Course Content

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

Lambda Functions in Python: Writing Concise and Anonymous Functions

In Python, lambda functions are anonymous functions defined using the lambda keyword. They are often used for short, single-operation functions without a name, and can be passed as arguments to other functions, just like regular functions.

Here's an example demonstrating how to pass a lambda function as an argument to another function:


              12345678
            
# Define a function that takes a function and a value as arguments
def apply_function(func, value):
    return func(value)

# Call the function with a lambda function as the first argument
result = apply_function(lambda x: x * x, 5)

print(result)

apply_function is a function that accepts another function (func) and a value (value), and then applies func to value.
A lambda function lambda x: x * x is defined inline and passed as an argument to apply_function. This lambda function squares its input.
The apply_function is called with the lambda function and the value 5, resulting in the lambda function squaring 5, which yields 25.

Task

Swipe to start coding

Suppose you have a list of numbers, and you want to apply different operations to the same list, like adding a constant value to each element or multiplying each element by a constant.

apply_to_list is our custom function that applies a given function (func) to each element in numbers.
We call apply_to_list twice with different lambda functions.
The first lambda function (lambda x: x + 10) adds 10 to each element.
The second lambda function (lambda x: x * 2) multiplies each element by 2.

Actually, we are creating our own version of the map function.

Solution

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Section 3. Chapter 2

Lambda Functions in Python: Writing Concise and Anonymous Functions

Here's an example demonstrating how to pass a lambda function as an argument to another function:


              12345678
            
# Define a function that takes a function and a value as arguments
def apply_function(func, value):
    return func(value)

# Call the function with a lambda function as the first argument
result = apply_function(lambda x: x * x, 5)

print(result)

apply_function is a function that accepts another function (func) and a value (value), and then applies func to value.
A lambda function lambda x: x * x is defined inline and passed as an argument to apply_function. This lambda function squares its input.
The apply_function is called with the lambda function and the value 5, resulting in the lambda function squaring 5, which yields 25.

Task

Swipe to start coding

Suppose you have a list of numbers, and you want to apply different operations to the same list, like adding a constant value to each element or multiplying each element by a constant.

apply_to_list is our custom function that applies a given function (func) to each element in numbers.
We call apply_to_list twice with different lambda functions.
The first lambda function (lambda x: x + 10) adds 10 to each element.
The second lambda function (lambda x: x * 2) multiplies each element by 2.

Actually, we are creating our own version of the map function.

Solution

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Thanks for your feedback!

Section 3. Chapter 2

Switch to desktop for real-world practiceContinue from where you are using one of the options below