Update, 
I ran the sample code I placed in this post over the weekend and it ended 
up consuming 1.8GB before python stopped functioning.
I am running pyDAL (17.1) with a stable web2py release.
Is this the built-in Rocket server issue I have run into?

On Friday, December 24, 2010 at 4:16:24 PM UTC-8, David Zejda wrote:
>
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> My web2py instance gradually eats memory, during day the consumption
> grows up to several gigs, so I have to restart often. According to guppy
> most of memory is occupied by gluon.dal.Field and other classes of dal:
>
> Partition of a set of 3231760 objects. Total size = 443724152 bytes.
>  Index  Count   %     Size   % Cumulative  % Kind
>      0 113419   4 189636568  43 189636568  43 dict of gluon.dal.Field
>      1 1324208  41 80561096  18 270197664  61 str
>      2 328642  10 15982732   4 286180396  64 tuple
>      3  26637   1 13851240   3 300031636  68 dict of
> gluon.validators.IS_IN_DB
>      4  98796   3 13436256   3 313467892  71 dict of gluon.dal.Set
>      5  20042   1 13344464   3 326812356  74 dict (no owner)
>      6   8199   0 11860464   3 338672820  76 gluon.dal.Row
>      7  16615   1 11482224   3 350155044  79 gluon.dal.Table
>      8  63682   2  8660752   2 358815796  81 dict of gluon.dal.Query
>      9 137779   4  7363776   2 366179572  83 list
> <2282 more rows. Type e.g. '_.more' to view.>
>
> The proportion is relatively stable. It seems that model definition
> remains in memory after each request. It is probably caused by a weird
> reference, but I'm not sure how to track it. Please do you have any ideas?
>
> Thanks :)
> David
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-- 
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