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1 A Red-Black Tree in Python
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2 ##########################
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3
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4 :date: 2012-12-28 11:10
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5 :tags: Python, datastructures
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6 :slug: a-red-black-tree-in-python
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7 :author: Brian Neal
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8
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9 I've been working my way through Allen Downey's `Think Complexity`_ book. I'm
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10 not very far in, but so far it's a great way to brush up on algorithms and
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11 datastructures, and learn some new stuff about complexity science. Plus, all of
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12 the code is written in Python! I've been doing the exercises, and most of them
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13 take at most fifteen or twenty minutes. But at the end of his explanation on
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14 hash tables he casually lobs this one out (3.4, exercise 5):
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15
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16 A drawback of hashtables is that the elements have to be hashable, which
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17 usually means they have to be immutable. That’s why, in Python, you can use
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18 tuples but not lists as keys in a dictionary. An alternative is to use
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19 a tree-based map.
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20
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21 Write an implementation of the map interface called TreeMap that uses
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22 a red-black tree to perform add and get in log time.
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23
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24 I've never researched red-black trees before, but as a C++ programmer I know
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25 they are the datastructure that powers ``std::set`` and ``std::map``. So
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26 I decided to take a look. I quickly realized this was not going to be a simple
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27 exercise, as red-black trees are quite complicated to understand and implement.
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28 They are basically binary search trees that do a lot of work to keep themselves
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29 approximately balanced.
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30
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31 I spent a few nights reading up on red-black trees. A good explanation can be
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32 found in Wikipedia_. There are even a handful of Python implementations
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33 floating about, of varying quality. But finally I found a detailed explanation
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34 that really clicked with me at `Eternally Confuzzled`_. Julienne Walker derives
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35 a unique algorithm based upon the rules for red-black trees, and the
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36 implementation code is non-recursive and top-down. Most of the other
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37 implementations I found on the web seem to be based on the textbook
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38 `Introduction To Algorithms`_, and often involve the use of parent pointers
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39 and using dummy nodes to represent the nil leaves of the tree. Julienne's
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40 solution avoided these things and seemed a bit less complex. However the best
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41 reason to study the tutorial was the explanation was very coherent and
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42 detailed. The other sources on the web seemed to be fragmented, missing
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43 details, and lacking in explanation.
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44
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45 So to complete my `Think Complexity`_ exercise, I decided to port Julienne's
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46 red-black tree algorithm from C to Python, and hopefully learn something along
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47 the way. After a couple nights of work, and one `very embarrassing bug`_, I've
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48 completed it. I can't say I quite understand every bit of the algorithm, but
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49 I certainly learned a lot. You can view the `source code at Bitbucket`_, or
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50 clone my `Think Complexity repository`_.
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51
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52 Many thanks to Julienne Walker for the `great tutorial`_! And I highly recommend
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53 `Think Complexity`_. Check them both out.
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54
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55
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56 .. _Think Complexity: http://www.greenteapress.com/compmod/
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57 .. _Wikipedia: http://en.wikipedia.org/wiki/Red%E2%80%93black_tree
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58 .. _Eternally Confuzzled: http://www.eternallyconfuzzled.com/tuts/datastructures/jsw_tut_rbtree.aspx
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59 .. _great tutorial: http://www.eternallyconfuzzled.com/tuts/datastructures/jsw_tut_rbtree.aspx
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60 .. _Introduction to Algorithms: http://mitpress.mit.edu/books/introduction-algorithms
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61 .. _very embarrassing bug: http://deathofagremmie.com/2012/12/27/a-c-python-chained-assignment-gotcha/
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62 .. _source code at Bitbucket: https://bitbucket.org/bgneal/think_complexity/src/0326803882adc4a598d890ee4d7d39d93cb64af7/redblacktree.py?at=default
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63 .. _Think Complexity repository: https://bitbucket.org/bgneal/think_complexity
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