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Clean Code in Python

Want to learn how to code cleanly? Discover Python basics to advanced topics like decorators, descriptors, and async programming. Get hands-on experience to confidently build skills and write maintainable code.

Advanced

136 Lessons

37h

Certificate of Completion

AI-POWERED

Explanations

AI-POWERED

Explanations

This course includes

200 Playgrounds

10 Quizzes

Course Overview

What You'll Learn

Course Content

Apply Your Skills

Recommendations

Course Overview

Writing high quality code is one of the highly desirable traits of software engineers in the industry. This course is useful for anyone interested in creating scalable and maintainable software design in Python. It is assumed that the learner is already familiar with the principles of object-oriented software design and has experience writing code in Python. In this course, you’ll go through the content in an increasing order of complexity, starting from the basics of Python. The course covers some advanc...Show More

Writing high quality code is one of the highly desirable traits of software engineers in the industry. This course is useful for...Show More

What You'll Learn

An understanding of general software engineering principles to write maintainable code in Python

An understanding of SOLID principles for effective object-oriented design in Python

Hands-on experience with decorators for reusing code, separating responsibilities, and creating granular functions in Python

Familiarity with descriptors to improve code readability in Python

Hands-on experience with generators, iterators, and asynchronous programming in Python

Familiarity with unit testing and refactoring in Python

An understanding of general software engineering principles to write maintainable code in Python

Course Content

Preface

1 Lessons

Get familiar with writing clean, maintainable Python code focusing on essential principles and practices.

Getting Started with Clean Code in Python

Introduction to Clean Code, Code Formatting, and Tools

8 Lessons

Look at clean code principles, formatting, documentation, annotations, and essential tooling.

An Introduction to Clean Code

Code Formatting

Documentation: Code Comments

Documentation: Docstrings

Documentation: Annotations

Tooling for Type Consistency and General Validations

Tooling for Automatic Formatting

Quiz on Introduction to Clean Code, Code Formatting, and Tools

Pythonic Code

10 Lessons

Master the steps to write idiomatic Python with indexing, context managers, and magic methods for enhanced clarity.

Indexes and Slices

Context Managers

Comprehensions and Assignment Expressions

Properties, Attributes, and Different Types of Methods for Objects

Creating Classes with a More Compact Syntax

Iterable Objects

Other Properties, Attributes, and Methods

Summary of Magic Methods

Caveats in Python

Quiz on Pythonic Code

General Traits of Good Code

14 Lessons

Grasp the fundamentals of robust code principles, design strategies, and effective function handling.

Design by Contract

Defensive Programming

Best Practices for Exception Handling

Using Assertions in Python

Separation of Concerns

Acronyms to Live By

Inheritance in Python

Multiple Inheritance in Python

Arguments in Functions and Methods

Variable Number of Arguments in Python

More on How Function Arguments Work in Python

Optimizing the Number of Arguments in Functions

Final Remarks on Good Practices for Software Design

Quiz on General Traits of Good Code

The SOLID Principles

8 Lessons

Deepen your knowledge of SOLID principles to enhance code maintainability and scalability.

The Single Responsibility Principle

The Open/Closed Principle

Liskov's Substitution Principle

Integration Segregation Principle

Dependency Inversion Principle

Quiz on the SOLID Principles

Challenge: The Single Responsibility Principle

Solution: The Single Responsibility Principle

Using Decorators to Improve Our Code

18 Lessons

See how decorators enhance Python code by promoting code reusability, separation of concerns, and the DRY principle.

What Are Decorators in Python?

Function Decorators

Class Decorators

More Advanced Decorators

Decorators with Default Values

Decorators for Coroutines

Extended Syntax for Decorators

Good Uses for Decorators

Effective Decorators—Avoiding Common Mistakes

Dealing with Side Effects in Decorators

Creating Decorators That Will Always Work

Decorators and Clean Code

The DRY Principle with Decorators

Decorators and Separation of Concerns

Analysis of Good Decorators

Quiz on Using Decorators to Improve Our Code

Challenge: Creating Function Decorators

Solution: Creating Function Decorators

Getting More Out of Our Objects with Descriptors

14 Lessons

Build on descriptors to enhance Python’s object-oriented programming with reusable abstractions and controlled attributes.

A First Look at Descriptors

Get Method of the Descriptor Protocol

Set Method of the Descriptor Protocol

Delete Method of the Descriptor Protocol

Set Name Method of the Descriptor Protocol

Types of Descriptors

An Application of Descriptors

Different Forms of Implementing Descriptors

More Considerations for Using Descriptors

Analysis of Descriptors

Final Remarks About Descriptors

Quiz on Getting More Out of Our Objects with Descriptors

Challenge: Creating Descriptors

Solution: Creating Descriptors

Generators, Iterators, and Asynchronous Programming

15 Lessons

Learn how to use generators, iterators, and asynchronous programming in Python effectively.

What are Generators?

Generator Expressions

Iterating Idiomatically

Itertools

Simplifying Code through Iterators

The Iterator Pattern in Python

Coroutines

More Advanced Coroutines

Further Uses of the yield from Construction

Asynchronous Programming

Magic Asynchronous Methods

Asynchronous Iteration and Asynchronous Generators

Quiz on Generators, Iterators, and Asynchronous Programming

Challenge: Asynchronous Programming

Solution: Asynchronous Programming

Unit Testing and Refactoring

18 Lessons

Unpack the core of effective unit testing, test design principles, and refactoring techniques.

Design Principles and Unit Testing

Forms of Automated Testing

Unit Testing and Agile Software Development

Unit Testing and Software Design

Getting Started with Testing

The unittest Module

Parameterised Tests Using unittest

The pytest Framework

Parameterized Tests Using pytest

Common Themes in Testing

Test-Driven Development

Quiz on Unit Testing and Refactoring

10.

Common Design Patterns

16 Lessons

Examine applying design patterns in Python, balancing inherent dynamic features with practical use cases.

Design Patterns Considerations in Python

Design Patterns in Action

Chain of Responsibility

The Template Method

Command

State

The Null Object Pattern

Final Thoughts about Design Patterns

Quiz on Common Design Patterns

11.

Clean Architecture

12 Lessons

Apply your skills to develop robust software architecture with modular, scalable, and maintainable systems.

From Clean Code to Clean Architecture

Separation of Concerns

Monolithic Applications and Microservices

Abstractions

Software Components

Packages

Managing Dependencies

Docker Containers

Use Case

The Service

Analysis of the Architectural Traits

Quiz on Clean Architecture

12.

Conclusion

2 Lessons

Dig deeper into clean code principles, coding guidelines, and adaptable software design in Python.

An Overview of the Course

Ending Notes

Course Author

Packt

Project

Tracking Moving Objects Using Python

intermediate

1 hour 20 min

Project

Tracking Moving Objects Using Python

Learn to automate object tracking in videos using Python and OpenCV, applying computer vision techniques to real-world scenarios.

intermediate

1 hour 20 mins

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