05 Functions - 02 Scope of Variables

If a variable is defined inside a function, it cannot be accessed outside its scope.

Function Calls and Scope Issues

The main() function prompts for a name and calls another function to process it.

# Defining and calling functions
>>> def main():
...     name = input("What's your name? ")    
...     hello(name)
... 
>>> def hello(to="world"):
...     print("Hello,", to)
... 
>>> main()
What's your name? : Sujith
Hello, Sujith

# Scope issue example
>>> def main():
...     name = input("What's your name? ")    
...     hello()
... 
>>> def hello():   # No parameter defined
...     print("Hello,", name)  
... 
>>> main()
What's your name? : Sujith
NameError: name is not defined

Since name is local to main(), hello() cannot access it directly.

Issue of “Scope” which refers to a variable only existing in the context it was defined in. name was defined in main() so it cannot be used directly in hello(). When the value is handed to hello() within the main(), it can be used. Its for each function to name its own variable so the “name” variable in main can be passed to “hello” which becomes “to”

Returning values allows functions to pass data back.

# Returning values between functions
>>> def main():
...     x = int(input("What's x? "))
...     print("Value of x squared is:", square(x))
... 
>>> def square(n):
...     return n * n  
... 
>>> main()
What's x? 4
Value of x squared is: 16

Scope in Functions

Local vs. Global Scope

Variables inside a function are separate from those outside.

# Scope demonstration
>>> def f():
...     y = x
...     print(y)
... 
>>> x = 7  # Global variable
>>> f()  
7

If a variable is defined inside the function, it does not check the external definition:

# Local scope overriding global
>>> def f():
...     y = x  
...     print(y)  
...     x = 22  # Local x is defined after usage  
... 
>>> x = 7
>>> f()
UnboundLocalError: local variable 'x' referenced before assignment

in first case, there is no x inside the function so it checks outside. this applies only to immutable values.

Global Variables and Mutability

Lists and dictionaries are mutable and can be updated globally.

# Modifying a global mutable variable

>>> def f():
...     y = x[0]
...     print(y)
...     x[0] = 22  # Modifies global list
... 
>>> x = [7]  # x is a list
>>> f()  # Prints 7 and updates x
7
>>> print(x)  
[22]

Modifying Global Immutable Variables

To modify global immutable variables, global must be declared.

# Using global to modify immutable variables
>>> def f():
...     global x  # Declare global usage
...     y = x
...     print(y)
...     x = 22  # Modifies global x
... 
>>> x = 7
>>> f()  #  Prints 7, updates x to 22  
7
>>> print(x)  
22

Nested Functions

A function can be defined inside another function called “helper” function.

# Nested functions example
>>> def f():
...     def g(a):
...         return a + 1
...     def h(b):
...         return 2 * b
...     global x
...     y = g(x) + h(x)
...     print(y)
...     x = 22
... 
>>> x = 7
>>> f()  
15
>>> print(x)  
22

Here, g() and h() are only accessible within f(). Nested functions are useful for encapsulating helper logic within a function.

Global Keyword

The global keyword in Python allows you to modify a variable defined outside a function from within the function. Without using global, a variable inside a function would be considered local, and changes to it wouldn’t affect the global variable.

>>> x = 5
>>> def modify_global():
...     global x
...     x = 10  # This modifies the global variable 'x'  
... 
>>> modify_global()
>>> print(x)  
10

• The global x statement inside the function tells Python to modify the global x variable, not a local one.
• After calling modify_global(), the value of x is updated to 10.

Passing a Group of Elements to a Function

To pass multiple elements (such as a list of numbers) to a function, you can group them together in a list or another collection type and pass that collection to the function.

Example: Passing a List to a Function

>>> def process_numbers(lst):
...     total = sum(lst)
...     print("Total:", total)
... 
>>> numbers = [int(x) for x in input().split()]
>>> process_numbers(numbers)
1 2 3 4
Total: 10

• The process_numbers() function accepts a list of numbers, calculates the total sum, and prints it.
• The list numbers is created by reading space-separated input values, converting them to integers, and passing the list to the function.

This approach is flexible and can be adapted to process any group of data.