[DB-SIG] NumPy, Python DB-API and MySQL

[Tim Churches]

I've been experimenting with pulling quantitative data out of a MySQL
table into NumPy arrays via Andy Dustman's excellent MySQLdb module and
then calculating various statistics from the data using Gary Strangman's
excellent stats.py functions, which when operating on NumPy arrays are
lightning-fast.

The problem is the speed with which data can be extracted from a column
of a MySQL (or any other SQL database) query result set and stuffed into
a NumPy array. This inevitably involves forming a Python list and then
assigning that to a NumPy array. This is both slow and memory-hungry,
especially with large datsets (I have een playing with a few million
rows).

I was wondering if it would be feasible to initially add a method to the
_mysql class in the MySQLdb module which iterated through a result set
using a C routine (rather than a Python routine) and stuffed the data
directly into a NumPy array (or arrays - one for each column in the
result set) in one fell swoop (or even iterating row-by-row but in C)? I
suspect that such a facility would be much faster than having to move
the data into NumPy via a standard Python list (or actually via tuples
within a list, which i sthe way the Python DB-API returns results).

If this direct MySQL-to-NumPy interface worked well, it might be
desirable to add it to the Python DB-API specification for optional
implementation in the other database modules which conform to the API.
There are probably other extensions which would make the DB-API more
useful for statistical applications, which tend to be set
(column)-oriented rather than row-oriented - will post to the list as
these occur to me.

Cheers,

Tim Churches

PS I will be away for the next week so apologies in advance for not
replying immediately to any follow-ups to this posting.

TC