Python Nested Functions

What is a Nested Function?

Functions are one of the "first-class citizens" of Python, which means that functions are at the same level as other Python objects like integers, strings, modules, etc. They can be created and destroyed dynamically, passed to other functions, returned as values, etc.

Python supports the concept of a "nested function" or "inner function", which is simply a function defined inside another function. In the rest of the article, we will use the word "inner function" and "nested function" interchangeably.

There are various reasons as to why one would like to create a function inside another function. The inner function is able to access the variables within the enclosing scope. In this article, we will be exploring various aspects of inner functions in Python.

Defining an Inner Function

To define an inner function in Python, we simply create a function inside another function using the Python's def keyword. Here is an example:

def function1(): # outer function
    print ("Hello from outer function")
    def function2(): # inner function
        print ("Hello from inner function")



Hello from outer function
Hello from inner function

In the above example, function2() has been defined inside function1(), making it an inner function. To call function2(), we must first call function1(). The function1() will then go ahead and call function2() as it has been defined inside it.

It is important to mention that the outer function has to be called in order for the inner function to execute. If the outer function is not called, the inner function will never execute. To demonstrate this, modify the above code to the following and run it:

def function1(): # outer function
    print ("Hello from outer function")
    def function2(): # inner function
        print ("Hello from inner function")

The code will return nothing when executed!

Here is another example:

def num1(x):
   def num2(y):
      return x * y
   return num2
res = num1(10)




The code returns the multiplication of the two numbers, that is, 10 and 5. The example shows that an inner function is able to access variables accessible in the outer function.

So far, you have seen that it is possible for us to access the variables of the outer function inside the inner function. What if we attempt to change the variables of the outer function from inside the inner function? Let us see what happens:

def function1(): # outer function
    x = 2 # A variable defined within the outer function
    def function2(a): # inner function
       # Let's define a new variable within the inner function
       # rather than changing the value of x of the outer function
        x = 6
        print (a+x)
    print (x) # to display the value of x of the outer function




The output shows that it is possible for us to display the value of a variable defined within the outer function from the inner function, but not change it. The statement x = 6 helped us create a new variable x inside the inner function function2() rather than changing the value of variable x defined in the outer function function1().

In the next section, we will be discussing the main reasons as to why we use inner functions in Python.

Why use Inner Functions?


A function can be created as an inner function in order to protect it from everything that is happening outside of the function. In that case, the function will be hidden from the global scope. Here is an example:

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def outer_function(x):
    # Hidden from the outer code
    def inner_increment(x):
        return x + 2
    y = inner_increment(x)
    print(x, y)



Traceback (most recent call last):
  File "C:/Users/admin/", line 7, in <module>
NameError: name 'inner_increment' is not defined

In the above code, we are trying to call the inner_increment() function, but instead we got an error.

Now, comment out the call to inner_increment() and uncomment the call to outer_function() as shown below:

def outer_function(x):
    # Hidden from the outer code
    def inner_increment(x):
        return x + 2
    y = inner_increment(x)
    print(x, y)



5 7

The script above shows that the inner function, that is, inner_increment() is protected from what is happening outside it since the variable x inside the inner_increment function is not affected by the value passed to the parameter x of the outer function. In other words, the variables inside the inner function is not accessible outside it. There is a great advantage with such a design pattern. After checking all arguments in the outer function, we can safely skip error checking within the inner function.

Closures and Factory Functions

All the examples we have seen till now just contain ordinary functions that have been nested inside other functions. It is possible for us to write such functions in another way instead of nesting them inside other functions. We don't have a specific reason as to why we should nest them.

However, for the case of closures, one must use the nested functions.

We can bind/pass data to a function without necessarily passing the data to the function via parameters. This is done using a closure. It is a function object that is able to remember values in the enclosing scopes even when they are not available in the memory. This means that we have a closure when a nested function references a value that is in its enclosing scope.

The purpose of a closure is to make the inner function remember the state of its environment when it is called, even if it is not in the memory. A closure is caused by an inner function, but it's not the inner function. The closure works by closing the local variable on the stack, which stays around after the creation of the stack has finished executing.

The following are the conditions that are required to be met in order to create a closure in Python:

  • There must be a nested function
  • The inner function has to refer to a value that is defined in the enclosing scope
  • The enclosing function has to return the nested function

Consider the following example:

def function1(name):
    def function2():
        print('Hello ' + name)
    return function2

func = function1('Nicholas')


Hello Nicholas

The above code demonstrates that with closures, we are able to generate and invoke a function from outside its scope via function passing. The scope of function2() is only inside function1(). However, with the use of closures, it was possible for us to extend this scope and invoke it from outside its scope.

Inner functions help us in defining factory functions. A factory function is a function that creates another object. For example:

def power_generator(num):

    # Create the inner function
    def power_n(power):
        return num ** power

    return power_n

power_two = power_generator(2)
power_three = power_generator(3)



In the script above, from the power_n(power) function, we have created two other objects, power_two and power_three. This makes power_n(power) a factory function since it generates the power_two and power_three functions for us using the parameter we pass it.


An inner function is simply a function that is defined inside another function. The inner function is able to access the variables that have been defined within the scope of the outer function, but it cannot change them. There are a number of reasons as to why we may need to create an inner function. For instance, an inner function is protected from what happens outside it. Inner functions are also a good way of creating closures in Python.

Last Updated: December 21st, 2018
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Nicholas SamuelAuthor

I am a programmer by profession. I am highly interested in Python, Java, Data Science and Machine learning. If you need help in any of these, don't hesitate to contact me.

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