is the sky blue, really really blue ? those kind of questions really makes me wonder. What is "high volume of traffic" ? 1k concurrent requests ? 10GB/hour of traffic ? many small requests? less requests but requesting a large chunk of data? The data returned to the users will be the result of many tables joined? questions like yours, to have back an answer given with a grain of salt, is going to require a lot more details. Anyway: 1. Database large: not a web2py problem, in fact, web2py is not a database (:-P). Be sure your db engine (that is often the bottleneck in almost every app) handles your traffic 2. have you tested your app with 10 users ? test it with 1000 and see if you app is scalable. The way you code it makes it scalable, not the framework. Again, web2py could handle 1k requests per minute, but if your db is going to kneel down at 200 requests per minute, don't blame the framework for being slow. 3. have you something (I mean, code) that runs faster on other frameworks to have web2py to blame ? 4. Inspect your idea of app. If that's going to be an api with 1m concurrent users, with no forms, no sessions, no auth, no model, probably you'll find other frameworks faster than web2py. If it's going to require all of those, or a generous subset, having your app in web2py saves you a lot of time (and errors)
General advices working with web2py: reduce models, use lazy tables (available in the last release), use session.forget() wisely, and a lot of bunch of advices you can find in the book. Want some proofs? Some users in this list have huge sites working on web2py. From what I can recall howesc has web2py handling a site servicing 2.5m requests per day. On Saturday, September 1, 2012 6:48:01 PM UTC+2, Webtechie wrote: > > > I would like to use web2py for a web application which has large databases > (really large) , expects high volume of traffic . Are there any ways to > make web2py apps run faster ? (like really faster ) , (looking for > solutions apart from pooling more hardware and replacing Cpython wth pypy , > running on a non-blocking server like tornado ) . How can i optimise web2py > for my needs ? are web2py applications scalable ? > --
