Closures (learnpython.org)

Closures in Python are functions that remember and retain references to variables from the scope in which they were defined. This unique feature enables the creation of self-contained functions that encapsulate both behavior and data, promoting code modularity and reusability.

#Closures
def transmit_to_space(message):
    "This is the enclosing function"
    def data_transmitter():
        "The nested function"
        print(message)

    data_transmitter()

print(transmit_to_space("Test message"))

Closures are formed when a nested function references variables from its containing scope. The inner function retains access to those variables, even when the outer function has finished executing, creating a persistent bond between the function and its environment.

#Nonlocal keyword (Result 3, 3)
def print_msg(number):
    def printer():
        "Here we are using the nonlocal keyword"
        nonlocal number
        number=3
        print(number)
    printer()
    print(number)

print_msg(9)

#Nonlocal keyword (Result 3, 9)
def print_msg(number):
    def printer():
        "Here we are using the nonlocal keyword"
#Removed the Nonlocal
        number=3
        print(number)
    printer()
    print(number)

print_msg(9)

Closures are formed when a nested function references variables from its containing scope. The inner function retains access to those variables, even when the outer function has finished executing, creating a persistent bond between the function and its environment.

#Return Nested Function
def transmit_to_space(message):
    "This is the enclosing function"
    def data_transmitter():
        "The nested function"
        print(message)
    return data_transmitter

#Calling the Function
def transmit_to_space(message):
  "This is the enclosing function"
  def data_transmitter():
      "The nested function"
      print(message)
  return data_transmitter

fun2 = transmit_to_space("Burn the Sun!")
fun2()

Closures find practical use in various scenarios, such as creating decorators, implementing callback functions, and facilitating partial function application. They are invaluable tools in functional programming and event-driven systems.

Closures Exercise Solution

#Code Completed
def multiplier_of(n):
    def multiplier(number):
        return number*n
    return multiplier

multiplywith5 = multiplier_of(5)
print(multiplywith5(9))

By understanding closures and incorporating them into our code, we can enhance code flexibility, encapsulation, and reusability. Leveraging closures empowers us to write elegant and modular code that effectively addresses complex programming challenges.