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Re: dbf.py API question

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Ethan Furman wrote:

> SQLite has a neat feature where if you give it a the file-name of
> ':memory:' the resulting table is in memory and not on disk.  I thought
> it was a cool feature, but expanded it slightly: any name surrounded by
> colons results in an in-memory table.
> 
> I'm looking at the same type of situation with indices, but now I'm
> wondering if the :name: method is not pythonic and I should use a flag
> (in_memory=True) when memory storage instead of disk storage is desired.
 
For SQLite it seems OK because you make the decision once per database. For 
dbase it'd be once per table, so I would prefer the flag.

Random

> Thoughts?

- Do you really want your users to work with multiple dbf files? I think I'd 
rather convert to SQLite, perform the desired operations using sql, then 
convert back.

- Are names required to manipulate the table? If not you could just omit 
them to make the table "in-memory".

- How about a connection object that may either correspond to a directory or 
RAM:

db = dbf.connect(":memory:")
table = db.Table("foo", ...)

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Re: dbf.py API question Peter Otten <__peter__@web.de> - 2012-08-03 11:03 +0200

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