Let’s say that a function A is required only by function B, should A be defined inside B?

Simple example. Two methods, one called from another:

def method_a(arg):
    some_data = method_b(arg)

def method_b(arg):
    return some_data

In Python we can declare def inside another def. So, if method_b is required for and called only from method_a, should I declare method_b inside method_a? like this :

def method_a(arg):
    
    def method_b(arg):
        return some_data

    some_data = method_b(arg)

Or should I avoid doing this?

>>> def sum(x, y):
...     def do_it():
...             return x + y
...     return do_it
... 
>>> a = sum(1, 3)
>>> a
<function do_it at 0xb772b304>
>>> a()
4

Is this what you were looking for? It’s called a closure.

You don’t really gain much by doing this, in fact it slows method_a down because it’ll define and recompile the other function every time it’s called. Given that, it would probably be better to just prefix the function name with underscore to indicate it’s a private method — i.e. _method_b.

I suppose you might want to do this if the nested function’s definition varied each time for some reason, but that may indicate a flaw in your design. That said, there is a valid reason to do this to allow the nested function to use arguments that were passed to the outer function but not explicitly passed on to them, which sometimes occurs when writing function decorators, for example. It’s what is being shown in the accepted answer although a decorator is not being defined or used.

Update:

Here’s proof that nesting them is slower (using Python 3.6.1), although admittedly not by much in this trivial case:

setup = """
class Test(object):
    def separate(self, arg):
        some_data = self._method_b(arg)

    def _method_b(self, arg):
        return arg+1

    def nested(self, arg):

        def method_b2(self, arg):
            return arg+1

        some_data = method_b2(self, arg)

obj = Test()
"""
from timeit import Timer
print(min(Timer(stmt='obj.separate(42)', setup=setup).repeat()))  # -> 0.24479823284461724
print(min(Timer(stmt='obj.nested(42)', setup=setup).repeat()))    # -> 0.26553459700452575

Note I added some self arguments to your sample functions to make them more like real methods (although method_b2 still isn’t technically a method of the Test class). Also the nested function is actually called in that version, unlike yours.

A function inside of a function is commonly used for closures.

(There is a lot of contention over what exactly makes a closure a closure.)

Here’s an example using the built-in . It defines start once and uses it from then on:

def sum_partial(start):
    def sum_start(iterable):
        return sum(iterable, start)
    return sum_start

In use:

>>> sum_with_1 = sum_partial(1)
>>> sum_with_3 = sum_partial(3)
>>> 
>>> sum_with_1
<function sum_start at 0x7f3726e70b90>
>>> sum_with_3
<function sum_start at 0x7f3726e70c08>
>>> sum_with_1((1,2,3))
7
>>> sum_with_3((1,2,3))
9

Built-in python closure

functools.partial is an example of a closure.

From the python docs, it’s roughly equivalent to:

def partial(func, *args, **keywords):
    def newfunc(*fargs, **fkeywords):
        newkeywords = keywords.copy()
        newkeywords.update(fkeywords)
        return func(*(args + fargs), **newkeywords)
    newfunc.func = func
    newfunc.args = args
    newfunc.keywords = keywords
    return newfunc

(Kudos to @user225312 below for the answer. I find this example easier to figure out, and hopefully will help answer @mango’s comment.)

Generally, no, do not define functions inside functions.

Unless you have a really good reason. Which you don’t.

Why not?

• It prevents easy hooks for unit testing. You are unit testing, aren’t you?
• It doesn’t actually obfuscate it completely anyway, it’s safer to assume nothing in python ever is.
• Use standard Python automagic code style guidelines to encapsulate methods instead.
• You will be needlessly recreating a function object for the identical code every single time you run the outer function.
• If your function is really that simple, you should be using a lambda expression instead.

What is a really good reason to define functions inside functions?

When what you actually want is a dingdang closure.

It’s actually fine to declare one function inside another one. This is specially useful creating decorators.

However, as a rule of thumb, if the function is complex (more than 10 lines) it might be a better idea to declare it on the module level.

I found this question because I wanted to pose a question why there is a performance impact if one uses nested functions. I ran tests for the following functions using Python 3.2.5 on a Windows Notebook with a Quad Core 2.5 GHz Intel i5-2530M processor

def square0(x):
    return x*x

def square1(x):
    def dummy(y):
        return y*y
    return x*x

def square2(x):
    def dummy1(y):
        return y*y
    def dummy2(y):
        return y*y
    return x*x

def square5(x):
    def dummy1(y):
        return y*y
    def dummy2(y):
        return y*y
    def dummy3(y):
        return y*y
    def dummy4(y):
        return y*y
    def dummy5(y):
        return y*y
    return x*x

I measured the following 20 times, also for square1, square2, and square5:

s=0
for i in range(10**6):
    s+=square0(i)

and got the following results

>>> 
m = mean, s = standard deviation, m0 = mean of first testcase
[m-3s,m+3s] is a 0.997 confidence interval if normal distributed

square? m     s       m/m0  [m-3s ,m+3s ]
square0 0.387 0.01515 1.000 [0.342,0.433]
square1 0.460 0.01422 1.188 [0.417,0.503]
square2 0.552 0.01803 1.425 [0.498,0.606]
square5 0.766 0.01654 1.979 [0.717,0.816]
>>> 

square0 has no nested function, square1 has one nested function, square2 has two nested functions and square5 has five nested functions. The nested functions are only declared but not called.

So if you have defined 5 nested funtions in a function that you don’t call then the execution time of the function is twice of the function without a nested function. I think should be cautious when using nested functions.

The Python file for the whole test that generates this output can be found at ideone.

It’s just a principle about exposure APIs.

Using python, It’s a good idea to avoid exposure API in outer space(module or class), function is a good encapsulation place.

It could be a good idea. when you ensure

1. inner function is ONLY used by outer function.
2. insider function has a good name to explain its purpose because the code talks.
3. code cannot directly understand by your colleagues(or other code-reader).

Even though, Abuse this technique may cause problems and implies a design flaw.

Just from my exp, Maybe misunderstand your question.

So in the end it is largely a question about how smart the python implementation is or is not, particularly in the case of the inner function not being a closure but simply an in function needed helper only.

In clean understandable design having functions only where they are needed and not exposed elsewhere is good design whether they be embedded in a module, a class as a method, or inside another function or method. When done well they really improve the clarity of the code.

And when the inner function is a closure that can also help with clarity quite a bit even if that function is not returned out of the containing function for use elsewhere.

So I would say generally do use them but be aware of the possible performance hit when you actually are concerned about performance and only remove them if you do actual profiling that shows they best be removed.

Do not do premature optimization of just using “inner functions BAD” throughout all python code you write. Please.

It’s perfectly OK doing it that way, but unless you need to use a closure or return the function I’d probably put in the module level. I imagine in the second code example you mean:

...
some_data = method_b() # not some_data = method_b

otherwise, some_data will be the function.

Having it at the module level will allow other functions to use method_b() and if you’re using something like Sphinx (and autodoc) for documentation, it will allow you to document method_b as well.

You also may want to consider just putting the functionality in two methods in a class if you’re doing something that can be representable by an object. This contains logic well too if that’s all you’re looking for.

Do something like:

def some_function():
    return some_other_function()
def some_other_function():
    return 42 

if you were to run some_function() it would then run some_other_function() and returns 42.

EDIT: I originally stated that you shouldn’t define a function inside of another but it was pointed out that it is practical to do this sometimes.

You can use it to avoid defining global variables. This gives you an alternative for other designs. 3 designs presenting a solution to a problem.

A) Using functions without globals

def calculate_salary(employee, list_with_all_employees):
    x = _calculate_tax(list_with_all_employees)

    # some other calculations done to x
    pass

    y = # something 

    return y

def _calculate_tax(list_with_all_employees):
    return 1.23456 # return something

B) Using functions with globals

_list_with_all_employees = None

def calculate_salary(employee, list_with_all_employees):

    global _list_with_all_employees
    _list_with_all_employees = list_with_all_employees

    x = _calculate_tax()

    # some other calculations done to x
    pass

    y = # something

    return y

def _calculate_tax():
    return 1.23456 # return something based on the _list_with_all_employees var

C) Using functions inside another function

def calculate_salary(employee, list_with_all_employees):

    def _calculate_tax():
        return 1.23456 # return something based on the list_with_a--Lemployees var

    x = _calculate_tax()

    # some other calculations done to x
    pass
    y = # something 

    return y

Solution C) allows to use variables in the scope of the outer function without having the need to declare them in the inner function. Might be useful in some situations.

Function In function python

def Greater(a,b):
    if a>b:
        return a
    return b

def Greater_new(a,b,c,d):
    return Greater(Greater(a,b),Greater(c,d))

print("Greater Number is :-",Greater_new(212,33,11,999))