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copied!<pre><code>flat_list = [item for sublist in l for item in sublist] </code></pre> <p>which means:</p> <pre><code>for sublist in l: for item in sublist: flat_list.append(item) </code></pre> <p>is faster than the shortcuts posted so far. (<code>l</code> is the list to flatten.)</p> <p>Here is a the corresponding function:</p> <pre><code>flatten = lambda l: [item for sublist in l for item in sublist] </code></pre> <p>For evidence, as always, you can use the <code>timeit</code> module in the standard library:</p> <pre><code>$ python -mtimeit -s'l=[[1,2,3],[4,5,6], [7], [8,9]]*99' '[item for sublist in l for item in sublist]' 10000 loops, best of 3: 143 usec per loop $ python -mtimeit -s'l=[[1,2,3],[4,5,6], [7], [8,9]]*99' 'sum(l, [])' 1000 loops, best of 3: 969 usec per loop $ python -mtimeit -s'l=[[1,2,3],[4,5,6], [7], [8,9]]*99' 'reduce(lambda x,y: x+y,l)' 1000 loops, best of 3: 1.1 msec per loop </code></pre> <p>Explanation: the shortcuts based on <code>+</code> (including the implied use in <code>sum</code>) are, of necessity, <code>O(L**2)</code> when there are L sublists -- as the intermediate result list keeps getting longer, at each step a new intermediate result list object gets allocated, and all the items in the previous intermediate result must be copied over (as well as a few new ones added at the end). So (for simplicity and without actual loss of generality) say you have L sublists of I items each: the first I items are copied back and forth L-1 times, the second I items L-2 times, and so on; total number of copies is I times the sum of x for x from 1 to L excluded, i.e., <code>I * (L**2)/2</code>.</p> <p>The list comprehension just generates one list, once, and copies each item over (from its original place of residence to the result list) also exactly once.</p>

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