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POData structure for maintaining tabular data in memory?
 

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  1. POData structure for maintaining tabular data in memory?
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    <p>My scenario is as follows: I have a table of data (handful of fields, less than a hundred rows) that I use extensively in my program. I also need this data to be persistent, so I save it as a CSV and load it on start-up. I choose not to use a database because every option (even SQLite) is an overkill for my humble requirement (also - I would like to be able to edit the values offline in a simple way, and nothing is simpler than notepad).</p> <p>Assume my data looks as follows (in the file it's comma separated without titles, this is just an illustration):</p> <pre><code> Row | Name | Year | Priority ------------------------------------ 1 | Cat | 1998 | 1 2 | Fish | 1998 | 2 3 | Dog | 1999 | 1 4 | Aardvark | 2000 | 1 5 | Wallaby | 2000 | 1 6 | Zebra | 2001 | 3 </code></pre> <p>Notes:</p> <ol> <li>Row may be a "real" value written to the file or just an auto-generated value that represents the row number. Either way it exists in memory.</li> <li>Names are unique.</li> </ol> <p>Things I do with the data:</p> <ol> <li>Look-up a row based on either ID (iteration) or name (direct access).</li> <li>Display the table in different orders based on multiple field: I need to sort it e.g. by Priority and then Year, or Year and then Priority, etc.</li> <li>I need to count instances based on sets of parameters, e.g. how many rows have their year between 1997 and 2002, or how many rows are in 1998 and priority > 2, etc.</li> </ol> <p>I know this "cries" for SQL...</p> <p>I'm trying to figure out what's the best choice for data structure. Following are several choices I see:</p> <p>List of row lists:</p> <pre><code>a = [] a.append( [1, "Cat", 1998, 1] ) a.append( [2, "Fish", 1998, 2] ) a.append( [3, "Dog", 1999, 1] ) ... </code></pre> <p>List of column lists (there will obviously be an API for add_row etc):</p> <pre><code>a = [] a.append( [1, 2, 3, 4, 5, 6] ) a.append( ["Cat", "Fish", "Dog", "Aardvark", "Wallaby", "Zebra"] ) a.append( [1998, 1998, 1999, 2000, 2000, 2001] ) a.append( [1, 2, 1, 1, 1, 3] ) </code></pre> <p>Dictionary of columns lists (constants can be created to replace the string keys):</p> <pre><code>a = {} a['ID'] = [1, 2, 3, 4, 5, 6] a['Name'] = ["Cat", "Fish", "Dog", "Aardvark", "Wallaby", "Zebra"] a['Year'] = [1998, 1998, 1999, 2000, 2000, 2001] a['Priority'] = [1, 2, 1, 1, 1, 3] </code></pre> <p>Dictionary with keys being tuples of (Row, Field):</p> <pre><code>Create constants to avoid string searching NAME=1 YEAR=2 PRIORITY=3 a={} a[(1, NAME)] = "Cat" a[(1, YEAR)] = 1998 a[(1, PRIORITY)] = 1 a[(2, NAME)] = "Fish" a[(2, YEAR)] = 1998 a[(2, PRIORITY)] = 2 ... </code></pre> <p>And I'm sure there are other ways... However each way has disadvantages when it comes to my requirements (complex ordering and counting). </p> <p>What's the recommended approach?</p> <p>EDIT:</p> <p>To clarify, performance is not a major issue for me. Because the table is so small, I believe almost every operation will be in the range of milliseconds, which is not a concern for my application.</p>
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