<p>I've been unable to find a source for this information, short of looking through the Python source code myself to determine how the objects work. Does anyone know where I could find this online?</p>

[{'answer_id': 45245, 'author': 'Brian Gianforcaro', 'author_id': 3415, 'author_profile': 'https://Stackoverflow.com/users/3415', 'pm_score': 2, 'selected': False, 'text': '<p>If your asking what I think your asking, you can find them <a href="http://books.google.com/books?id=vpTAq4dnmuAC&amp;pg=RA1-PA476&amp;lpg=RA1-PA476&amp;dq=Big-O+of+Python+data+structures&amp;source=web&amp;ots=AOM5B5D7yA&amp;sig=deLGb6VrftTpnNYN6fILVbiirXM&amp;hl=en&amp;sa=X&amp;oi=book_result&amp;resnum=7&amp;ct=result#PRA1-PA479,M1" rel="nofollow noreferrer">Here</a>... page 476 and on.</p>\n\n<p>It\'s written around optimization techniques for Python; It\'s mostly Big-O notation of time efficiencies not much memory.</p>\n'}, {'answer_id': 45538, 'author': 'Will Harris', 'author_id': 4702, 'author_profile': 'https://Stackoverflow.com/users/4702', 'pm_score': 4, 'selected': False, 'text': '<p>Raymond D. Hettinger does <a href="http://www.youtube.com/watch?v=hYUsssClE94" rel="noreferrer">an excellent talk</a> (<a href="http://wenku.baidu.com/view/9c6fb20dcc1755270722089d.html" rel="noreferrer">slides</a>) about Python\'s built-in collections called \'Core Python Containers - Under the Hood\'. The version I saw focussed mainly on <code>set</code> and <code>dict</code>, but <code>list</code> was covered too.</p>\n\n<p>There are also some photos of the pertinent slides from EuroPython in <a href="http://paranoid-engineering.blogspot.com/2008/07/europython-2008-day-3.html" rel="noreferrer">a blog</a>.</p>\n\n<p>Here is a summary of my notes on <code>list</code>:</p>\n\n<ul>\n<li>Stores items as an array of pointers. Subscript costs O(1) time. Append costs amortized O(1) time. Insert costs O(n) time.</li>\n<li>Tries to avoid <code>memcpy</code> when growing by over-allocating. Many small lists will waste a lot of space, but large lists never waste more than about 12.5% to overallocation.</li>\n<li>Some operations pre-size. Examples given were <code>range(n)</code>, <code>map()</code>, <code>list()</code>, <code>[None] * n</code>, and slicing.</li>\n<li>When shrinking, the array is <code>realloc</code>ed only when it is wasting 50% of space. <code>pop</code> is cheap.</li>\n</ul>\n'}, {'answer_id': 46201, 'author': 'Aaron Maenpaa', 'author_id': 2603, 'author_profile': 'https://Stackoverflow.com/users/2603', 'pm_score': 5, 'selected': True, 'text': '<p>Checkout the <a href="http://wiki.python.org/moin/TimeComplexity" rel="noreferrer">TimeComplexity</a> page on the py dot org wiki. It covers set/dicts/lists/etc at least as far as time complexity goes.</p>\n'}]
['https://Stackoverflow.com/questions/45228', 'https://Stackoverflow.com', 'https://Stackoverflow.com/users/1114/']