purpose is to keep a single renewable pseudo-random data sample live
the w2p books describes a situation of a constant query : http://web2py.com/books/default/chapter/29/06/the-database-abstraction-layer?search=caching+selects#Caching-selects def cache_db_select(): logs = db().select(db.log.ALL, cache=(cache.ram, 60)) return dict(logs=logs) now suppose every call a different query like here : def cache_this(): nget = somevalue kount = db(db.atable.id > 0).count() offset = randint(0, kount - nget) limitby = (offset, offset + nget) rows = db(db.atable.id > 0).select(limitby=limitby, cache=(cache.redis, 60)) return dict(rows=rows) this accumulates cached 'material' and returns a different rows on every call how do I make *cache_this* behave like the book example ? I could cache kount and offset variables as well : kount = db(db.atable.id > 0).count(cache=(cache.redis, 60)) offset = cache.redis('offset', lambda: randint(0, kount-nget), time_expire=60) but i suppose this would lead to a synchronization problem and thus possible duplicate cached select -- Resources: - http://web2py.com - http://web2py.com/book (Documentation) - http://github.com/web2py/web2py (Source code) - https://code.google.com/p/web2py/issues/list (Report Issues) --- You received this message because you are subscribed to the Google Groups "web2py-users" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. For more options, visit https://groups.google.com/d/optout.
