I suppose your right, but I was a little thrown, by the:
max(variable_here)
That was mentioned was not the solution at all, I kept looking for ways to 
use max as a function.
My issue now, is that the group by doesn't like me getting all the tables I 
want in the return.
BR,
Jason Brower

On Thursday, August 25, 2016 at 8:36:58 AM UTC+3, Dave S wrote:
>
>
>
> On Wednesday, August 24, 2016 at 10:29:09 PM UTC-7, Encompass solutions 
> wrote:
>>
>> Does this seem sensible?  It seems to work with my initial tests.
>>
>> latest_versions = db(  (db.item.id == db.item_version.artifact_id) &
>>                             (db.item_version.id > 0)
>>                         
>> ).select(db.item.ALL,db.item_version.version_date.max(), groupby=
>> db.item.id)
>>
>> the .max() feature, at least what I found, was totally undocumented.
>>
>
> Totally?
> You mean, there isn't 
>
> <URL:
> http://web2py.com/books/default/chapter/29/06/the-database-abstraction-layer#sum--avg--min--max-and-len
> >
>
> ?
>
> We should have an example database as part of the documentation with a 
>> collection of examples around it so we can all relate better. :/
>>
>>
> Examples in book, using it on severity of logged events.
>
> /dps
>  
>
>> On Monday, August 22, 2016 at 10:52:55 AM UTC+3, Encompass solutions 
>> wrote:
>>>
>>> Consider the following pseudo model.
>>>
>>> item
>>>  ->name = "string"
>>>
>>> version
>>>  ->item_id =  item.id
>>>  ->version_date = "datetime"
>>>
>>>
>>> While I can easily create a collection of the item with it's versions.
>>> all_items = db((db.item.id > 0) & (db.version.item_id == db.item.id
>>> )).select(orderby=db.item.name | db.version.version_date)
>>>
>>> How do get just all items with just the latest version of each item 
>>> without having to do this....
>>> items = []
>>> current_id = all_items.first().item.id 
>>> for thing in all_items:
>>>     if thing.item.id != current_id:
>>>         current_id = thing.item.id
>>>         items.append(thing)
>>>
>>> It seems a bit silly and heavy to be doing this especially since my data 
>>> could get quite large.  I imaging the database has some way to do this, 
>>> just never learned how.
>>>
>>> Ideas on how this could be done?
>>>
>>> BR,
>>> Jason Brower
>>>
>>>

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