We're in the migration process from webapp2 to the latest version of Django. We want to keep using legacy services like Appengine NDB for now before we move to the latest technologies. For running the development environment locally I am…
I have a query like: query = HistoryLogs.query() query = query.filter(HistoryLogs.exec_id == exec_id) iter = query.iter() for ent in iter: # write log to file, nothing memory intensive I added logs in the for loop and reading 10K rows increases…
From NDB Caching: NDB manages caches for you. There are two caching levels: an in-context cache and a gateway to App Engine's standard caching service, memcache. Both caches are enabled by default for all entity types, but can be configured…