use the rows field in auth_permission as described here. http://web2py.com/books/default/chapter/29/09/access-control#Authorization
On Tuesday, October 22, 2013 5:40:49 AM UTC-4, Thomas S wrote: > > Ok, I am making progress. I guess all those JavaScript tools are not great > when it comes to plotting millions of points but I am happy to downsample > on the server side and send less points > > - I am using flot instead of highcharts > > - Currently, the user is uploading a csv file. I don't do any parsing at > this stage. However, I rather keep the file (under uploads) and parse it on > request. Having said that this will become a lot more slick soon. This is > my first application. > > One thing that puzzles me for now... > > A user has to login to upload a file (that's good), but he can then also > modify or delete entries in the SQL database created by others. How can I > make sure he/she only deletes rows he/she has created in the first place. > All users should be able to see all files though. > > Here's a link: > https://tschmelz.pythonanywhere.com/csv > > I will soon post it to my Github (username tschm) > thomas > > > On Sunday, 20 October 2013 15:38:07 UTC+2, Niphlod wrote: >> >> first things first: are you sure that highcharts can handle 10*100k >> points to draw a graph ? >> As for the storage, you can do anything you like: if the data doesn't >> change that much, storing into the database will be a long process only on >> the first time. >> On the other end, if you need to fetch 100k records and transform them to >> json, it's going to take some time. >> Not sure on how much you'll gain from parsing i.e. a csv file instead of >> a querying a db.... >> if the returning json object is , let's say, 10 mb, it's always gonna >> feel heavy. >> >> On Sunday, October 20, 2013 9:11:07 AM UTC+2, Thomas S wrote: >>> >>> >>> Hi, >>> >>> I have created a standard application relying on Pandas and PyQt4 to >>> browse through a Pandas Dataframe. >>> A dataframe is essentially a dictionary of time series data. >>> >>> I am new to web2py but I have experience with Pandas and matplotlib. >>> I am also tempted to embed www.highcharts.com into my application. >>> >>> Before I dig into web2py I would like to know which route is probably >>> most promising. >>> >>> Should I parse the dataframe on the webserver and write it into a SQL >>> database? I guess that could be slow? >>> Such a dataframe may consist of a dictionary with 100 elements each >>> several 100k points. >>> >>> Should I parse a time series onto request into a json format and export >>> to javaScript? >>> In this case how could I provide a way to generate a menu from the keys >>> in the dictionary. >>> E.g. user clicks on a key, python does all the computations for some >>> stats. >>> >>> The plan is to upload the data using csv files. >>> >>> So, I am a bit lost by the wide range of possibilities in web2py. I >>> would be delighted if you would like to get involved in this open source >>> project. >>> The main goal for now is to learn web2py :-) >>> >>> Please find the Github of the original application here >>> https://github.com/tschm/PandasMonitor >>> >>> Sorry for being so unprecise in my questions but it just reflects that I >>> don't have a very precise plan at this stage. >>> >>> Kind regards >>> Thomas >>> >> -- 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/groups/opt_out.
