Python: Coding Guidelines, Tools, Tests and Packages [2024]
Python: Coding Guidelines, Tools, Tests and Packages [2024], available at $79.99, has an average rating of 4.63, with 61 lectures, 9 quizzes, based on 416 reviews, and has 4029 subscribers.
You will learn about The Coding guidelines and good practice programming (PEP8) Tooling with Pylint, Flake8, Autopep8, Black etc. Type Annotations and Mypy The usage of Debugging, Profiling, Timing and Unit Testing The creation of own Python packages The creation of a modern HTML documentation The usage of continouos integration tools This course is ideal for individuals who are (Junior) Python developer who want to master the language It is particularly useful for (Junior) Python developer who want to master the language.
Enroll now: Python: Coding Guidelines, Tools, Tests and Packages [2024]
Summary
Title: Python: Coding Guidelines, Tools, Tests and Packages [2024]
Price: $79.99
Average Rating: 4.63
Number of Lectures: 61
Number of Quizzes: 9
Number of Published Lectures: 60
Number of Published Quizzes: 9
Number of Curriculum Items: 70
Number of Published Curriculum Objects: 69
Original Price: $29.99
Quality Status: approved
Status: Live
What You Will Learn
- The Coding guidelines and good practice programming (PEP8)
- Tooling with Pylint, Flake8, Autopep8, Black etc.
- Type Annotations and Mypy
- The usage of Debugging, Profiling, Timing and Unit Testing
- The creation of own Python packages
- The creation of a modern HTML documentation
- The usage of continouos integration tools
Who Should Attend
- (Junior) Python developer who want to master the language
Target Audiences
- (Junior) Python developer who want to master the language
Course description:
In this course, you will explore coding guidelines and best practices, such as PEP8, as well as using popular Python tools like Pylint, Flake8, Autopep8, Black, and Pydocstyle. Additionally, you will learn about different docstring styles, such as Sphinx, Numpy, and Google, as well as using type annotations and the static type checker, MyPy. You will also gain practical experience in debugging, profiling, timing, and unit testing (TDD). Furthermore, you will learn how to create your own Python packages, modern HTML documentation using MkDocs and Google documentation strings, and how to use continuous integration tools like GitHub Actions for testing and code documentation.
The Course covers the following Topics:
Installing and setting up the software
The coding guidelines and good practice programming (PEP8)
The usage of Pylint, Flake8, Autopep8, Black and Pydocstyle
Different docstring styles for your code (sphinx, numpy and google)
The usage of type annotations and the static type checker MyPy
The usage of debugging, profiling, execution time measuring (timing) and unit testing (TDD)
The creation of own Python packages that can be uploaded to PyPi
The creation of a modern HTML documentation with mkdocs and google documenation strings
The usage of continouos integration tools (Github actions for testing and codedoc)
Step ahead in your Python career and join this course!
I hope will see you there!
Course Curriculum
Chapter 1: Chapter 1: Introduction and Software
Lecture 1: Introduction to the course
Lecture 2: Course manual
Lecture 3: Note: Materials and Software
Lecture 4: Setup the Python Environment
Lecture 5: Setup Visual Studio Code
Chapter 2: Chapter 2: Coding Guidelines and Docstrings
Lecture 1: PEP8 Coding Guidelines – Part 1
Lecture 2: PEP8 Coding Guidelines – Part 2
Lecture 3: Vscode Settings for the Tools
Lecture 4: Tool: isort
Lecture 5: Code Linter: Why do we need them?
Lecture 6: Code Linter: Flake8 and Pylint
Lecture 7: Code Linter: Ruff
Lecture 8: Formatter: Why do we need them?
Lecture 9: Formatter: Black
Lecture 10: Formatter: Ruff
Lecture 11: Example Class: Vector2D
Lecture 12: Docstring Styles
Lecture 13: Code Linter: Pydocstyle
Lecture 14: What is a Python Type Annotation? – Part 1
Lecture 15: What is a Python Type Annotation? – Part 2
Lecture 16: What is a Python Type Annotation? – Part 3
Lecture 17: Type Annotations: Union
Lecture 18: Type Annotations: Any and Optional
Lecture 19: Python 3.9 Type Annoations
Lecture 20: Type Annotation: List
Lecture 21: Type Annotation: Tuple
Lecture 22: Type Annotation: Callable
Lecture 23: Python 3.10 Type Annoations
Lecture 24: Type Annotation: Dict and Mapping
Lecture 25: Type Annotation: NoReturn
Lecture 26: Python 3.10 Type Annotations: TypeGuard
Lecture 27: Type Annotation: Protocol
Lecture 28: Type Annotation: Generic Functions
Lecture 29: Type Annotation: Generic Classes
Lecture 30: Type Annotations: NamedTuple and TypedDict
Lecture 31: Python 3.11 Type Annoations: Literals
Lecture 32: Python 3.12 Type Annoations
Lecture 33: pre-commit
Lecture 34: Config files for the tools
Lecture 35: Real World Example for the Tools
Chapter 3: Chapter 3: Debugging, Unit-Testing and Timing
Lecture 1: Debugging in VS Code: Python Part 1
Lecture 2: Debugging in VS Code: Python Part 2
Lecture 3: Debugging in VS Code: Jupyter Notebook
Lecture 4: Tasks in VS Code
Lecture 5: Timing
Lecture 6: Profiling
Lecture 7: Unit-Testing with unittest
Lecture 8: Unit-Testing with pytest
Chapter 4: Chapter 4: Packaging
Lecture 1: Modules and Packages – Part 1
Lecture 2: Modules and Packages – Part 2
Lecture 3: Modules and Packages – Part 3
Lecture 4: Modules and Packages – Part 4
Lecture 5: Overview for our Vector Python Package
Lecture 6: Metadata and Install the Library
Lecture 7: Mkdocs and Github Pages
Lecture 8: Pre-Commit Hooks
Lecture 9: More to Github Actions
Lecture 10: Code Coverage
Chapter 5: Chapter 5: Course conclusion
Lecture 1: Course conclusion
Lecture 2: Bonus Lecture
Instructors
-
Jan Schaffranek
M.Sc in Computer Science – Machine Learning, C/C++, Python
Rating Distribution
- 1 stars: 1 votes
- 2 stars: 6 votes
- 3 stars: 37 votes
- 4 stars: 142 votes
- 5 stars: 230 votes
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