[Tut] Python List append() Method

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Python List append() Method

How can you add more elements to a given list? Use the

Code:

append()

method in Python. This tutorial shows you everything you need to know to help you master an essential method of the most fundamental container data type in the Python programming language.

Definition and Usage

The

Code:

list.append(x)

method—as the name suggests—appends element

Code:

x

to the end of the

Code:

list

.

Here’s a short example:

Code:

>>> l = [] >>> l.append(42) >>> l [42] >>> l.append(21) >>> l [42, 21]

In the first line of the example, you create the list

Code:

l

. You then append the integer element

Code:

42

to the end of the list. The result is the list with one element

Code:

[42]

. Finally, you append the integer element

Code:

21

to the end of that list which results in the list with two elements

Code:

[42, 21]

.

Syntax

You can call this method on each list object in Python. Here’s the syntax:

Code:

list.append(element)

Arguments

Argument |
Description

Code:

element

|
The object you want to append to the list.

Code Puzzle

Now you know the basics. Let’s deepen your understanding with a short code puzzle—can you solve it?

Code:

# Puzzle nums = [1, 2, 3] nums.append(nums[:]) print(len(nums)) # What's the output of this code snippet?

You can check out the solution on the Finxter app. (I know it’s tricky!)

Examples

Let’s dive into a few more examples:

Code:

>>> lst = [2, 3] >>> lst.append(3) >>> lst.append([1,2]) >>> lst.append((3,4)) >>> lst [2, 3, 3, [1, 2], (3, 4)]

You can see that the

Code:

append()

method also allows for other objects. But be careful: you cannot append multiple elements in one method call. This will only add one new element (even if this new element is a list by itself). Instead, to add multiple elements to your list, you need to call the

Code:

append()

method multiple times.

Python List append() At The Beginning

What if you want to use the append() method at the beginning: you want to “append” an element just before the first element of the list.

Well, you should work on your terminology for starters. But if you insist, you can use the

Code:

insert()

method instead.

Here’s an example:

Code:

>>> lst = [1, 2, 3] >>> lst.insert(0, 99) >>> lst [99, 1, 2, 3]

The

Code:

insert(i, x)

method inserts an element

Code:

x

at position

Code:

i

in the list. This way, you can insert an element to each position in the list—even at the first position. Note that if you insert an element at the first position, each subsequent element will be moved by one position. In other words, element

Code:

i

will move to position

Code:

i+1

.

Python List append() Multiple or All Elements

But what if you want to append not one but multiple elements? Or even all elements of a given iterable. Can you do it with

Code:

append()

? Well, let’s try:

Code:

>>> l = [1, 2, 3] >>> l.append([4, 5, 6]) >>> l [1, 2, 3, [4, 5, 6]]

The answer is no—you cannot append multiple elements to a list by using the

Code:

append()

method. But you can use another method: the

Code:

extend()

method:

Code:

>>> l = [1, 2, 3] >>> l.extend([1, 2, 3]) >>> l [1, 2, 3, 1, 2, 3]

You call the

Code:

extend()

method on a list object. It takes an iterable as an input argument. Then, it adds all elements of the iterable to the list, in the order of their occurrence.

Python List append() vs extend()

I shot a small video explaining the difference and which method is faster, too:



The method

Code:

list.append(x)

adds element

Code:

x

to the end of the

Code:

list

.

The method

Code:

list.extend(iter)

adds all elements in

Code:

iter

to the end of the

Code:

list

.

The difference between

Code:

append()

and

Code:

extend()

is that the former adds only one element and the latter adds a collection of elements to the list.

You can see this in the following example:

Code:

>>> l = [] >>> l.append(1) >>> l.append(2) >>> l [1, 2] >>> l.extend([3, 4, 5]) >>> l [1, 2, 3, 4, 5]

In the code, you first add integer elements 1 and 2 to the list using two calls to the

Code:

append()

method. Then, you use the extend method to add the three elements 3, 4, and 5 in a single call of the

Code:

extend()

method.

[b]Which method is faster — extend() vs append()?[/b]

To answer this question, I’ve written a short script that tests the runtime performance of creating large lists of increasing sizes using the

Code:

extend()

and the

Code:

append()

methods.

Our thesis is that the

Code:

extend()

method should be faster for larger list sizes because Python can append elements to a list in a batch rather than by calling the same method again and again.

I used my notebook with an Intel® Core™ i7-8565U 1.8GHz processor (with Turbo Boost up to 4.6 GHz) and 8 GB of RAM.

Then, I created 100 lists with both methods, extend() and append(), with sizes ranging from 10,000 elements to 1,000,000 elements. As elements, I simply incremented integer numbers by one starting from 0.

Here’s the code I used to measure and plot the results: which method is faster—append() or extend()?

Code:

import time def list_by_append(n): '''Creates a list & appends n elements''' lst = [] for i in range(n): lst.append(n) return lst def list_by_extend(n): '''Creates a list & extends it with n elements''' lst = [] lst.extend(range(n)) return lst # Compare runtime of both methods list_sizes = [i * 10000 for i in range(100)] append_runtimes = [] extend_runtimes = [] for size in list_sizes: # Get time stamps time_0 = time.time() list_by_append(size) time_1 = time.time() list_by_extend(size) time_2 = time.time() # Calculate runtimes append_runtimes.append((size, time_1 - time_0)) extend_runtimes.append((size, time_2 - time_1)) # Plot everything import matplotlib.pyplot as plt import numpy as np append_runtimes = np.array(append_runtimes) extend_runtimes = np.array(extend_runtimes) print(append_runtimes) print(extend_runtimes) plt.plot(append_runtimes[:,0], append_runtimes[:,1], label='append()') plt.plot(extend_runtimes[:,0], extend_runtimes[:,1], label='extend()') plt.xlabel('list size') plt.ylabel('runtime (seconds)') plt.legend() plt.savefig('append_vs_extend.jpg') plt.show()

The code consists of three high-level parts:

• In the first part of the code, you define two functions
  Code:

  list_by_append(n)
  and
  Code:

  list_by_extend(n)
  that take as input argument an integer list size
  Code:

  n
  and create lists of successively increasing integer elements using the
  Code:

  append()
  and
  Code:

  extend()
  methods, respectively.
  
  
• In the second part of the code, you compare the runtime of both functions using 100 different values for the list size
  Code:

  n
  .
  
  
• In the third part of the code, you plot everything using the Python matplotlib library.
  

Here’s the resulting plot that compares the runtime of the two methods append() vs extend(). On the x axis, you can see the list size from 0 to 1,000,000 elements. On the y axis, you can see the runtime in seconds needed to execute the respective functions.



The resulting plot shows that both methods are extremely fast for a few tens of thousands of elements. In fact, they are so fast that the

Code:

time()

function of the time module cannot capture the elapsed time.

But as you increase the size of the lists to hundreds of thousands of elements, the

Code:

extend()

method starts to win:

For large lists with one million elements, the runtime of the

Code:

extend()

method is 60% faster than the runtime of the

Code:

append()

method.

The reason is the already mentioned batching of individual append operations.

However, the effect only plays out for very large lists. For small lists, you can choose either method. Well, for clarity of your code, it would still make sense to prefer

Code:

extend()

over

Code:

append()

if you need to add a bunch of elements rather than only a single element.

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Python List append() at Index

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Python List append() Dictionary

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