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+--- Thread: [Tut] Python List append() vs extend() (/thread-93991.html)
[Tut] Python List append() vs extend() - xSicKxBot - 03-12-2020
Python List append() vs extend()
<div><p>A profound understanding of Python lists is fundamental to your Python education. Today, I wondered: what’s the difference between two of the most-frequently used <a rel="noreferrer noopener" href="https://blog.finxter.com/python-list-methods/" target="_blank">list methods</a>: <code>append()</code> vs. <code>extend()</code>?</p>
<p>I shot a small video explaining the difference and which method is faster—you can play it as you read over this tutorial:</p>
<figure class="wp-block-embed-youtube wp-block-embed is-type-video is-provider-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio">
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<div class="ast-oembed-container"><iframe title="Python List append() vs extend() - Semantic and Speed Difference" width="1400" height="788" src="https://www.youtube.com/embed/VGg8sNJ9kOM?feature=oembed" frameborder="0" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe></div>
</div>
</figure>
<p>Here’s the short answer — <code>append()</code> vs <code>extend()</code>:</p>
<ul>
<li><strong>The method <code>list.append(x)</code> adds element <code>x</code> to the end of the <code>list</code>. </strong></li>
<li><strong>The method <code>list.extend(iter)</code> adds all elements in <code>iter</code> to the end of the <code>list</code>.</strong></li>
</ul>
<p><strong>The difference between <code>append()</code> and <code>extend()</code> is that the former adds only one element and the latter adds a collection of elements to the list.</strong></p>
<p>You can see this in the following example:</p>
<pre class="EnlighterJSRAW" data-enlighter-language="generic" data-enlighter-theme="" data-enlighter-highlight="" data-enlighter-linenumbers="" data-enlighter-lineoffset="" data-enlighter-title="" data-enlighter-group="">>>> l = []
>>> l.append(1)
>>> l.append(2)
>>> l
[1, 2]
>>> l.extend([3, 4, 5])
>>> l
[1, 2, 3, 4, 5]</pre>
<p>In the code, you first add integer elements 1 and 2 to the list using two calls to the <code>append()</code> method. <a href="https://blog.finxter.com/python-list-append/" target="_blank" rel="noreferrer noopener">(If you need a deeper understanding, check out my detailed article about the append() method on this blog.)</a></p>
<p>Then, you use the extend method to add the three elements 3, 4, and 5 in a single call of the <code>extend()</code> method.</p>
<h3><strong>Which Method is Faster — extend() or append()?</strong></h3>
<p>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()</code> and the <code>append()</code> methods. </p>
<p>My thesis is that the <code>extend()</code> 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.</p>
<p>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. </p>
<p>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.</p>
<p>Here’s the code I used to measure and plot the results: which method is faster—append() or extend()?</p>
<pre class="EnlighterJSRAW" data-enlighter-language="generic" data-enlighter-theme="" data-enlighter-highlight="" data-enlighter-linenumbers="" data-enlighter-lineoffset="" data-enlighter-title="" data-enlighter-group="">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()</pre>
<p>The code consists of three high-level parts:</p>
<ul>
<li>In the first part, you define two functions <code>list_by_append(n)</code> and <code>list_by_extend(n)</code> that take as input argument an integer list size <code>n</code> and create lists of successively increasing integer elements using the <code>append()</code> and <code>extend()</code> methods, respectively.</li>
<li>In the second part, you compare the runtime of both functions using 100 different values for the list size <code>n</code>. </li>
<li>In the third part of, you plot everything using the Python <a rel="noreferrer noopener" href="https://blog.finxter.com/matplotlib-line-plot/" target="_blank">matplotlib library</a>.</li>
</ul>
<p>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.</p>
<figure class="wp-block-image size-large"><img src="https://blog.finxter.com/wp-content/uploads/2020/03/append_vs_extend-1.jpg" alt="" class="wp-image-6631" srcset="https://blog.finxter.com/wp-content/uploads/2020/03/append_vs_extend-1.jpg 640w, https://blog.finxter.com/wp-content/uploads/2020/03/append_vs_extend-1-300x225.jpg 300w" sizes="(max-width: 640px) 100vw, 640px" /></figure>
<p>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()</code> function of the <a rel="noreferrer noopener" href="https://docs.python.org/2/library/time.html#time.time" target="_blank">time module</a> cannot capture the elapsed time.</p>
<p>But as you increase the size of the lists to hundreds of thousands of elements, the <code>extend()</code> method starts to win:</p>
<p><strong>For large lists with one million elements, the runtime of the <code>extend()</code> method is 60% faster than the runtime of the <code>append()</code> method.</strong></p>
<p>The reason is the already mentioned batching of individual append operations. </p>
<p>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()</code> over <code>append()</code> if you need to add a bunch of elements rather than only a single element. </p>
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<p>If you love coding and you want to do this full-time from the comfort of your own home, you’re in luck: </p>
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<p>Join 21,419 ambitious Python coders. It’s fun! <img src="https://s.w.org/images/core/emoji/12.0.0-1/72x72/1f604.png" alt="?" class="wp-smiley" style="height: 1em; max-height: 1em;" /><img src="https://s.w.org/images/core/emoji/12.0.0-1/72x72/1f40d.png" alt="?" class="wp-smiley" style="height: 1em; max-height: 1em;" /></p>
</div>
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