Well, it does more than that. It converts each column from a string
(because MySQL returns all columns as strings) into the appropriate
Python type. Then you were converting all the Python types back into
strings. So it's no mystery that using the command line client is
faster, since it would take
There are no performance overhead except when you are dragging a huge
chunk of information out of the database, in that case, python is
converting the data to its tuple data type which adds one more
processing.
I found this when I didn't have the priviledge to do "mysql> SELECT *
FROM TBL INTO OUT
There aren't any "issues", but there are a few things to keep in mind.
First of all, prior to 4.1, MySQL does no parameter binding, which
means that the parameters must be inserted into your SQL statements as
literals. MySQLdb will do this for you automatically, but keep in mind
that you will be c
"sandy" <[EMAIL PROTECTED]> wrote in message
news:[EMAIL PROTECTED]
> Hi All,
>
> I am a newbie to MySQL and Python. At the first place, I would like to
> know what are the general performance issues (if any) of using MySQL
> with Python.
>
> By performance, I wanted to know how will the speed be,
Wow, you give us too much credit out here. From your
post we can't determine anything about what you plan
to do (how is your data structured, how much data do
you have, can it be indexed to speed up searching...).
Python and MySQL work together beautifully. ANY SQL
database's performance is more
Hi All,
I am a newbie to MySQL and Python. At the first place, I would like to
know what are the general performance issues (if any) of using MySQL
with Python.
By performance, I wanted to know how will the speed be, what is the
memory overhead involved, etc during database specific operations
(r
