor Use Case

Lecture 32: Python hasattr() Method

Lecture 33: Python expandtabs() Method

Chapter 5: Summary

Lecture 1: Summary

Instructors

Sean Bradley
Software and Networking Engineer for 20 Years

Rating Distribution

1 stars: 5 votes
2 stars: 3 votes
3 stars: 20 votes
4 stars: 64 votes
5 stars: 124 votes

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