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Building More Python 2 Design Patterns

Python is a popular programming language in the world today and that popularity is growing! Developing large, complex programs in Python requires more than just a knowledge of syntax. This course builds on the Design Patterns with Python.

At the core of professional programming practice is a thorough knowledge of software design patterns. In this course, Building More Python 2 Design Patterns, you'll learn eight more patterns and how to implement them in Python. First, you'll learn how to recognize problems that are solvable using design patterns. Next, you'll explore how to implement them professionally. Finally, you'll discover how they can be used to make your programs easier to write, read, and maintain. When you're finished with this course, you'll have grown your knowledge of the elements of reusable object-oriented software design that will help you as you move beyond simple scripts to complex systems built in Python.

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What's inside

Syllabus

Course Overview

Introduction

Facade Pattern

Adapter Pattern

Decorator Pattern

Template Pattern

Iterator Pattern

Composite Pattern

State Pattern

Proxy Pattern

Summary

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Develops advanced principles of software design using Python, which is incredibly relevant in industry worldwide

Taught by Gerald Britton, who is recognized for his work in Python design patterns

Covers eight design patterns: Facade, Adapter, Decorator, Template, Iterator, Composite, State, and Proxy, which are essential for professional programming

Builds on Design Patterns with Python, which provides a solid foundation for this course

Assumes familiarity with software design patterns and Python programming, so may not be suitable for beginners

Requires learners to come in with extensive knowledge of object-oriented programming (OOP) concepts

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Building More Python 2 Design Patterns with these activities:

Review Python Syntax and Basic Concepts

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Strengthen your foundation in Python syntax and concepts, which will help you better understand design patterns.

Browse courses on Python

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Review your class notes or an online Python tutorial.
Complete a few practice exercises to test your understanding.
Ask for help from a classmate or instructor if needed.

Read Head First Design Patterns

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Gain a comprehensive understanding of design patterns and their applications in Python.

View Entwurfsmuster von Kopf bis Fuß on Amazon

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Purchase or borrow a copy of Head First Design Patterns.
Read the book, focusing on the chapters that cover design patterns in Python.
Complete the exercises and examples provided in the book.

Learn the Basics of Design Patterns in Python

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Reinforce your understanding of the fundamental concepts of design patterns and how they can be applied in Python.

Browse courses on Design Patterns

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Watch the first few videos of a Python design patterns tutorial series.
Complete any coding exercises or quizzes associated with the videos.

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Attend a Python Design Patterns Workshop

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Gain exposure to different perspectives and best practices in design patterns.

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Find a Python design patterns workshop that fits your schedule.
Register for the workshop and attend all sessions.
Participate actively in discussions and exercises.

Volunteer as a Python Mentor

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Share your knowledge and reinforce your understanding of design patterns by helping others learn.

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Find a volunteer opportunity where you can mentor Python learners.
Prepare a lesson plan that includes content on design patterns.
Meet with your mentee(s) regularly to provide guidance and support.

Implement Design Patterns in Practice Exercises

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Solidify your understanding of how to implement design patterns by working through a series of coding exercises.

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Find a set of Python design patterns practice exercises online or in a textbook.
Choose a few exercises to work on, starting with the easier ones.
Implement the design patterns in Python code.
Test your code to ensure that it works as intended.

Develop a Small Python Project Using Design Patterns

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Apply your knowledge of design patterns to a real-world project, solidifying your understanding and practical skills.

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Identify a small project idea that you can complete in a reasonable amount of time.
Design the project architecture using design patterns.
Implement the project in Python, applying the design patterns you chose.
Test and debug your project to ensure that it works as intended.

Write a Blog Post Explaining a Design Pattern

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Deepen your understanding of a specific design pattern by explaining it to others in a blog post.

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Choose a design pattern that you are familiar with.
Write a blog post that explains the pattern, its benefits, and how to implement it in Python.
Publish your blog post on a platform like Medium or LinkedIn.

Career center

Learners who complete Building More Python 2 Design Patterns will develop knowledge and skills that may be useful to these careers:

Python Developer

Python Developers specialize in developing software applications using the Python programming language. They may work on a variety of projects, from web development to data analysis. This course may be useful for Python Developers who wish to improve their skills in software design and architecture.

See salaries and explore the career path for Python Developer

Backend Engineer

Backend Engineers design, develop, and maintain the back-end of software applications. They are responsible for the server-side logic, databases, and APIs. This course may be useful for Backend Engineers who wish to specialize in Python development and gain a deep understanding of design patterns for scalable and reliable back-end systems.

See salaries and explore the career path for Backend Engineer

Machine Learning Engineer

Machine Learning Engineers develop and deploy machine learning models. They work on a variety of projects, from predictive analytics to natural language processing. This course may be helpful for Machine Learning Engineers who wish to gain a deeper understanding of design patterns for machine learning applications.

See salaries and explore the career path for Machine Learning Engineer

Web Developer

Web Developers are responsible for designing, developing, and maintaining websites. They may work on a variety of projects, from small personal blogs to large e-commerce sites. This course may be useful for Web Developers who wish to specialize in Python development and gain a deeper understanding of design patterns for scalable and reliable web applications.

See salaries and explore the career path for Web Developer

Full Stack Engineer

Full-Stack Engineers work on both the front-end and back-end of software applications. They are responsible for the entire stack, from the database to the user interface. This course may be helpful for Full-Stack Engineers who wish to focus on the back-end of applications and gain a better understanding of design patterns for robust and scalable software.

See salaries and explore the career path for Full Stack Engineer

Computer Programmer

Computer Programmers write and maintain the code that makes software applications work. They may work on a variety of projects, from small personal projects to large enterprise systems. This course may be useful for Computer Programmers who wish to specialize in Python development and gain a deeper understanding of design patterns for scalable and reliable software.

See salaries and explore the career path for Computer Programmer

Software Architect

Software Architects create the overall structure and design for software systems. They ensure that the system is well-architected and meets the needs of the business. Most roles require at least a bachelor's degree in computer science, with many architects holding advanced degrees. This course may be useful for Software Architects who wish to expand their knowledge of design patterns for complex software systems.

See salaries and explore the career path for Software Architect

DevOps Engineer

DevOps Engineers work to bridge the gap between development and operations teams. They are responsible for automating and streamlining the software development lifecycle. This course may be useful for DevOps Engineers who wish to gain a foundation in Python programming and design patterns for building and maintaining automated systems.

See salaries and explore the career path for DevOps Engineer

Software Engineer

Software Engineers often work with Python to design, develop, test, and deploy software applications. Roles in this job may require a bachelor's degree in software engineering or computer science. Advanced degrees are not typical, but may allow quicker advancement in some circumstances. This course may be useful for Software Engineers who wish to expand their knowledge of best practices and design patterns for Python applications.

See salaries and explore the career path for Software Engineer

Computer Scientist

Computer Scientists conduct research in the field of computer science. They develop new algorithms and techniques for solving problems in a variety of areas, including software engineering, artificial intelligence, and data science. This course may be useful for Computer Scientists who wish to gain a deeper understanding of design patterns for developing complex software systems.

See salaries and explore the career path for Computer Scientist

Software Tester

Software Testers ensure that software applications are working as intended. They develop and execute test cases to identify bugs and defects. This course may be useful for Software Testers who wish to gain a deeper understanding of design patterns for testing complex software systems.

See salaries and explore the career path for Software Tester

Data Analyst

Similar to Data Scientists, Data Analysts also work with data. However, their focus is primarily on data cleaning and preparation rather than complex modeling. Most roles require at least a bachelor's degree in a quantitative field, with a master's degree generally only being necessary for senior roles or those involving highly complex data. This course may be useful to Data Analysts who wish to gain a foundation in design patterns for more complex analyses and data architecture.

See salaries and explore the career path for Data Analyst

Data Scientist

Data Scientists use programming languages like Python to collect, analyze, and interpret large datasets. Many roles require at least a master's degree in data science, but some roles are available to those with a bachelor's degree. This course may be helpful for Data Scientists who wish to gain a deeper understanding of design patterns for data-intensive applications.

See salaries and explore the career path for Data Scientist

Quantitative Analyst

Quantitative Analysts apply mathematical and statistical models to financial data. The work often involves risk management and algorithmic trading. Most roles require a master's degree in financial engineering, quantitative finance, or a related field. This course may be useful for Quantitative Analysts who wish to gain a foundation in Python programming and design patterns.

See salaries and explore the career path for Quantitative Analyst

Technical Writer

Technical Writers create documentation for software applications and other technical products. They explain how to use and maintain the product in clear and concise language. This course may be useful for Technical Writers who wish to gain a deeper understanding of design patterns for creating well-structured and easy-to-understand documentation.

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Reading list

We've selected 14 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Building More Python 2 Design Patterns.

Think Python

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Provides a practical guide to design patterns in Python. It covers a wide range of patterns, from the basics to more advanced topics such as concurrency and metaprogramming.

Building More Python 2 Design Patterns

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What's inside

Syllabus

Good to know

Save this course

Activities

Career center

Reading list

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