Hi Daniel, Thanks for the suggestion. Would look into django-import-export.
Thanks. On Saturday, March 11, 2017 at 6:29:57 PM UTC+5:30, Daniel Hepper wrote: > > In additions to the suggestions you already received from others, have a > look at django-import-export. It allows you to easily export data in > various formats. > > Hope that helps, > Daniel Hepper > https://consideratecode.com > > On Friday, March 10, 2017 at 12:06:13 PM UTC+1, Web Architect wrote: >> >> Hi James, >> >> Thanks for your response. Melvyn also posed a similar point of not >> loading the whole records. >> >> But all the records are needed for reporting purposes - where the data is >> read from the DB and a csv report is created. I am not quite an expert on >> Django but I am not sure if there is a better way to do it. >> >> The scenario is as follows to make it clearer: >> >> Ours is an ecommerce site built on Django. Our admin/accounting team >> needs to download reports now and then. We have a Django model for the line >> items purchased. Now there could be 10k line items sold and each line items >> are associated with other models like payments, shipments etc which is a >> complex set of relations. >> >> We do not yet have a sophisticated reporting mechanism but was working on >> building a simplistic reporting system on Django. But I am finding issues >> with scaling up - as reported with CPU Usage and the amount of time taken. >> If there is a way to optimise this - would be great otherwise we might not >> have to look for standard methods of reporting tools. >> >> Would appreciate suggestions/advices on the above. >> >> Thanks, >> >> On Friday, March 10, 2017 at 2:52:50 PM UTC+5:30, James Schneider wrote: >>> >>> >>> >>> On Mar 9, 2017 9:37 PM, "Web Architect" <[email protected]> wrote: >>> >>> Would like to further add - the python CPU Usage is hitting almost 100 >>> %. When I run a Select * query on Mysql, its quite fast and CPU is normal. >>> I am not sure if anything more needs to be done in Django. >>> >>> >>> Ironically, things being done in Django is the reason for your CPU >>> utilization issue in the first place. >>> >>> Calling a qs.all() is NOT the same as a SELECT * statement, even more so >>> when speaking to the scale of query that you mention. >>> >>> Your SQL query is simply listing data in a table. A very easy thing to >>> do, hence the reason it runs quickly. >>> >>> The qs.all() call is also running the same query (probably). However, in >>> addition to pulling all of the data, it is performing a transformation of >>> that data in to Django model objects. If you are pulling 10K items, then >>> Django is creating 10K objects, which is easily more intensive than a raw >>> SQL query, even for simple model objects. >>> >>> In general, there's usually no practical reason to ever pull that many >>> objects from a DB for display on a page. Filter down to a reasonable number >>> (<100 for almost all sane cases) or implement a paging system to limit >>> returned results. It's also probably using a ton of RAM only to be >>> immediately thrown away at the end of the request. Browsers will >>> disintegrate trying to render that many HTML elements simultaneously. >>> >>> Look at implementing a paging system, possibly through Django's built-in >>> mechanism, or something like Datatables and the infinite scroll plugin. >>> >>> https://docs.djangoproject.com/en/dev/topics/pagination/ >>> >>> https://datatables.net/extensions/scroller/ >>> >>> -James >>> >> -- You received this message because you are subscribed to the Google Groups "Django users" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To post to this group, send email to [email protected]. Visit this group at https://groups.google.com/group/django-users. To view this discussion on the web visit https://groups.google.com/d/msgid/django-users/29c0528f-57a7-4f73-be77-3158fe6e61dd%40googlegroups.com. For more options, visit https://groups.google.com/d/optout.
