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Reindert-Jan Ekker

Once you are beyond the junior stages of learning to program, you are ready to start thinking about what makes good, clean code. This course will give you a set of tools to help you create higher quality, maintainable Python projects.

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Once you are beyond the junior stages of learning to program, you are ready to start thinking about what makes good, clean code. This course will give you a set of tools to help you create higher quality, maintainable Python projects.

In this course, Python 3 Best Practices, you will learn a number of best practices that will help you improve the quality of your Python code. First, you will discover the guidelines for formatting code called Pep8. Next, you will create beautiful and publishable documentation with Python docstrings and a tool called Sphinx. Finally. you will explore how to improve maintainability and prevent errors by adding type hints to your code. By the end of this course, you will be able to write clearer, more readable, and more maintainable code with better documentation.

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What's inside

Syllabus

Course Overview
Following Python Style Guidelines: Pep8
Documenting Your Project
Improve Your Code with Type Checking
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Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Explores Python style guidelines, which are standard in industry
Teaches Python docstrings, which helps learners create beautiful and publishable documentation
Examines type checking, which is highly relevant to improving maintainability

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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 Python 3 Best Practices with these activities:
Guided tutorials: Formatting Python code according to PEP8
Following Python's style guidelines will help ensure consistency in your code, improve readability, and reduce errors.
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  • Review the PEP8 style guide.
  • Install an extension like Jedi for your IDE to help automatically format your code according to PEP8.
Practice: Applying Pep8 to existing code
Manually refactoring code to adhere to PEP8 will solidify your understanding of the guidelines.
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  • Find a code sample with poor Python style.
  • Refactor the code sample to adhere to PEP8 guidelines.
  • Compare your refactored code to the original code and identify the changes you made to adhere to PEP8.
Create: Python Docstrings for a sample function
Writing clear and concise docstrings will improve the readability and maintainability of your code.
Show steps
  • Choose a Python function from your code or an open-source project.
  • Write a complete docstring for the function following the PEP257 conventions.
Four other activities
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Guided Tutorials: Using Sphinx to Generate Documentation
Using Sphinx to generate documentation will allow you to create professional-looking documentation for your codebase.
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Show steps
  • Review the Sphinx documentation.
  • Install Sphinx.
  • Create a sample Sphinx project and include your docstrings.
Practice: Adding Type Hints to Existing Code
Adding type hints to your code will help identify potential issues and improve code maintainability.
Browse courses on Type Hints
Show steps
  • Find a Python code sample without type hints.
  • Add type hints to the code sample.
  • Run type checking on the code sample within your IDE or using an external tool like mypy.
Create: Blog Post on Python Type Checking
Writing a blog post about type checking will allow you to share your knowledge with others and solidify your understanding of the topic.
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Show steps
  • Choose a topic related to Python type checking that you are familiar with.
  • Research and gather information on your topic.
  • Write a blog post that is informative and engaging.
Contribute: Fix a Python Bug on GitHub
Make changes to this open-source Python library that improves the implementation.
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  • Browse popular Python repositories on GitHub.
  • Identify a bug report issue you are interested in.
  • Fork the repository, make your changes, and submit a pull request.

Career center

Learners who complete Python 3 Best Practices will develop knowledge and skills that may be useful to these careers:
Data Scientist
Data Scientists analyze data to extract insights and solve problems. Python is a popular language for data science thanks to its extensive libraries. This course will teach you best practices for writing Python code, which will make you more competitive as a Data Scientist.
Machine Learning Engineer
Machine Learning Engineers build and maintain machine learning models. Python is a popular language for machine learning thanks to its extensive libraries. This course will teach you best practices for writing Python code, which will make you more competitive as a Machine Learning Engineer.
Web Developer
Web Developers design and develop websites and web applications. Python is a popular language for web development thanks to its extensive libraries. This course will teach you best practices for writing Python code, which will make you more competitive as a Web Developer.
Data Analyst
Data Analysts analyze data to extract insights and solve problems. Python is a popular language for data analysis thanks to its extensive libraries. This course will teach you best practices for writing Python code, which will make you more competitive as a Data Analyst.
DevOps Engineer
DevOps Engineers bridge the gap between development and operations teams. Python is a popular language for DevOps thanks to its extensive libraries. This course will teach you best practices for writing Python code, which will make you more competitive as a DevOps Engineer.
Software Engineer
Software Engineers design, develop, test, and maintain software systems. Python is very popular in software engineering. This course will teach you best practices for writing Python code, which will make you more employable as a software engineer.
Cloud Engineer
Cloud Engineers design, build, and maintain cloud-based systems. Python is a popular language for cloud engineering thanks to its extensive libraries. This course will teach you best practices for writing Python code, which will make you more competitive as a Cloud Engineer.
Project Manager
Project Managers plan, execute, and close projects. Python is a popular language for project management thanks to its extensive libraries. This course will teach you best practices for writing Python code, which will make you more competitive as a Project Manager.
Business Analyst
Business Analysts analyze business needs and develop solutions to improve business processes. Python is a popular language for business analysis thanks to its extensive libraries. This course will teach you best practices for writing Python code, which will make you more competitive as a Business Analyst.
Product Manager
Product Managers lead the development and launch of new products. Python is a popular language for product management thanks to its extensive libraries. This course will teach you best practices for writing Python code, which will make you more competitive as a Product Manager.
Network Administrator
Network Administrators manage and maintain computer networks. Python is a popular language for network administration thanks to its extensive libraries. This course will teach you best practices for writing Python code, which will make you more competitive as a Network Administrator.
Database Administrator
Database Administrators manage and maintain databases. Python is a popular language for database administration thanks to its extensive libraries. This course will teach you best practices for writing Python code, which will make you more competitive as a Database Administrator.
Technical Writer
Technical Writers create and maintain technical documentation. Python is a popular language for technical writing thanks to its extensive libraries. This course will teach you best practices for writing Python code, which will make you more competitive as a Technical Writer.
Systems Administrator
Systems Administrators manage and maintain computer systems. Python is a popular language for systems administration thanks to its extensive libraries. This course will teach you best practices for writing Python code, which will make you more competitive as a Systems Administrator.
Software Tester
Software Testers test software to find and fix bugs. Python is a popular language for software testing thanks to its extensive libraries. This course will teach you best practices for writing Python code, which will make you more competitive as a Software Tester.

Reading list

We've selected 12 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 Python 3 Best Practices.
Provides a comprehensive set of best practices and guidelines for writing clean and maintainable code. It covers topics such as naming conventions, code organization, and testing.
Provides a catalog of design patterns that can be used to solve common software design problems. It covers topics such as creational patterns, structural patterns, and behavioral patterns.
Provides a more accessible introduction to design patterns than the classic "Design Patterns" book. It uses a conversational style and lots of diagrams to explain complex concepts.
Provides a practical guide to agile software development in C#. It covers topics such as test-driven development, refactoring, and continuous integration.
Provides a comprehensive guide to unit testing. It covers topics such as test design, test automation, and mocking.
Provides a practical introduction to test-driven development. It uses a simple example to explain the key concepts and benefits of TDD.
Provides a comprehensive guide to domain-driven design. It covers topics such as identifying domain concepts, building domain models, and implementing domain-driven applications.
Provides a practical guide to software architecture. It covers topics such as layering, dependency inversion, and hexagonal architecture.
Provides a comprehensive guide to the architecture of open source applications. It covers topics such as design patterns, refactoring, and testing.
Provides a practical guide to implementing domain-driven design. It covers topics such as identifying domain concepts, building domain models, and implementing domain-driven applications.

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