Contenuti del Corso

Intermediate Python Techniques

1. Mastering Packing and Unpacking in Python

Unpacking in Python: Extracting Values from Lists and Tuples Packing in Python: Grouping Multiple Values into a Single Variable Using Packing and Unpacking for Efficient Code in Python Challenge: Mastering Dictionary Unpacking in Python Challenge: The Champions League

2. Mastering Function Arguments in Python

Python Function Arguments: Overview of Parameters and Arguments Using *args in Python: Handling Variable-Length Positional Arguments Challenge: Calculating the Average Mark with *args Using **kwargs in Python: Flexible Keyword Arguments for Dynamic Functions Challenge: Mastering **kwargs in Python Functions

3. Function as an Argument in Python

High-Order Functions in Python: Passing Functions as Arguments Lambda Functions in Python: Writing Concise and Anonymous Functions Using Python Built-in Functions

4. Understanding Variable Scope in Python

Global Variables in Python: Accessing and Modifying Global Data Local Variables in Python: Understanding Function-Level Scope Challenge: Modifying a Global Variable in Python Nested Functions in Python: Scope and Accessibility Nonlocal Variables in Python: Working with Enclosed Scopes Python Closures: Retaining State in Nested Functions Challenge: Implementing a Threshold Checker with Closures

5. Mastering Python Decorators

Introduction to Python Decorators Python Decorator Syntax: Writing and Applying Decorators Challenge: Create Your First Python Decorator Using Decorators with Parameters in Python Chaining Multiple Decorators: Advanced Function Modifications Challenge: Basic Smores Recipe Practical Examples of Python Decorator Usage in Real Applications

Practical Examples of Python Decorator Usage in Real Applications

Decorators in Python are a powerful tool for modifying the behavior of functions or methods. The most common usages are sleeping, timing validation, and logging.

1. Sleeping Decorator

This decorator will make the function wait for a specified amount of time before executing.


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import time

def sleep_decorator(seconds):
    def decorator(func):
        def wrapper(*args, **kwargs):
            print(f"Sleeping for {seconds} seconds before executing '{func.__name__}'")
            time.sleep(seconds)
            return func(*args, **kwargs)
        return wrapper
    return decorator

@sleep_decorator(2)
def my_function():
    print("Function executed!")

# Usage
my_function()

2. Validation Decorator

This decorator checks if the inputs to a function meet certain criteria.


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def validate_decorator(func):
    def wrapper(number):
        if not isinstance(number, int) or number < 0:
            raise ValueError("Input must be a non-negative integer")
        return func(number)
    return wrapper

@validate_decorator
def factorial(n):
    if n == 0:
        return 1
    else:
        return n * factorial(n - 1)

# Usage
print(factorial(5))
# factorial(-1) # This will raise an error

3. Timing Decorator

This decorator measures the execution time of a function. We have already used it previous chapter.


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import time

def timing_decorator(func):
    def wrapper(*args, **kwargs):
        start_time = time.time()
        result = func(*args, **kwargs)
        end_time = time.time()
        print(f"'{func.__name__}' executed in {end_time - start_time} seconds")
        return result
    return wrapper

@timing_decorator
def some_function():
    time.sleep(1)  # Simulating a task
    print("Function completed")

# Usage
some_function()

The decorator for login verification uses additional libraries and is used in website development, so it is more appropriate to consider this decorator in the context of website creation.

As we said, decorators are a complex topic in Python and sometimes require more practice to fully understand this topic. You are on the right path in building a programmer's mindset.

Download notes on the course. 😉

1. What will be the output of the following code?

2. What will be the output of the following code?

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Sezione 5. Capitolo 7

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