Intermediate Python Techniques

Challenge: Calculating the Average Mark with *args

Tehtävä

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Let's calculate the average mark for the student. Each student has a different number of marks, so we don't know how many arguments will be passed to the function.

Set the first positional argument as name in the average_mark function;
For other arguments use *args;
In the equation that counts the mark variable use args without *;
In the print statement use name and mark variables.

Ratkaisu

def average_mark(name, *args):

mark = round(sum(args)/len(args), 1) # average value rounded to the 1 num after the dot

print(f"{name} got {mark}")

average_mark("Tom", 4.0, 3.5, 3.0, 3.3, 3.8)

average_mark("Dick", 2.5, 3.8)

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def average_mark(___, ___):

mark = round(sum(___)/len(___), 1) # average value rounded to the 1 num after the dot

print(f"{___} got {___}")

average_mark("Tom", 4.0, 3.5, 3.0, 3.3, 3.8)

average_mark("Dick", 2.5, 3.8)

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Intermediate Python Techniques

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1. Mastering Packing and Unpacking in Python

You'll find this topic enjoyable, and you'll learn how to pack and unpack values in a single assignment.

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

Explore the power of Python's function arguments, *args, **kwargs, and learn how to effectively use functions as arguments.

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

Discover the higher-order functions and how functions can be passed as arguments to other functions in programming.

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

What is variable scope, and how did we manage without it before? This topic is essential for understanding the following subjects: Closures and Decorators. I assure you that this topic will be both enjoyable and practical. You will gain knowledge about local, nonlocal, and global variables.

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

This section provides an in-depth exploration of Python decorators, a powerful feature that allows for the modification and enhancement of function behavior. Participants will learn how to write their own decorators, understand built-in decorators, and apply decorators in practical scenarios.

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