Kursusindhold

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

Python Decorator Syntax: Writing and Applying Decorators

Decorator works by taking a function as an argument and then executing it within a wrapper function.

To apply a decorator, one can use the @ symbol followed by the decorator function's name, placed right above the function that needs to be modified. Here's an example:

def decorator(func):
    ...

# First method
@decorator
add(a,b):
    print(f"Function add: {a} + {b}")

add(2, 3)

# Second method
add(a,b):
    print(f"Function add: {a} + {b}")

inner = decorator(add)

inner(2, 3)

In this example, both methods achieve the same outcome. The first method, using the @ symbol, is a more readable and concise way to apply decorators, often referred to as "syntactic sugar".

It's typical to use a nested function named wrapper within decorators.

Flexible Decorators: Accommodating Diverse Function Arguments

Functions often require a varying number of arguments. To develop a decorator capable of being applied to functions with differing argument counts, it's effective to utilize *args and **kwargs in the wrapper() function.


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def indicate(func):
    def wrapper(*args, **kwargs):
        print("=" * 15)
        print("Taken arguments:", *args, kwargs)
        result = func(*args, **kwargs)
        print("=" * 15)
        return result
    return wrapper


@indicate
def avg_two(a, b):
    """Calculate the average of two numbers"""
    return round((a + b) / 2, 1)

@indicate
def avg_three(a, b, c):
    """Calculate the average of three numbers"""
    return round((a + b + c) / 3, 1)

@indicate
def avg_many_kwargs(**kwargs):
    """Calculate the average of multiple numbers in a dictionary"""
    keys = 0
    total = 0

    for value in kwargs.values():
        keys += 1
        total += value

    return round(total / keys, 1)

print("Returned:", avg_two(14, 21), "\n")
print("Returned:", avg_three(225, 12, 11), "\n")
print("Returned:", avg_many_kwargs(first=51, second=11, third=47, fourth=93))

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