> If you're talking about building queries, your point is moot -- the 
>> operations happen in the database, not Python.
>>
>
> I don't know what you mean by this...
> For complex-queries, I would still be using web2py's DAL layer, even if I 
> had this ORM on top. I would either use them outside the ORM, or insert 
> them into the ORM.
>

Not sure what you mean here -- you can do simple queries in the db as well 
as complex filtering in Python -- they are orthogonal considerations.
 

> My example was not meant to show that you should do complex queries in 
> Python - that would obviously be absurd, and you don't even need a 
> relational database for that - any NoSQL one would do fine.
>

Now you've really lost me -- what does any of this have to do with RDBMS 
vs. NoSQL? And why shouldn't you do complex filtering in Python?
 

> I was giving an example to a case in which I have a simple comparison to 
> make, and want to reuse the ORM objects I already have for it.
> The DAL is not built for that.
>

Not sure what you mean. The DAL returns a Rows object. You can filter it 
with any simple or complex comparison you like. It even has a .find() 
method to simplify the process:

db.Country(france).select().find(lambda r: r.Language != spanish and r.
Population > 1000000)

As for comparisons in Python, in web2py, you wouldn't be testing equality 
>> of a whole object/record -- typically it would be a scalar (e.g., the 
>> integer ID).
>>
>
> That would still be much slower than an equality-test - especially for 
> large data-sets.
>

OK, please provide some benchmarks. What percentage decrease in CPU usage 
can we expect if we compare object identities rather than integer 
equivalencies?
 

> And you wouldn't have multiple copies of records in memory either.
>>
>>
> How so?
>
> If I do this:
>
> row1 = db.Country[1]
> ...
> row2 = db.Country[1]
>

And why are you doing that? 

Anthony

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