What is the difference between Pythons list methods append and extend?

What is the difference between Pythons list methods append and extend?

append appends object at the end.

>>> x = [1, 2, 3]
>>> x.append([4, 5])
>>> print(x)
[1, 2, 3, [4, 5]]

extend extends list by appending elements from the iterable.

>>> x = [1, 2, 3]
>>> x.extend([4, 5])
>>> print(x)
[1, 2, 3, 4, 5]

append adds an element to a list, and extend concatenates the first list with another list (or another iterable, not necessarily a list.)

>>> li = [a, b, mpilgrim, z, example]
>>> li
[a, b, mpilgrim, z, example]

>>> li.append(new)
>>> li
[a, b, mpilgrim, z, example, new]

>>> li.append([new, 2])
>>> li
[a, b, mpilgrim, z, example, new, [new, 2]]

>>> li.insert(2, new)
>>> li
[a, b, new, mpilgrim, z, example, new, [new, 2]]

>>> li.extend([two, elements])
>>> li
[a, b, new, mpilgrim, z, example, new, [new, 2], two, elements]

What is the difference between Pythons list methods append and extend?

What is the difference between the list methods append and extend?

  • append adds its argument as a single element to the end of a list. The length of the list itself will increase by one.
  • extend iterates over its argument adding each element to the list, extending the list. The length of the list will increase by however many elements were in the iterable argument.


The list.append method appends an object to the end of the list.


Whatever the object is, whether a number, a string, another list, or something else, it gets added onto the end of my_list as a single entry on the list.

>>> my_list
[foo, bar]
>>> my_list.append(baz)
>>> my_list
[foo, bar, baz]

So keep in mind that a list is an object. If you append another list onto a list, the first list will be a single object at the end of the list (which may not be what you want):

>>> another_list = [1, 2, 3]
>>> my_list.append(another_list)
>>> my_list
[foo, bar, baz, [1, 2, 3]]
                     #^^^^^^^^^--- single item at the end of the list.


The list.extend method extends a list by appending elements from an iterable:


So with extend, each element of the iterable gets appended onto the list. For example:

>>> my_list
[foo, bar]
>>> another_list = [1, 2, 3]
>>> my_list.extend(another_list)
>>> my_list
[foo, bar, 1, 2, 3]

Keep in mind that a string is an iterable, so if you extend a list with a string, youll append each character as you iterate over the string (which may not be what you want):

>>> my_list.extend(baz)
>>> my_list
[foo, bar, 1, 2, 3, b, a, z]

Operator Overload, __add__ (+) and __iadd__ (+=)

Both + and += operators are defined for list. They are semantically similar to extend.

my_list + another_list creates a third list in memory, so you can return the result of it, but it requires that the second iterable be a list.

my_list += another_list modifies the list in-place (it is the in-place operator, and lists are mutable objects, as weve seen) so it does not create a new list. It also works like extend, in that the second iterable can be any kind of iterable.

Dont get confused – my_list = my_list + another_list is not equivalent to += – it gives you a brand new list assigned to my_list.

Time Complexity

Append has (amortized) constant time complexity, O(1).

Extend has time complexity, O(k).

Iterating through the multiple calls to append adds to the complexity, making it equivalent to that of extend, and since extends iteration is implemented in C, it will always be faster if you intend to append successive items from an iterable onto a list.

Regarding amortized – from the list object implementation source:

    /* This over-allocates proportional to the list size, making room
     * for additional growth.  The over-allocation is mild, but is
     * enough to give linear-time amortized behavior over a long
     * sequence of appends() in the presence of a poorly-performing
     * system realloc().

This means that we get the benefits of a larger than needed memory reallocation up front, but we may pay for it on the next marginal reallocation with an even larger one. Total time for all appends is linear at O(n), and that time allocated per append, becomes O(1).


You may wonder what is more performant, since append can be used to achieve the same outcome as extend. The following functions do the same thing:

def append(alist, iterable):
    for item in iterable:
def extend(alist, iterable):

So lets time them:

import timeit

>>> min(timeit.repeat(lambda: append([], abcdefghijklmnopqrstuvwxyz)))
>>> min(timeit.repeat(lambda: extend([], abcdefghijklmnopqrstuvwxyz)))

Addressing a comment on timings

A commenter said:

Perfect answer, I just miss the timing of comparing adding only one element

Do the semantically correct thing. If you want to append all elements in an iterable, use extend. If youre just adding one element, use append.

Ok, so lets create an experiment to see how this works out in time:

def append_one(a_list, element):

def extend_one(a_list, element):
    creating a new list is semantically the most direct
    way to create an iterable to give to extend

import timeit

And we see that going out of our way to create an iterable just to use extend is a (minor) waste of time:

>>> min(timeit.repeat(lambda: append_one([], 0)))
>>> min(timeit.repeat(lambda: extend_one([], 0)))

We learn from this that theres nothing gained from using extend when we have only one element to append.

Also, these timings are not that important. I am just showing them to make the point that, in Python, doing the semantically correct thing is doing things the Right Way™.

Its conceivable that you might test timings on two comparable operations and get an ambiguous or inverse result. Just focus on doing the semantically correct thing.


We see that extend is semantically clearer, and that it can run much faster than append, when you intend to append each element in an iterable to a list.

If you only have a single element (not in an iterable) to add to the list, use append.

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