On Thu, 2007-08-30 at 07:27 +0800, Russell Keith-Magee wrote:
> 1) If you have a non-trivial amount of data in your production
> database, the space and time required to deserialize, store and
> reserialize the contents of the databse could be problematic.

Fortunately I have a small amount of data for the moment
> 
> 2) The technique you propose doesn't address any changes that may be
> required to your data. This isn't a problem if you all you do is add a
> new field that allows null=True,  but if you add a non-optional field,
> the fixture load won't work because the fixture won't contain data for
> the new field. At the very least, there is a transform step between
> the dump and the load.

Yeah thats what I was alluding to with munging the yaml format data.

> Solving this sort of problem is what the SQL ALTER statement, and by
> extension, the schema-evolution pushes, are all about. These change
> the database in-situ, rather than going through an intermediate
> database.

Yeah I've worked on projects where we applied versioned sql scripts,
using a tool that applied any new ones that weren't already in a db
table of applied scripts. But all the sql was in these scripts, whereas
django's handy syncdb lulls the simple minded developer into forgetting
about these issues until upgrade time.

I haven't found a lot of information on how people typically do schema
migrations for Django after reading the docs/scanning the wiki/googling.
However the manual route seems to be a preferred option...

this FAQ entry...
http://www.djangoproject.com/documentation/faq/#if-i-make-changes-to-a-model-how-do-i-update-the-database
recommends hand crafting the upgrade sql and avoiding trying to automate
too much.

cheers,
Graham



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