On Tue, May 15, 2012 at 5:09 AM, Steve Sawyer <ssaw...@stephensawyer.com> wrote:
> Thanks - now, given my query that returns the table structure, this
> works fine:
>
> table_dict = {}
> table_specs = cursor.execute(query_string)
> for row in table_specs:
> row_dict = {}
> row_dict['type'] = row.DataType
> row_dict['size'] = row.Length
> table_dict[row.name] = row_dict
>
> table_dict['path']['type'] #-> 'nvarchar'
> table_dict['path']['size'] # -> 200
> table_dict['Artist']['size'] #-> 50
>
> Is this (nesting dictionaries) a good way to store multiple attributes
> associated with a single key value?
There's lots of options. The dictionary works; or you could create a
class for your record - also, check out namedtuple from the
collections module, which is a shortcut to the second option.
# Option 2
class Field:
def __init__(self,datatype,length):
self.datatype=datatype
self.length=length
# Option 3:
import collections
Field=collections.namedtuple('Field',('datatype','length'))
table_dict = {}
table_specs = cursor.execute(query_string)
for row in table_specs:
# Option 1: no need to start with an empty dictionary and then populate it
table_dict[row.name] = {'type': row.DataType, 'size': row.Length}
# Option 2 or 3: your own record type, or a namedtuple
table_dict[row.name] = Field(row.DataType,row.Length)
# Option 1:
table_dict['path']['type'] #-> 'nvarchar'
table_dict['path']['size'] # -> 200
table_dict['Artist']['size'] #-> 50
# Option 2 or 3
table_dict['path'].datatype #-> 'nvarchar'
table_dict['path'].size # -> 200
table_dict['Artist'].size #-> 50
You'll notice that I've used 'datatype' rather than 'type' - the
latter would work, but since 'type' has other meaning (it's the class
that all classes subclass, if that makes sense), I like to avoid using
it.
The choice between these three options comes down to style, so pick
whichever one "feels best" to you.
ChrisA
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