Question

Often I select data from a SQLite database into a list of dictionaries using something like:

conn.row_factory = sqlite3.Row
c = conn.cursor()
selection = c.execute('select * from myTable')
dataset = selection.fetchall()
dataset1 = [dict(row) for row in dataset]

However, given my database background (Foxpro, SQL-server, etc.) I am more used to using table.column format, which I can get using:

dataset2 = [RowObj(row) for row in dataset]  

where

class RowObj(dict):
    def __getattr__(self, name):
        return self[name]

Question – What is preferable for column value addressing, table[‘column’] or table.column? In my opinion the latter looks neater. Is it just a matter of personal preference, or are there pros+cons of each approach?

I also need to bear-in mind that one day the database might be changed from SQLite to something line mySQL, so I want minimum code changes if/when that happens.

I don’t want to use an ORM package like SQLObject or SQLAlchemy at this stage – not until I am convinced they will benefit my applications.

Regards,
Alan

Answer 1

I fought the row['column'] syntax for a while, but in the end I prefer it. It has two distinct advantages:

1. row['class'] is correct syntax, but row.class is not; keywords cannot directly be used as property names.
2. And, more generally, if you ever craft a query whose column names are not valid property names (the above case included) the dictionary-style syntax will allow you to address that column. row.COUNT(*) is obviously not valid syntax, but row['COUNT(*)'] is, etc. (Yes, you could use AS in the query to alias, and that’s fine of course. Still, it’s a valid concern.)

Having said that, your RowObj class of course supports both means of addressing the columns. I’d still prefer consistency though, and if you have a class column, it’s going to look weird if you address it differently: row.widget, row.dingus, row['class']. (One of these things is not like the other…)