Ultimate Python Decorators Crash Course
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Kuldeep Singh
Outline:
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Chapter 1: Introduction to Python Decorators
- Brief on Python decorators
- Importance and use cases of decorators
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Chapter 2: Understanding Functions in Python
- Defining and calling functions
- Function parameters and return values
- First-class functions
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Chapter 3: Creating a Simple Decorator
- Structure of a Python decorator
- Creating a basic decorator
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Chapter 4: Practical Applications of Decorators
- Using decorators for timing functions
- Using decorators for counting function calls
-
Chapter 5: Advanced Decorator Concepts
- Nested decorators
- Decorators with parameters
- Chaining decorators
-
Chapter 6: Useful Decorators in the Python Standard Library
- The
@staticmethod
decorator - The
@classmethod
decorator - The
@property
decorator
- The
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Chapter 7: Creating a Logger Decorator
- Introduction to Python's logging module
- Creating a logger decorator
-
Chapter 8: Creating a Cache Decorator
- Explanation of memoization
- Creating a cache decorator
-
Chapter 9: Creating a Rate-Limiting Decorator
- Explanation of rate limiting
- Creating a rate limiting decorator
-
Chapter 10: Testing Decorators
- Importance of testing
- Testing decorators using Python's
unittest
module
Comprehensive
This eBook covers a wide range of topics, from the basics of Python functions and decorators to creating and testing your own decorators. It provides a complete overview of Python decorators for both beginners and experienced developers.
Practical and Hands-on
The eBook is designed to be practical, with numerous examples and exercises. It includes step-by-step guides to creating different types of decorators, such as a logger decorator, a cache decorator, and a rate limiting decorator.
Useful Code Snippets
Each chapter includes relevant and ready-to-use Python code snippets. This feature allows readers to practice and understand the concepts better.
Accessible for Various Skill Levels
The eBook starts with basic concepts, making it accessible for beginners. It then progressively covers more advanced topics, making it a valuable resource for more experienced Python programmers as well.
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