Understanding Generators in Python.

Generators is a function in which objects are created at once but not all code is executed at once as done in normal function. In normal function execution from top to the return statement. A function that consists of a yield statement is called a generators function. The execution of the generator function happens differently, in which the code execution stops at the yield statement rather than a return statement, to move to the next statement next() method is called which will start the execution of the code from where it is left over. If no yield statement is found a StopIteration exception is raised.

So lets see how to create, execute a Generators in python.

def fib(n):
    a, b = 0, 1
    while a <= n:
        yield a   # yield statement.
        a, b = b, a + b

Now let execute the method fib().

fib_fun = fib(10)
next(fib_fun) # 0
next(fib_fun) # 1
next(fib_fun) # 1
.
.
.
next(fib_fun) # 8
next(fib_fun) # reached the end will raise StopIteration Error.
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
StopIteration
 

# Else you can use for loop which call next() in the background.

for fib_value in fib(10):
    print(fib)

# Output
0
1
1
2
3
5
8

So here we today understand the Generators concept in python. Now you would be thinking where we can use this, let me state some use cases.

  • Can be used for memory management, where we pass the whole list as once, we can use Generator to pass data one by one so that less load comes on memory.
  • Generator can be used to define infinite streams.

If you know any more use case, please do share in the comments and if want to share something else or talk about Generators feel free to ping me on twitter

Till then Cheers 🙂
Happy Digging.

What is Closures ?

Today we will talk about Closure a functional object in Python.

Closure is a function object which has access to the local variables/free variables of the enclosing scope and can be executed outside of its scope. Nested function is a Closure function if

  • It can access variables that are local to enclosing scope.
  • It can be executed outside for its scope.

Closure can used for one of these

  • Replacing the hard coded constants.
  • Eliminating global.
  • Can be used for data hiding and many other things.

So lets see with a code snippet to see how closure and nested function are different from each other.

# nested functions 
def inc_x(x):  
    def add_10(x=x):
        print("{0} is increased by 10 = {1}".format(x, x+10)) 
    return add_10()  # remember about the parenthesis.
  
inc_value = inc_x(10)
inc_value  #Output: 10 is increased by 10 = 20

So above function will be called a Nested function, not a Closure because

  • Inner function [add_10] doesn’t access the local variable of enclosing function inc_x. It used the value of X rather than using a reference.
  • Inner function [add_10] cannot be executed outside the scope of inc_x.

Now let see the Closure function example.

# closure functions 
def inc_x(x):  
    def add_10(): 
        print("{0} is increased by 10 = {1}".format(x, x+10)) 
    return add_10 # returning function without parenthesis, passing only references.
  
inc_value = inc_x(10)
# We are able to execute the inner function outside of its scope.
inc_value() 
#Output: 10 is increased by 10 = 20

So above code will be called as Closure function rather than Nested function because

  • add_10 function is accessing the local variable of the inc_x function.Here a reference to the local variable of inc_x is maintained in the add_10.
  • add_10 can even be executed outside the body/scope of inc_x function.

Closure in python is created by a function call, here every time inc_x is called a new instance of this function is created. So whenever you call inc_x a binding reference is made to x which is used in add_10 function.

So let see how under the hood these variable reference are maintained

  • Function attributes func_closure in python < 3.X or closure in python > 3.X save the these references to these variable or also called as free variable. Let see how to access these values.
# Taking same example for the above code
def inc_x(x):  
    def add_10(): 
        print("{0} is increased by 10 = {1}".format(x, x+10)) 
    return add_10

add_10 = inc_x(30)

add_10()
# Output: 30 is increased by 10 = 40

# Checking whether it is Closure or not.

'__closure__'  in  dir(add_10)

# Output: True

# Getting the free variable value from closure.

add_10.__closure__[0].cell_contents 

# Output: 30

While talking about the closure we also heard the term free variables which is also an interesting topic to discuss, which I will cover in the next blog post, till then

Cheers !! 🙂
Happy Learning

Image by JacLou DL from Pixabay